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8 April 2009 Outlier analysis and principal component analysis to detect fatigue cracks in waveguides
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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), outlier analysis 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 defectsensitive features to perform a multivariate diagnosis of damage. 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.
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Piervincenzo Rizzo, Marcello Cammarata, Debaditya Dutta, and Hoon Sohn "Outlier analysis and principal component analysis to detect fatigue cracks in waveguides", Proc. SPIE 7295, Health Monitoring of Structural and Biological Systems 2009, 72950S (8 April 2009); https://doi.org/10.1117/12.815512
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