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基于同源性检验的干扰信号识别方法 被引量:5

Identification method of interference signals based on homology test
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摘要 针对强干扰背景下管道泄漏声波检测产生的误报和漏报,提出一种基于同源性检验的干扰信号识别方法。将干扰信号和泄漏信号均作为异常信号,在基于迭代计算的异常信号自适应提取和一对一互相关延时估计的基础上,找出定位在站点的上下游异常信号并计算出相应的传播衰减特性。以同源信号的传播衰减频域特征和互相关系数为特征向量,建立异常信号同源性检验的支持向量数据描述(SVDD)诊断模型,实现站上干扰信号的识别和分离。对实际原油输送管线历史数据的离线测试结果表明:提出的方法能够可靠识别与分离干扰信号,有效减少系统的误报和漏报,并提高泄漏检测的可靠性和定位精度。 Aiming at false and missing alarms generated by pipeline leak acoustic wave detection under strong interference background,an approach for interference signal identification based on homology test is proposed.Interference and leak signals are all regarded as abnormal signals,on the basis of abnormal signal adaptive extraction of iterative computations and one to one cross-correlation time delay estimation,the abnormal signals from upstream and downstream,which located on the site with cross correlation are extracted,and the propagation damping characteristics are calculated. Use propagation damping frequency domain features and the crosscorrelation coefficient as the feature vector,a SVDD diagnostic model for homology test of abnormal signals is established. With the homology test diagnostic model,the identification and separation of interference signals can be implemented. The off-line test of historical field data collected from a crude oil transportation pipeline is conducted,test result shows that: the approach can reliably distinguish interference signals caused by site operation;false and missing alarms are effectively reduced,and the reliability of leak detection and the precision of localization are both improved.
作者 许春香 许海涛 林伟国 XU Chun-xiang;XU Hai-tao;LIN Wei-guo(School of Civil Engineering,Zhengzhou Institute of Technology,Zhengzhou 450044,China;College of Information Science and Technology,Beijing University of Chemical Technology,Beijing 100029,China)
出处 《传感器与微系统》 CSCD 2019年第1期36-40,共5页 Transducer and Microsystem Technologies
基金 2016年度河南省科技攻关计划资助项目(162102210131) 中州大学科技创新团队建设计划资助项目(CXTD2017K4)
关键词 强干扰背景 异常信号提取 同源性检验 一对一互相关估计 干扰信号识别 strong interference background abnormal signal extraction homology test one to one crosscorrelation estimation interference signal identification
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