Time frequency and wavelet transform applied to selected problems in ultrasonics NDE

• Published in: NDT & E international : independent nondestructive testing and evaluation Vol. 35; no. 8; pp. 567 - 572
• Main Authors: Drai, Redouane, Khelil, Mohamed, Benchaala, Amar
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.12.2002; Elsevier Science
• Subjects: Acoustic signal processing; Acoustical measurements and instrumentation; Acoustics; Cross-disciplinary physics: materials science; rheology; Exact sciences and technology; Fundamental areas of phenomenology (including applications); Materials science; Materials testing; NDT/NDE; Nondestructive testing: ultrasonic testing, photoacoustic testing; Physics; Time frequency representation; Ultrasonic; Wavelet transform; Wavelet transform; NDT/NDE; Time frequency representation; Ultrasonic; Bayes estimation; Wigner theory; Wavelet transforms; Gabor filter; Nearest neighbour; Statistical analysis; Probabilistic approach; Time frequency domain method; Nondestructive testing; Thickness measurement; Neural networks; Discrete time; Signal processing; Acoustic measurements; Ultrasonic testing; Defect detection
• ISSN: 0963-8695; 1879-1174
• DOI: 10.1016/S0963-8695(02)00041-5

In this paper, we contribute by the development of some signal processing in order to enhance the sensibility of flaw detection, to measure thin materials thickness and to characterize defects in nature (planar or volumetric). Features for discrimination of detected echos are extracted in time domain, spectral domain and discrete wavelet representation. Compact feature vector obtained is then classified by different methods: K nearest neighbour algorithm, statistical Bayesian algorithm and artificial neural network. Mallat decomposition algorithm is also developed in order to enhance flaw detectability. Finally, time frequency algorithms based on STFT, Wigner–Ville, Gabor transform are developed and applied to thickness measurements of materials with small thickness.