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非高斯噪声下基于Unscented粒子滤波器的非线性系统故障诊断方法
引用本文:葛哲学,杨拥民,胡政,陈仲生.非高斯噪声下基于Unscented粒子滤波器的非线性系统故障诊断方法[J].兵工学报,2007,28(3):332-335.
作者姓名:葛哲学  杨拥民  胡政  陈仲生
作者单位:国防科技大学机电工程研究所,湖南长沙410073
基金项目:国家自然科学基金,部委预先研究项目
摘    要:非高斯噪声下非线性系统的故障诊断中,一般是基于粒子滤波器的方法,但普通粒子滤波器通常会发生“退化”现象,严重影响故障的检测和诊断品质。本文通过引入Unscented粒子滤波器方法,利用Unscented变换对随机分布的非线性概率传递能力来产生建议分布,能明显地改善普通粒子滤波器的性能;然后,提出了基于该滤波器的序贯式故障诊断策略,采用负对数似然比方法监控系统的运行状态,故障发后利用状态联合估计器进行故障隔离。计算实例表明,该新方法能实时检测诊断出非线性系统的故障,同时能抑制非高斯噪声的影响。

关 键 词:机械制造自动化      故障诊断      粒子滤波      非高斯噪卢      Unscented变换      联合估计  
文章编号:1000-1093(2007)03-0332-04
修稿时间:04 12 2006 12:00AM

Unscented Particle Filter-based Fault Diagnosis of Non-linear System with Non-Gaussian Noises
GE Zhe-xue,YANG Yong-min,HU Zheng,CHEN Zhong-sheng.Unscented Particle Filter-based Fault Diagnosis of Non-linear System with Non-Gaussian Noises[J].Acta Armamentarii,2007,28(3):332-335.
Authors:GE Zhe-xue  YANG Yong-min  HU Zheng  CHEN Zhong-sheng
Affiliation:College of Mechatronics Engineering and Automation, National University of Defense Technology, Changsha 410073,Hunan, China
Abstract:The traditional method of fault diagnosis of nonlinear system with non-Gaussian noises is based on particle filter. However, ordinary particle filter has the problem of degeneracy and therefore deteriorates the fault diagnosis performance. Based on generic particle filter, a new Unscented particle filter method was brought forward to estimate the system true state. The estimation performance of the new method was markedly improved by generated importance proposal distribution. A sequential strategy of fault diagnosis was presented and negative log likelihood ratio was used to detect the fault. When a fault occurred, a new joint estimation method was used to isolate the fault. Computational results demonstrate that the proposed method can detect and diagnose faults Of a nonlinear system, and suppress non-Gaussian noises.
Keywords:mechanical manufacture and automation  fault diagnosis  particle filtering  non-Gaussian noise  Unscented transform  joint estimation
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