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Pipeline leakage signal denoising method based on improved BAS-VMD

A pipeline leakage and signal technology, applied in the pipeline system, pattern recognition in signals, instruments, etc., can solve the problems of leak detection accuracy and pipeline influence

Pending Publication Date: 2022-01-21
NORTHEAST GASOLINEEUM UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to provide a kind of pipeline leakage signal denoising method based on improved BAS-VMD, this pipeline leakage signal denoising method based on improved BAS-VMD is used to solve the problem caused by the existence of noise in the natural gas pipeline leakage signal Problems Affecting the Accuracy of Pipeline Leakage Detection

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Embodiment 1

[0033] The experimental parameters are as follows: the experimental data of the present invention all come from the natural gas pipeline leakage detection simulation experiment platform of Northeast Petroleum University, which uses the HD-II pipeline leakage detection system to simulate the actual on-site pipeline as a high-pressure gas pipeline leakage detection device. By controlling the 4-point ball valve switch installed on the pipeline to simulate the leakage effect of natural gas pipelines under real conditions. The pipeline pressure is 0.5MPa, the flow rate is 60m3 / h, and the signal sampling frequency is set to 1000Hz.

[0034] This improved BAS-VMD-based pipeline leakage signal denoising method, such as figure 1 Shown: including the following steps:

[0035] S1. First, use the acoustic wave sensor to collect the pipeline leakage signal of the laboratory pipeline under the leakage condition. The time-domain waveform and spectrum of the leakage signal are as follows: ...

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Abstract

The invention relates to a pipeline leakage signal denoising method based on improved BAS-VMD. The method comprises the steps that a sonic sensor is used for collecting a pipeline leakage signal of a natural gas pipeline under the leakage working condition; BAS is improved, a single long-horned beetle is changed into multiple long-horned beetles, and the long-horned beetles learn group experience in the moving process to improve the algorithm accuracy; the method also includes determining a parameter mode number K and a bandwidth constraint alpha in the VMD by using an improved BAS algorithm, decomposing a signal by the VMD, and performing adaptive decomposition on a pipeline leakage signal to obtain a plurality of mode components; and screening out effective components by using an Euclidean distance ED, reconstructing the effective components, and removing noise components to obtain a denoised leakage signal. A good effect can be obtained by denoising the pipeline leakage signal through the method, and effective features in the pipeline leakage signal are reserved while noise is filtered out.

Description

technical field [0001] The invention relates to a denoising method used in signal processing in pipeline leakage detection technology, in particular to a pipeline leakage signal denoising method based on the improved BAS-VMD. Background technique [0002] In the natural gas pipeline system, due to the existence of various external sound interference and random noise in the acquisition system, the acoustic signal collected by the sensor contains a lot of noise, and these noises in the signal will seriously affect the analysis of useful signals. Therefore, it is very critical to perform denoising processing before signal analysis, which helps to improve the accuracy of signal analysis. [0003] There is a lot of noise in the leakage signal collected by the sensor, and the pipeline signal needs to be denoised. Variational mode decomposition (VMD) is an effective signal denoising method, which not only has a solid theoretical basis, but also effectively solves the problem of Th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62F17D5/02F17D5/00
CPCF17D5/02F17D5/005G06F2218/04G06F2218/12G06F18/22
Inventor 路敬祎国剑锋董宏丽王冬梅刘庆强杨帆宋金波
Owner NORTHEAST GASOLINEEUM UNIV
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