May 2014 

NASA/TM–2014-218259 

Applying Pressure Sensitive Paint Technology 

to Rotor Blades 

A. Neal Watkins, Bradley D. Leighty, and William E. Lipford 

Langley Research Center, Hampton, Virginia 

Kyle Z. Goodman 

Analytical Mechanics Associates, Inc., Hampton, Virginia 

Jim Crafton 

Innovative Scientific Solutions, Inc., Dayton, Ohio 

James W. Gregory 

The Ohio State University, Columbus, Ohio 
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May 2014 

NASA/TM–2014-218259 

Applying Pressure Sensitive Paint Technology 

to Rotor Blades 

A. Neal Watkins, Bradley D. Leighty, and William E. Lipford 

Langley Research Center, Hampton, Virginia 

Kyle Z. Goodman 

Analytical Mechanics Associates, Inc., Hampton, Virginia 

Jim Crafton 

Innovative Scientific Solutions, Inc., Dayton, Ohio 

James W. Gregory 

The Ohio State University, Columbus, Ohio 
Available from: 

NASA Center for AeroSpace Information 

7115 Standard Drive 

Hanover, MD 21076-1320 

443-757-5802 

The use of trademarks or names of manufacturers in this report is for accurate reporting and does not 

constitute an official endorsement, either expressed or implied, of such products or manufacturers by the 

National Aeronautics and Space Administration. 
Abstract 

This report will present details of a Pressure Sensitive Paint (PSP) 

system for measuring global surface pressures on rotorcrtaft blades in 

simulated forward flight at the 14- by 22-Foot Subsonic Tunnel at the 

NASA Langley Research Center. The basics of the PSP method will be 

discussed and the modifications that were needed to extend this 

technology for use on rotor blades. Results from a series of tests will also 

be presented as well as several areas of improvement that have been 

identified and are currently being developed for future testing.

1. Introduction 

The accurate determination of spatially continuous pressure and temperature distributions on aerodynamic 

surfaces is critical for the understanding of complex flow mechanisms and for comparison with 

computational fluid dynamics (CFD) predictions. Conventional pressure measurements are based on 

pressure taps and electronically scanned pressure transducers or embedded pressure transducers. While 

these approaches provide accurate pressure information, pressure taps/transducers are limited to providing 

data at discrete points. Moreover, the integration of a sufficient number of pressure taps/transducers on a 

surface can be time and labor intensive and expensive. 

This is especially true in rotorcraft research, where the examination of pressure distributions on the blade 

is vital to advance analytical prediction methods for rotorcraft aerodynamics, acoustics, and interactional 

effects. There has been considerable research involving pressure measurements on rotor blades.1-4

However, these measurements typically lack the spatial resolution necessary to capture phenomena such 

as the nascent tip vortex or dynamic stall. Instrumenting the blades with additional transducers to increase 

spatial resolution can quickly become prohibitive due to the cost and practicality of fitting a large number 

of sensors into a small area. In addition, the added centrifugal loads of the pressure transducers can 

rapidly become unmanageable. 

The Pressure Sensitive Paint (PSP) technique may provide a means to non-intrusively measure the global 

surface pressures on these types of surfaces. Over the last several years, the U.S. Army 

Aeroflightdynamics Directorate, Joint Research Program Office, and the NASA Subsonic Rotary Wing 

Project have partnered to develop the PSP measurement technique for use on rotor blades. This work 

included an initial proof of concept work in 20035 which resulted in the development of instrumented 

pressure blades for more extended testing in 2008.6 From these results, a new PSP system based on the 

previously described system was developed with several modifications for use with rotating test articles 

and successfully demonstrated for a rotorcraft in hover.18 This report will detail these modifications as 

well as present results from the deployment of this system in the 14- by 22-Foot Subsonic Tunnel 

(hereafter abbreviated 14x22). 

2. Pressure Sensitive Paint 

Introduction to PSP 

The PSP technique7-11 exploits the oxygen (O2) sensitivity of luminescent probe molecules suspended in 

gas-permeable binder materials. When a luminescent molecule absorbs a photon, it transitions to an 

excited singlet energy state. The molecule can then recover to the ground state by the emission of a 

photon of a longer wavelength, known as a radiative process. However, certain of these materials can also 
2 

interact with an O2 molecule such that the transition back to the ground state is non-radiative in a process 

known as collisional quenching. The rate at which these two process (radiative vs. non-radiative) compete 

is dependent on the concentration of O2 present and can be described by the Stern-Volmer relationship12

2

)(1/ 0  SV PTKII O

(1) 

where I0 is the luminescence intensity in the absence of O2 (i.e. vacuum), I is the luminescence intensity at 

some partial pressure of oxygen PO2, and KSV is the Stern-Volmer constant, which is dependent on 

temperature (T).

There are several issues with this relationship, especially in regards to wind-tunnel applications; first, it is 

a practical impossibility to measure I0 in a wind tunnel application. Second, the luminescent signal from 

the paint is not only a function of pressure; it also varies with factors such as illumination intensity, probe 

concentration, paint layer thickness, and detector sensitivity. These spatial variations typically result in a 

non-uniform luminescent signal from the painted surface. The spatial variations are usually eliminated by 

taking a ratio of the luminescent intensity of the paint at the test condition with the luminescent intensity 

of the paint at a known reference condition (usually wind-off). Thus Eq. 1 can be cast into a more suitable 

form 

)/(*)()(/ REF  PPTBTAII REF

(2) 

where IREF is the recovered luminescence intensity at a reference pressure, PREF. The coefficients A(T) and 

B(T) are temperature dependent constants for a given PSP formulation and are usually determined 

beforehand using laboratory calibration procedures. 

Sources of Error in PSP Measurements for Rotor Blades 

While there are several approaches to acquiring PSP data, each suffer from the same sources of error, 

which have been investigated and modeled by Liu.11 These error sources include temperature, 

illumination, model displacement/deformation, sedimentation, photo-degradation of the luminophore, 

stray light, and camera shot noise. In the case of a helicopter rotor blade, illumination errors associated 

with model deformation (as caused by aeroelastic effects) are a significant source of error. 

The relationship between surface illumination and paint luminescence is linear; thus, any change in 

surface illumination will result in an equal change in paint luminescence. Errors in pressure 

measurements caused by surface illumination variations can stem from several sources. An example of 

this with illumination from a point source is shown in Fig. 1. The relationship between illumination 

intensity at a point on the surface and the distance between the source and the point of interest are an 

inverse function of the distance squared. Any movement of the painted surface or illumination source will 

result in a change in the distance between these two points, thus causing a change in the illumination 

intensity at the surface. Using some common assumptions about the PSP, the example shown in Fig. 1 

shows that for a modest change in the illumination field, there can be fairly large pressure errors. 

Moreover, this source of error can result from deformation of the model surface or physical displacement 

of the model or illumination source. Another source of illumination error is the temporal stability of the 

illumination source. Any variation of the intensity source between the wind-off (reference) and wind-on 

images will register as an error in illumination. 
3 

As described above, PSP is an intensity-based approach that requires the use of (at least) two images 

leading to the introduction of this type of error. For this work, a system capable of compensating for this 

error has been developed based on the lifetime-based method. 

Lifetime-Based Pressure Sensitive Paint Measurements 

For this work, the PSP data was acquired using a “lifetime-based” approach.13-17 In the traditional 

lifetime-based technique, excitation of the PSP is accomplished using a modulated light source (e.g. laser, 

flash lamp, or pulsed LED arrays). A fast framing camera (intensified CCD or interline transfer CCD) is 

used to collect the excited state luminescence decay. Typically the decay is approximated by acquiring 

two or more images at different delay times during and/or after the pulsed excitation and integrating 

photons for fixed periods of time (i.e. gate widths) that have been predetermined to maximize the pressure 

sensitivity, as demonstrated in Fig. 2. The first image (Gate 1) usually consists of a short gate width and is 

collected either during the excitation pulse or shortly after it ends. This can be thought of as the reference 

image because the excited-state decay has the least pressure sensitivity. The second image (Gate 2) is 

taken at a later time after the excitation pulse and usually has a longer gate width, ensuring maximum 

pressure (and temperature) sensitivity. More information on this lifetime technique can be found in 

Watkins et al.17

 

Fast Responding Pressure Sensitive Paint 

Typical paint formulations are comprised of an oxygen sensitive fluorescent dye and a binder to 

physically adhere the dye to the model surface. Conventional formulations typically use a polymer as a 

Figure 1. Schematic of illumination errors in PSP measurements.
4 

binder material. The disadvantage of the 

binder is that it inhibits interaction of 

atmospheric oxygen with the embedded dye 

molecules. The response time of the paint to 

pressure is largely governed by the rate of 

diffusion of gas into the binder. 

Conventional, polymer-based paint 

formulations have response times on the 

order of one second, making them unsuitable 

for evaluating unsteady aerodynamic 

phenomena. Aeroelastic and rotorcraft 

phenomena are inherently unsteady with 

frequency content of 10-Hz to 1,000-Hz, and 

therefore, conventional paint formulations 

are insufficient for the tests to be conducted 

in this program. 

