Applications of object-oriented approaches to neural networks in fault diagnosis

Shao Hung Chang; Jiann Liang Chen; Huan Wen Tzeng; Chin Ming Hong

Applications of object-oriented approaches to neural networks in fault diagnosis

Shao Hung Chang^*, Jiann Liang Chen, Huan Wen Tzeng, Chin Ming Hong

^*此作品的通信作者

研究成果: 書貢獻/報告類型 › 會議論文篇章

摘要

A fault diagnosis system incorporating object-oriented programming models into a neural network is developed and reported in the paper. At the same time, to draw an inference efficiently, back-propagation learning rules, statistical process control, and alpha-beta depth-first algorithm are also embedded in the system. For the purpose of fault diagnosis, the object-oriented multilayer perceptron network is first trained by the back-propagation learning rule. Then, the statistical process control is used to analyze the trends by historical data and detect suspicious components. At last, by means of the alpha-beta search technology, the most plausible fault candidates and the rank of those candidates are generated speedily.

原文	英語
主出版物標題	Proceedings of the IEEE Conference on Decision and Control
發行者	Publ by IEEE
頁面	3708-3709
頁數	2
ISBN（列印）	0780312988
出版狀態	已發佈 - 1993
對外發佈	是
事件	Proceedings of the 32nd IEEE Conference on Decision and Control. Part 2 (of 4) - San Antonio, TX, USA 持續時間: 1993 12月 15 → 1993 12月 17

出版系列

名字	Proceedings of the IEEE Conference on Decision and Control
卷	4
ISSN（列印）	0191-2216

會議

會議	Proceedings of the 32nd IEEE Conference on Decision and Control. Part 2 (of 4)
城市	San Antonio, TX, USA
期間	1993/12/15 → 1993/12/17

ASJC Scopus subject areas

控制與系統工程
建模與模擬
控制和優化

其它文件與鏈接

引用此

Chang, SH, Chen, JL, Tzeng, HW & Hong, CM 1993, Applications of object-oriented approaches to neural networks in fault diagnosis. 於 Proceedings of the IEEE Conference on Decision and Control. Proceedings of the IEEE Conference on Decision and Control, 卷 4, Publ by IEEE, 頁 3708-3709, Proceedings of the 32nd IEEE Conference on Decision and Control. Part 2 (of 4), San Antonio, TX, USA, 1993/12/15.

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abstract = "A fault diagnosis system incorporating object-oriented programming models into a neural network is developed and reported in the paper. At the same time, to draw an inference efficiently, back-propagation learning rules, statistical process control, and alpha-beta depth-first algorithm are also embedded in the system. For the purpose of fault diagnosis, the object-oriented multilayer perceptron network is first trained by the back-propagation learning rule. Then, the statistical process control is used to analyze the trends by historical data and detect suspicious components. At last, by means of the alpha-beta search technology, the most plausible fault candidates and the rank of those candidates are generated speedily.",

author = "Chang, {Shao Hung} and Chen, {Jiann Liang} and Tzeng, {Huan Wen} and Hong, {Chin Ming}",

year = "1993",

language = "English",

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N2 - A fault diagnosis system incorporating object-oriented programming models into a neural network is developed and reported in the paper. At the same time, to draw an inference efficiently, back-propagation learning rules, statistical process control, and alpha-beta depth-first algorithm are also embedded in the system. For the purpose of fault diagnosis, the object-oriented multilayer perceptron network is first trained by the back-propagation learning rule. Then, the statistical process control is used to analyze the trends by historical data and detect suspicious components. At last, by means of the alpha-beta search technology, the most plausible fault candidates and the rank of those candidates are generated speedily.

AB - A fault diagnosis system incorporating object-oriented programming models into a neural network is developed and reported in the paper. At the same time, to draw an inference efficiently, back-propagation learning rules, statistical process control, and alpha-beta depth-first algorithm are also embedded in the system. For the purpose of fault diagnosis, the object-oriented multilayer perceptron network is first trained by the back-propagation learning rule. Then, the statistical process control is used to analyze the trends by historical data and detect suspicious components. At last, by means of the alpha-beta search technology, the most plausible fault candidates and the rank of those candidates are generated speedily.

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T3 - Proceedings of the IEEE Conference on Decision and Control

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BT - Proceedings of the IEEE Conference on Decision and Control

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Applications of object-oriented approaches to neural networks in fault diagnosis

摘要

出版系列

會議

ASJC Scopus subject areas

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