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Technical Brief

Examining Sample Rate, Sample Time, and Test Replication for Reducing Uncertainty in Steady Timewise Experiments

[+] Author and Article Information
Anthony M. Ferrar

B and E Applied Research and Science Lab, Nuclear Engineering Program, University of Florida, Gainesville, FL 32611 e-mail: ferrar@ufl.edu

Manuscript received November 17, 2015; final manuscript received April 11, 2016; published online August 19, 2016. Assoc. Editor: Ioannis Kougioumtzoglou.

ASME J. Risk Uncertainty Part B 2(4), 044503 (Aug 19, 2016) (4 pages) Paper No: RISK-15-1109; doi: 10.1115/1.4033406 History: Received November 17, 2015; Accepted April 11, 2016

This paper presents the ways that sample rate, sample time, and number of test replications can affect the random uncertainty in a measurement. Typical steady timewise experiments seek the average values of measured variables. Even in this case, sample rate and sample time can affect the signal standard deviations and yield different random uncertainty estimates. In addition, many random error sources vary slowly relative to the test time and take on a single value. Test replications can convert systematic uncertainties to random uncertainties by allowing their values to change from test to test. The goal is to record individual tests at a sample rate and time that capture the short timescale error sources, and to replicate tests on the scale of long timescale error sources. This paper presents how to leverage these effects to reduce the overall uncertainty of a measured result without increasing the cost of the experiment.

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Copyright © 2016 by ASME
Topics: Errors , Signals , Uncertainty
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References

Ferrar, A. M., 2015, “Measurement and Uncertainty Analysis of Transonic Fan Response to Total Pressure Inlet Distortion,” Ph.D. thesis, Virginia Polytechnic Institute and State University, Blacksburg, VA.
Figliola, R., and Beasley, D., 2006, Theory and Design for Mechanical Measurements, 4th ed., Wiley, Hoboken, NJ.
Coleman, H., and Steele, G., 2009, Experimentation, Validation, and Uncertainty Analysis for Engineers, 3rd ed., Wiley, Hoboken, NJ.
Smith, S. W., 1997, The Scientist and Engineer’s Guide to Digital Signal Processing, California Technical Publishing, San Diego, CA. ISBN: 0-9660176-3-3.

Figures

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Fig. 1

Phase effects on standard deviation for a sample signal measured at the Nyquist sample rate. Each plot shows the ratio of the measured standard deviation to the true signal standard deviation

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Fig. 2

Sample rate effects on standard deviation for a sample signal

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Fig. 3

Standard deviation convergence with increased sample rate

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Fig. 4

Sample time effects on standard deviation for a sample signal

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Fig. 5

Uncertainty convergence with test replications from the case study. The prediction of Eq. (1) using the signal standard deviation from a single test predicted the actual convergence well. This trend confirms that the sample time and sample rate were well chosen.

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