Paper Title:
An Overview of Signal-Based Damage Detection Methods
  Abstract

Deterioration of structures due to aging, cumulative crack growth or excessive response significantly affects the performance and safety of structures during their service life. Recently, signal-based methods have received many attentions for structural health monitoring and damage detection. These methods examine changes in the features derived directly from the measured time histories or their corresponding spectra through proper signal processing methods and algorithms to detect damage. Based on different signal processing techniques for feature extraction, these methods are classified into time-domain methods, frequency-domain methods, and time-frequency (or time-scale)-domain methods. As an enhancement for feature extraction, selection and classification, pattern recognition techniques are deeply integrated into signal-based damage detection. This paper provided an overview of these methods based on two aspects: (1) feature extraction and selection, and (2) pattern recognition. Signal-based methods are particularly more effective for structures with complicated nonlinear behavior and the incomplete, incoherent, and noise-contaminated measurements of structural response.

  Info
Periodical
Chapter
Chapter 2: Monitoring and Control of Structures
Edited by
Xuejun Zhou
Pages
834-851
DOI
10.4028/www.scientific.net/AMM.94-96.834
Citation
L. Qiao, A. Esmaeily, "An Overview of Signal-Based Damage Detection Methods", Applied Mechanics and Materials, Vols. 94-96, pp. 834-851, 2011
Online since
September 2011
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Price
$32.00
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