基于VMD和SVM的充液管道泄漏检测方法

IF 1.6 3区 环境科学与生态学 Q3 WATER RESOURCES
Si-Liang Zhao, Shaogang Liu, Bo Qiu, Zhou Hong, Dan Zhao, Liqiang Dong
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引用次数: 2

摘要

摘要为了解决外部噪声干扰下泄漏信号特征不明显的问题,提出了一种基于变分模态分解(VMD)和支持向量机(SVM)相结合的泄漏检测方法。该方法首先计算VMD获得的多个固有模态分量(IMF)与源信号的斯皮尔曼相关系数(SCC),然后提取SCC较大的IMF的能量和中心频率特征,最后使用SVM分类器进行泄漏检测。实验结果表明,VMD-SVM方法能够有效地进行泄漏检测,准确率为98.27%。与时频(TF)特征SVM、经验模态分解(EMD)特征SVM和小波(DWT)特征SVM方法相比,本文提出的VMD-SVM法的准确率分别提高了6.5%、5.63%和10.39%。此外,还分析了特征灵敏度,以在确保准确性的同时降低模型复杂性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Leak detection method of liquid-filled pipeline based on VMD and SVM
ABSTRACT In order to solve the problem of inconspicuous leakage signal characteristics under external noise interference, a leakage detection method based on the combination of variational modal decomposition (VMD) and support vector machine (SVM) is proposed. The method first calculates the spearman correlation coefficients (SCC) of multiple intrinsic modal components (IMFs) obtained by VMD with the source signal, then extracts the energy and central frequency features of IMFs with larger SCC, and finally performs leak detection using the SVM classifier. The experimental results show that the VMD-SVM method can effectively perform leak detection with an accuracy of 98.27%. The accuracy of the VMD-SVM method proposed in this paper is improved by 6.5%, 5.63% and 10.39% compared to the time-frequency (TF) feature SVM, empirical modal decomposition (EMD) feature SVM and wavelet (DWT) feature SVM, methods, respectively. In addition, feature sensitivities are analyzed to reduce model complexity while ensuring accuracy.
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来源期刊
Urban Water Journal
Urban Water Journal WATER RESOURCES-
CiteScore
4.40
自引率
11.10%
发文量
101
审稿时长
3 months
期刊介绍: Urban Water Journal provides a forum for the research and professional communities dealing with water systems in the urban environment, directly contributing to the furtherance of sustainable development. Particular emphasis is placed on the analysis of interrelationships and interactions between the individual water systems, urban water bodies and the wider environment. The Journal encourages the adoption of an integrated approach, and system''s thinking to solve the numerous problems associated with sustainable urban water management. Urban Water Journal focuses on the water-related infrastructure in the city: namely potable water supply, treatment and distribution; wastewater collection, treatment and management, and environmental return; storm drainage and urban flood management. Specific topics of interest include: network design, optimisation, management, operation and rehabilitation; novel treatment processes for water and wastewater, resource recovery, treatment plant design and optimisation as well as treatment plants as part of the integrated urban water system; demand management and water efficiency, water recycling and source control; stormwater management, urban flood risk quantification and management; monitoring, utilisation and management of urban water bodies including groundwater; water-sensitive planning and design (including analysis of interactions of the urban water cycle with city planning and green infrastructure); resilience of the urban water system, long term scenarios to manage uncertainty, system stress testing; data needs, smart metering and sensors, advanced data analytics for knowledge discovery, quantification and management of uncertainty, smart technologies for urban water systems; decision-support and informatic tools;...
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