基于能量分析重构VMD分量的直埋供热管道泄漏定位研究
摘要：为提高声波法在复杂噪声环境下进行直埋供热管道泄漏定位的准确性，本文提出了基于能量分析重构有效模态分量的供热管道泄漏定位方法，即采用变分模态分解(VMD)将检测信号自适应地分解为一组本征模态函数(IMF),识别、提取有泄漏特征的有效模态分量，并通过能量占比分析完成信号加权重构。泄漏实验和工程实测表明：常规VMD泄漏定位方法与本文方法的平均定位偏差分别为1.57、0.51 m,相对定位偏差分别为8.42%、2.75%,采用本文方法定位准确性提高67.34%;工程实测中，常规VMD方法未能发现管道泄漏位置，本文方法确定的泄漏位置定位偏差为1.78 m;本文方法可抑制有效模态分量中的残余噪声，降低噪声成分对泄漏定位的影响，提高复杂噪声环境下供热管道泄漏定位精度。
关键词：声波法供热管道变分模态分解能量分析信号重构信号降噪泄漏定位
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[2] 国家统计局.中国统计年鉴2022[M].北京：中国统计出版社，2022:10.
[3] 任鹏召.大管径直埋供热管道受力与稳定性分析[D].北京：北京科技大学，2019:1.
[4] 曹姗姗，王芃，姚杨.直埋敷设供热管道腐蚀失效概率仿真研究[J].暖通空调，2019,49(3):115- 120.
[5] SEKHAVATI J,HASHEMABADI S H,SOROUSH M.Computational methods for pipeline leakage detection and localization:a review and comparative study[J].Journal of loss prevention in the process industries,2022,77:104771.
[6] 路炜，文玉梅.供水管道泄漏声信号及其传播特性[J].声学技术，2007,26(5):871- 876.
[7] DRAGOMIRETSKIY K,ZOSSO D.Variational mode decomposition[J].IEEE transactions on signal processing,2014,62(3):531- 544.
[8] 路敬祎，马雯萍，高丙坤，等.可变模态分解算法及其在天然气管道泄漏检测中的应用[J].化工自动化及仪表，2016,43(7):694- 700,739.
[9] LIU Y Y,YANG G L,LI M,et al.Variational mode decomposition denoising combined the detrended fluctuation analysis[J].Signal processing,2016,125:349- 364.
[10] 钱林，康敏，傅秀清，等.基于VMD的自适应形态学在轴承故障诊断中的应用[J].振动与冲击，2017,36(3):227- 233.
[11] 吴珊珊，胡国兵，张照锋，等.变模式分解在供水管道漏点定位中的应用研究[J].电子器件，2017,40(4):1036- 1043.
[12] 马增强，张俊甲，张安，等.基于VMD-SVD联合降噪和频率切片小波变换的滚动轴承故障特征提取[J].振动与冲击，2018,37(17):210- 217.
[13] 李帅永，夏传强，程振华，等.基于VMD和互谱分析的供水管道泄漏定位方法[J].仪器仪表学报，2019,40(7):195- 205.
[14] LU J Y,YUE J K,ZHU L J,et al.Variational mode decomposition denoising combined with improved Bhattacharyya distance[J].Measurement,2020,151:107283.
[15] 阮强，王贵勇，刘韬，等.自适应VMD联合MOMEDA的滚动轴承故障提取[J].电子测量技术，2022,45(1):165- 171.
[16] ZENG W,CAZZOLATO B,LAMBERT M,et al.Coherenceogram for leak detection in water pipes[J].Journal of sound and vibration,2022,530:116979.
[17] LEE W T,TAN A C,TEY J Y,et al.Wave velocity selection for leakage localization of water pipeline by variational mode decomposition[J].IOP conference series:earth and environmental science,2019,268(1):012054.
[18] KNAPP C,CARTER G.The generalized correlation method for estimation of time delay[J].IEEE transactions on acoustics,speech,and signal processing,1976,24(4):320- 327.
[19] 张俊甲，马增强，王梦奇，等.基于VMD与自相关分析的滚动轴承故障特征提取[J].电子测量与仪器学报，2017,31(9):1372- 1378.
[20] 廖康桥，张立申，王随林，等.热水供热管道泄漏声波特性与传播规律[J].暖通空调，2022,52(4):152- 159.
[21] 李帅永，韩明秀，文井辉.基于VMD-SVD自优化的管道微泄漏信号增强方法[J].电子测量与仪器学报，2021,35(12):68- 78.
Study on leakage location of directly buried heating pipelines by reconstructed VMD components based on energy analysis
Abstract: To improve the accuracy of acoustic wave method for the directly buried heating pipeline leakage location in the complex noise environments, this paper proposes a leakage location method for heating pipelines based on energy analysis to reconstruct the effective modal components, that is, the variational mode decomposition(VMD) is used to adaptively decompose the detection signals into a group of intrinsic mode functions(IMF), identify and extract the effective modal components with leakage features, and complete the signal weighted reconstruction through energy proportion analysis. The leakage tests and engineering measurements show that the average location deviation by the conventional VMD leakage location method is 1.57 m while that of the proposed method is 0.51 m, along with their relative deviations of 8.42% and 2.75%, respectively. The leakage location accuracy of the proposed method is improved by 67.34%. In the engineering measurements, the conventional VMD method fails to find the leakage location of the pipeline, while the proposed method finds the leakage location and its location deviation is 1.78 m different from the actual location. The proposed method can effectively suppress the residual noises in the effective modal components, reduce the influence of noise components on the leakage location, and improve the leakage location accuracy of heating pipeline in the complex noise environments.
Keywords: acoustic wave method; heating pipeline; variational mode decomposition(VMD); energy analysis; signal reconstruction; signal denoising; leakage location;
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