Pipeline leakage positioning method based on VMD component relative entropy analysis

Abstract

The invention provides a pipeline leakage positioning method based on VMD component relative entropy analysis. A VMD is applied to treat a leakage sound emission signal, an IMF component is obtained,the component is combined with the leakage sound emission signal and a non-leakage sound emission signal to calculate relative entropy value, the relative entropy value is subjected to self-adaptationoption analysis, the IMF component corresponding to a signal containing leakage characteristics is extracted for signal reconstruction, and an optimal observation signal is obtained; time-frequency analysis is used for obtaining observation signal delay and frequency, the obtained frequency is combined with a modal frequency dispersion curve to determine a signal sound speed, and finally, throughthe time difference positioning principle, the pipeline leakage position is obtained. Through contrastive analysis of the non-leakage signal and leakage signal IMF component relative entropy value, an interference signal and a virtual component are removed, extraction of an effective leakage signal is achieved, and in joint with the time-frequency analysis and the modal frequency dispersion curve, the problems that the leakage signal is hard to extract, and due to the dispersion property, the leakage positioning error is large are solved.

Description

technical field [0001] The present invention relates to the technical field of pipeline leakage detection, in particular to a method for locating pipeline leakage based on relative entropy analysis of VMD components. Can accurately locate the leak point. Background technique [0002] Due to the long service life of pipelines, environmental corrosion, third-party damage and other reasons, pipeline leakage accidents occur from time to time. Pipeline leakage not only causes waste of precious resources, but also causes substances in the pipe to flow out through the leakage point, causing environmental pollution and bringing safety hazards to people's lives. Therefore, it is particularly important to effectively detect and deal with pipeline faults in time. In recent years, a lot of research work has been done on pipeline leakage detection technology, leakage signal feature extraction and pipeline leakage location at home and abroad. Among them, the pipeline leakage detection ...

AI Technical Summary

Problems solved by technology

[0004] In the previous VMD component extraction, only the IMF component obtained by VMD decomposition of the collected leakage signal was compared with the original leakage signal, and the comparison with the signal without leakage was ignored. There was a lack of reference comparison analysis, and the useful IMF component was ignored. IMF component of

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