Fault diagnosis of nuclear-powered equipment based on HMM&SVM

被引：0
|
作者：
Yue, Xia [1 ,2 ]
Zhang, Chun-Liang [2 ]
Quan, Yan-Ming [1 ]
Zhu, Hou-Yao [2 ]
机构：
[1] South China University of Technology, Guangzhou, 510641, China
[2] Guangzhou University, Guangzhou, 510006, China
来源：
Hedongli Gongcheng/Nuclear Power Engineering | 2012年 / 33卷 / 03期
关键词：
Hidden Markov models - Fault detection - Support vector machines;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
For the complexity and the small fault samples of nuclear-powered equipment, a hybrid HMM/SVM method was introduced in fault diagnosis. The hybrid method has two steps: first, HMM is utilized for primary diagnosis, in which the range of possible failure is reduced and the state trends can be observed; then faults can be recognized taking the advantage of the generalization ability of SVM. Experiments on the main pump failure simulator show that the HMM/SVM system has a high recognition rate and can be used in the fault diagnosis of nuclear-powered equipment.
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页码：104 / 108
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