利用自适应粒子滤波的传感器故障诊断识别  

Sensor Fault Diagnosis and Identification Method Using Adaptive Particle Filter

作　　者：刘红艳[1] 麦艳红[1] 孔繁镍[2] 母三民[1] LIU Hong-yan;MAI Yan-hong;KONG Fan-nie;MU San-min(School of Mechatronic Engineering, Nanning Collage for Vocational Technology, Nanning 530008, China;School of Electrical Engineering, Guangxi University, Nanning 530004, China)

机构地区：[1]南宁职业技术学院机电工程学院,南宁530008 [2]广西大学电气工程学院,南宁530004

出　　处：《控制工程》2019年第7期1425-1430,共6页Control Engineering of China

基　　金：国家自然科学基金(51167003);2018年度广西高校中青年教师基础能力提升项目(2018KY0974);2018中国高等教育学会职业技术教育分会重点课题(GZYZD2018030);2018年度南宁职业技术学院职业教育教学改革研究项目(2018JG12);2017年度广西职业教育教学改革研究项目(GXGZJG2017B212),2017年度广西职业教育教学改革研究项目(GXGZJG2017B164)

摘　　要：在随机非线性或非高斯系统中,因突然发生的校准型错误而引发的读数偏置或缩放等传感器故障,会对系统的准确检测与稳定控制带来不利影响.针对该问题,提出一种新型的故障诊断和识别方法.设计一种自适应粒子滤波器来计算测量值和粒子滤波器估计值之差,进而利用最大似然估计来确定故障的类型和幅值,从而精确地诊断传感器故障,并对故障造成的影响进行实时补偿.在锅炉模型中进行了相关仿真实验,实验结果证明了所提方法的有效性.In the general stochastic nonlinear and non-Gaussian systems, the sensor faults including biased and scaled readings caused by sudden calibration errors have adverse effect on the precise monitor and stable control of the system. To deal with this problem, a novel diagnosis and identification method is proposed. An adaptive particle filter is developed to calculate the difference between the measurements and the particle filter estimates, then the type and magnitude of sensor faults are determined through with maximum likelihood estimation, thus the fast and precise detection of sensor fault is realized, and the adverse effect caused by the faults can be compensated. Some simulations are carried out on a boiler model, and the results validate the effectiveness of the proposed method.

关 键 词：传感器 故障检测和识别 自适应粒子滤波器 最大似然估计 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]