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Application of principal component analysis and wavelet transform to fatigue crack detection in waveguides
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  • Application of principal component analysis and wavelet transform to fatigue crack detection in waveguides
  • Application of principal component analysis and wavelet transform to fatigue crack detection in waveguides
저자명
Cammarata. Marcello,Rizzo. Piervincenzo,Dutta. Debaditya,Sohn. Hoon
간행물명
Smart structures and systems
권/호정보
2010년|6권 4호|pp.349-362 (14 pages)
발행정보
테크노프레스
파일정보
정기간행물|ENG|
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기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

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.