Particle Filter Method for Fault Diagnosis in Nonlinear System

ZHANG Ling-xia; LIU Zhi-cang; WANG Hui; QI Hui-yun; HU Dan

doi:10.3969/j.issn.0372-2112.2015.03.031

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Particle Filter Method for Fault Diagnosis in Nonlinear System

更新时间：2025-07-16

- Particle Filter Method for Fault Diagnosis in Nonlinear System
- Acta Electronica Sinica Vol. 43, Issue 3, Pages: 615-619(2015)
- 作者机构：
  
  1. 西安电子科技大学空间科学与技术学院,陕西,西安,710126
  2. 电子科技大学自动化工程学院,四川,成都,611731
- 作者简介：
- 基金信息：
  
  Innovation Fund of Near Space Vehicle Test and Control and Special Measurement and Xidian University (No.20140106)
- DOI：10.3969/j.issn.0372-2112.2015.03.031
  CLC： TP391
- Published：2015
- 稿件说明：
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ZHANG Ling-xia, LIU Zhi-cang, WANG Hui, et al. Particle Filter Method for Fault Diagnosis in Nonlinear System[J]. Acta Electronica Sinica, 2015, 43(3): 615-619.
DOI：

ZHANG Ling-xia, LIU Zhi-cang, WANG Hui, et al. Particle Filter Method for Fault Diagnosis in Nonlinear System[J]. Acta Electronica Sinica, 2015, 43(3): 615-619. DOI： 10.3969/j.issn.0372-2112.2015.03.031.

摘要

针对粒子滤波存在粒子退化问题

提出一种基于无迹卡尔曼滤波和部分重采样的改进的粒子滤波算法.通过无迹卡尔曼滤波产生重要性分布函数和使用部分重采样算法进行重采样

以丰富粒子的多样性.并针对非线性系统故障诊断中非高斯背景下

似然函数检测量难以导出的问题

提出一种基于多模型和似然函数值的诊断方法.仿真结果表明:改进的滤波算法的估计精度优于标准的粒子滤波算法及其现有的两种改进算法

提出的故障诊断方法能够做到快速检测与准确隔离.

Abstract

In order to solve particle degeneracy problem

we present an improved particle filter algorithm based on unscented Kalman filter and partial resampling algorithm.By using unscented Kalman filter to generate importance distribution function and partial resampling algorithm to resample particles

the method enriches the diversity of the particles.Furthermore

to solve the problem which likelihood detection statistics is obtained with difficulty in typically nonlinear and non-Gaussian

a fault diagnosis method based on the multiple model and the likelihood is proposed.Simulation results show the precision of the presented filter algorithm outperforms that of the standard particle filter and the improved particle filter existed in the filter system

and the proposed fault diagnosis method can detect fault quickly and isolate accurately.

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