Damage identification by wavelet analysis

• Published in: Mechanical systems and signal processing Vol. 22; no. 7; pp. 1623 - 1635
• Main Authors: Grabowska, J., Palacz, M., Krawczuk, M.
• Format: Journal Article
• Language: English
• Published: London Elsevier Ltd 01.10.2008; Elsevier
• Subjects: Acoustical measurements and instrumentation; Acoustics; Damage detection; Exact sciences and technology; Fracture mechanics (crack, fatigue, damage...); Fundamental areas of phenomenology (including applications); Lamb wave; Measurement and testing methods; Physics; Signal processing; Solid mechanics; Structural and continuum mechanics; Vibration, mechanical wave, dynamic stability (aeroelasticity, vibration control...); Wavelet analysis; Lamb wave; Signal processing; Wavelet analysis; Damage detection; Acoustic emission testing; Fast Fourier transformation; Structure integrity; Travelling wave; Fatigue fracture; Modeling; Cavity; Failure analysis; Ultrasonic control; Spectral element method; System identification; Ultrasound; Monitoring; Damaging; Novelty; Fatigue life; Acoustic measurement; Guided wave; Surface wave; Wavelet transformation; Signal analysis; Non destructive test; Strength; Defect detection
• ISSN: 0888-3270; 1096-1216
• DOI: 10.1016/j.ymssp.2008.01.003

Structural health monitoring (SHM) has been related to damage monitoring with operational loads playing a significant role in terms of fatigue life and damage accumulation prognostics. A lot of different techniques like acoustic emission, ultrasonic, acousto-ultrasonic, guided ultrasonic waves or Lamb waves are nowadays investigated in terms of efficient and user-friendly damage identification system. Every damage identification system available consists of the hardware and software. This paper deals with the latter which is based on propagating Lamb wave measurements. It has been developed especially for distinguishing different kinds of damages. The reason for that research is that for example small voids in material, classified as damage, do not influence its overall strength. The literature gives enormous number of application of wavelets and Lamb waves but only for detecting the damage. Distinguishing seems not to be a subject of wide interest. The usage of wavelet transformation with propagating Lamb waves for distinguishing between different failures is the most important novelty of the research done. To obtain the presented results for modelling, the FFT-based spectral element method has been used. For signal processing, the wavelet analysis has been employed. The proper results are given and future of this research direction is discussed.