Dynamic Multiple Fault Diagnosis Based on HMM and BPSO

被引：1

作者：

Liu Xiaoqin ^{[1
]}

Dong Zewei ^{[1
]}

Qu Hongdong ^{[1
]}

Song Limei ^{[2
]}

机构：

[1] Army Aviat Inst PLA, Dept Avion & Weap Engn, Beijing, Peoples R China

[2] Army Aviat Inst PLA, Dept Flight Simulat Training, Beijing, Peoples R China

来源：

2015 FIFTH INTERNATIONAL CONFERENCE ON INSTRUMENTATION AND MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC) | 2015年

关键词：

dynamic multiple fault diagnosis; Hidden Markov Model; BPSO;

D O I：

10.1109/IMCCC.2015.46

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

For systems needed short diagnosis delay, dynamic multiple faults diagnosis (DMFD) is put forward for the systems of demanding diagnosis quickly. In this paper, a method of DMFD based Hidden Markov Mode (HMM) is established for the system's inner states transform and the corresponding external observing sequence, thus the inner states transform could be recovered from the external observing sequence with the decoding algorithm of HMM, which belongs to NP completeness problems. This paper decomposes original DMFD problem into several separable subproblems, and solves each of them with binary particle swarm optimization algorithm(BPSO). It is shown from the application examples that the system's real-time health status could be evaluated at a high correct ratio with this method.

引用

页码：186 / 191

页数：6

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