The temporal response characteristics of 

pressure-sensitive paint are primarily 

governed by the thickness of the paint formulation and the diffusion coefficient of the binder material, 

according to the relation 

  (3)

where the response time due to diffusion (diff) increases with the paint thickness (h) squared and 

decreases with increasing diffusion coefficient 

(Dm). Some investigators have focused on 

decreasing the thickness of the paint in order to 

improve the response characteristics. This 

approach, however, has the disadvantage of 

sacrificing luminescent output from the paint, and 

thus signal-to-noise ratio (SNR). The paint 

formulation used in this work has been developed 

based on the strategy of increasing the diffusivity 

of gas within the paint binder, as described by 

Gregory.18 Porous binders have been developed 

with the goal of enhancing the oxygen diffusion 

within the paint layer and thus improving the 

temporal response characteristics. 

The difference between conventional polymerbased PSP and a porous PSP is described 

schematically in Fig. 3. For conventional PSP, 

oxygen molecules in a test gas need to permeate 

into the binder layer for oxygen quenching. The 

process of oxygen permeation in a polymer binder 

layer produces slow response times for a 

conventional PSP. On the other hand, the dye in a 

Figure 2. Schematic representation of lifetime-based 

data acquisition showing excitation (blue) and 

measured emission (red). The gate regions represent 

example Gate 1 (during excitation) and Gate 2 (after 

excitation).

Figure 3. Schematic difference between 

conventional PSP (bottom) and fast PSP (top).
5 

porous PSP is opened to the test gas so that the 

oxygen molecules are free to interact with the dye. 

The open binder creates a PSP that responds 

quickly to changes in oxygen concentration, and 

thus pressure. A large effective surface area due to 

porous surface improves luminescence intensity, 

and thus a higher SNR can be achieved. The 

drawback of the porous PSP approach is that the 

dye is too accessible to the oxygen. This results in 

near complete quenching of all dye molecules at 

very low pressures. These formulations are 

effective for supersonic tunnels where the static 

pressure is below 3-psia. For lower speed 

applications, the signal-to-noise ratio suffers.

Hybrid paint formulations have been developed 

that incorporate the advantages of both traditional 

and porous PSP. The resulting system is a fast time response paint layer with favorable signal-to-noise at 

higher pressure, and the paint can by air brushed onto a model. The polymer/ceramic formulation 

incorporates a high percentage of ceramic particles that provide the porous structure for rapid oxygen 

quenching, with a small amount of polymer to bind the paint to the surface. A dye molecule such as 

PtTFPP is deposited onto the polymer/ceramic surface to complete the paint formulation. Gregory and 

Sullivan19 have used these polymer/ceramic PSP formulations to measure oscillating pressure fluctuations 

with frequencies up to 20-kHz. Porous polymer PSP has been used for unsteady pressure measurements 

on a turbocharger compressor blade,20 model airplane propeller blades,21 and rotorcraft blades. 

Temperature Measurements on the Blade using TSP 

Temperature sensitivity has long been a major source of error for PSP systems. The temperature 

sensitivity of the fast PP-PtTFPP PSP is quite high, as can be seen from the calibration in Fig. 4. 

Temperature sensitivity can be minimized and compensated for using a variety of tools such as isothermal 

models and in-situ transducer corrections. These tools are of limited value for the rotorcraft measurement 

as transducers are difficult to install and blade composition is driven by other issues. Uncertainty in the 

temperature of the blade is one of the most significant remaining errors in the fast PSP system. It is clear 

from the data acquired in previous tests that there are at least two major temperature variations to be dealt 

with, 1) a change in the blade bulk temperature between wind-off and wind-on as the tunnel heats up, and 

2) a radial temperature gradient on the blade due to the local dynamic temperature. 

Conceptually the addition of a TSP to the blade should be relatively simple; unfortunately there are 

several constraints that complicate the process. The TSP should operate using the same excitation and 

detection hardware used for the PSP, the single-shot lifetime system. An ideal TSP could be combined 

with the existing PSP to form a binary system; this would allow measurements of temperature at each 

location of the blade and therefore, local temperature variations caused by structures in the blade could be 

identified and corrected. 

Figure 4. Calibration of PSP formulation for 

various temperatures and pressures.
6 

3. Experimental 

Paint Formulation and Calibration 

For making PSP measurements, the blades were coated with a porous polymer formulation described 

above. The oxygen sensitive luminophore chosen was platinum meso-tetrakis(pentafluorophenyl) 

porphine (abbreviated Pt(TfPP)), which is a common luminophore for PSP applications. A typical 

application of the PSP involved initially applying the porous polymer binder to a basecoat (usually white 

to maximize intensity collection efficiency) using conventional spraying techniques. After the binder 

dries, a solution of the luminophore is then typically over-sprayed onto the binder. This helps to ensure 

that the luminophore is resting on the surface for maximum interaction with oxygen (thus increasing the 

frequency response). The disadvantage of this is that the luminophore can degrade fairly quickly. 

However, this can be alleviated by simply over-spraying with additional luminophore solution. For this 

work, it was found that over-spraying once a day before running was sufficient for data acquisition. 

Calibration of the paint formulation was performed separate from the wind tunnel in a laboratory 

calibration chamber. This chamber is only capable of measuring pressure and temperature sensitivities; no 

attempt to determine the frequency response of this paint was attempted. However, as mentioned above, 

previous testing has shown that this formulation can respond to 5 kHz, well above the frequency range 

needed for this test. For calibrations, the PSP was applied to 3-inch diameter aluminum coupons that were 

then placed in the calibration chamber. Illumination of the PSP and acquisition of the luminescent 

intensity was accomplished using the same system as used in the tunnel. 

The PSP formulation was calibrated over a pressure range of 41 to 101 kPa (6 to 14.7 psia) at temperature 

ranging from 25 to 60 oC (77 to 140 oF). A calibration model for the coating was derived by solving Eq. 

(2) for normalized pressure in terms of the normalized temperature and the gate intensities acquired from 

the images as described in the previous section. The calibration data showed a multi-dimensional 

dependence on both pressure and temperature, which can be attributed to the complex nature of oxygen 

diffusion into the paint binder.9-11 A linear least squares algorithm was used to fit the data to a modified 

and expanded version of Eq. (2) above assuming a second order relationship in both temperature and 

pressure 

2

21

2

3 23 1 3 3

21

2

2 22 1 2 3

2

1 21 1 1 3

( a )(G)(T/Ta)(T/Ta /G )

( a )(G)(T/Ta)(T/Ta /G )

)(P/P ( a ))(T/Ta)(T/Ta

REF REF

REF REF

REF REF REF

 

  

  

(4)

where P and PREF are the pressures, T and TREF are the temperatures, G1 and G2 are the intensities in the 

respective gates (analogous to IREF [G1] and I [G2]), and axy are the calibration coefficients. A typical 

calibration is shown in Fig. 4. 

For the temperature measurements, the TSP was formulated based on the same porous polymer binder. 

However, instead of employing Pt(TfPP) as the luminophore, a ruthenium complex was used instead. In 

the porous polymer binder, the ruthenium showed little pressure sensitivity with an easily measured 

temperature sensitivity. In addition, its excited state lifetime was found to be similar to the Pt(TfPP), thus 

allowing a similar timing scheme to be used with each paint. For this work, the TSP sensitivity was found 

to be linear in the range of 15-55 oC with a sensitivity of 2.85%/oC.
7 

Model and Facilities 

The rotor blades that were tested have been constructed from carbon fiber, fiberglass, and aromatic nylon 

fiber honeycomb trailing-edge core. Each blade has been painted with a white basecoat to enhance the 

PSP luminescent output (by scattering the luminescence away from the surface and back to the camera) as 

well as to seal the blade to protect the blade structure from the solvents used in the painting process. The 

blades are constant chord with a swept-tapered tip and a 14 degree linear twist distribution, using the RC 

family of airfoils.22-23 The upper portion of Fig. 3 shows the distribution of airfoils and the dimensions of 

the blades (in inches). Of the four blades, two are pressure instrumented using Kulite pressure sensors. 

The first instrumented blade has two rows of chord-wise transducers, with rows located at the 93% and 

99% radial stations. The second has one chord-wise row at 93% radius. Each row has 10 pressure 

transducers located on the upper surface, as shown in the lower portion of Fig. 5. 

The forward flight testing was conducted in the 14x22 facility at NASA Langley Research Center. The 

tunnel is an atmospheric, closed return tunnel with a test section 4.4 m (14.5 ft) high, 6.6 m (21.75 ft) 

wide, and 15.2 m (50 ft) long. The tunnel can reach a maximum velocity of 106 m/s (348 ft/s) with a 

dynamic pressure of 6.9 kPa (144 psf). The achievable Reynolds number of the tunnel ranges from 0 to 

7.2 x 106 per meter (0 to 2.2 x106 per foot). Test section airflow is produced by a 12.2 m (40 ft) 9 bladed 

fan driven by an 8.9 MW (12,000 Hp) main drive. 

