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2006, 7

Patrick J. Vitarius, Don A. Gregory, John T. Wiley, Valentin Korman

Sampling rate error in acoustic measurements

language: English

received 01.03.2006, published 04.04.2006

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ABSTRACT

Two aspects of data collection and analysis are considered in the paper: the transfer function of the detector and the sampling method used on the data the detector reports. Following a brief look at transfer function theory, a simple model is constructed which shows the effect of sampling time dependent functions (acoustic or otherwise) at different rates. The average value of a time dependent parameter (pressure for example) is calculated to illustrate the analysis method. Four different type functions were chosen to represent the parameter: sinusoidal, pseudo-sinusoidal, asymmetric triangular, and random. The results illustrate the important role played by sampling rate when analyzing time dependent data.

9 pages, 5 figures

Сitation: Patrick J. Vitarius, Don A. Gregory, John T. Wiley, Valentin Korman. Sampling rate error in acoustic measurements. Electronic Journal “Technical Acoustics”, http://www.ejta.org, 2006, 7.

REFERENCES

1. Halliday D., Resnick R., Walker J. Fundamentals of Physics, John Wiley and Sons, 5th ed., 1997.
2. Ono T., Yamaguchi K., Suzuki H., Kawaura J., Ohashi, M. A New Error Index for the Determination of the Number of Averages in Transfer Function Estimation. Appl. Acoustics, vol. 28, issue 1, 1989, p. 21.
3. Poularikas A., Seely S. Properties of Delta Functions. Signals and Systems, 2nd ed., Krieger Publishing, Boston, 1991, pp. 690–694.
4. Goodman J. Fourier Optics. McGraw-Hill Publishing, New York, 2nd ed., 1996, pp. 21–22.
5. Hecht, E. Optics. Addison-Wesley Publishing, 4th ed., 2002.
6. Randall R., Tech B. Application of B&K Equipment to Frequency Analysis. Bruel & Kjaer, Denmark, 2nd ed., 1977.
7. Yamaguchi S., Kato Y. A Statistical Study for Determining the Minimum Sample Size Leq Estimation of Periodic Nonstationary Random Noise. Appl. Acoustics, vol. 32, issue 1, 1991, p 35.
8. Moler Cleve. Ziggurat Algorithm Generates Normally Distributed Random Numbers. Matlab News and Notes, The Mathworks, Spring, 2001.


 

Patrick Vitarius earned his undergraduate degree in Physics from Rensselaer Polytechnic Institute in Troy, NY. After teaching physics and mathematics with the United States Peace Corps, he earned his master’s degree in physics from the University of Alabama in Huntsville. He is currently completing his Ph.D. research in physics on the topic of orbital mechanics. He is currently working for Freel Innovations as an Associate Engineer performing data analysis and algorithm development.

 
 

Don A. Gregory, Ph.D. Physics, the University of Alabama in Huntsville (1984). Professor Gregory was a material scientist for NASA and a Supervisory Research Physicist for the US Army Missile Command before joining UAH in 1992 as an Associate Professor of Physics. He has graduated 30 students with MS or Ph.D.’s and has supervised research in a wide variety of topics ranging from fundamental optical properties of materials to optical engineering solutions to practical problems. He has more than 100 refereed open literature publications in optics, engineering, and chemistry journals. His current interests are in the areas of optical properties of blown glass, basic radiometry, and acoustic signal propagation.

e-mail: gregoryd(at)uah.edu

 
 

John Wiley: B.S. Electrical Engineering, University of Alabama, Huntsville (1989), M.S. Applied Science, University of Arkansas, Little Rock (1998). 16 years experience as a propulsion test instrumentation engineer. Provided test support for sensor applications, data validation, data acquisition system configuration and data analysis. Experience in sensor applications and data validation of measurements made in cryogenic fluids. Team leader in the design and development of an advanced measurement system for engine test facilities. Sensor development projects include: high flow cryogenic fluid RTD temperature sensor, optical cryogenic fluid density sensor.

 
 

Valentin Korman earned his undergraduate degree in Astrophysics from New Mexico Tech. and then earned a masters degree in physics from the University of Alabama in Huntsville in 1999. He currently is completing his PhD research in optical science and engineering on the topic of optical cryogenic mass flow. He has conducted research for the past 5 years at NASA’s Marshall Space Flight Center propulsion test area. He is currently working for Madison Research Corporation as a Senior Researcher performing sensor development and evaluation for NASA.