Method for detecting leakage of pipeline based on artificial neural network

An artificial neural network and detection method technology, applied in the field of computer control, can solve the problems of inaccurate identification, imperfect technology, accuracy error, etc.

Inactive Publication Date: 2007-08-01
BEIJING MUNICIPAL INST OF LABOUR PROTECTION
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AI Technical Summary

Problems solved by technology

[0005] 1. The pipeline leakage detection system based on acoustic emission technology has the advantages of real-time and continuous measurement and analysis, accurate leakage point location and external measurement without dismantling the pipeline; however, for large-flow pipelines, the background noise will affect the leakage noise. cause serious interference
In addition, the accuracy of pipeline leakage detection based on acoustic emission technology has a large error compar

Method used

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  • Method for detecting leakage of pipeline based on artificial neural network
  • Method for detecting leakage of pipeline based on artificial neural network
  • Method for detecting leakage of pipeline based on artificial neural network

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Embodiment Construction

[0032] As shown in Figure 1: The pipeline leakage detection method based on artificial neural network is divided into two stages. The first stage is to collect the data F1 in the on-site flowmeter through the communication module composed of communication hardware, and process data such as filtering. , sent to the neuron network training module F2. The neural network training module F2 performs offline training according to the data, and the results are obtained, which are sent to the neuron network diagnosis module F3.

[0033] In the second stage, leakage is manually set on site, and the field data enters the neuron network diagnosis module F3 through the communication module F1, and the neuron network diagnosis module F3 performs online diagnosis on the field data according to the training results obtained by the neuron network training module F2. At the same time, the communication module F2 sends data to the display module F4, and the display module can display the trend ...

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Abstract

This invention discloses one tube leakage test method based on human neural network, which comprises the following four steps: gas phase flow tube relative signals collecting and delivering; neural element network training; neural element signals dialoguing and signal displaying, wherein, the above steps test the gas tube leakage based on current tube test base device to provide one computer identification technique with accurate test method.

Description

Technical field: [0001] The invention relates to a computer control technology, in particular to a method for detecting pipeline leakage by using a computer neural network system. Background technique: [0002] Substances leaked from pipelines are usually poisonous and harmful. Leakage accidents may cause serious damage or impact on the surrounding environment and its ecological balance, resulting in loss of national property and threat to people's lives. Especially for gas transportation pipelines, such as city gas pipeline network, because they are buried underground and lack effective maintenance and monitoring methods, they have become a major hidden danger to public safety. Due to the highly compressible nature of gases, common leak detection methods do not work well for them. Coupled with many gas transportation pipelines in service, the delivery pressure is medium and low pressure. How to effectively detect and locate leaks under low pressure conditions is an import...

Claims

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Application Information

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IPC IPC(8): G06N3/04G06N3/08G01M3/00G01M3/28
Inventor 丁辉王立李青春董晓国张贝克陈舜琮齐刚
Owner BEIJING MUNICIPAL INST OF LABOUR PROTECTION
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