Ali Abdul-Aziz

Cleveland State University, Cleveland, Ohio

Ben S. Curatolo and Mark R. Woike

Glenn Research Center, Cleveland, Ohio

Improving Data Collection and Analysis Interface 

for the Data Acquisition Software of the Spin

Laboratory at NASA Glenn Research Center

NASA/TM—2011-217214

September 2011
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Ali Abdul-Aziz

Cleveland State University, Cleveland, Ohio

Ben S. Curatolo and Mark R. Woike

Glenn Research Center, Cleveland, Ohio

Improving Data Collection and Analysis Interface 

for the Data Acquisition Software of the Spin

Laboratory at NASA Glenn Research Center

NASA/TM—2011-217214

September 2011

National Aeronautics and

Space Administration

Glenn Research Center

Cleveland, Ohio 44135
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NASA/TM—2011-217214 1 

Improving Data Collection and Analysis Interface for the Data Acquisition 

Software of the Spin Laboratory at NASA Glenn Research Center 

Ali Abdul-Aziz 

Cleveland State University 

Cleveland, Ohio 44115 

Ben S. Curatolo1

 and Mark R. Woike 

National Aeronautics and Space Administration 

Glenn Research Center 

Cleveland, Ohio 44135 

Abstract 

In jet engines, turbines spin at high rotational speeds. The forces generated from these high speeds make 

the rotating components of the turbines susceptible to developing cracks that can lead to major engine 

failures. The current inspection technologies only allow periodic examinations to check for cracks and other 

anomalies due to the requirements involved, which often necessitate entire engine disassembly. Also, many 

of these technologies cannot detect cracks that are below the surface or closed when the crack is at rest. 

Therefore, to overcome these limitations, efforts at NASA Glenn Research Center are underway to develop 

techniques and algorithms to detect cracks in rotating engine components. As a part of these activities, a 

high-precision spin laboratory is being utilized to expand and conduct highly specialized tests to develop 

methodologies that can assist in detecting predetermined cracks in a rotating turbine engine rotor. 

This paper discusses the various features involved in the ongoing testing at the spin laboratory and 

elaborates on its functionality and on the supporting data system tools needed to enable successfully 

running optimal tests and collecting accurate results. The data acquisition system and the associated 

software were updated and customized to adapt to the changes implemented on the test rig system and to 

accommodate the data produced by various sensor technologies. Discussion and presentation of these 

updates and the new attributes implemented are herein reported. 

Introduction 

The theory behind the crack detection scheme is that a crack, or some other related condition, will 

cause a shift in the center of mass of the disk, thus modifying the turbine disk’s vibrational characteristics 

compared with those typically experienced by an undamaged turbine disk. Earlier work on this research 

covered running spin tests of a 32-blade disk that simulated a turbine engine-like rotor, where tip 

clearance measurements were collected using capacitive sensors (Refs. 1 to 4). These tests were 

conducted to help establish a crack detection methodology to monitor the health of rotating aircraft engine 

components. This is to improve safety and lower maintenance costs. Typically, health monitoring systems 

require a sensor system that must sustain operation in a harsh engine environment. For rotors, the sensor 

and software must be able to detect a crack above a pre-specified size, but below a critical length that 

would lead to failure. The intended health management system should operate independently and act 

neutrally upon the overall performance of the engine system and not interfere with engine maintenance 

operations. Presently, there are research activities and many techniques that are being used in the 

detection of any cracks that may have formed before failure (Refs. 5 to 10). These techniques are limited 

to applying nondestructive evaluation (NDE) approaches. However, their effectiveness and reliability 

vary substantially depending on the inspection conditions (Ref. 1). This highlights the need for more 

 

 

1

NASA Glenn Research Center, John Carroll University, summer intern. 
NASA/TM—2011-217214 2 

trusty and reliable diagnostic tools for damage detection and health monitoring of the rotating components 

to ensure engine safety and dependability. Besides improving safety, health monitoring can also reduce 

maintenance costs. 

The NASA Aviation Safety Program (AvSP) recognizes that issues regarding safety and 

maintainability are of high concern, so efforts to develop the needed technology are ongoing. This 

ambitious program is a partnership that includes NASA, the Federal Aviation Administration (FAA), the 

aviation industry, and the Department of Defense (Ref. 2). Developing health management and ultrasafe 

engine technologies are the primary goals of this project. 

This paper discusses the spin rig capabilities, hardware upgrades, and data acquisition software 

updates. These upgrades include eddy current sensors for measuring shaft displacement positions and 

enhancement of the usability of the LabVIEW (Ref. 12) data-acquisition-based software by integrating 

three modules into one single cohesive entity written in the most current version of LabVIEW. Discussion 

and presentations of these updates and the new attributes implemented are summarized in this report. 

