NASA Technical Memorandum 107406 

Determination of Shed Ice Particle Size 

U sing High Speed Digital Imaging 

Howard Broughton, Jay Owens, and James J. Sims 

Cortez III Service Corporation 

Cleveland, Ohio 

Thomas H. Bond 

Lewis Research Center 

Cleveland, Ohio 

Prepared for 

AeroSense '96 

sponsored by the International Society for Optical Engineering 

Orlando, Florida, April 8-12, 1996 

National Aeronautics and 

Space Administration 

///-o~ 

0.2/300 

12.PJS 

I _J 
Trade names or manufacturers' names are used in this report for identification 

only. This usage does not constitute an official endorsement, either expressed 

or implied, by the National Aeronautics and Space Administration. 
L __ ~ 

.---- ' ._- ... _---- ----~ 

Determination of shed ice particle size using high speed 

digital imaging 

Howard Broughton, Jay Owens, James J. Sims 

Cortez III Service Corporation, Cleveland, Ohio 44135 

Thomas H. Bond 

NASA Lewis Research Center, Cleveland, Ohio 44135 

Abstract 

A full scale model of an aircraft engine inlet was 

tested at NASA Lewis Research Center's Icing 

Research Tunnel. Simulated natural ice sheds from 

the engine inlet lip were studied using high speed 

digital image acquisition and image analysis, 

Strategic camera placement integrated at the model 

design phase allowed the study of ice accretion on 

the inlet lip and the resulting shed ice particles at the 

aerodynamic interface plane at the rear of the inlet 

prior to engine ingestion. The resulting digital images 

were analyzed using commercial and proprietary 

software to determine the size of the ice particles 

that could potentially be ingested by the engine 

during a natural shedding event. A methodology was 

developed to calibrate the imaging system and insure 

consistent and accurate measurements of the ice 

particles for a wide range of icing conditions. 

Keywords: aircraft, icing, imaging, digital, 

calibrate, ice, high speed, particles, accretion 

1. Introduction 

In flight icing has been a hazard to aviation since its 

earliest days. Ingested ice has the potential to 

damage the engine requiring maintenance or overhaul 

and in severe cases, it can cause loss of power or 

engine flame out. Engine inlets typically have antiice systems on the leading edges and portions of the 

inlet to protect against ice buildup. Civilian aircraft 

are all required to comply to specific ice protection 

standards for the wing and inlet surfaces, including 

ice ingested foreign object damage (FOD) criteria for 

engine survivability. Military aircraft have ice 

protection and ice ingestion requirements based on 

the mission of the vehicle. In cases where there is a 

concern about the level of ice protection on and 

inside the inlet a determination needs to be made to 

assess the potential for ice ingested damage to the 

engine. One way to define the potential for damage is 

to quantify the size of the shed ice particles that shed 

off the inlet and duct surfaces in front of the engine. 

The use of sharp leading edges and a long sinuous 

inlet duct have raised a question about the final 

particle size of naturally shed ice and the benefit of 

particle breakup as it impacts the sides of the inlet 

duct as it travels down the body of the inlet. The 

purpose of the test described within this paper was to 

simulate the accretion and natural shedding of ice on 

an engine inlet, and by using imaging techniques 

assess the risk posed by the ingested particles. This 

was determined by measuring the shed ice particle 

size at a plane in the inlet where the engine section 

would begin. This plane is designated as the 

aerodynamic interface plane (AlP). 

The imaging of such phenomenon presents several 

challenging technical problems; determining the size, 

location, and distribution of large numbers of 

particles in a high velocity low temperature 

environment. The purpose of this paper is to describe 

in detail the steps taken toward solving this problem. 

This test was performed in March of 1995 in the 

NASA Lewis Research Center's Icing Research 

Tunnell (IRT). The IRT is the worlds largest 

refrigerated wind tunnel and has been a pioneering 

facility in the study of icing as it relates to aviation 

(see Figure 1). The imaging support for this test was 

provided by the Imaging Technology Center's 

Scientific Imaging Group. 