The rotor blades were mounted to the General Rotor Model System (GRMS) and a modified ROtor Body 

INteraction (ROBIN) fuselage. GRMS is a generic rotor drive system that allows testing of different rotor 

and fuselage configurations. GRMS is powered by two 55.9 kW (75 Hp) water-cooled electric motors that 

Figure 5. Rotor blades for use with PSP. The upper diagram shows the distribution of the airfoils 

and the dimensions of the blades (in inches). The lower diagram shows the rotor instrumentation 

locations.
8 

drive a 5.47:1 transmission. Two six component strain gage force and moment balances are contained 

within GRMS to enable separate measurement of rotor and fuselage loads. The rotor hub is a four bladed 

fully articulated hub. One blade cuff is instrumented to measure cuff pitch, lead lag, and flapping. 

Additional instrumentation on GRMS includes an encoder to provide 1/rev and 1024/rev timing signals 

and accelerometers to monitor machine health. The fuselage is similar to the original ROBIN fuselage 

with the exception of a rear ramp section. The ROBIN fuselage is an analytically defined representative 

generic helicopter fuselage that has been used in previous work.24 

The modified ROBIN fuselage used in this test uses the same family of super-ellipse equations as the 

original ROBIN fuselage while employing a modified set of coefficients to generate the ramp section. 

All PSP instrumentation was mounted on the ceiling of the 14x22 so that illumination and image 

acquisition were performed though AcryliteTM OP-4 windows. OP-4 is a brand of acrylic plastic that can 

transmit UV light. It also has a high clarity, transmitting ~90% of visible light. Two 

instrumentation/illumination packages were mounted above the test section ceiling to enable 

measurements at two locations on the rotor disk. For the first test entry in which only the last 10% of the 

blade was painted near the tip, data was collected when the blade was on the Advancing Blade Side 

(ABS) and on the Retreating Blade Side (RBS) as shown in Fig. 6. During the second test entry, the entire 

upper surface of the blade was painted and the instrumentation/illumination packages were placed to 

image the blades directly over the tail and on the RBS. 

Figure 6. Wind tunnel configuration of model with instrumentation for first entry. The 

measurement locations are depicted in the lower image.
9 

Instrumentation 

Illumination for this work was provided by a series of frequency doubled Nd:YAG lasers (532 nm). A 

laser-based illumination system was used to attempt to acquire the PSP images needed in one single laser 

pulse as opposed to several hundred LED flashes (with one flash per revolution). This would provide 

instantaneous pressure data on the blade while also alleviating issues with the dynamic nature of 

rotorcraft flight (i.e. blade lead-lag and flap motion). The laser employed was a rugged, compact dual 

laser head system originally designed for Particle Image Velocimetry (PIV) applications. Because of this, 

the lasers have been pre-aligned so that the laser path from each head is co-linear and the timing can be 

manipulated so that both heads fire at nearly the same time (though a slight delay of ~ 20ns is needed to 

achieve maximum power25). The lasers employed had a nominal power of 200 mJ per pulse per head. 

For the first test entry, PCO1600 cameras were used for data collection. The PCO1600 is a specialized 

interline transfer camera developed specifically for use in PIV applications and operated by masking 

every other line of the chip, allowing for charge to be transferred quickly (~200 ns transfer time) from the 

unmasked to the masked region for either storage or readout. This allows for the rapid collection of image 

pairs with a minimal time delay between images (the interline transfer time above). The camera employs 

a CCD chip with an active area of 1600 x 1200 pixels with peak quantum efficiency greater than 50% at 

650 nm. The camera has 14-bit digitization as well as on-board memory that will allow it to rapidly store 

images on the camera, making it possible to run multiple cameras simultaneously from the same computer 

platform. However, the main limitation of the PCO1600 is that it employs a 100 ns clock, resulting in this 

amount of timing jitter when the camera is triggered externally. If only one camera is needed for imaging 

(as in the case of the first tunnel entry), this is not an issue. Unfortunately, multiple cameras were needed 

to image the entire upper surface of the blade in the second entry (3 cameras at the RBS and 2 cameras 

over the tail). 

For the second entry, a new camera system was designed that incorporated the same interline transfer 

CCD chip employed in the PCO1600 but was driven using a clock with an accuracy greater than 10 ns, 

resulting in significantly reduced timing jitter. The camera also operates using a Gig-E interface (capable 

of transferring data up to 1GB/s) and thus can frame at over 30 fps streaming data directly to a hard drive. 

The stability of the external triggering of the new cameras was conducted using three camera systems 

triggering from the same source. The results indicate that the timing jitter was less than 20 ns. Calibrating 

a porous polymer PSP using the three cameras show essentially no change in the paint performance. 

These cameras were used for the second tunnel entry. 

Due to the testing and safety requirements as well as efficiency, it was necessary to have nearly full 

remote control of the pan and tilt as well as focus of the cameras during the test. The cameras were 

mounted onto a commercial pan/tilt head that was capable of being controlled at distances of several 

hundred feet. Remote focus and zoom lenses were also employed to remotely focus the cameras. 

Data Acquisition 

All image acquisition was accomplished using the lifetime-based approach, which was found to be 

essential in previous testing.5-6 However, these previous tests employed LED-based arrays and functioned 

by on-chip accumulation of several images to build the necessary data. This was shown to suffer from 

excessive blurring due to flapping and lead lag of the blade. Thus, a method to acquire the data in one 

single rotation was needed to account for this. Using the high powered pulse laser provided sufficient 
10

levels of illumination and operating the cameras in the double exposure mode described above allowed 

the acquisition of the two gate images from one laser pulse. In addition, there was a requirement to 

synchronize the actual PSP data acquisition with the wind tunnel dynamic data acquisition system to be 

able to compare the dynamic pressure transducer measurements with the PSP at the correct azimuth 

positions. Timing for the acquisition was accomplished using a custom designed and built system based 

on a configurable counting board and software interface (Rotor Azimuth Synchronization Program, or 

RASP26) and the signals from the 1/ref and 1024/rev encoders on the GRMS. The RASP allowed for 

accurate and reproducible alignment of the blades with a specific azimuth location in the rotor disk. 

Programmable delay generators were also used to synch the camera acquisition with the flash lamp and 

Q-switch firing of each laser head. The overall control of the data acquisition was accomplished via an 

external signal sent from the wind tunnel dynamic data acquisition system. Each individual firing of the 

Q-switch was also recorded by the dynamic data acquisition system to enable comparison between the 

pressure transducer data with the PSP data at the same rotor azimuth. A simplified diagram of the timing 

setup is shown in Fig. 7. 

The actual acquisition of the PSP data was acquired using a double frame imaging technique in which a 

short exposure image was taken followed immediately by a longer exposure image, as described by 

Juliano et al.21 The longer exposure image was started after the interline transfer time of the pixels (200 

ns) and lasted as long as it took for the first image to be read into the on-board RAM of the camera (for 

the PCO1600) or downloaded to the PC (for the cameras developed for the second test entry). For an 

image pair, the camera was set for an initial exposure time corresponding to the optimal delay between 

flash lamp and Q-switch firing. The initiation of the camera exposure also triggered the programmable 

delay generator to trigger the flash lamp and Q-switch at the desired times. These times were set to ensure 

that the laser flash occurred just before the end of the first exposure, exciting the paint. Then the second 

image was collected so that the remainder of the excited state decay occurred in this frame. A diagram of 

the nominal PSP imaging process is shown in Fig. 8. 

For the first test entry, PSP images were acquired on the ABS at an approximate rotor azimuth of 98 

degrees and on the RBS at an approximate rotor azimuth of 258 degrees. The ABS is the side where the 

blade is advancing into the freestream velocity and the RBS is the side where the blade is moving in the 

same direction as the freestream. For the second test entry, the ABS camera was moved to an azimuth 

Figure 7. Timing schematic for multiple

laser/camera systems (though only two were 

used in this test). LC880: Programmable logic 

gate controller; DAQ: Laser/camera system; 

DDAS: Dynamic Data Acquisition System.

Figure 8. Schematic representation of data 

acquisition using dual frame imaging and laser 

pulse excitation. Laser pulse width and delay

between images is exaggerated to show 

difference
11

location of 0 degrees (over the tail) to investigate possible rotor-tail interactions. All data were acquired 

from the same blade and rotation speed was 1150 rpm. 

Data Analysis 

Data analysis for this work followed the standard procedure for analysis of PSP data acquired using the 

lifetime-based data acquisition procedures with some exceptions. Usually the lifetime-based data analysis 

is simply dividing Gate 1 by Gate 2 to form an IREF/I image. However, the chosen paint formulation (the 

porous polymer) displays a significant change in performance that is tied to the application process. This 

phenomenon has been observed previously in many PSP formulations27-29 but is very pronounced in this 

formulation. Essentially, the excited state lifetime of the Pt(TfPP) shows heterogeneity with application, 

where the lifetime can change dramatically based on the relative localized concentration of the probe. To 

solve this, a single wind-off image set was acquired immediately after the overspray. Since the overspray 

was done each morning, this wind-off image set was also acquired each morning. The wind-off image 

pair served as a further reference for the lifetime data and can account for much of the non-homogeneity 

effects. The basic data analysis used the following protocol: 

1. Background correction of all images and deblurring of appropriate images 

2. Registration of wind-on images Gate 1 and Gate 2 to the second gate image of the wind-off pair 

3. Creating a “ratio of ratios” image using the wind-off image pair 

4. Mapping the resultant image to the surface grid using the previously determined three dimensional 

coordinates of registration marks added to the blade 

5. Final calibration of the image to convert to pressure. This was accomplished using hybrid calibration9

by performing an a priori calibration using Eq. (3) and correcting any bias error using the pressure 

transducers. 