Spin Laboratory Description 

Figure 1(a) shows a full layout of the Rotor Dynamics Laboratory along with all the equipment. The 

spin laboratory operates under specified conditions and it allows the disk rotor to be rotated at variable 

speeds at various conditions and at settings that are monitored by the operator via a series of equipment 

and the data acquisition system. A picture showing an artificially induced crack-notch in the disk, along 

with the blade tip clearance probe, is shown in Figure 1(b). The test specimen disk has an outside 

diameter of 23.495 cm (9.25 in.); a bore and an outside rim thickness of 2.54 cm (1 in.) and 3.175 cm 

(1.25 in.). The thickness of the web is 0.254 cm (0.10 in.), and the cross section and height of the blades 

are 3.175 by 0.330 cm (1.25 by 0.13 in.) and 0.838 cm (0.33 in.), respectively. The disk rotor has 32 

blades evenly spaced around the circumference. 

Eight holes with a 0.508 cm (0.20 in.) diameter each were drilled through the disk halfway in the rim. 

The holes were spaced every 45° and were designed for future studies as possible mass attachment points 

or notch initiation sites. The weight of the disk is (4.88 KG) 10.75 lb and the materials being used for 

manufacturing the disk are nickel-base alloy Haynes X–750 and Grade 2 Titanium; test specimens were 

made for each material. Additional details about the system can be found in Reference 3. 

 a) Spin laboratory layout b) Test disk with a notch 

Figure 1.―Rotor dynamics spin laboratory equipment layout and the disk specimen. 

Shielding

Capacitive 

probe

In-line 12 HP, 

electric motor

Subscale disk

Rolling element 

bearing

Adjustable 

damper

Tachometer
NASA/TM—2011-217214 3 

Data Acquisition Software Description 

The data acquisition software in the spin rig setup is considered the focal element in terms of data 

acquisition and analysis. The previous data collection routine utilized LabVIEW Version 6 (Ref. 11) 

based software and consisted of three different subroutines each with a separate function. They are simply 

a collection of functions introduced in Virtual Instrument (VI) modules or front end panels. The purpose 

of such tools and programming is to automate the usage of processing and measuring equipment in the 

laboratory setup. However, the previous data collection routine lacks flexibility and robustness. It is very 

primitive and uses an old file format that requires a long processing time to analyze and sort data. In 

addition, the files produced during data acquisition are relatively large and processing time is dependent 

on test length and mission profile complexity. For instance, for a simple 10-min, 3000-rpm test 

acquisition run, data processing and analysis takes 541 sec, or approximately 9 min. This deficiency 

created an undesired situation and caused holdups in evaluating the results and delays in testing. 

Simultaneously with the continuous equipment upgrades, such as new sensors, digital tachometers, 

high-speed cameras, etc., the LabVIEW-based data acquisition software needed to be modified to 

accommodate the changes made. Figures 2(a) and (b) show the original and the currently updated data 

logger front panel VI for recording the data measurements. The original setup consisted of three programs. 

The data logger, or the first VI, functioned as a standalone unit that recorded measurements and readings 

from the sensors and other instruments. The second VI, also known as the reader, was used to analyze, sort, 

and convert the raw data voltage readings into meaningful units. The last VI module, referred to as the 

display, allows the representation of the results in graphical charts, such as the trace of vibration vector, X 

and Y components, blade tip clearance, rotational speed versus time, blade time of arrival, amplitude, and 

phase angle. Figure 2(b), which represents a view of the updated front panel, has all of the previously 

mentioned options combined into one single panel that displays more selections with greater details. 

Therefore, the need for a more efficient VI module to overcome all of the later difficulties and enable the 

use of the latest programming technology and tools available was a necessary option to pursue. 

 a) Original display b) Updated display 

Figure 2.―Display of the front end data logger VI. 
NASA/TM—2011-217214 4 

Software Enhancements and Updates 

To overcome the above difficulties in the data analysis and processing, a complete restructuring of the 

three LabVIEW programs front panels was implemented. A major shift in the file format was adopted by 

switching from the standard old high-speed data logger (HSDL) format (LabVIEW Version 6.0) to the 

newer technical data management streaming (TDMS) format, in the latest LabVIEW version, that is, 

LabVIEW 9.0. National Instruments (NI) introduced the Technical Data Management Streaming (TDMS) 

file format as a result of the deficiencies of other data storage options commonly used in test and 

measurement applications. The binary TDMS file format is an easily exchangeable, inherently structured, 

high-speed-streaming-capable file format that, when combined with the other technologies in the NI TDM 

solution, becomes quickly searchable without the need for complicated and expensive database design, 

architecture, or maintenance (Ref. 12). 

