Research on the peak detection method based on derivative transformation for ultrasonic guided wave signals in the rail

Abstract

Abstract To solve the problem of difficult identification and localization of structural defects by utilizing nonlinear ultrasonic guided waves with coding characteristics in the rail, a novel adaptive peak detection method is proposed in this work, which is based on multi-cascade moving average filter and derivative transformation. First, the ultrasonic guided wave detection system in the steel rail environment is introduced and the parameters of the piezoelectric ultrasonic transducer used in this paper are given. Secondly, analyze the characteristics of the coded excitation ultrasonic guide wave signal, consider the effects of peak sidelobe level, multipath effect, and noise, and use multi-cascade moving average filtering and Hilbert transforms to reduce peak sidelobe interference and extract the envelope. Finally, the peak position of the correlation sequence is detected according to the derivative transformation. The experiment shows that the proposed algorithm can effectively extract the peak information and has good anti-noise performance. It has good recognition ability in complex track environments and the algorithm's accuracy can reach 94.34. This is suitable for coded excitation ultrasonic transmission systems and is easy to implement in the real-time detection system.