摘要
针对混杂系统故障诊断难题,在对混杂系统描述的基础上,根据混杂系统的随机滤波公式,给出了混杂系统状态估计及离散模态识别的粒子滤波算法,并将此算法扩展到混杂系统状态与参数的联合估计,最后利用修正的Bayes算法作出故障判决,实现了混杂系统的故障诊断.通过对两容水箱这个典型混杂系统的仿真实验,结果表明,此方法不仅能准确、快速地诊断出混杂系统故障,而且在故障发生时能够保持比较高的状态与参数估计精度.本方法可推广应用于混杂系统的自适应滤波、可靠性预测、容错控制等领域.
Aimed at the problem of fault diagnosis in the hybrid system, a particle filter algorithm for hy- brid system state estimation and discrete modal identification was proposed. The proposed algorithm was spread to joint estimation of state and parameters, modified Bayes algorithm was utilized to give fault judg- ment, and fault diagnosis of hybrid system was implemented. The results of the simulation of the two-tank state estimation and fault diagnosis show that the proposed algorithm can not only accurately diagnose the hybrid system fault, maintain better state and parameter estimation accuracy when fault occurs, but also be used for adaptive filtering, reliability prediction, fault tolerant control and many other fields.
出处
《上海交通大学学报》
EI
CAS
CSCD
北大核心
2015年第6期849-854,共6页
Journal of Shanghai Jiaotong University
基金
国家自然科学基金项目(61210012)
广东省石化装备故障诊断重点实验室开放基金项目(201332)
关键词
混杂系统
粒子滤波器
故障诊断
状态估计
离散模态识别
hybrid system
particle filter
fault diagnosis
state estimation
discrete modal identification
