Pipeline small defect axial length detection method and application thereof

Abstract

The invention discloses a method for detecting the axial length of a small defect of a pipeline and application of the method. According to the method, on the basis of analyzing the reflection characteristics of ultrasonic guided wave pipeline detection defect signals, an over-complete atom library is established, atoms which are most matched with to-be-decomposed signals are selected from the over-complete atom library, the signals can be decomposed into components and residual errors on the optimal atoms, the remaining residual error parts continue to be decomposed until the end conditions are met, and finally, the detection defect signals are obtained. The axial length of the defect can be obtained by calculating the product of the time difference of the front-end reflection signal and the rear-end reflection signal and the propagation speed of the ultrasonic guided wave in the pipeline. In the calculation process, due to the fact that the capacity of an over-complete atom library is large, the calculation workload is large, and convergence is slow, the improved matching pursuit algorithm is adopted for optimizing and solving, the calculation speed can be increased, the axial length of small defects can be quantitatively measured, and pipeline ultrasonic guided wave detection and diagnosis health state evaluation can be achieved.

Description

technical field [0001] The invention belongs to the technical field of non-destructive testing, and more specifically relates to a method for detecting the axial length of small defects in pipelines and its application. Background technique [0002] Ultrasonic guided wave testing technology has been widely used in non-destructive testing, and has broad application prospects because of its advantages such as fast, long-distance, and large-scale testing. However, the guided wave detection signal often contains various noises, which affect the identification and location of the defect signal. Therefore, it is a difficult problem in the guided wave nondestructive testing technology to extract valuable signals from the noisy guided wave signal. [0003] Commonly used guided wave signal processing methods include short-time Fourier transform, wavelet transform, time-frequency analysis, spectrum analysis and correlation analysis. Large defects can be decomposed into front and rear...

AI Technical Summary

Problems solved by technology

Large defects can be decomposed into front and rear reflection signals by traditional matching pursuit algorithm. However, when the size of the defect is small and the noise is large, it is difficult for these conventional signal processing methods to quickly extract the defect signal. In the prior art, it is proposed to use differential Evolutionary Algorithm Improves Matching Pursuit Method to Extract Guided Wave Signal

However, the differential evolution algorithm has the disadvantages that it is easy to fall into local optimum and the global convergence probability is low

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