Figure 3 shows a display of the new and improved front panel VI that includes all of the three original 

programs or VIs. The data reader option tab, shown in the figure, reads the newly installed eddy current 

sensors. Improvements and updates consist of making the displays interactive and adding the capability of 

simultaneously overlaying two data sets during analysis. Options to include additional sensors and the 

ability to perform signal processing on raw data are examples of the new features that have been added. This 

version of the software is automated such that upon completion of logging or recording the data, the 

software will automatically activate the reader, and subsequently the display and the eddy current data 

analyzer, respectively. The user will only have to perform periodic monitoring and save the results files as 

prompted during the analysis process. Interactive displays of critical testing information are also displayed 

in real time during the analysis procedure. The graphs in Figure 3 show signal processing of voltage data 

and the sinusoidal response, blade tip clearance, speed versus time, and critical speed response in addition to 

many other parameters that are of importance to testing. Such information is highly essential and beneficial 

to the success of test runs and proper achievements of anticipated results. Furthermore, the front end 

contained functions to display, record, and input various parameters. Examples of such parameters are dates, 

clock time test time, test length, scanning rate, experimental constraints and limits, hardware identification 

channels and settings, buffer size, image captures, report generation, critical speed and center of mass 

calculations, performance data of the equipment (e.g., voltage and temperature), as well as other important 

statistics. Data file directory names and locations are also displayed. 

Figure 3.―Data acquisition software front end display. 

One single main

function module
NASA/TM—2011-217214 5 

Figure 4 represents a sample output display of the newly updated software. As noted, the display is 

widely diversified and offers an ample range of information. It is designed to show various results in 

different representations and other relevant test data. The software displays are interactive and the 

software has the capability of simultaneously overlaying two data sets during analysis. This feature has 

simplified the comparison of test results and characterization of the findings with a higher level of 

accuracy than was previously attainable. An action window, identified as the Data Analysis Progress 

Display in Figure 4, has also been added to the VI display to monitor the elapsed processing time and 

completion percentage. Such options greatly assisted in the data processing, analysis, and time 

management. Options to include additional sensors and the ability to perform signal processing on raw 

data are also examples of new software features that have been added (see Fig. 5). 

Figure 5 represents an output display showing the newly added feature of sensor reader of both eddy 

current and capacitive sensors. The earlier version of the software lacked this option due to the 

nonexistence of the eddy current sensors. The eddy current sensor monitors the rotating shaft 

displacement and the capacitive one observes the rotor blade tip displacement. Such addition has added a 

much needed attribute to the software capabilities and to the experimental capacities. The sensors reader 

display allows the user to monitor the sensors response and other information related to the files directory, 

storage locations, experimental outputs, etc. 

Figure 4.―Data acquisition software sample output display. 

Figure 5.―Data acquisition sample output display showing eddy current response. 

Data Analysis

ProgressDisplay

Trace of Vibration vector, 

X-Y Plot (in.Vs.in) Mission Profile

Vibration Amplitude 

(In.vs. Rpm)

Vibration Phase 

(degree Vs. Rpm)

Eddy Current

Sensor Response

Capacitive

Sensor Response

Directory, Files

allocations and

storage info.
NASA/TM—2011-217214 6 

Figure 6.―Data acquisition hardware system diagram. 

TABLE I.―DATA COMPARISON AND TIME SAVING RATE USING THE UPDATED HARDWARE 

Transient spin test Data file 

size, MB 

Old software processing 

time, sec 

New software processing 

time, sec 

Time saving rate, 

percent 

Old 3000 rpm 159 541 284 47 

Old 5000 rpm 195 910 478 47 

New 3000 rpm 219 541 304 44 

New 5000 rpm 260 910 476 48 

10 000 rpm 1188 3504 1501 57 

Figure 6 represents the data acquisition system hardware diagram. It contains one set of capacitive 

sensors, a digital tachometer, a preamplifier, and an analog processor. Data is recorded from the sensors at 

a rate of 1 MHz per channel. The output of the analog processor was interfaced with a NI controller 

having a Windows XP-based NI PXI–1042Q chassis with core 2 capacity, a T6400 2.13-GHz processor, 

and 4 GB of RAM. The PXI–1042Q was the best NI controller available; higher capacity systems were 

not available when the spin rig was being upgraded. The prior system was a PXI–8171 series with a 

maximum of 1.266 GHz and a memory size of 512 KB RAM. This had resulted in a noticeable reduction 

of processing time. 