~ray bar / 

control /// 

room --

~hPfan ~D ( \ 

Shop Model """T access door ....J 

Figure 1.-Schematic of Icing Research Tunnel. 
2. Experimental 

The engine inlet duct was instrumented along its 

length with a variety of imaging systems. This 

included conventional RS-170 black and white video 

cameras with customized pinhole optics, and Kodak 

Ektapro high speed video systems utilizing remote 

imager heads. In all, two RS-170 cameras and two 

Kodak Ektapro EM (electronic memory) systems 

were mounted directly to the inlet duct, with two 

additional Kodak Ektapro EM high speed video 

systems located outside the test section. 

Attachment points for all imaging hardware and 

environmental enclosures, as well as window size 

and placement, were designated during the model 

design phase. Steel mounting plates were embedded 

into the fiberglass resin of the model during 

fabrication, providing solid attachment points for all 

imagers and environmental boxes. Electrically heated 

windows measure one foot square and 3/4 inches 

thick were installed at the AIP to provide clear views 

for the imagers even under the most severe icing 

conditions. A large area between these two Ektapro 

imagers was designated for illumination, which 

contained several individually reinforced halogen 

lamps which reflected off the inside of the enclosure 

in order to provide a diffused, flat illumination. 

Due to the severe environmental conditions inside the 

test section all imaging hardware and lighting 

assemblies attached directly to the inlet model had to 

be ruggedized and protected. This was accomplished 

by designing and fabricating enclosures to seal out 

moisture and maintain internal operating temperatures by means of electric heaters. Additionally, the 

enclosures required aerodynamic profiles to reduce 

model vibration and drag. 

All four Kodak Ektapro EM intensified imagers were 

used to capture views of ice particles as they shed off 

the front lip of the inlet and traveled inside the duct 

to the AIP section. Two imagers (EM3 and EM4) 

were placed at the front of the model to view the ice 

as it shed from the inlet lip (see Figure 3). EM4 

viewed the upper lip of the leading edge while EM3 

viewed the inboard side of the leading edge. 

__ 

EM4 -" 

~l ( 

Figure 2.-Side view of inlet. 

2 

South 

wall 

Imaging Control Room 

Figure 3.-Top view of inlet. 

The other two Kodak Ektapro imagers (EM! and 

EM2) were placed at AIP, just ahead of the location 

of the engine (see Figure 3). It is here that the 

magnitude of the ice particle size is critical. These 

two cameras were placed orthogonal to each other 

and mounted on the outside of the inlet. 

Ektapro 

Heated window 

Inlet duct 

AlP 

.. Flow 

Figure 4.-Camera position at AlP. 

As shown in Figure 4, the imager heads were 

mounted parallel to the inlet with first surface mirrors 

mounted 45 degrees relative to the target to reflect 

the area of interest into each imager. Both 

imager/mirror assemblies were then protected by 

environmental enclosures and instrumented with 

thermocouples to monitor and maintain operating 

temperatures. 

Natural shedding events are unpredictable and 

difficult to capture. Therefore, a pneumatic de-icing 

boot with larger tubes than conventional pneumatic 

systems was attached to the inlet lip and used to 

release the accreted ice to simulate a natural 

shedding event. The Ektrapro imaging systems were 

triggered to initiate the image by the signal to fire the 

pneumatic de-icing boot. This allowed the high speed 

imaging systems to capture the ice at the moment it 

was in the field of view. 
2.1 Digital acquisition 

Video 

EktaPro 

EM 

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CD 

writer 

Figure 5.-Digital acquisition schematic. 

The hardware for the acquisition consisted of four 

pentium computers connected via GPIB interfaces to 

the four Kodak Ektapro EMs. Each electronic memory 

(EM) unit stored a total of 5000 images at a rate of 

1000 frames per second. After a shedding event was 

recorded the images were transferred from the EM's 

volatile RAM memory to the internal hard drive of 

the host computers using Kodak's custom transfer 

utility. Once several sessions of images from different 

experimental runs were stored on the internal hard 

drive they were written to CD-ROM for storage. 

