摘要
针对非线性、非高斯环境下多传感器的系统故障诊断问题,提出了一种新的基于粒子滤波的分布式故障诊断方法。通过粒子滤波得到的状态估计值的全概率分布信息可用于故障检测。首先建立系统分布式故障诊断模型,由于通信限制,假设各传感器只能向信息融合中心传输二进制数。在各观测值独立同分布的条件下,提出了分布式故障诊断算法,包括本地判决的设计和融合中心的准则设计。仿真结果表明了所提出算法的有效性和优越性。
Aiming at the fault diagnosis for nonlinear, non-Gaussian systems monitored by multiple sensors, a novel particle filtering based approach to distributed fault diagnosis is developed. One of its advantages is that the complete probability distribution information of state estimation from particle filtering is utilized for fault detection. Firstly the distributed fault model of system is set up, and it is assumed that sensors can only send binary data to the fusion center because of the communication constraints. Under the assumption of independent, identically distributed observations, a distributed fault detection algorithm is proposed, including local detector design and decision fusion rule design. Simulation results show the efficiency and superiority of our proposed algorithm.
出处
《传感器与微系统》
CSCD
北大核心
2008年第3期30-33,共4页
Transducer and Microsystem Technologies
关键词
粒子滤波
故障诊断
分布式
状态估计
particle filtering
fault diagnosis
distributed
state estimation ]
