The Key Technique Of Digital Signal Processing For Pipeline Nondestructive Testing Using Magnetostrictive Guided Wave

Magnetostrictive guided wave technique shows a good prospect in the long distance and large-scale structure of the non-destructive testing (NDT) and health monitoring, thanks to its advantages such as single-ended excitation, long propagation distance,100%detection of cross section. However, guided wave signal is mixed with a lot of noise, and its characteristics such as dispersion, multi-modal, non-stationary make the research of guided wave signal processing be difficult and extensible. In this paper, three key techniques of magnetostrictive guided wave signal processing such as joint time-frequency analysis, signal denoise and axial defects quantitative analysis were studied in this paper,The detail work was presented as follows:(1) The importance of signal processing in magnetostrictive guided wave testing was discussed, the bottlenecks of current signal processing technology were analyzed, on the basis of those, the key technologies of magnetostrictive guided wave were summarized and the content of this research were determined.(2) On the basis of the research of magnetostrictive guided wave testing theory and guide wave detection method, characteristics of guided wave and the technical difficulties of signal processing were mainly discussed. The MSGW magnetostrictive guided wave detection system was introduced, by this system, artificial engraved injury steel pipe was detected and the testing signal was analyzed.(3) Some of time-frequency analysis methods such as short-time Fourier transform, wavelet transform, Wigner-Will distribution theory, Hilbert Huang Transform were studied. By experiment, the preferences as well as the ability of time-frequency analysis of these methods were summarized.(4) Two noise reduction algorithms for magnetostrictive guided wave signal were proposed: noise reduction algorithm based on walvet time-frequency analysis and matching pursuit, guided wave noise reduction algorithm based on EMD. The SNR of magnetostrictive guided wave testing signal is improved through these two methods. Contrast to wavelet threshold filtering algorithm, the validity of these two methods were verified by experiment.(5) Aiming at the quantitative analysis of axial defect size problem in magnetostictive guided wave testing, a method based on matching pursuit for quantifying the severity of pipeline defect along axial direction is proposed. Validation experiments of finite element numerical simulation as well as detecting the artificial defects in the aluminum pipe by using MSGW magnetostrictive guided wave detector show that the algorithm is effective.