Finally the image files were transferred to an external 

hard drive where they remained as a back up to the 

CDs. Each pair of computers utilized one CD writer 

via a SCSI switch allowing the user to switch 

between each computer for the writing process (see 

Figure 5). At the conclusion of the experiment 

approximately five gigabytes of image data had been 

stored onto several CD-ROMs. 

2.2 Description of imaging zones 

There are three types of regions at the engine plane 

(AIP section) where an ice particle may be viewed 

(see Figure 6). There is the sweet spot, where a 

particle is located in the view of both cameras, the 

upper zones where a particle can only be seen by one 

camera, the lower zones where a particle is down 

along the side of the inlet in the view of only one 

camera. Finally there are the dead zones, near the top 

of the inlet where a particle cannot be seen by either 

camera. 

3 

Upper 

zone 2 

Lower 

zone 1 

Dead 

zone 

Sweet 

spot 

-

Upper 

zone 1 

zone 

Lower 

zone 2 

Figure 6.-Cross-sectional view of inlet and zones. 

The sweet spot zone provides for the most accurate 

determination of the particle location, while the 

upper and lower zones allow for the location of the 

ice particle to be determined within a specific error 

range. It is impossible to determine if there are 

particles in the dead zones because neither camera 

views those areas. 

2.3 Grid shots/scaling factor/calibration 

Before any measurement of ice particle size could be 

performed each of the cameras had to be calibrated. 

This calibration procedure provided a scaling factor 

used to transform measurements of pixels in the digital images to inches. This could be done analytically 

by utilizing the magnification of the imaging system 

and the known distance to the target. However, it was 

decided to obtain a scaling factor experimentally in 

order to detect and correct for any nonlinear effects 

that may influence the size of the particle. 

To obtain the data needed to calculate a scaling 

factor a known size target must be imaged and 

measured. In our case a white panel with black 

squares measuring 2.75 inches with 0.25 inch lines 

was constructed (see Figure 7). This grid board was 

placed in the field of view perpendicular to each 

camera. Each time a grid image was captured the 

distance from the grid to the camera sensor was 

recorded. This process was repeated through a series 

of different distances for each camera. 
Figure 7.-Typical grid shot. 

The scaling factor is determined by measuring a 

single grid square in inches and dividing this value by 

the square size in pixels from the digital image. This 

provides a discrete scaling factor for that particular 

~stanc~ from the camera. The scaling factor, or pixel 

pItch, IS the number of pixels in one inch at a 

particular distance based on the magnification of the 

imaging system. For example, given that the width of 

one black square and a single white line of the grid 

combined is three inches, and the grid board is 

imaged 45 inches away from the camera, that same 

black square and line will measure 21 pixels in the 

digital image. Therefore, each pixel will represent 

0.143 inches in the image (see equation 1) in this 

case. 

S / 0 F grid square size (inches) ca mg actor = 0 ° (1) gnd square size (pixels) 

A scaling factor was calculated for each grid shot and 

the discrete values plotted as a function of distance. 

A best-fit equation was then used to determine the 

scaling factor for any given distance from the camera. 

This calibration procedure was performed for each of 

the Kodak Ektapro cameras. 

2.4 Determining measurable particles 

During the acquisition portion of the experiment a 

total of 109,206 individual images were saved to 

CD-ROM for analysis. This amount of data proved to 

be very difficult to handle and it was apparent that a 

method had to be developed to view the images 

easily to determine which images held the most 

significant ice particles. Using Kodak ShoeBoxTM, an 

image cataloging application, an entire run (session) 

could be loaded and viewed (see Figure 8). Each run 

had between 500 to 5000 images of which only about 

200 would be selected for particle analysis. With this 

application one could load the entire run, quickly 

view all the images, select images with significant 

shed ice, and catalog only those images for subsequent analysis. 

4 

Figure B.-Determining measurable particles. 

2.5 Sweet spoUparticle distance 

To determine if a particle resides in the sweet spot, 

the runs from both AIP cameras were loaded into 

Kodak ShoeBoxTM on separate computers that were 

positioned side by side. This enabled the user to view 

both runs simultaneously to determine if a given 

particle can be seen in both camera views. Additionally each run was loaded onto a Silicon Graphics 

workstation and the images were played at video 

speed to view a sweet spot particle in motion. Both 

methods of sweet spot particle identification proved 

to be effective. Once a particle was deter-mined to be 

in the sweet spot its spatial location was determined 

by concepti ally dividing the region into a crosshatched, grid zone based on the distance and 

magnification of both cameras. This spatial location 

was then measured using a grid ruler. 

