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管道泄漏检测方法研究综述

Review of diagnostic technique for pipe leakage

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【作者】 高琳曹建国

【Author】 GAO Lin;CAO Jianguo;School of Mechanical Engineering, University of Science and Technology Beijing;School of Mechanical Engineering, Inner Mongolia University of Science and Technology;Institute of Artificial Intelligence, University of Science and Technology Beijing;

【机构】 北京科技大学机械工程学院内蒙古科技大学机械工程学院北京科技大学人工智能研究院

【摘要】 管道泄漏常常造成环境污染、财产损失和人员伤亡,由于其发生的隐蔽性,对管道泄漏的及时识别与准确定位具有重要的现实意义。按照结构损伤识别方法的分类标准,将管道泄漏检测方法分为基于模型的方法、基于信号处理的方法和基于人工智能的方法。围绕这3类方法,分别重点介绍了管道泄漏固体模型、流体模型、泄漏信号识别和定位处理方法、人工神经网络,以及支持向量机辨识管道泄漏方法的国内外研究现状,梳理了众多文献间的区别和联系。最后分析了各检测方法存在的不足,对未来管道泄漏检测研究方向进行了展望。

【Abstract】 Pipe leakage may cause environmental pollution, property losses and casualties. It was very important to detect in time and accurately locate pipe leakage for its concealment. According to the classification criteria of structure damage identification, diagnostic technique for pipe leakage will fall into three categories: first, method based on model; second, method based on signal processing; third, method based on artificial intelligence. Concerned with a summarization at home and abroad on some typical diagnostic technique research for pipe leakage, including solid leakage model, fluid leakage model, signal processing for leakage detection and localization, identification of leakage based on neural network and support vector machine, the difference and relationship of the previous relevant literatures were combed through in detail. Finally, the deficiencies of present diagnostic techniques were discussed and future research objects on pipe leakage diagnostic were proposed.

【关键词】 管道泄漏检测技术
【Key words】 pipeleakagediagnostic technique
【基金】 内蒙古自然科学基金项目(2021LHMS05027)
  • 【文献出处】 现代制造工程 ,Modern Manufacturing Engineering , 编辑部邮箱 ,2022年02期
  • 【分类号】TE973.6
  • 【被引频次】8
  • 【下载频次】1175
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