Smart Structures and Systems

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Application of principal component analysis and wavelet transform to fatigue crack detection in waveguides

  • Cammarata, Marcello (Laboratory for NDE and Structural Health Monitoring studies, Department of Civil and Environmental Engineering, University of Pittsburgh) ;
  • Rizzo, Piervincenzo (Department of Civil and Environmental Engineering, University of Pittsburgh) ;
  • Dutta, Debaditya (Department of Civil and Environmental Engineering, Carnegie Mellon University) ;
  • Sohn, Hoon (Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology)
  • Received : 2008.12.15
  • Accepted : 2009.07.29
  • Published : 2010.05.25
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Abstract

Ultrasonic Guided Waves (UGWs) are a useful tool in structural health monitoring (SHM) applications that can benefit from built-in transduction, moderately large inspection ranges and high sensitivity to small flaws. This paper describes a SHM method based on UGWs, discrete wavelet transform (DWT), and principal component analysis (PCA) able to detect and quantify the onset and propagation of fatigue cracks in structural waveguides. The method combines the advantages of guided wave signals processed through the DWT with the outcomes of selecting defect-sensitive features to perform a multivariate diagnosis of damage. This diagnosis is based on the PCA. The framework presented in this paper is applied to the detection of fatigue cracks in a steel beam. The probing hardware consists of a PXI platform that controls the generation and measurement of the ultrasonic signals by means of piezoelectric transducers made of Lead Zirconate Titanate. Although the approach is demonstrated in a beam test, it is argued that the proposed method is general and applicable to any structure that can sustain the propagation of UGWs.

Keywords

Acknowledgement

Supported by : Korea Science and Engineering Foundation, Korea Research Foundation

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