ME 6622 Experimental Methods

ME 6622: Experimental Methods
Offered Every Spring

Credit Hours:	3-0-3
Prerequisites:	Graduate standing, a graduate-level understanding of mechanics, and the appropriate mathematical and computational background, or the consent of instructor.
Catalog Description:	Experimental methods in mechanics. Includes measurement techniques, instrumentation, data acquisition, signal processing, and linear and digital electronics.
Textbook:	Philip Bevington, D. Keith Robinson, Data Reduction and Error Analysis for the Physical Science, 3rd Edition, McGraw-Hill, 2002.
Instructor:	Ari Glezer (Spring 2004)

References:

P. R. Bevington & D. K. Robinson, Data Reduction and Error Analysis for the Physical Sciences, Mc-Graw-Hill, Inc., 1992.

R. J. Goldstein, Fluid Mechanics Measurements, Taylor & Francis, Inc., 1996.

Goals:

This course is intended to provide the student with a broad background in the fundamentals of experimental data acquisition and analysis along with an introduction to a few specific measurement techniques. After this course, the student should have a system-level perspective on analyzing, processing and evaluating the data obtained from experimental measurements.

Topics:

1) Uncertainty Analysis

Error propagation, fractional uncertainty, probability distribution functions, statistics of sample mean, and the central-limit theorem.

2) Time-Series Analysis

Zero-crossings statistics, autocorrelations and cross correlations, power spectrum, digitizing of continuous data, and digital filtering.

3) Signal Conditioning

Linear circuits, digital circuits, and electronic noise.

4) Data Acquisition

Sampling theory, FFT, A/D, and D/A.

5) Special Topics and Projects

Velocimetry, anemometry, thermometry, and imaging.

Prepared by: Minami Yoda and Ari Glezer
Date: March 1997

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Revised June 2004