摘要
粒子滤波算法在故障检测应用中面临的两个难题是退化问题和难以跟踪突变状态。针对上述问题,将随机摄动再采样方法和强跟踪滤波算法引入粒子滤波,提出了一种摄动粒子滤波故障检测方法,旨在于解决粒子滤波的退化问题并提高算法对突变状态的跟踪能力,从而提高故障检测方法对故障的检测准确度。通过强跟踪滤波更新粒子,来提高算法跟踪突变状态的能力;当出现退化现象时,采用随机摄动再采样方法,对粒子集中的最优粒子迭加一个随机摄动量,用摄动粒子替换粒子集中的退化粒子,解决退化问题。仿真结果显示该算法能及时、准确地检测系统故障。
Degeneracy phenomenon and the ability to track breaking states are two difficult problems for particle filter applied to fault detection.A strong tracking particle filter with perturbation for fault detection was proposed to resolve the above problems,in which,strong tracking filter and stochastic perturbation resampling were introduced to advance the veracity of fault detection.Strong tracking filter was introduced to improve the ability to track breaking states,and stochastic perturbation resampling was introduced to update the particles when the degeneracy phenomenon emerged.A stochastic perturbation was added to the best particle to form some new particles to displace the degenerative particles to solve the degeneracy phenomenon.The proposed algorithm accurately predicts faults in good time which is demonstrated by the simulation results.
作者
张琪
张志利
李天梅
郑建飞
ZHANG Qi;ZHANG Zhi-li;LI Tian-mei;ZHENG Jian-fei(Department of Control Engineering,Rocket Force University of Engineering,Xi’an 710025,China;Department of Fire Engineering,Rocket Force University of Engineering,Xi’an 710025,China)
出处
《电机与控制学报》
EI
CSCD
北大核心
2017年第11期107-113,共7页
Electric Machines and Control
基金
国家自然科学基金(61104223
61573366)
关键词
随机摄动
粒子滤波
强跟踪滤波
故障检测
stochastic perturbation
particle filter
strong tracking filter
fault detection
作者简介
通信作者：张琪（1980—），女，博士，副教授，研究方向为故障诊断、非线性滤波等；;张志利（1966—），男，博士，教授，研究方向为分布式交互仿真等；;李天梅（1980—)，女，博士，讲师，研究方向为测控工程；;郑建飞（1980—)，男，博士，讲师，研究方向为寿命预测。
