An Guorui, Huang Zuheng, Li Yanbing
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, 100044, China.
Sci Rep. 2023 Aug 29;13(1):14149. doi: 10.1038/s41598-023-41177-3.
During the transportation of oil and gas pipelines, there are many potential factors that can lead to pipeline leakage with serious consequences, making automatic and real-time pipeline leakage detection urgent. In response to the inconvenience of manual detection, constant false alarm rate (CFAR) detection technique in radar target detection theory is introduced for pipeline leakage detection based on acoustic signals. In this paper, an automatic pipeline leakage detection algorithm based on an improved CFAR detector is proposed. The improved CFAR detection is executed after pre-processing the acoustic signals so as to adaptively set the detection threshold to achieve the purpose of automatic detection of pipeline leakage incidents. A simulated leakage test of a real pipeline is used for validation, and the proposed method achieves detection accuracies of 84.6%, 97.7%, and 98% for different leakage diameter settings, i.e., 5 mm, 7 mm, and 10 mm leak hole diameters, respectively, with an overall accuracy of 94.1%, while the false alarm rates are 3.3%, 0.7%, and 0, respectively, as well as an overall of 1.2%. The results of experimental data based on real scenarios demonstrate the effectiveness of the proposed method.
在油气管道运输过程中,存在许多潜在因素可能导致管道泄漏,后果严重,因此管道泄漏的自动实时检测迫在眉睫。针对人工检测的不便,将雷达目标检测理论中的恒虚警率(CFAR)检测技术引入到基于声信号的管道泄漏检测中。本文提出了一种基于改进CFAR检测器的管道泄漏自动检测算法。对声信号进行预处理后执行改进的CFAR检测,以自适应设置检测阈值,达到自动检测管道泄漏事件的目的。利用真实管道的模拟泄漏试验进行验证,该方法对于不同泄漏直径设置(即泄漏孔直径分别为5mm、7mm和10mm)的检测准确率分别达到84.6%、97.7%和98%,总体准确率为94.1%,而误报率分别为3.3%、0.7%和0,总体误报率为1.2%。基于实际场景的实验数据结果证明了该方法的有效性。