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
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 十二月 151993 十二月 17

出版系列

名字Proceedings of the IEEE Conference on Decision and Control
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1993/12/151993/12/17

ASJC Scopus subject areas

  • 控制與系統工程
  • 建模與模擬
  • 控制和優化

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