Pipeline defect type distinguishing method based on ultrasonic guided waves

Abstract

The invention provides a pipeline defect type distinguishing method based on ultrasonic guided waves. The pipeline defect type distinguishing method comprises the following steps: uniformly distributing guided wave sensors on a pipeline in the peripheral direction to acquire a guided wave echo signal; carrying out wavelet decomposition reconstruction on the signal to obtain a defect wave curve, so as to obtain a characteristic wavelet packet curve; and finally, taking characteristic parameter specific values of the defect wave curve and the characteristic wavelet packet curve as defect type distinguishing coefficients, rapidly judging whether pipeline defects exist or not and accurately judging defect types of the pipeline through comparing the defect type distinguishing coefficients with width size threshold value sizes of crack defects and corrosion defects. The method is simple and rapid, and a lot of detection time can be saved; and technical requirements on detection workers are relatively low, and the distinguishing accuracy of the distinguishing method is more than 85%.

Description

technical field [0001] The invention belongs to the emerging field of pipeline non-destructive testing technology, and in particular relates to a method for discriminating pipeline defect types based on ultrasonic guided waves. Background technique [0002] The pipeline mileage in our country is very large. If the defects in the pipeline cannot be found in time, pipeline leakage accidents will easily occur, and in severe cases, it will easily cause casualties of life and property. Since most of the pipelines are overhead or buried pipelines with cladding. The traditional pipeline non-destructive testing method can only be a point test, the detection efficiency is low, and the requirements for technical personnel are high, which can no longer meet the needs of pipeline testing. As an emerging non-destructive testing technology, ultrasonic guided wave testing can obtain the health information of pipelines in a long distance only by testing in one place of the pipeline, and th...

AI Technical Summary

Problems solved by technology

This method still obtains the simulated image data by extracting defect features and then judges the defect surface damage. The signal extraction is complicated, and it is still not possible to directly judge the defect type based on the acquired data.

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