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Pipeline Leak Detection and Location Based on Model-Free Isolation of Abnormal Acoustic Signals Wang, Fang; Lin, Weiguo; Liu, Zheng (Professor of engineering); Qiu, Xianbo

Abstract

Pipeline leaks will lead to energy waste, environmental pollution and a threat to human safety. This paper proposes a pipeline leak detection and location method based on the model-free isolation of abnormal (leak and operation) signals. An acoustic signal is first decomposed into “sub-signals” according to its zero-crossing points. Then, based on the definition of signal-to-noise ratio (SNR), the function between the SNR of sub-signal and the number of abnormal sub-signals is established, following which the position of each abnormal sub-signal in the acoustic signal is obtained by tracing its index. Based on this and the cross-correlation analysis, the operation sub-signals can be filtered, which is helpful for the precise leak location. The experimental results demonstrate the computational efficiency and lower false/missing alarm rate of the proposed method that provides an innovative solution for pipeline leak detection.

Item Metadata

Title
Pipeline Leak Detection and Location Based on Model-Free Isolation of Abnormal Acoustic Signals
Creator
Wang, Fang; Lin, Weiguo; Liu, Zheng (Professor of engineering); Qiu, Xianbo
Publisher
Multidisciplinary Digital Publishing Institute
Date Issued
2019-08-18
Description
Pipeline leaks will lead to energy waste, environmental pollution and a threat to human safety. This paper proposes a pipeline leak detection and location method based on the model-free isolation of abnormal (leak and operation) signals. An acoustic signal is first decomposed into “sub-signals” according to its zero-crossing points. Then, based on the definition of signal-to-noise ratio (SNR), the function between the SNR of sub-signal and the number of abnormal sub-signals is established, following which the position of each abnormal sub-signal in the acoustic signal is obtained by tracing its index. Based on this and the cross-correlation analysis, the operation sub-signals can be filtered, which is helpful for the precise leak location. The experimental results demonstrate the computational efficiency and lower false/missing alarm rate of the proposed method that provides an innovative solution for pipeline leak detection.
Subject
Leak detection; Signal decomposition; Signal-to-noise ratio calculation; Model-free; Abnormal signal isolation
Genre
Article
Type
Text
Language
eng
Date Available
2019-08-27
Provider
Vancouver : University of British Columbia Library
Rights
CC BY 4.0
DOI
10.14288/1.0380663
URI
http://hdl.handle.net/2429/71475
Affiliation
Applied Science, Faculty of; Non UBC
Citation
Energies 12 (16): 3172 (2019)
Publisher DOI
10.3390/en12163172
Peer Review Status
Reviewed
Scholarly Level
Faculty
Rights URI
https://creativecommons.org/licenses/by/4.0/
Aggregated Source Repository
DSpace

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CC BY 4.0