Two sensor development programs being conducted at the Fluid Mechanics Laboratory, NASA Ames Research Center are described, one in progress and the other being initiated. The ongoing program involves digital image velocimetry for velocity field measurements of time-dependent flows. The new program involves advanced acoustic sensors for wind tunnel applications

Cho, Y.-C.

English

NASA Technical Reports Server

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NASA Technical Memorandum 10221 7 
Sensor Development Programs 
at NASA Ames Research Center 
Y.-C. Cho, Ames Research Center, Moffett Field, California 
August 1989 
National Aeronautics and 
Space Administration 
AmesResearchcentet 
Moffett Field, California 94035 
https://ntrs.nasa.gov/search.jsp?R=19890017437 2020-03-20T02:13:39+00:00Z
Sensor Development Programs at NASA Ames Research Center 
Y.-C. Cho 
* NASA Ames Research Center, Moffeu Field, California 94035 
ABSTRACT 
This paper presents a brief description of two sensor development programs at the Fluid Mechanics Laboratory, NASA Ames 
Research Center, one in progress and the other being initiated. The ongoing programs involve digital image velocimetry for 
velocity field measurements of time-dependent flows. The new program involves advanced acoustic sensors for wind tunnel 
applications. 
1. DIGITAL IMAGE VELOCIMETRY 
Digital image velocimetry @IV) is a new technique which is currently being developed for real-time measurements of 
instantaneous velocity fields of timedependent flows or of a collection of objects moving with varying velocities.1 Such 
measurements will yield infomation not possible to obtain using conventional point-measurement methods such as hot-wire 
anemometry and lascr Doppler velocimetry. This new information will provide a greater understanding of time-dependent 
flows a of objects moving with varying velocities. 
Recently, fluid dynamicists have exploited modern computer and optics technologies to develop methuds for measuring 
instantaneous velocity fields, including particle image velocimetry (PIV) and laser speckle velocimetry (LSV). With these 
methods, multiply exposad images of seed particles embedded in the flow or of moving objects arc caprured on a phom 
graphic film. The object travel distances betweem exposures are obtained h m  the image separatons of the same seed parti- 
cles or objects. The velocities arc then detamincd by dividing the travel distances with the timc interval between the e x p  
sures. These methods are, however, subject to some serious restrictions, such as limited dynamic range of the velocity . 
measurements, ambiguity of the direction of the velocity vectors to be detarmned * , and difficulties of development into a real- 
time measurement capability. 
DIV, which is designed to eliminate these nsrrictions. exploits high-speed video photography, image processing. and digital 
Fourier transformation. With this technique, a time sequence of images of seed particles or moving objects are captured using 
a high-speed video camera, with cach frame containing a single-exposure image. A finite number of singleexposure images 
are sampled with a certain separation time. The sampled images are then digitized on the image pmxssor, enhanced. and 
linearly superposed to construct an image. This process is illustrated in Figure 1. 
The superposed image is equivalent to the multipleexposure image used in LSVPIV. However, there exists a subtle but 
important difference between the superposed image and the multiple-exposure image, especially with high concentrations of 
seed particles as in cases whue a derailed determination of velocity fields is required. With a high cancennation of seed par- 
ticles. the different-time exposure images of individual objects can easily overlap. On the multipleexposure image in LSV or 
PIV, the intensity in the overlapped region may not differ much from that in the nonoverlapping images. Such overlapping 
will suppress the correlation between the images of the same objects, resulting in an increase of the uncatainty of the veloc- 
ity determination. In contrast, on the linearly superposed image in DIV, the intensity of the image overlap is equal to the 
arithmetic sum of the intensities of the individual images, and thus the correlation between the images of the same objects is 
preserved. (See Figure 2.) 
The velocities are determined from the image separations recaptured on the supaposcd image. A single-exposure image is 
used to eliminate the uncertainty effects that are due to the finite image sizes and some interference effects caused by unde- 
sirable distributions of h e  seed particles or the objects. An example of this procedure. in which a Fourier-transform technique 
is used, is shown in Figures 3-5. The fringes shown in the figures are directly related to the magnitude and the orientation of 
the velocity. The direction of the velocity vector can be determined unambiguously using a singleexposure image, since this 
image contains information on the time history. 
It should be emphasized that the singleexposure images are not available in, nor can they be isolated from, the multiple- 
exposure image with the photographic film technique used in LSV or PIV. 
2. ADVANCED ACOUSTIC SENSORS FOR WIND TUNNEL APPLICATIONS 
Acoustic measurements in wind tunnels are subject to certain interference effects not found in anechoic chambers. Such 
effects include wind noise. flow-sensor interaction noise, flow-induced sensor vibration, deflection of acoustic waves by 
sensor-induced boundary layers, and reflections fmm facility and sensor suppon components. Furthermore, it is often desir- 
able to investigate specific source regions on the models being studied. Currently existing acoustic sensor techniques are not 
