A Fault Diagnosis Model of Surface to Air Missile Equipment Based on Wavelet Transformation and Support Vector Machine

被引：0

作者：

Zhheng Ni ^{[1
]}

Zhang Lin ^{[1
]}

Zhang Bo ^{[1
]}

Wang Wenfeng ^{[1
]}

Shi Wenjie ^{[1
]}

Si Wei ^{[2
]}

机构：

[1] Air Force Engn Univ, Air Def & Antimissile Inst, Xian 710051, Peoples R China

[2] PLA, EAAF, Res Inst Gen Dev & Evaluat Equipment, Beijing 100191, Peoples R China

来源：

2016 ASIA CONFERENCE ON POWER AND ELECTRICAL ENGINEERING (ACPEE 2016) | 2016年 / 55卷

关键词：

D O I：

10.1051/matecconf/20165503004

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

At present, the fault signals of surface to air missile equipment are hard to collect and the accuracy of fault diagnosis is very low. To solve the above problems, based on the superiority of wavelet transformation on processing non-stationary signals and the advantage of SVM on pattern classification, this paper proposes a fault diagnosis model and takes the typical analog circuit diagnosis of one power distribution system as an example to verify the fault diagnosis model based on Wavelet Transformation and SVM. The simulation results show that the model is able to achieve fault diagnosis based on a small amount of training samples, which improves the accuracy of fault diagnosis.

引用

页数：6

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