Higher order statistical frequency domain decomposition for operational modal analysis

Document Type

Article

Publication Date

2-1-2017

Abstract

Experimental methods based on modal analysis under ambient vibrational excitation are often employed to detect structural damages of mechanical systems. Many of such frequency domain methods, such as Basic Frequency Domain (BFD), Frequency Domain Decomposition (FFD), or Enhanced Frequency Domain Decomposition (EFFD), use as first step a Fast Fourier Transform (FFT) estimate of the power spectral density (PSD) associated with the response of the system. In this study it is shown that higher order statistical estimators such as Spectral Kurtosis (SK) and Sample to Model Ratio (SMR) may be successfully employed not only to more reliably discriminate the response of the system against the ambient noise fluctuations, but also to better identify and separate contributions from closely spaced individual modes. It is shown that a SMR-based Maximum Likelihood curve fitting algorithm may improve the accuracy of the spectral shape and location of the individual modes and, when combined with the SK analysis, it provides efficient means to categorize such individual spectral components according to their temporal dynamics as coherent or incoherent system responses to unknown ambient excitations.

Identifier

84991821238 (Scopus)

Publication Title

Mechanical Systems and Signal Processing

External Full Text Location

https://doi.org/10.1016/j.ymssp.2016.07.004

e-ISSN

10961216

ISSN

08883270

First Page

100

Last Page

112

Volume

84

Fund Ref

Qatar National Research Fund

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