The updated software capabilities were checked against the old data acquisition routine. Several spin 

tests were conducted to gather enough data to enable verification of the robustness and the efficiency of 

the updated software. The speed applied during the current testing ranged from a minimum of 3000 rpm 

up to a maximum of 10 000 rpm, with acceleration-deceleration rates of 60 rpm/sec. This speed range 

ensured surpassing the critical speed of 2610 rpm leading to post-critical state, which is the state where 

the system reaches stability without any systemic vibration. Table I contains a display of the results of test 

data comparisons for various rotational speeds and test times using the upgraded computer hardware, the 

PXI–1042Q. An obvious improvement can be noted as a nearly 50 percent decrease in processing time 

was achieved. For instance, for the 10 000 rpm test, data processing required 3504 sec or 58.4 min. The 

newly updated routine resulted in a 57 percent reduction in processing time, which equates to 33.4 min. 

This delivered a tremendous outcome resulting in increased testing capability and faster data, which in 

return helped expanding the productivity of experiments. The effectiveness of the algorithms employed in 

managing and sorting the data has facilitated and minimized the workload enormously. One disadvantage 

of using the TDMS file format lies in its tendency to generate larger file sizes than the compressed HSDL. 

However, this constituted no major issue since vastly larger data storage devices are now easily available 

and are relatively very inexpensive. 

 

In      0       1       2       3

Aerogage

Model HP‐04

H1 Band Preamp

Out   0       1       2      3

Aerogage

Model AP‐02

Analog Processor

In     0      1       2      3       Out

XP‐basedNI PXI‐1042QNI PXI‐6115

NI PXI‐4495

NI PXI‐8106

embedded

controller

Back Capacitive Sensor

Front Capacitive Sensor

HT‐5200 Digital Tachometer
NASA/TM—2011-217214 7 

TABLE II.―DATA COMPARISON AND TIME SAVING RATE BETWEEN OLD AND NEW HARDWARE 

FOR EQUAL SIZE DATA FILES 

Spin test Data file size,

KB

New software 

processing time, 

sec 

Old software 

processing time, 

sec 

Time saving 

rate, 

percent 

Computer hardware 

10 000 rpm 

transient (short 

test) 

1 142 579 695 885 21.45 Updated 

PXI–1042Q 

10 000 rpm 

transient (short 

test) 

1 142 579 N/A 14 220 95 Old PXI–8171 series 

Figure 7.―Typical test mission history profile; variable amplitude. 

Table II shows a comparison of data processing time for test results of data files that are of equal size 

for the two NI systems used, outdated older and new updated. In fact, the data listed in Table II clearly 

shows that the updated hardware has made a substantial improvement to the data processing acquisition 

time. For instance, for a 10 000 rpm transient test, its data file size of 1 142 579-KB processing time is 

reduced by 21 percent from 885 to 695 sec by using the updated PXI–1042Q system. Furthermore, for the 

same 10 000 rpm transient test, the difference between the old data acquisition system and the updated 

one has shown that the processing time has been reduced by 95 percent from a high of 14 220 sec to a low 

of 695 sec. Therefore, the combination of both the updated hardware system and the new software has 

offered remarkable and much needed improvements to the testing procedure and resulted in hefty time 

saving in the data collection and processing time. 

In addition, testing indicated that the memory limitation of the PXI–1042Q, a maximum of 4 GB of 

RAM, had impacted the performance of the data processing to some extent. Also, adding the capability to 

log data from the eddy current sensor has made the software far more user friendly than the initial data 

logger routine. With the updated layout, the user is able to completely process and analyze the data using 

a single screen window. Figure 7 shows a typical test mission history test profile indicating the 

complexity of the test and the time required for completion. The total time needed to wrap up this test 

required 970 sec of data collection and over 4 GB of data storage. 

Conclusions and Future Work 

The necessity of coordinating the results from separate applications was removed by integrating the 

functions of the three applications into one new program. The updated program has the ability to record 

and process data from eddy current sensors in parallel with the already existing capacitive sensors. New 

program features include the ability to display data from two different trial runs simultaneously to aid in 

data analysis. The addition of center of mass and critical speed disk calculations enhanced the software 

Time, Seconds

0 200 400 600 800 1000

Rotaional Speed, Rpm

0

2000

4000

6000

8000

10000

12000 Variable-Amplitude - History Profile
NASA/TM—2011-217214 8 

support for the LabVIEW technical data management streaming (TDMS) file format, and a reader Virtual 

Instrument (VI) that can apply filters, compute Fast Fourier Transform (FFT), and simulate signal 

processing to the raw data collected from the spin rig. Also, hardware improvements and updates were the 

key factors in enhancing the overall performance of the system. Future goals are to include syncing 

rotational speed with eddy current data, integrating newer rotor dynamics calculations, validation of 

center of mass and critical speed calculations, and improving documentation of results. 