EM 1 EM2 

Figure 9.-EM1 and EM2 image orientation in inlet. 
The grid ruler was constructed from a grid shot taken 

at the furthest point from the camera. This was 

displayed on the computer monitor and enlarged. A 

cardboard square ruler was fabricated to match the 

scale of the grid board lines across the top and side of 

the image (see Figure 10). Because the grid ruler has 

the same dimensions as the grid shot in Figure 7: 

Typical grid shot the measurement procedure is 

analogous to overlaying the grid shot on the particle 

image and determine which square the particle 

resides in. 

Figure 10.-Construction of grid ruler. 

The use of the grid ruler provided for the quick 

location of a particle in the field of view. An image 

with a measurable particle in the sweet spot was read 

from the CD-ROM and enlarged to the exact size as 

the grid was previously. The grid ruler was then 

placed on the monitor and aligned to the frame of the 

image. The number of squares (tic marks) from the 

comer of the ruler to the square where the particle 

Figure 11.-Particle and grid ruler. 

5 

resides, are counted to provide the distance from the 

bottom of the inlet (see Figure 11). 

To calculate the distance from the bottom of the inlet 

to the particle simply multiply the number of tic 

marks by three inches, the width of one square and 

line. Then subtract this distance from 39.8 inches, the 

farthest grid board distance, giving you the distance 

from the particle to the camera sensor. All ice in the 

sweet spot were measured utilizing this method. 

2.6 Upper and lower zones I Particle distance 

A particle resides in the upper or lower zone if it 

appears in ooly one of the two camera views. 

Determination of whether the particle resides in the 

upper or lower zone is made on the bases of particle 

illumination and velocity. The lighting originates 

from the top of the inlet directly between both 

cameras, therefore ice particles in the upper zones 

are very close to the light source and achieve near 

maximum intensity when digitized. Particles in the 

lower zones receive less illumination due to 

increased distance from the light source and achieve 

a middle to low range intensity value. The determination of upper and lower zone particles were 

made visually based on this intensity difference. 

Additionally particles in the upper zones appeared to 

move very rapidly because of their closeness to the 

camera, while lower zone particles appeared to move 

slowly. This second method of zone determination 

acted as a verification of particle location. The size 

of a particle that resides in the upper or lower zones 

could not be calculated using the same method as the 

sweet spot region because of the inability to 

triangulate on the particle. The particles were 

calculated within an error bound based on the upper 

and lower and lower zone distances from the camera 

sensor (see Figure 12). 

±13% 

Upper 

zone 2 

Lower 

zone 1 

Dead 

zone 

Sweet 

spot 

-

±13 0 

Upp' 

e1 

zone 

Lower 

zone 2 

Figure 12.-Error analysis for upper and lower zones. 
The error due to only one camera view of the particle 

can be quantified for both the upper and lower zones. 

In the lower zone the farthest distance from the 

camera sensor D2 (Figure 13) to the bottom of 

the intake is 47.8 inches, with a scaling factor of 

0.15 inches/pixel. 

Figure 13.-Calculation of error bound. 

The distance from EM 1 to the boundary between the 

lower zone and the sweet spot is approximately 

36.0 inches Dl , with a scaling factor of 0.11 

inches/pixel (see Figure 13). The Error Per Pixel 

(EPP) was calculated using equation 2 resulting in 

the percentage error for the entire region of ±13 %. 

[1-( D1 )]* 100 

EPP= D2 

2 

(2) 

The EPP for the upper zones were determined in the 

same manner. Since the scaling factors were linear 

with respect to distance, and the relative difference 

between the extremes of the upper and lower zones 

were similar, the EPP for both zones are the same. 

