Energies · 2019 · 19 citations · 30 references
EngineeringEnvironmental EngineeringPetroleum EngineeringAcousticsComputational AcousticsProcess SafetyAcoustic DiagnosticsAcoustic SensorsAcoustic Signal ProcessingDigital Signal ProcessingLeak DetectionSignal Detection TheoryAcoustic Leak LocalizationCross-correlation AnalysisEnvironmental PollutionLeak LocalizationLeak LocationLeakage LocalizationPipeline Leak DetectionSignal-to-noise Ratio
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.
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Support Vector Data Description
David M. J. Tax, Robert P. W. Duin · Machine Learning · 2003 · 3.5K citations · Full text
Pipeline Leak Detection by Using Time-Domain Statistical Features
Fang Wang, Weiguo Lin, Zheng Liu et al. · IEEE Sensors Journal · 2017 · 145 citations