References 

1. Woike, M.R.; and Abdul-Aziz, A.: Crack-Detection Experiments on Simulated Turbine Engine Disks 

in NASA Glenn Research Center’s Rotordynamics Laboratory. AIAA–2010–587 

(NASA/TM―2010-216239), 2010. 

2. Abdul-Aziz, A., et al.: Development of a Flaw Detection/Health Monitoring Scheme for Turbine 

Engine Rotating Components. Presented at the AIAA Infotech@Aerospace 2010, Atlanta, GA, 2010. 

3. Abdul-Aziz, Ali, et al.: NDE Using Sensor Based Approach to Propulsion Health Monitoring of a 

Turbine Engine Disk. SPIE Smart Structure/NDE, San Diego, CA, 2009. 

4. Abdul-Aziz, A.; Trudell, J.J.; and Baaklini, George Y.: Finite Element Design Study of a Bladed, Flat 

Rotating Disk To Simulate Cracking in a Typical Turbine Disk, Part II. Proceedings of the 11th 

SPIE’s Annual International Symposium on Nondestructive Evaluation for Health Monitoring and 

Diagnostics, San Diego, CA, 2006. 

5. Simon; Donald L.: An Overview of the NASA Aviation Safety Program Propulsion Health 

Monitoring Element. NASA/TM―2000-210348 (AIAA–2000–3624), 2000. 

6. Drumm, M.J.: Nondestructive, Real-Time Measurement of Cracks in Jet Engine Rotors. 1998. 

www.testdevices.com Accessed August 29, 2011. 

7. Sonnichsen, H.E.: Real-Time Detection of Developing Cracks in Jet Engine Rotors. IEEE 0–7803–

5846–5/00, 2000. www.testdevices.com Accessed August 29, 2011. 

8. Bently, D.E.: Detecting Cracked Shafts at Earlier Levels. Orbit Magazine, vol. 3, no. 2, 1982. 

9. Sekar, A.S.; and Prabhu, B.S.: Condition Monitoring of Cracked Rotors Through Transient Response. 

Mechanism and Machine Theory, vol. 33, issue 8, 1998, pp. 1167–1175. 

10. Wauer, J.: On the Dynamics of Cracked Rotors: A Literature Survey. Appl. Mech. Rev., vol. 43, 

no. 1, 1990, pp. 13–17. 

11. LabVIEW 2010 Software. Austin, TX, 2010. 

12. National Instruments Developer Zone. August 16, 2010. 

http://zone.ni.com/devzone/cda/tut/p/id/3727%20 Accessed August 29, 2011. 
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Improving Data Collection and Analysis Interface for the Data Acquisition Software of the 

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13. SUPPLEMENTARY NOTES

Ben S. Curatolo, NASA Glenn Research Center, John Carroll University, summer intern. 

14. ABSTRACT

In jet engines, turbines spin at high rotational speeds. The forces generated from these high speeds make the rotating components of the 

turbines susceptible to developing cracks that can lead to major engine failures. The current inspection technologies only allow periodic 

examinations to check for cracks and other anomalies due to the requirements involved, which often necessitate entire engine disassembly. 

Also, many of these technologies cannot detect cracks that are below the surface or closed when the crack is at rest. Therefore, to overcome 

these limitations, efforts at NASA Glenn Research Center are underway to develop techniques and algorithms to detect cracks in rotating 

engine components. As a part of these activities, a high-precision spin laboratory is being utilized to expand and conduct highly specialized 

tests to develop methodologies that can assist in detecting predetermined cracks in a rotating turbine engine rotor. This paper discusses the 

various features involved in the ongoing testing at the spin laboratory and elaborates on its functionality and on the supporting data system 

tools needed to enable successfully running optimal tests and collecting accurate results. The data acquisition system and the associated 

software were updated and customized to adapt to the changes implemented on the test rig system and to accommodate the data produced by 

various sensor technologies. Discussion and presentation of these updates and the new attributes implemented are herein reported.

15. SUBJECT TERMS

Rotor dynamics; Spin laboratory; Labview; Software development; Data acquisition; Crack detection; Eddy current 

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