基于ICEEMD样本熵分析的管道多点泄漏定位

消防科学与技术 ›› 2022, Vol. 41 ›› Issue (6): 757-762.

基于ICEEMD样本熵分析的管道多点泄漏定位

杨健1，吴雨佳2，许宁1，李敏2

（1.常州市港华燃气有限公司，江苏常州 213161；2.常州大学环境与安全工程学院，江苏常州 213164）

出版日期:2022-06-15 发布日期:2022-06-15
作者简介:杨健（1978-），男，常州港华燃气有限公司，工程师，硕士，主要从事燃气管道泄漏检测与风险防控方面的研究工作，江苏省常州市长江中路300号，213161。
基金资助:
江苏省重点研发计划专项（BE2021641）；常州市科技项目（CM20200085）；江苏省研究生科研创新项目（KYCX21-2884）

Locating of multi-point leakage in pipeline based on ICEEMD sample entropy

YANG Jian1, WU Yu-jia2, XU Ning1, LI Min2

(1. Changzhou Ganghua Gas Co., Ltd., Jiangsu Changzhou 213161, China; 2. School of Environmental & Safety Engineering, Changzhou University, Jiangsu Changzhou 213164, China)

Online:2022-06-15 Published:2022-06-15

摘要/Abstract

摘要： 摘要：为解决城市管道多点泄漏定位误差较大的问题，提出一种基于改进的互补集合经验模态分解（ICEEMD）样本熵分析的管道多点泄漏定位方法。首先提出改进的CEEMD算法，利用CEEMD算法对多点泄漏声信号去噪、分解为真实泄漏信号分量和冗余分量，并通过样本熵分析去除冗余分量，获得多点泄漏声信号的有效信号；再利用盲源分离与极大似然估计算法分离观测信号，得到有效泄漏信号；然后利用互相关时延法计算两路信号到达上下游传感器的时差；最后计算得到单个泄漏点的精确定位。结果表明，该方法具有较好的信号分解效果，能提高管道多点泄漏定位的精度。

关键词: 关键词：多点泄漏, 互补集合经验模态分解, 样本熵, 盲源分离, 极大似然估计

Abstract: Abstract: In order to reduce the multi-point leakage positioning error of urban pipeline, a method of locating multi-point leakage in pipeline based on improved complete ensemble empirical mode decomposition (ICEEMD) sample entropy was proposed. Firstly, the ICEEMD algorithm was suggested, to denoise and decompose the multi-point leakage sound signal into real leakage signal component and redundant component; sample entropy analysis was used to remove redundant components, and obtain effective signal. Secondly, observed signal was separated by blind source separation and maximum likelihood estimation, which obtains independent effective leakage signal.Then, the cross-correlation time delay method was used to calculate the time difference between the two signals reaching the upstream and downstream sensors. Finally, the precise location of a single leakage point was calculated. The results show that the method has better signal decomposition effect and can greatly improve the accuracy of multi-point leak location of pipelines.

Key words: Key words: multiple leaks, improved complete ensemble empirical mode decomposition, sample entropy, blind source separation, maximum likelihood estimation

杨健, 吴雨佳, 许宁, 李敏. 基于ICEEMD样本熵分析的管道多点泄漏定位[J]. 消防科学与技术, 2022, 41(6): 757-762.

YANG Jian, WU Yu-jia, XU Ning, LI Min. Locating of multi-point leakage in pipeline based on ICEEMD sample entropy[J]. Fire Science and Technology, 2022, 41(6): 757-762.