The research of sensor fault diagnosis based on genetic algorithm and one-against-one support vector machine

Lishuang Xu; Tao Cai; Fang Deng; Xin Liu

doi:10.1109/ICICIP.2011.6008360

The research of sensor fault diagnosis based on genetic algorithm and one-against-one support vector machine

Lishuang Xu^*, Tao Cai, Fang Deng, Xin Liu

^*此作品的通讯作者

Beijing Institute of Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

2 引用（Scopus）

摘要

Fault diagnosis based on the wavelet packet decomposition, one-against-one support vector machine (SVM) and genetic algorithm (GA) is proposed in order to realize the real-time sensor fault diagnosis accurately. The input feature vectors of one-against-one SVM are produced by wavelet packet decomposition of the sensor output signal. GA is used to obtain optimal parameters of one-against-one SVM network model automatically, which can enhance the training speed and performance. The experiments of photoelectric encoder fault diagnosis show that the combination of these methods makes SVM own a better recognition rate and overall performance, which can improve the accuracy and time efficiency of fault diagnosis.

源语言	英语
主期刊名	Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011
页	808-812
页数	5
版本	PART 2
DOI	https://doi.org/10.1109/ICICIP.2011.6008360
出版状态	已出版 - 2011
活动	2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011 - Harbin, 中国期限: 25 7月 2011 → 28 7月 2011

出版系列

姓名	Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011
编号	PART 2

会议

会议	2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011
国家/地区	中国
市	Harbin
时期	25/07/11 → 28/07/11

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10.1109/ICICIP.2011.6008360

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引用此

Xu, L., Cai, T., Deng, F., & Liu, X. (2011). The research of sensor fault diagnosis based on genetic algorithm and one-against-one support vector machine. 在 Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011 (PART 2 编辑, 页码 808-812). 文章 6008360 (Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011; 号码 PART 2). https://doi.org/10.1109/ICICIP.2011.6008360

Xu, Lishuang ; Cai, Tao ; Deng, Fang 等. / The research of sensor fault diagnosis based on genetic algorithm and one-against-one support vector machine. Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011. PART 2. 编辑 2011. 页码 808-812 (Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011; PART 2).

@inproceedings{a2819f5e4e4b4b0cb6ac7eacb47b8794,

title = "The research of sensor fault diagnosis based on genetic algorithm and one-against-one support vector machine",

abstract = "Fault diagnosis based on the wavelet packet decomposition, one-against-one support vector machine (SVM) and genetic algorithm (GA) is proposed in order to realize the real-time sensor fault diagnosis accurately. The input feature vectors of one-against-one SVM are produced by wavelet packet decomposition of the sensor output signal. GA is used to obtain optimal parameters of one-against-one SVM network model automatically, which can enhance the training speed and performance. The experiments of photoelectric encoder fault diagnosis show that the combination of these methods makes SVM own a better recognition rate and overall performance, which can improve the accuracy and time efficiency of fault diagnosis.",

author = "Lishuang Xu and Tao Cai and Fang Deng and Xin Liu",

year = "2011",

doi = "10.1109/ICICIP.2011.6008360",

language = "English",

isbn = "9781457708145",

series = "Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011",

number = "PART 2",

pages = "808--812",

booktitle = "Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011",

edition = "PART 2",

note = "2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011 ; Conference date: 25-07-2011 Through 28-07-2011",

}

Xu, L, Cai, T , Deng, F & Liu, X 2011, The research of sensor fault diagnosis based on genetic algorithm and one-against-one support vector machine. 在 Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011. PART 2 编辑, 6008360, Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011, 号码 PART 2, 页码 808-812, 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011, Harbin, 中国, 25/07/11. https://doi.org/10.1109/ICICIP.2011.6008360

The research of sensor fault diagnosis based on genetic algorithm and one-against-one support vector machine. / Xu, Lishuang; Cai, Tao ; Deng, Fang 等.
Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011. PART 2. 编辑 2011. 页码 808-812 6008360 (Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011; 号码 PART 2).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

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T1 - The research of sensor fault diagnosis based on genetic algorithm and one-against-one support vector machine

AU - Xu, Lishuang

AU - Cai, Tao

AU - Deng, Fang

AU - Liu, Xin

PY - 2011

Y1 - 2011

N2 - Fault diagnosis based on the wavelet packet decomposition, one-against-one support vector machine (SVM) and genetic algorithm (GA) is proposed in order to realize the real-time sensor fault diagnosis accurately. The input feature vectors of one-against-one SVM are produced by wavelet packet decomposition of the sensor output signal. GA is used to obtain optimal parameters of one-against-one SVM network model automatically, which can enhance the training speed and performance. The experiments of photoelectric encoder fault diagnosis show that the combination of these methods makes SVM own a better recognition rate and overall performance, which can improve the accuracy and time efficiency of fault diagnosis.

AB - Fault diagnosis based on the wavelet packet decomposition, one-against-one support vector machine (SVM) and genetic algorithm (GA) is proposed in order to realize the real-time sensor fault diagnosis accurately. The input feature vectors of one-against-one SVM are produced by wavelet packet decomposition of the sensor output signal. GA is used to obtain optimal parameters of one-against-one SVM network model automatically, which can enhance the training speed and performance. The experiments of photoelectric encoder fault diagnosis show that the combination of these methods makes SVM own a better recognition rate and overall performance, which can improve the accuracy and time efficiency of fault diagnosis.

UR - http://www.scopus.com/inward/record.url?scp=80053201507&partnerID=8YFLogxK

U2 - 10.1109/ICICIP.2011.6008360

DO - 10.1109/ICICIP.2011.6008360

M3 - Conference contribution

AN - SCOPUS:80053201507

SN - 9781457708145

T3 - Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011

SP - 808

EP - 812

BT - Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011

T2 - 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011

Y2 - 25 July 2011 through 28 July 2011

ER -

Xu L, Cai T , Deng F , Liu X. The research of sensor fault diagnosis based on genetic algorithm and one-against-one support vector machine. 在 Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011. PART 2 编辑 2011. 页码 808-812. 6008360. (Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, ICICIP 2011; PART 2). doi: 10.1109/ICICIP.2011.6008360

The research of sensor fault diagnosis based on genetic algorithm and one-against-one support vector machine

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