However, for the second entry in which the entire upper surface is imaged, there was a serious mismatch 

of the wind-off images from the wind-on images. Thus, most of the data analysis needs to be performed 

on the surface mesh of the blade. For this entry, the following protocol was employed: 

1. Background correction of all images 

2. Registration of wind-on images to the Gate 1 of the first wind-on pair collected 

3. Registration of wind-off images to the Gate 1 of the first wind-off pair collected 

4. Creating a wind-on ratio and a wind-off ratio 

5. Mapping the resultant images to the surface grid using the previously determined three dimensional 

coordinates of registration marks added to the blade 

6. Creating a “ratio of ratios” on the mesh using the wind-off images 

7. Final calibration of the image to convert to pressure. 
12

Results and Discussion 

Improvements from Using Laser-Based Data Acquisition 

An initial concern with using a pulsed laser for illumination was the pulse-to-pulse repeatability of the 

laser itself. For the lasers used in this test, the stated power stability is +/- 4%, which could results in 

pressures errors up to 6%. However, since all data is taken in a single laser pulse through the interline 

transfer technique, the variation of the laser pulse power is not a concern. The benefits from using the 

laser-based data acquisition technique were 

apparent from the start. The greatest improvement 

was the clarity of the images. This is depicted in 

Fig. 9, which shows a comparison of a raw image 

taken using the LEDs and integrating over 

multiple revolutions and a raw image from this 

test. Because of the multiple revolutions that were 

required for the LED-based approach, the image 

has noticeable blur around the pressure 

transducers, especially when compared with the 

laser-based data acquisition technique. While the 

laser-based acquisition technique significantly 

reduces the blur caused by acquiring data over 

multiple rotations, it cannot compensate for 

rotational blur. The rotational blur is due to the 

exposure time of the second gate image and the 

motion of the blade. The second image is acquired 

after the laser pulse and is effectively the length of the luminescent decay, on the order of 5-10 

microseconds (for this formulation). Thus, the exposure time of the second image is two to three orders of 

magnitude longer than the exposure time of the first image (the exposure time of the first image is 

governed by the laser pulse, which is ~ 10 ns wide). As a result of this, there is a rotational blur imparted 

to the Gate 2 image which is most evident at the trailing and leading edges, though does have an effect 

across the surface as well. 

Juliano, et al.,

30 have developed a method to deconvolute this type of blurring from an image by using a 

Point Spread Function (PSF) for the blur. Construction of the PSF for the blurred rotor blade was 

constructed by first assuming the luminescent intensity decay was first order 

/

0

*

t

eII





(5)

where I is the intensity, I0 is the initial intensity at the excitation peak, t is time, and τ is the excited state 

lifetime of the luminescent material. The blade rotates as a solid body, wherein the distance moved (Δx) 

at a point is proportional to the angular velocity, ω, and its radius from the center r (Δx = ωrΔt). The 

motion was treated as rectilinear: the angle moved by the blade during 10τ was only 0.01 radian (less than 

1

o

), so the width of the path traced by a point on the blade was sub-pixel (but about 20 pixels long at the 

tip). By combining I(t) and Δx(t), the PSF can be defined as

/( )

0

*

rx 

eII





(6)

Figure 9. Raw images from LED-based (left) 

and laser-based (right) data acquisition 

techniques showing the reduced blurring.
13

Application of this PSF to the second image 

greatly reduced the blur as seen in Fig. 10. The 

effects of the deblurring algorithm on the 

recovered PSP results are shown in Fig. 11. Visual 

inspection of the images in Fig. 11 show that the 

most dramatic effect of the deblurring technique is 

on the trailing edge. This is also shown in the 

graph of Fig. 11, which is a comparison of a chord 

of PSP data. The deblurring technique greatly 

reduces the anomalous high pressure region at the 

trailing edge and shows little effect over the rest of 

the blade. However, in regions of sharp edges 

(such as the leading and trailing edges), this 

technique does introduce a slight ringing. All data 

analyzed from the first test entry (looking only at 

the tip) was deblurred using this technique. 

An additional benefit of the laser-based data acquisition is the greater increase in efficiency. Acquiring a 

data image over multiple revolutions required data acquisition times on the order a minute to acquire a 

single image pair. This precluded many of the advantages in signal-to-noise that can be achieved with 

averaging. Additionally, the comparison with pressure transducers would become tenuous as only an 

ensemble average could be used over that time frame, severely mitigating any dynamic effects that may 

exist. Alternatively, with the laser-based data acquisition technique, an image pair can be obtained in 

single laser flash, corresponding to a single rotation. Now, the comparison with pressure transducers is 

much cleaner as the image is collected at a single point in time. Also, with the current setup, as many as 

Figure 10. (Left) Original Gate 2 image 

showing the rotational blur. (Right) Same image 

after the deblurring technique described by 

Juliano, et al.

Figure 11. Comparison of PSP results obtained without (Original) and with (Deblurred) the application 

of the deblurring algorithm. The dashed line in the figures represents the location of the chord used for 

the comparison in the graph at the right.
14

30 image pairs could be obtained in a single test point collection from the rotorcraft dynamic data 

acquisition system, which required approximately 15 seconds. 

Results from Test Entry 1 

As mentioned in the Data Analysis section 

above, a single wind-off image pair was needed 

to correct some anomalies that happen with this 

particular paint formulation (the porous polymer 

PSP). In the wind-off image pair collected for 

this work, there was a series of anomalies that 

occurred near the pressure transducers. This is 

shown in Fig. 12. In the first gate image (left), 

the effect is not really noticeable. However, in 

the second gate image (right) there are 

significant variations at the transducer row at 

99% chord. This image contains most of the 

excited state decay, thus any variations in the 

lifetime should be convoluted with the actual 

excitation field. After the test entry occurred and 

many discussions with the blade fabricators, it 

was postulated that these anomalies are due to 

the temperature compensating electronics of the 

Kulite sensors. This was a reasonable 

assumption as only the 99% chord pressure 

transducers were actually active for this test, and 

the anomalies are not seen at the 93% chord 

Kulites. 

This effect was confirmed by imaging the blade 

with a thermal (IR) camera. This occurred after 

the test was complete and the Kulites in all of 

the blades were repaired. For this test, the blade 

was positioned on the bench top and the Kulites 

powered with 10V (as is done during normal 

operation). With the IR camera imaging the 

blade, the Kulite system was powered on. 

Within a very short time (a few seconds), the position of the Kulites became very noticeable in the IR 

image, and stabilized after a few minutes to show localized heating increases of ~10 oC. Representative 

IR images before powering the Kulites and after is shown in Fig. 13. It should also be noted that this 

effect is only seen in the wind-off images. It can be assumed that in the wind-on condition, there is 

enough air flow to cause this heat to be convectively dissipated. For this entry, the Kulites were 

continuously powered to ensure that they had adequate temperature compensation. However, for future 

testing, a modification of this was put in place to allow for the remote depowering of the system to 

mitigate this effect. 

For this entry, however, a means to mitigate this was attempted by simply “cloning” this area of the paint 

with small regions near the 99% chord row. A comparison of the wind-off IREF/I image before and after 

Figure 12. Raw wind-off images. (Left) The 

first gate image taken at the laser flash; (B) the 

second gate image encompassing the majority of 

the excited-state decay showing the anomaly at 

the 99% chord transducer row.

Figure 13. IR images of the blade before (Top) 

and after (Bottom) powering the Kulite 

transducers in the 93% chord row.
15

the “patching” is shown in Fig. 14. Ideally, this 

image should have a uniform appearance, but 

lifetime variations in the paint (again, usually 

caused by application) can be seen. In the original 

image (left), these variations at the 99% chord are 

extreme. Patching (right) can remove much of this 

effect. Obviously this can bias the results in this 

region, so further study on the effects needs to be 

carried out as well as strategies to mitigate the 

effect from happening in the first place. All data 

analysis was accomplished using the patched 

reference images. 

For the hybrid calibration mentioned in the Data 

Analysis section, the location of the pressure 

transducers was virtually moved on the surface grid 

away from the taped regions. If the pressure 

transducers would have been covered with only a 

small piece of tape individually, this probably 

would not have needed to be done. However, the 

tape strip afforded the maximum protection to the 

transducers, as well as significantly reduced the 

amount of time needed for application. For the final 

data analysis, the transducers were virtually moved 

toward the hub about 0.3 inches (0.5%R). This 

move was also structured to maintain the same 

locations in x/c as were in the original. This moved 

the transducers a significant (> 5 pixels) distance 

from the transducer to allow their use in calibration 

(the spatial resolution in the blade is ~0.03”/pixel) 

while keeping a close proximity to their actual location. All PSP comparison to the measured pressure 

from the transducers was carried out in this region. Unfortunately, the largest contamination region also 

corresponds to this region. However, due to the highly three-dimensional flow at the tip, it is not 

reasonable to move the virtual transducer line any further from the true transducer line. The effect of the 

Kapton tape as well as the original and virtually moved transducer locations are shown in Fig. 15. 

