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

Marcello Cammarata, Marcello Cammarata, Piervincenzo Rizzo, Debaditya Dutta, Hoon Sohn

    Risultato della ricerca: Articlepeer review

    16 Citazioni (Scopus)

    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 sensitivityto small flaws. This paper describes a SHM method based on UGWs, discrete wavelet transform (DWT), andprincipal component analysis (PCA) able to detect and quantify the onset and propagation of fatigue cracks instructural waveguides. The method combines the advantages of guided wave signals processed through theDWT 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 offatigue cracks in a steel beam. The probing hardware consists of a PXI platform that controls the generationand measurement of the ultrasonic signals by means of piezoelectric transducers made of Lead ZirconateTitanate. Although the approach is demonstrated in a beam test, it is argued that the proposed method isgeneral and applicable to any structure that can sustain the propagation of UGWs.
    Lingua originaleEnglish
    pagine (da-a)349-362
    Numero di pagine13
    RivistaSmart Structures and Systems
    VolumeVol. 6
    Stato di pubblicazionePublished - 2010

    All Science Journal Classification (ASJC) codes

    • Control and Systems Engineering
    • Computer Science Applications
    • Electrical and Electronic Engineering

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