adequate to cope with these problems. 
Ames Research Center is initiating a program to develop advanced acoustic sensors to eliminate or minimize these interfer- 
ence restrictions. The program is based on new concepts for adaptive arrays using optical fibers as acoustic sensor elements. 
An ada tive array is a system composcd of a number of geometrically configured sensor elements and a real-time signal pro- 
spectral response for the acoustic signal. ”he directional properties of such a system allows discrimination against unwanted 
sound coming from directions other than the acoustic some under study. A proper adjustment of the spectral response dis- 
criminates noise of frequencies different from the signal frequencies. Another significant advantage of an adaptive a m y  can 
be derived from the &-time manipulation of the correlation of signals detected by various sen= elements. Such a manipu- 
lation can be used to discriminate random noise or prcssurc fluctuations generated locally on individual sensor elements. 
D 
. 
cessor. f The signal processor is designed to automatically adjust the array sensitivity for enhancing the directivity and the 
i 
The technology of fiba-optic acoustic setlsocs has matured in undenvata awustics applications, and is readily available for 
implementation to aero-acoustics? Fiber-optic acoustic sensors offer a number of advantages. The sensor element package 
can be very compact, thus reducing flow-sensor interactions. The optical fibers arc geometrically versatile and can therefore 
be configured with gnat flexibility as extended (or distributed) sensar elements. Such configurations would generate a great 
variety of array sensitivity patterns. Fu~thmore, the optical f i b  can be molded on the surface of a solid body. With the 
sensor elements molded on an aerodynamically smooth body, the flow interaction can be made negligible. the aerodynami- 
cally induced vibration Will be minimized, and effects of the boundary layer wil l  be made more tractable. 
An adaptive array with fiberqtic intcrfaomeuic acoustic sulsors is schematically displayed in Figure 6. The system is 
composed of three elements: a light source, fiber optic interferometric sensor elements, and a phouxWct0p intufaced with a 
signal processor. Light, transmitted from the light some into the optical fik (waveguide), will be split at the first coupling 
branch. One part will propagate through the reference 8nn without expaiaing any cxtcmal effect The otha pars which 
will propagate through the sensing ann, will be af€ccted by the external acoustic signals. The exation of the acoustic pres- 
sure, Ap, on the optical fibex will result in the phase shift, At), of the light (or the optical wave). In other words, the acoustic 
erence light at the second coupling branch. The interference will then be recurded on the photodetector, and processed on the 
signal processor to extract information on the acoustic signal. 
I signal modulates the phase of the optical wave. The phasc-modulated optical wave will be combined with the unaffected ref- 
I 
3. REFERENCES 
‘Y.-C. Cho. “Digital image velocimefry,” App. Op. 28,740-748 (1989). 
2R. A. Monzingo and T. M. Mille.r,Introduction to Adaptive h a y s ,  John Wiley & Sons, New York (1980). 
3T. G. Giallorenz, J. A. Bucaro, A. Dandridge, G. H. Sigel, Jr., J. H. Cole, S. C. Rasbleigh, and R. G. Priest, “Optical fiber 
sensor technology,” EEE J. Quantum Electronics, QE-18,626-665 (1982). 
2 
t = O  
l- 
a 
t = T  
r 
t = 2T 
A 
A 
Figure 1. Construction of a multiple-exposure image as a superposition of singlecxposure images. 
I 
XO 
PHOTOGRAPH IC IMAGE 
IN LSV OR PIV 
I I  
x 1  x2 
x 1  x2 
X 
I 
x 3  
SUPERIMPOSED IMAGE 
IN DIV 
xO x 1  x 2  x 3  
Figure 2. Intensity of multiple-exposure images in overlap region. 
3 
I 1 
(b) (8)  
Figure 3. (a) Triple-exposure image and (b) the modulus of the FoUria transformed image. 
e 
A e 
m A  
e e 
A 
c 
a 
Figure 4. (a) Single-exposurc image which is contained in the image in Figurc 3(a) as a component detected at the initial 
exposure and (b) the modulus of the Fourier-uansfomed image. 
, 
4 
f 
5 0 
(h1 
1 
f 
Figure 5. (a) Fringe paetcm. which is obtained by dividing the Fourier-transformed image in Figure 30)  
with that in Figure 4(b); and (b) magnified fiinge pattan. 
LIGHT OPTICAL FIBER 
SOURCE 
t 
SIGNAL 
Ap - An -. 69 
n: REFRACTIVE INDEX OF FIBER 
+: PHASE OF OPTICAL WAVE 
Figure 6. Schematic of an adaptive array with fibu-optic interfernmetric sensor elements. 
5 
2. Government Accession No. 1. Report No. 3. Recipient's Catalog No. 
Y.-C. Cho 
NASA TM-102217 
4. Title and Subtile 
Sensor Development Programs at NASA Ames Research Center 
7. Author@) 
A-89167 
10. Wok Unit No. 
5. Report Date 
August 1989 
6. Performing Organization Code 
8. Performing Organization Report No. 
505-61-01 
9. Performing Organization Name and Address 
11. Contract or Grant No. 
Ames Research Center 
12. Sponsoring Agency Name and Address 
National Aeronautics and Space Administration 
Washington, DC 20546-0001 
Moffett Field, CA 94035 I 
Technical Memorandum 
14. Sponsoring Agency Code 
13. Type of Report and Period Covered 
19. Security Classif. (of this report) 20. Security Chssif. (of this page) 
Unclassified Unclassified 
21. No. of Pages 22. Price 
6 A02 
17. Key Words (Suggested by Author(s)) 1 18. Distribution Statement I '  
Digital image velocimetry 
Sensors 
Fiber optics 
Unclassified-Unlimited 
Subject Category - 01 
I 
1 I I I 1 
NASA FORM 1626 OCT 88 
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Sensor development programs at NASA Ames Research Center

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