With the transducers virtually moved to a clear region, they can now be used to anchor the a priori

calibration, which was calculated using an assumed temperature. A comparison of the a priori calibration 

with the hybrid calibration is shown in Fig. 16. The comparison between the pressure transducer 

measurements and the PSP data is also included and shows that the hybrid calibration does bring the PSP 

data closer in line to the transducers. It should also be noted that the PSP data at the extremely low x/c 

locations is probably biased due to a combination of unaccounted for blurring and the need for patching 

due to the contamination. Because of the higher concentration of transducers in this region, the 

contamination region was much larger (as seen in Fig. 15) and this corresponds to the region of poor 

correlation between the PSP and the transducers. Even with this, the PSP shows relatively good 

agreement with the transducers. For consistency, all final calibrations were done using the hybrid 

calibration technique to anchor the a priori calibration. 

Figure 14. Wind-off Gate 1/Gate 2 images. 

(Left) Original images showing Kulite heating; 

(right) patched images showing nearly complete 

removal of the heating.

Figure 15. Blade tip region detailing masked 

areas the original transducer locations (yellow 

spheres) and the transducer regions after 

moving inboard 0.3 inch (red spheres).
16

A representative set of data was acquired at a constant velocity of 138 knots (71.0 m/s) and at four thrust 

coefficients. A comparison of a PSP image at each thrust condition is shown in Fig. 17. This is the ABS 

and shows good qualitative agreement with what should be expected. It also shows that the pressure on 

Figure 16. Comparison of PSP data calibrated using the a priori calibration (left) with an assumed 

temperature and the hybrid calibration (right) using the pressure transducers to “anchor” the a

priori calibration. The comparison between the transducers and the PSP is shown below each 

image. The black region on the blade is unmapped data.

Figure 17. PSP images acquired from the ABS. The arrow represents the direction of the tunnel 

flow. The black regions on the blade are unmapped data.
17

the blade at this position has little 

dependence on the thrust coefficient. The 

comparison between the pressure transducers 

and the PSP is also shown in Fig. 18, and 

shows the same result. The PSP does not 

agree as well as the previous figure, most 

likely due to the smaller pressure changes on 

the blade as well as the reasons cited above 

(ringing from the deblurring technique as 

well as the patching used to account for the 

temperature effects from the Kulites in the 

wind-off image). However, both the PSP and 

the transducers show the higher pressure 

region at the extreme leading edge with the 

pressure decreasing as the flow accelerates 

over the center of the blade, followed by a 

gradual return to higher pressure at the 

trailing edge. As with the PSP data, the 

pressure transducer measurements also show 

little dependence on the thrust coefficient. 

The reason for the relatively small variations 

in pressure with CT on the ABS is better 

illustrated by examining the ensemble 

averaged blade pitch during a revolution as 

shown in Fig. 19. The approximate locations 

of the measurement are shown by the dashed 

lines, with the ABS taken at Ψ = 101o, the 

blade pitch for all of the cases is almost 

identical with only 0.6o separating the CT = 

0.004 and CT = 0.010 cases. Thus, the nearly 

constant pressure distribution regardless of 

CT for the ABS is to be expected. 

However, the same cannot be said of the 

blade in the “retreating” position (the blade 

is moving in the direction of the air flow in the tunnel). From Fig. 19 it is readily apparent that when Ψ = 

258o (the measurement location for the RBS), the pitch angle increases approximately 12o through the 

thrust sweep. Thus, a much larger pressure dependence on CT should be expected. Fig. 20 shows PSP data 

taken from this location. The PSP data shows that there is a much larger dependence on the thrust 

coefficient, as evidenced by the lower pressure region near the leading edge of the blade. Additionally, 

there is evidence of a flow phenomenon near the blade tip, such as a vortex shedding off the tip. This is 

highly dependent on the thrust coefficient, and evidence of it can be seen from CT greater than 0.006. The 

larger pressure differentials are also evident from the pressure transducer and PSP comparisons, which is 

shown in Fig. 21. As with the previous data, the transducer agreement is very good (except near the 

leading edge). However, the flow phenomenon that is seen in the PSP at the tip does not appear in the 

transducer data. From visual inspection of the PSP data, it seems that the phenomenon flows just past the 

last pressure transducer, or possibly between two transducers. This does show one of the greatest 

Figure 18. ABS comparisons between PSP data and 

pressure transducer measurements from Fig. 17.

Figure 19. Average blade pitch during one 

revolution. The vertical dashed lines represent the 

azimuths where PSP data was collected.
18

advantages to using PSP: the ability to visualize and measure global pressure distributions as opposed to 

localized pressure measurements as is acquired from pressure transducers. 

Results from Test Entry 2 

For this test entry, the entire upper surface 

of the blade was painted. In addition, since 

there was little change in the measured 

pressures on the blade at the ABS, the 

imaging systems were moved to investigate 

the blade behavior over the tail. To fully 

image the upper surface of the blades, the 

imaging system was further expanded to 

include multiple cameras with overlapping 

fields of view. For the condition where the 

blade is over the RBS, three cameras were 

used; while two cameras were used to image 

the blade over the tail (technical limitations 

prevented the use of the third camera over 

the tail. The approximate fields of view of 

the three cameras over the RBS along with 

representative raw images are shown in Fig. 

22. 

Figure 20. PSP images acquired from the RBS. The arrow represents the direction of the tunnel 

flow. The black regions on the blade are unmapped data.

Figure 21. RBS comparisons between PSP data 

and pressure transducer measurements from Fig. 

20.
19

This entry posed several new challenges. There was significant movement between the wind-off images 

and the wind-on images, requiring all of the data be processed on the surface mesh. A typical “ratio of 

ratios” image (wind-on image pair divided by the wind-off image pair) on the mesh is shown in Fig. 23. 

This image shows several aspects that need to be taken into account when performing these types of 

measurements. First, there is some slight misalignment between the wind-off and wind-on images, even 

when mapped to the mesh as evidenced by the slight misalignment of the pressure transducer rows at 99% 

and 93% chord. This is most likely due to the aeroelastic deformation that occurs, especially at the tip. 

This data is mapped to the unwarped mesh, even though under bending and twist, the blade does not have 

that same shape any longer. Second, there is an anomaly that can be seen at the trailing edge, which is 

most likely due to unaccounted for blurring in the wind-on image. The numerical deblurring technique 

described above would not completely remove this artifact with the addition of ringing noise due to the 

sharp intensity gradient present at these locations.30 Third, there is a greater amount of overall noise 

present near the root of the blade. This is due to overall errors in the mapping of the data to the mesh. The 

coefficients for mapping the data were generated using reference marks (the transducers themselves) that 

Figure 22. Approximate fields of view of the three cameras imaging the blade at the RBS as well 

as representative images.
20

are clustered nearest the blade tip. For this model, 

there were no well-known reference marks near the 

root of the blade. Thus the coefficients for 

mapping needed to be extrapolated for these 

regions, leading to greater mapping errors. These 

errors tended to increase further away from the 

blade tip. Finally, there is a significant gradient 

along the span of the blade from the root to the tip. 

This is almost entirely due to the surface 

temperature on the blade itself. As mentioned 

previously, temperature is the major source of 

error in PSP measurements, and this is especially 

true in rotating environments where portions of the 

model can be rotating significantly slower than 

other portions. The rotation adds heat through 

simple friction, with the faster rotation generating 

higher temperatures. In the previous test entry, this 

effect was minimized as only the tip area was 

being investigated. However, when measuring over 

a large area as in this entry, temperature effects on 

the entire surface must be corrected. 

As mentioned in the experimental two methods for 

accounting for blade temperature were attempted. 

First, a second blade was painted with a TSP and 

measured in close temporal proximity to the PSP 

blades. Second, three TSP “stripes” were applied 

to the PSP blade in radial locations as shown in 

Fig. 24. Since the excited state lifetime of the 

ruthenium complex was of the same magnitude as 

the Pt(TfPP), the same camera and laser timing 

could be employed for both paints. 

The results from the TSP blade at the same condition above are shown in Fig. 25. As should be expected, 

there is a significant temperature gradient (~20 oC) along the span of the blade. However, there is also a 

chordwise temperature gradient which is rather surprising. While mapping the data to the surface mesh is 

crucial to adequately analyze the data, this process tends to smooth the data somewhat (as the mesh has 

much lower spatial resolution that the cameras). A TSP ratio image of the area near the root of the blade 

is shown in Fig. 26. This image is before mapping to the surface mesh, thus has the full resolution of the 

camera. From this data it is readily apparent that there are regions of significant temperature difference on 

the blade which tends to indicate that there is internal structure in the blade itself (e.g. a spar) that exhibits 

different thermal conductivity. The spar in question can be seen as a horizontal line in the image. The 

vertical lines are an artifact of the camera. In theory, if the blades are all made the same (which in this 

case is true), then this internal structure should affect the blades nearly equally, thus using the TSP blade, 

one should be able to account for the temperature effects on the PSP. 

