Fault prediction method of improving particle filter with support vector regression

被引：0

作者：

Deng, Sen ^{[1
]}

Jing, Bo ^{[1
]}

Zhou, Hong-Liang ^{[1
]}

机构：

[1] Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi'an 710038, China

来源：

Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2012年 / 18卷 / 09期

关键词：

Fault prediction - Linear functions - Particle degeneracy - Particle filter - Particle state - Posterior probability - Sample impoverishment - System faults;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Aiming at the problem of particle degeneracy and sample impoverishment in fault prediction, an improving particle filter with support vector regression was proposed. The no-linear function of particle state and its weight was established by using support vector regression to estimate the particle's posterior probability density model. Based on this model, the new particle was obtained and weights of particles were updated by resampling, and the diversity and effectiveness of samples were improved. Thus the ability to control and predict the fault was raised. Simulation result demonstrated that the method was feasible and system fault could be predicted correctly.

引用

页码：2012 / 2017