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

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 classificati...

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Main Authors:	Zhheng Ni, Zhang Lin, Zhang Bo, Wang Wenfeng, Shi Wenjie, Si Wei
Format:	Article
Language:	English
Published:	EDP Sciences 2016-01-01
Series:	MATEC Web of Conferences
Online Access:	http://dx.doi.org/10.1051/matecconf/20165503004

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spelling	doaj-9ecd32955aa34b4bb44c49db12a6ac562021-02-02T00:48:35ZengEDP SciencesMATEC Web of Conferences2261-236X2016-01-01550300410.1051/matecconf/20165503004matecconf_acpee2016_03004A Fault Diagnosis Model of Surface to Air Missile Equipment Based on Wavelet Transformation and Support Vector MachineZhheng Ni0Zhang Lin1Zhang Bo2Wang Wenfeng3Shi Wenjie4Si Wei5Air Defense and Antimissile Institute, Air Force Engineering UniversityAir Defense and Antimissile Institute, Air Force Engineering UniversityAir Defense and Antimissile Institute, Air Force Engineering UniversityAir Defense and Antimissile Institute, Air Force Engineering UniversityAir Defense and Antimissile Institute, Air Force Engineering UniversityThe Research Institute on General Development and Evaluation of Equipment, EAAF of PLAAt 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.http://dx.doi.org/10.1051/matecconf/20165503004
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Zhheng Ni Zhang Lin Zhang Bo Wang Wenfeng Shi Wenjie Si Wei
spellingShingle	Zhheng Ni Zhang Lin Zhang Bo Wang Wenfeng Shi Wenjie Si Wei A Fault Diagnosis Model of Surface to Air Missile Equipment Based on Wavelet Transformation and Support Vector Machine MATEC Web of Conferences
author_facet	Zhheng Ni Zhang Lin Zhang Bo Wang Wenfeng Shi Wenjie Si Wei
author_sort	Zhheng Ni
title	A Fault Diagnosis Model of Surface to Air Missile Equipment Based on Wavelet Transformation and Support Vector Machine
title_short	A Fault Diagnosis Model of Surface to Air Missile Equipment Based on Wavelet Transformation and Support Vector Machine
title_full	A Fault Diagnosis Model of Surface to Air Missile Equipment Based on Wavelet Transformation and Support Vector Machine
title_fullStr	A Fault Diagnosis Model of Surface to Air Missile Equipment Based on Wavelet Transformation and Support Vector Machine
title_full_unstemmed	A Fault Diagnosis Model of Surface to Air Missile Equipment Based on Wavelet Transformation and Support Vector Machine
title_sort	fault diagnosis model of surface to air missile equipment based on wavelet transformation and support vector machine
publisher	EDP Sciences
series	MATEC Web of Conferences
issn	2261-236X
publishDate	2016-01-01
description	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.
url	http://dx.doi.org/10.1051/matecconf/20165503004
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A Fault Diagnosis Model of Surface to Air Missile Equipment Based on Wavelet Transformation and Support Vector Machine

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