Figure 23. Representative ratio-of-ratio PSP 

image. The red arrow represents the direction of 

blade rotation and the black arrow represents 

tunnel flow. Tunnel velocity is 120 knots and 

blade thrust (CT) is 0.08.
21

This was done by simply applying the calibration equation (Eq. 2) using a point-by-point temperature 

value calculated from the TSP. The results for this calibration are shown in Fig. 27, which show very poor 

results, with excessive noise as well as an overall offset to the data. The noise is most likely due to the 

fact that the TSP data was in fact acquired from 

another blade. The surface mesh that was used for 

this work was generated from a laser scan of the 

blade that was used for the PSP measurements. A 

separate surface grid for the TSP blade was not 

available, thus if there are slight differences 

between the two blades, this type of misalignment noise will manifest. In addition, the 

mapping coefficients for the TSP images were 

acquired using a similar procedure as the PSP 

images described above. However, in the case of 

this blade, there were even less reference markers 

(only one transducer row) that required using even 

less reliable reference markers/regions (like blade tip, screw holes, etc.) that had even higher uncertainty. 

Thus, the mapping uncertainty for this blade is also higher. For this reason, temperature corrections must 

be carried out using the TSP “stripes” on the PSP blade.

Figure 24. Locations of the TSP stripes

applied to the PSP blade.

Figure 25. Temperature measured by TSP 

blade. Conditions are the same as Fig. 23.

Figure 26. TSP ratio before mapping to surface 

mesh.
22

The most likely theoretical temperature across the 

blade surface can be computed based on the local 

stagnation temperature. The temperature 

distribution should be parabolic as the local velocity 

of the blade is a function of radius, and therefore, 

the stagnation temperature will depend on the 

square of the radius. A comparison of these 

measured temperatures along a spanwise 

distribution and 50% chord is shown in Fig. 28. For 

this case, both the TSP blade and the TSP stripes follow the expected behavior qualitatively, though there 

is a deviation both from each other as well as from the theoretical value. The deviation between the TSP 

blade and stripe is most likely due to the difference in time between when each was collected. This would 

be expected and would also differ from run to run. The deviation from the theoretical temperature could 

be due to some thermal properties of the paint as well as the chordwise effects on the temperature 

distribution as shown in Fig. 25. For the temperature compensation of the PSP, the TSP “stripes” were 

used and fit to a linear solution to generate a calibration curve. A linear model was chosen based on the 

number of stripes available for use. It is fully realized that this could over- or under-compensate for 

temperature, especially at the blade tip. 

The results of this process are shown in Fig. 29. For this process, the linear regression of the TSP stripes 

was used to generate a pseudo-temperature image. Then this image is used to make a pixel-by-pixel 

correction of the PSP data using Eq. 2. While the results are much cleaner than those seen in Fig. 27, there 

still seems to be a bias in the data. This can be further seen if the calculated pressures are compared with 

the pressure transducers on the blade, as seen in Fig. 30. The a priori calibration shows a systematic bias 

from the transducer values. This is most likely due to uncorrected temperature, and could show a 

disadvantage of the method used to correct for temperature. However, if the hybrid calibration described 

in the previous section is used, the PSP shows good agreement with the transducers (except near the 

trailing edge, where the previous cited anomaly lies). When this calibration is applied over the entire 

surface of the blade, the results are shown in Fig. 31. However, some caution should be heeded when 

applying this type of calibration over an entire surface when only a few localized transducers are available 

Figure 27. PSP measurements corrected 

using temperature from TSP blade. 

Conditions are the same as Fig. 23.

Figure 28. Comparison of theoretical blade 

temperature with temperatures measured by TSP 

stripes and TSP blade. Conditions are the same 

as Fig. 23.
23

as this may bias other regions (e.g. near the blade 

root). 

A sample of the results from a thrust sweep are 

shown in Fig. 32, For this data, the rotor speed 

and forward velocity of the wind tunnel were 

maintained at constant values. However, the lift 

was increased from CT = 0.04 to CT= 0.094. The 

results agree qualitatively with what should be 

expected (the lower pressure region at the leading 

edge of the blade becomes more pronounced at 

higher thrust conditions. These results show that 

reasonable PSP results can be obtained over the 

entire upper surface of the blade, though care 

must be taken to compensate for the natural 

temperature increase along the span of the blade. 

Figure 29. PSP measurements correct with 

the TSP slices. Conditions are the same as 

in Fig. 23.

Figure 30. Comparison of PSP data and 

transducer readings from Fig. 29. The red line is 

an a priori calibration of the PSP while the 

green line is a hybrid calibration of the PSP.

Figure 31. PSP results obtained using a hybrid 

calibration. Conditions are the same as in Fig. 

23.
24

Future Improvements 

This work has proven that the PSP technique can indeed collect qualitative and quantitatively accurate 

pressure data from the surface of rotor blades in both hover and forward flight. However, there are several 

avenues which can be explored to greatly improve the efficiency as well as the results. Several have 

already been alluded to in this report, including better temperature compensation and the need to develop 

rapid shape determination procedures to be able to accurately analyze the data under aeroelastic effects. 

These efforts are currently underway, but there are other areas that also are being investigated and a 

summary of these follows. 

Light shaping and steering 

Throughout both of these tests, several methods of trying to shape the light beam to concentrate the light 

into the areas of interest have been tested. One of the simplest ways was to simply insert a negative lens 

into the laser beam to spread the light into a spot. However, this lead to the creation of Newton rings 

through the lens that is then projected onto the surface. While the laser-based data acquisition technique is 

excellent for removing such laser phenomena as speckle as both images are acquired from the same laser 

shot, this is not the case with the Newton rings. When a pair of images that display these rings, ratioing 

them will still leave a significant interference pattern that is difficult to remove by compensation. In order 

to remove these rings, it was found that a diffuser was needed after the lens. The diffuser significantly 

destroyed the structure of the beam, thus removing the Newton rings. However, adding the diffuser 

caused an even greater expansion of the light, so that more than 90% of the light is being “thrown away” 

by illuminating everything except the blade. Several ideas for improving the spot generation are currently 

Figure 32. PSP results from a thrust sweep at the same conditions listed in Fig. 23.
25

being investigated. One of the most promising is to develop a parabolic reflector with a glass diffuser at 

the focus. The glass diffuser is strong enough to withstand the laser power, while the reflector can 

somewhat keep the scattered light from diffusing too much. The parabolic reflector can be machined in 

many different shapes (e.g. to produce an oval as opposed to round spot) and can be made to be mounted 

to a variety of components. 

Another improvement with the laser spot is to 

include the ability to steer the beam. There are 

currently mechanisms capable of this, most 

notably an articulated laser guide. These are 

available from many different manufacturers 

and find common use in areas such as robotic 

laser welding systems. Several of these arms 

were used in the second entry test. However, 

without adequate control of the laser spot size, 

they were mostly just used to align the laser to 

the blade in a certain position and left 

stationary. One of these laser arms is shown 

in Fig. 33 attached to the mounting hardware 

used in the tunnel. If the development of the 

parabolic reflector is a success, then it is 

conceivable that this could then be attached to 

the end of the laser arm. Additionally, the end 

of the arm can be easily attached to a standard 

pan/tilt stage allowing of remote steering of 

the beam. Fig. 34 shows this type of 

arrangement. 

Figure 33. Articulated laser arm.

Figure 34. Articulated laser arm beam exit mounted 

to pan/tilt stage.
26

Remote Control of the Camera Field of View 

For both entries described above, the cameras were placed on standard pan/tilt stages and used remote 

focus zoom lenses for increased efficiency as well as remote operation. The current system operates 

productively at a specific experimental condition. The implementation of the pan/tilt stages and remote 

focus/zoom/aperture lens means that if it is necessary to vary the field of view, this process can be 

accomplished without shutting down the tunnel. Unfortunately, the use of 6 cameras and 4 lasers means 

that the system requires 10 pan/tilt stages and 6 lens controllers. The system, as currently constructed, 

employs manual controllers for each lens and stage, and therefore, the process of modifying the field of 

view is quite slow. Furthermore, it is not possible to restore the system to a specific position for later 

testing. 

There are several commercial systems available that are more rugged than the one currently used. Stages 

such as PT-CP-S4 from Telemetrics include a stiffer motor, Ethernet communication, presets, and a lens 

controller all for about $15,000. While an interesting option, the device was designed for video 

surveillance and does have some limitations. There is not readily available software development kit for 

integration of the system into the data acquisition program and there is a limited selection of lenses. Other 

options include devices built for studio production film cameras. These are generally very expensive 

(starting at $40,000) and still lack some features that would be of value. 