2.7 Particle size 

Particle size determination was made using a 

commercial image analysis package called Sigma 

ScanlImageTM. This application allows the user to 

make very quick and precise measurements with the 

added feature of compiling all the data into a 

convenient format for statistical analysis. A main 

goal in the measurement methodology was to minimize human judgment associated with setting the 

threshold values which ultimately cause variability in 

the data. 

6 

A method was developed based on thresholding the 

image. Normal thresholding allows the user to set a 

threshold value such that all the intensities above the 

threshold value go to maximum white (255) and all 

the intensities below that value go to black (0). This 

threshold technique is adaptable to the variation of 

particle intensity found within the digitized images. 

Threshold 

value 

High 

Z' 

'iii 

c: 

Q) 

..... 

.E 

Low 

Idealedge / 

/ 

Pixels 

Imaged 

/ edge 

Figure 14.-Traditional thresholding effects on image 

size. 

Figure 14 shows the effects that traditional threshold 

has on the size of the particle being measured. The 

center graphic shows an ideal edge and the edge 

once it has been imaged. The imaged edge has a 

slope with a variation in intensity, whereas the ideal 

edge has a single intensity with an abrupt change to 

no intensity. Where the imaged and ideal edges 

intersect is the proper threshold value one would 

apply to the digitized edge to regain the proper sized 

ideal edge. The upper left graphic shows the result of 

setting too low a threshold value, resulting in the 

particle appearing larger than actual size. The upper 

right graphic shows the effect of setting too high a 

threshold value which results in a smaller particle 

size. Figure 15 shows the effect on particle size 

utilizing a single threshold value for the entire image. 

Setting a threshold value too low includes much of 

background as ice particle data, whereas selecting a 

threshold value too high excludes particles that 

should be part of the data set. 

There are a number problems with utilizing 

traditional thresholding. First the user is allowed to 

make an assumption or judgment of where the proper 

threshold value lies in relation to the entire image. 

Secondly, a single threshold value for the entire 

image results in false particle sizes due to uneven 

illumination across the field of view. Finally, the 

threshold value is selected by the user according to 

their personal perception of how the ice particle 

should look like. This can certainly create 

consistency problem for a single user from one image 

to the next, and a repeatability problem for multiple 
Actual Low 

Medium High 

Figure 15.-Traditional threshold values applied to 

particle images. 

users who analyze the same images. The ideal case 

is to make a measurement based upon a flexible 

parameter that maintains consistency throughout the 

experiment and has the ability to be applied to an 

individual particle regardless of the variation in 

illumination. Using Sigma Scan's auto threshold 

feature, a user is able to apply a percentage threshold 

as a function of the maximum intensity in the ice 

particle. 

The correct percentage to threshold the ice particles 

was determined by utilizing the 2X2 inch white 

reference squares painted on the bottom and sides of 

the inlet. With these known targets several threshold 

settings were applied to a small set of images 

initially. A 70 percent threshold value provided the 

closest to the actual size of the white squares. 

Figure 16 shows the distribution when the algorithm 

was applied to two hundred images of the reference 

squares from a variety of icing conditions. 

To make a size measurement the brightest pixel of 

the measured particle is identified and all pixels at 

and above the selected percentage of the maximum 

intensity value are thresholded, and the rest of the 

image remains unchanged. For example, if a selected 

ice particle has a maximum intensity of 100 and the 

threshold percentage is set to 70%, then every pxiel 

with a value of 70 or more within that particle would 

be counted for the total area measurement. 

This process was repeated for each particle and the 

total area data placed into a spreadsheet. The length 

and width of the particles were also measured 

because a particle may be 25 pixels in area, but only 

1 or 2 pixels wide, and therefore a fragile sliver able 

to slip between the turbine blades. On the other hand 

a block of ice 5 pixels by 5 pixels has a much higher 

potential to cause engine damage. These two 

7 

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2.0 2.5 3.0 3.5 4.0 4.5 5.0 

Area, sq. in. 

Figure 16.-Calibration white square test data. 

particles have the same area, but present very 

different potential damage criteria for ice ingestion. 

3. Discussion 

Several aspects of this project became evident early 

in the design of the inlet model. It was critical to the 

success of the experiment that the hardware and 

mounting points for imaging equipment be designed 

and integrated into the model during manufacture. 

