基于多时延识别的电站锅炉多源泄漏被动定位方法  

Passive Location of Multi-source Leakage in Power Plant Boilers Based on Multiple TDOA Recognition

作　　者：安连锁[1] 冯强[1] 沈国清[1] 姜根山[1] 张世平[1] 王鹏[1] 

机构地区：[1]华北电力大学电站设备状态监测与控制教育部重点实验室,北京102206

出　　处：《动力工程学报》2015年第10期798-804,共7页Journal of Chinese Society of Power Engineering

基　　金：国家自然科学基金资助项目(11274111);北京高等学校青年英才计划资助项目(YETP0700);华北电力大学中央高校基本科研业务费专项资金资助项目(2014MS10;2015XS77)

摘　　要：针对电站锅炉多源泄漏问题,对被动定位技术中多时延识别及定位方法等关键技术进行研究.采用PHAT加权广义互相关函数(GCC-PHAT)算法测量多时延值,通过高斯白噪声叠加炉膛背景噪声方法对其测量精度进行研究,选用球形插值法(SI算法)获得多组时延值对应定位结果,采用基于三基阵最大异类密度聚类算法筛除虚假泄漏源,并对单源、双源及三源泄漏情况进行仿真研究.结果表明:GCC-PHAT算法能够在多源泄漏情况下有效地进行多时延识别,-6db信噪比下的误差范围在0.01ms以内;随着阵元数的增加,SI算法定位精度随之提高,基于三基阵最大异类密度聚类算法在多源识别仿真中的定位精度保持在1.3%以内;通过多时延识别及基于三基阵最大异类密度聚类算法能够有效地识别泄漏源个数及位置信息.To solve the problem of multi-source leakage in power plant boilers, key technologies of passive location about multiple time delay of arrival （TDOA） recognition and location were studied. The specific way is to measure the multiple TDOA using GCC-PHAT, study the accuracy of GCC-PHAT through Gaussian white noise within boiler background noise, choose SI algorithm for location, exclude false leakage source by three-array maximum heterogeneous density cluster algorithm, and simulate the leakage con- dition under single-, dual- and triple-source environments. Results show that the GCC-PHAT algorithm can effectively identify the multiple TDOA under multi-source environments, and the range of error is 0.01 ms under the signal-to-noise ratio（SNR） of -6 db. With the rise of array elements, the accuracy of SI algorithm increases, and that of three-array maximum heterogeneous density cluster algorithm is kept within 1.3%. The number and position of leakage source can be effectively identified through multiple TDOA recognition and triple-array maximum heterogeneous density cluster algorithm.

关 键 词：电站锅炉 泄漏 多时延识别 球形插值法 基于三基阵最大异类密度聚类算法 

分 类 号：TK227[动力工程及工程热物理—动力机械及工程]