Ideally, a package designed specifically for a PSP system would be ideal. The specific requirements of a 

system likes this would include: 

1) Integrated pan/tilt and remote focus/zoom/aperture 

2) Stiff stages that can carry at least 5-kg loads 

3) Ethernet control of all components over a single IP 

4) Presets on all components 

5) Compatibility with a variety of lenses 

6) A programmable interface compatible with C or LabView or other language 

A prototype of a device capable of this has been designed and constructed by Innovative Scientific 

Solutions, Inc. It was designed using servo motors manufactured for robotics and a custom built Ethernet 

based lens controller and the device is shown in Fig. 35. This 

is a motor-controlled pan and tilt (P/T) mount optimized for 

remote operation and ideally suited for light bench-top work 

up to wind tunnel camera surveillance and data collection. 

The mount can be moved 60o to the left or right of center 

(pan) and 180o vertical up to vertical down (tilt) and support 

loads of 7 kg. Mounting feet are included that can 

accommodate 1⁄4-20 or M6 screws on optical breadboards with 

25.4 mm on center spacing. The mount utilizes a 

microcontroller for motion control and control of the remote 

focus, zoom, and iris lenses. 

Figure 35. Prototype pan/tilt stage.
27

The articulation of the mount and lens settings are controlled by an intuitive LabVIEW graphical user 

interface (GUI). The standard software allows for 10 presets for lens (zoom, focus, and iris) plus pan and 

tilt, with more presets possible as an option. The speed of each motion and lens control is adjusted within 

the GUI. The GUI recognizes the device by its unique IP address. This allows networking of multiple P/T 

mounts via an Ethernet switch for multi-camera applications. 

Motion Blur at Blade Tip 

A numerical method to account for the motion blur exhibited in the higher exposure time second gate 

image was discussed previously, and used satisfactorily for some of the data. However, it does exhibit 

some limitations that were discussed previously. Ideally, a physical means to compensate for this type of 

blurring should be used. One method for optically correcting the motion of the blade is to use a mirror 

setup as shown in Fig. 36. The camera and lens are connected to a custom 2-inch galvanic mirror. The 

system is oriented so that the axis of rotation of the mirror is in line with the blade rotation. As the blade 

tip velocity and operating distance of the mirror are known, the rotation rate of the mirror can be 

estimated. For the tunnel entries described above, the operating distance is about 2.5 meters and the blade 

tip speed is about 200-m/s. A slew rate of about 80 radians per second is required for the mirror to track 

the blade. The custom galvanic mirror can be run from a simple ramp generator which is triggered 

externally, and therefore, blade synchronization is relatively simple. The resulting image should have very 

little motion blur, and therefore, the data at the leading and trailing edges should be improved. 

The galvanic mirror system is composed on a 2 inch mirror, a high voltage amplifier, and a Stanford 

Research DS345 Waveform Generator as shown in Fig. 37. The waveform from the DS345 drives the 

high voltage amplifier, which in turn drives the galvanic mirror. The amplitude versus frequency 

performance of the mirror was characterized using a laser, a pair of photo-diodes, and an oscilloscope. 

The laser was projected off of the mirror and onto a 

screen approximately 2.43 meters away. The 

amplitude and frequency of a sinusoidal waveform 

were set using the DS345. The amplitude of the 

mirror sweep was varied from 0.43 to 0.07 radians 

and the frequency was varied from 1 – 200 Hz. The 

amplitude of the mirror sweep was monitored on the 

screen, and the approximate slew rate of the sweep 

near 0 degrees was monitored using the photo-diodes. 

The amplitude of the mirror sweep at each frequency 

was normalized by the amplitude at 1-Hz and plotted 

versus frequency for each drive amplitude. The 

resulting Bode diagram is shown in the lower left 

corner of Fig. 37. Note that the higher the drive 

amplitude, the lower the frequency at which the curve 

begins to exhibit amplitude clipping. Operation of the 

mirror in the flat portion of the curve is preferable, 

thus avoiding any phase lag or amplitude clipping 

issues. This should also allow the user to predict the 

mirror rotation rate and position accurately. 

While the amplitude data was being collected, the 

Figure 36. Galvanic mirror
28

photo-diodes were used to experimentally measure the rotation rate (slew rate) of the mirror near 0 

degrees. The photo-diodes were placed about 10-cm apart along the scan line of the laser and the time 

between the passage of the laser over the photo-diodes was measured using the oscilloscope. This data 

was used to compute the angular rate of rotation of the mirror. This data was plotted as a function of 

frequency for each drive amplitude in the lower right corner of Fig. 37. Note that each curve is relatively 

linear below the frequency at which amplitude clipping begins. It is also clear that the maximum slew rate 

is achieved with the highest drive amplitude. A slew rate of about 30 radians/second is achieved at 40 Hz 

with a rive amplitude of 0.43 radians. 

To demonstrate the application of the single-shot lifetime PSP system for rotorcraft applications, a simple 

rotating airfoil setup (Fig. 38, lower right corner) was constructed using a model airplane propeller and 

electric motor. The tip speed of this 225-mm diameter blade is about 100-m/s. One blade was painted 

with PSP and the laser, and camera with galvanic mirror were placed approximately 12 feet from the rotor 

hub. At this distance the mirror scan should generate an effective slew rate of 110 m/s, and therefore, it 

should be possible to compensate for the motion of the blade tip.

The rotor and mirror were first set to an off position, a data set was collected, and the Gate 2 over Gate 1 

ratio was computed. This ratio, shown in the upper left corner of Fig. 38, displays no motion blur. The 

leading and trailing edge are well defined and there are no strong intensity modulations. The rotor was 

Figure 37. Characterization of the galvanic mirror response.
29

then set so that the blade tip was at 92-m/s and the mirror was left stationary while a second data set was 

collected. This data set, shown in the upper right corner of Fig. 38, displays the motion blur issues. The 

intensity ratio is reasonable through the majority of the chord, but the leading and trailing edges show 

strong defects caused by the motion of the blade. Finally, the mirror was scanned and adjusted to a rate 

close to 90-m/s. Data was collected and the ratio of Gate 2 over Gate 1 is shown in the lower left corner 

of Fig. 38. Note the well-defined edges at the leading and trailing edges, similar to the stationary blade. 

This indicates that the galvanic mirror is effectively compensating for the motion of the blade. 

A final demonstration of the galvanic mirror was also conducted in the second test entry. For this 

demonstration, the mirror was set to image the blade in the retreating position. The system was positioned 

about 30 deg. downstream of the RBS (so ~300o) and was triggered from the same system operating the 

RBS cameras. Timing for the mirror sweep involved acquiring the 1/rev signal from the rotor and using a 

delay generator to trigger the DS345 sweep. The mirror slew rate was set to its maximum value, which 

yielded an effective sweep rate of about 140-m/s. 

Data was acquired at several test condition using the galvanic mirror. This data was acquired 

simultaneously with the retreating blade system, thus demonstrating integration of the galvanic mirror 

into the multi-camera system. An example of the Gate 2 image at the blade tip from the standard system 

and galvanic mirror system is shown in Fig. 39. It is noted that the galvanic mirror system position was 

not optimum as it was not directly over the blade and the slew rate was about 60% of the blade tip speed. 

The galvanic mirror position resulted in a lower signal level due to the longer operating distance and the 

use of a slower lens. The mirror system was successfully synchronized to the blade and image data was 

successfully captured with the existing PSP camera system. 

Figure 38. Use of galvanic mirror on airplane propeller.
30

Processing of Fast PSP Data 

The single-shot data acquisition has matured over the last several years to a point where a substantial 

quantity of data can be acquired in a short time. The system demonstrated here composed of six 2-

Megapixel cameras capable of streaming data over Gigabit Ethernet at over 10 fps. This can lead to a 

system capable of collecting hundreds of images at multiple locations in an azimuth sweep in a matter of 

a few minutes. 

As an example, a 3 camera system placed over the retreating blade could collect 100 images at 2 degree 

increments over a +/- 10 degree blade sweep in under 5 minutes. This data set would include over 6000 

images that must be processed. With the current data processing tools, this would require about 1 hour per 

image, or about 3 man years of labor. A reasonably productive day in the tunnel with a single 3 camera 

system is capable of producing more data than can be analyzed in a lifetime. Clearly, this issue must be 

addressed for the fast PSP system to be of value. 

The current data processing method has been summarized previously. Resection markers on each image 

must be located manually prior to processing. The background is subtracted from each image and the ratio 

of Gate 2 over Gate 1 is computed for each image pair and any manual image processing to remove paint 

defects must be performed manually. The wind-off and wind-on ratio data must them be mapped to the 

mesh. Once on mesh, the ratio of the wind-off over wind-on is computed, a temperature correction is 

applied, any available pressure tap correction is applied, and the data is then combined with any 

overlapping camera views on the full mesh. This process must be repeated for all images at each station. 

It is also noted that the temperature correction can be quite complex on a rotorcraft flow due to the radial 

temperature gradient. 

One means of quickly evaluating the data is to break the data set into mean and unsteady components. 