This reduced the additional time normally required to 

fabricate mounting hardware during the model 

installation and buildup allowing more time to be 

spent on productive testing. Additionally, the nature 

of the necessary views was so complex, trying to 

integrate equipment after manufacture would have 

been impossible. Finally, this project proved to be the 

most extensive use of imaging hardware operating 

under severe environmental conditions that the Icing 

Tunnel and the Scientific Imaging Group has ever 

conducted. 

Considering the number of data points requested and 

the complexity of the data gathering system, an effort 

was made to utilize as much automation and commercial hardware and software as possible. Image 

analysis proved to be the most challenging and time 

consuming portion of the research, requiring the use 

of several software packages along with developing 

customized methodologies. 

During the course of this project several possible 

improvements were noted for future tests of this kind. 

In order to image the dead zones, modifications to the 

aft section could be incorporated. Also, optoelectronic solutions have been proposed eliminating the 

need and storage for the images. 
4. Conclusion 

The techniques in this paper represent an icing test in 

which severe environmental conditions, high speed 

imaging technology, data analysis methods, computer 

and related storage technology pushed the state-ofthe-art for shed ice particle visualization. 

Advances in aerospace technology and aircraft design 

often necessitate testing under adverse conditions 

such as those created in the Icing Research Tunnel at 

NASA Lewis. The results of this test are a product of 

the continued development of complex imaging systems and data analysis techniques to meet the needs 

of the IRT by the Scientific Imaging Group at NASA 

Lewis. 

8 

5. References 

1. Soeder, R.H. and Andracchio, C. R.: NASA Lewis 

Icing Research Tunnel User Manual, NASA 

TM-102319, June 1990. 

6. Acknowledgments 

The authors would like to thank interns Michele Hill 

and Joshua Greenwald of the Rochester Institute of 

Technology for their assistance in the data acquisition and image analysis portions of the experiment. 

We would also like to thank Tammy Langhals for 

verifying our particle size data. 

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Determination of Shed Ice Particle Size Using High Speed Digital Imaging 

6. AUTHOR(S) WU-505-68-10 

Howard Broughton, Jay Owens, James J. Sims, and Thomas H. Bond 

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION 

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National Aeronautics and Space Administration 

Lewis Research Center E-10618 

Cleveland, Ohio 44135-3191 

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AGENCY REPORT NUMBER 

National Aeronautics and Space Administration 

Washington, DC 20546-0001 NASA TM- 107406 

11. SUPPLEMENTARY NOTES 

Prepared for AeroSense '96 sponsored by the International Society for Optical Engineering, Orlando, Florida, April 8-12, 1996. 

Howard Broughton, Jay Owens, and James J. Sims, Cortez ill Service Corporation, 21000 Brookpark Road, Cleveland, Ohio 44135 

(work funded by NASA Contract NAS3- 24816); Thomas H. Bond, NASA Lewis Research Center. Responsible person, Thomas H. 

Bond, organization code 5840, (216) 433- 3414. 

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Unclassified -Unlimited 

Subject Categories 74, 01 , 02, 60, and 61 

This publication is available from the NASA Center for AeroSpace Information, (301) 621-0390. 

13. ABSTRACT (Maximum 200 words) 

A full scale model of an aircraft engine inlet was tested at NASA Lewis Research Center's Icing Research Tunnel. 

Simulated natural ice sheds from the engine inlet lip were studied using high speed digital image acquisition and image 

analysis. Strategic camera placement integrated at the model design phase allowed the study of ice accretion on the inlet 

lip and the resulting shed ice particles at the aerodynamic interface plane at the rear of the inlet prior to engine ingestion. 

The resulting digital images were analyzed using commercial and proprietary software to determine the size of the ice 

particles that could potentially be ingested by the engine during a natural shedding event. A methodology was developed to 

calibrate the imaging system and insure consistent and accurate measurements of the ice particles for a wide range of icing 

conditions. 

14. SUBJECT TERMS 15. NUMBER OF PAGES 

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Ice; Tunnel; Aircraft icing; High speed; Digital; Imaging 16. PRICE CODE 

A02 

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