A Model of Uncertainty Quantification in the Estimation of Noise-Contaminated Transmissibility Measurements for System Identification
System identification via techniques applied in the frequency domain is a very common activity across many applications in engineering. Among many forms of frequency domain system identification, transmissibility estimation has been regarded as one of the most practical tools for its clear physical interpretation, its compatibility with output-only data, and its sensitivity to structural parameters. Due to operational variability, estimation errors, and extraneous noise, the computation of transmissibility may contain significant uncertainty, and this will affect the system identification quality. In this paper, a probability density function for transmissibility estimates is derived analytically via a Chi-square bivariate approach, and validated with Monte Carlo simulation.
KeywordsCovariance Coherence Convolution Acoustics Estima
Unable to display preview. Download preview PDF.
- 2.Doebling SW, Farrar CR, Prime MB, A Summary Review of Vibration-Based Damage Identification Methods. The Shock and Vibration Digest 30(2)(1998):91-105Google Scholar
- 6.Worden K, Manson G, Fieller NRJ, Damage detection using outlier analysis. Journal of Sound and Vibration 229(3)(2000):647-667Google Scholar
- 7.Bendat JS, Piersol AG, Random Data: Analysis and Measurement Procedures (2nd Edition), John Wiley & Sons (New York), 1986Google Scholar
- 8.Bendat JS, Piersol AG, Engineering Applications of Correlation and Spectral Analysis (2nd Edition), John Wiley & Sons (New York), 1993Google Scholar
- 9.Bendat JS, Statistical Errors in Measurement of Coherence Function and Input/Output Quantities. Journal of Sound and Vibration 59(3) (1978):405-421Google Scholar