The mean pressure can be evaluated by aligning and averaging each Gate 1 and Gate 2 image from the 

full data set. These data are then processed using the wind-off image and the temperature correction. This 

data would represent the phase-averaged pressure on the blade at a particular station or condition. By 

averaging all wind-on images, the resulting data would have the added advantage of a good signal-tonoise ratio. 

The unsteady pressure can be computed using only the wind-on data set. The averaged wind-on Gate 1 

and Gate 2 data serve as the wind-off images, a running wind-off. The variation from this mean condition 

Figure 39. Gate 2 image of the blade tip with the standard system and galvanic mirror system.
31

is computed for each image. This approach to 

processing the unsteady data has several 

advantages. These include processing all data on 

the bitmap, simplified mapping, and elimination of 

temperature errors. 

Since all data was acquired at the wind-on 

condition, there is relatively little change in the 

image of the blade between the running wind-off 

and each wind-on image as is the case between the 

true wind-off and wind-on. This simplifies the 

mapping and allows the data to be processed on the 

bitmap. This also suggests that it may be possible 

to present preliminary data, such as RMS pressure 

fluctuations on the bitmap in near real time. 

A second advantage is that it is possible to process 

the unsteady data without knowledge of the local temperature distribution. The radial temperature 

gradient is already present in the running wind-off image. If one is using an ideal PSP with a linear slope, 

such at the PtTFPP-PP, this can be especially advantageous. An ideal PSP has the unique property of 

having a constant slope at a range of temperatures, as shown in Fig. 40. As the running wind-off and each 

wind-on image have the same thermal distribution, any temperature sensitivity is automatically eliminated 

from the unsteady data set and only the slope of the curve in Fig. 40 is required for converting the data to 

pressure. 

This procedure was done for one of the camera views that encompass the data presented in Fig. 23 above. 

The first step in the process is to compute the average wind-on image for each gate. It is noted that there 

is some degree of jitter in the blade position from shot-to-shot, and therefore one cannot simply load and 

average the images without introducing a degree of smearing. A simple average of the data from Gate 1 is 

presented on the left of Fig. 41. Note that the edges of the blade are slightly blurred, and the markers are 

no longer distinguishable. The average image has been effectively low-pass filtered by the blade jitter. 

As described previously, it is possible to locate the markers on each image and map the data so that it 

would align, then average. The process of locating the markers and mapping each image is very time 

Figure 40. Calibration of porous polymer (ISSI 

PP) and Turbo-Fib (another fast PSP) showing 

ideal behavior.

Figure 41. Automatic image registration.
32

consuming, and this is just the kind of process that should be avoided for efficient processing of PSP data. 

An alternative solution was implemented using ImageJ.31 

ImageJ is a Java based image processing package developed by NIH. A variety of user developed plugins can be downloaded, including an automatic image registration tool that operates on a stack of images. 

The image registration tool, StackReg,32 operates by computing a cross-correlation between the images 

and performing a mapping, such as a translation or solid body rotation to the image. As the blades are 

solid bodies, a simple translation or solid body rotation is sufficient for the program to align all the 

images at a given test condition. The result of a StackReg and average is shown on the right of Fig. 41. 

Note that the markers are now distinct, indicating a successful alignment. 

The data was registered and averaged using ImageJ. Once the images were aligned, the average Gate 1 

and Gate 2 image were computed, these are shown on the left of Fig. 42. The registered stack of Gate 1 

and Gate 2 images were then saved for processing, an example of an individual image pair is shown at the 

right of Fig. 42. Note that at this point, all images should be in alignment, thus greatly simplifying the 

conversion of the data to pressure. It should only be necessary to subtract backgrounds, ratio, and convert 

to relative pressure. 

Close inspection of the images in Fig. 42 does reveal several issues. Of most concern is that the signal 

near the tip of the blade is quite low. This was a result of poor lighting near the tip rather than the paint 

signal. Means to improve this lighting have been discussed in the section above. A second issue is the 

presence of a long lifetime florescence at several points on the blade. Near the rows of pressure taps, the 

blade was taped before spraying to mask the taps. It appears that the overspray may have leached some 

material out of the tape adhesive and left a residue near the edges. This residue is fluorescent, and has a 

relatively long lifetime as all signal is present in Gate 2. This signal is most notable as streaks that appear 

Figure 42. Registered and averaged images for the data set depicted in Fig. 23..
33

to lead the blade near the tap strips. It is also noted that a similar contaminate appears along the leading 

edge of the blade near the region of taper. No tape was used in this region, and therefore this is 

unexpected. The data in this region is likely compromised. 

With the images aligned and the wind-on average computed, the data can be converted to pressure. A 

Matlab script was written that loads the images, applies a 5 pixel low-pass filter, computes the ratio, and 

converts the results to relative pressure. For this data set, 44 image pairs were processed and the RMS 

pressure fluctuation was computed. The script operated in about 5 seconds, demonstrating the potential 

for real time data visualization using this approach. The resulting image of pressure fluctuations is shown 

in Fig. 43. 

Several comments regarding the data in Fig. 43 are relevant. The data indicate large amplitude of pressure 

fluctuations on the boundaries. This is likely an artifact of slightly misaligned images. The data also 

indicates a larger degree of unsteadiness at the tip, where the signal was low. To determine the validity of 

this data, it is necessary to estimate the uncertainty in the data. 

For this estimation, we will consider the shot noise to be the dominate factor. The signal in Gate 2 was 

quite low in this data set, about 2000 photo-electrons over the main part of the blade and as low as 500 

photo-electrons near the tip, and therefore, should dominate the shot noise. Assuming the use of a 5 pixel 

low pass filter, the shot noise from this tip region could be expected to be over 2400-Pa in amplitude. At 

most the amplitude of the pressure fluctuations are about 2-kPa on the main part of the blade and 5-kPa 

near the tip. Based on this rough estimation, it is likely that the pressure fluctuations shown in Fig. 43 are 

a result of poor signal-to-noise rather than real aerodynamic effects. 

Figure 43. Image of RMS pressure fluctuations at the tip.
34

Conclusions 

This study details a series of tests using PSP for the global pressure determination on the upper surface of 

rotorcraft blades in forward flight. These tests were performed using the General Rotor Model System 

installed in the 14- x 22-Foot Subsonic Tunnel at NASA Langley Research Center. Blades were painted 

with a porous polymer PSP formulation capable of routine frequency responses on the order of 5 kHz. 

The blades were instrumented with pressure transducers, with the actual blade used in the measurement 

instrumented with a row at 93% and 99% chord, respectively. 

For this testing, a laser-based data acquisition system was designed and deployed. This system is capable 

of obtaining near instantaneous data by exciting the paint with the laser and using an interline transfer 

camera to take a pair of images. With correct timing, the laser flash occurs at the end of the first gate with 

the majority of the excited-state decay being recorded by the second gate. This is analogous to the 

traditional lifetime-based approach in which two images are collected, one during the excitation pulse, 

and one after the pulse. 

Analysis of the data shows fairly good agreement (within 10%) of the pressure transducer measurements, 

though there are some issues that were encountered. First, care must be taken to ensure that the Kulite 

transducers are powered down for the wind-off images, as the temperature compensation of the 

transducers manifests as significant noise in the transducer area. Second, the rotational blur that is evident 

in the second image can limit the results, especially near the leading and trailing edges. A numerical 

method for compensating for this blur has been discussed and showed good results, though the edges are 

still suspect due to the addition of noise from the technique. Finally, if the entire upper surface of the 

blade is to be investigated, accounting for the temperature change across the blade is a must. Two 

methods for this were presented, and the best results occurred when TSP “striped” on the PSP blade were 

used for compensation. 

Even with these limitations, the data agreed both qualitatively and somewhat quantitatively with the 

expected results. To date, these are some of the first successful tests of PSP on flexible rotating surfaces 

capable of measuring dynamic phenomena. Further enhancements in the instrumentation, data acquisition, 

and data analysis areas are being investigated. 

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New York, 1999, pp. 239-242. 

13Engler, R., and Klein, C., “DLR PSP System: Intensity and Lifetime Measurements,” 17th International 

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31Available at http://rsb.info.nih.gov/ij/ 

32Available at http://bigwww.epfl.ch/thevenaz/stackreg/ 
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 4. TITLE AND SUBTITLE

Applying Pressure Sensitive Paint Technology to Rotor Blades 

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Watkins, Anthony N.; Leighty, Bradley D.; Lipford, William E.; Goodman, 

Kyle Z.; Crafton, Jim; Gregory, James W.

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NASA Langley Research Center

Hampton, VA 23681-2199

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14. ABSTRACT

This report will present details of a Pressure Sensitive Paint (PSP) system for measuring global surface pressures on rotorcrtaft 

blades in simulated forward flight at the 14- by 22-Foot Subsonic Tunnel at the NASA Langley Research Center. The basics of 

the PSP method will be discussed and the modifications that were needed to extend this technology for use on rotor blades. 

Results from a series of tests will also be presented as well as several areas of improvement that have been identified and are

currently being developed for future testing. 

15. SUBJECT TERMS

Global pressure measurement; Optical diagnositcs; Pressure sensitive paint; Rotorcraft; Temperature sensitive paint

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