Automatic feature selection and failure diagnosis for bearing faults

Haw Ching Yang, Hao Tieng, Shih Fang Chen

研究成果: Conference contribution

摘要

This study develops a novel dual-stage diagnosis scheme for accelerating bearing failure diagnosis. The schema integrates the intelligent methods, i.e., genetic algorithm, k-nearest neighbors, and neural network, in the featuring and modeling stages to automatically select the significant features from various feature candidates for modeling bearing failure modes. After applying the scheme to classify two cases of bearing faults, the mean training time for model diagnosis is reduced to 8.1% that of using a neural network model. In this work, case 1 indicates that training and testing accuracies of seven failure modes are 98.8% and 94.5%, respectively; in addition, case 2 shows that the training and testing accuracies are 96.2% and 91.8% while using the top seven features.

原文English
主出版物標題SICE 2011 - SICE Annual Conference 2011, Final Program and Abstracts
發行者Society of Instrument and Control Engineers (SICE)
頁面235-239
頁數5
ISBN(列印)9784907764395
出版狀態Published - 2011 一月 1
事件50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011 - Tokyo, Japan
持續時間: 2011 九月 132011 九月 18

出版系列

名字Proceedings of the SICE Annual Conference

Other

Other50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011
國家Japan
城市Tokyo
期間11-09-1311-09-18

指紋

Bearings (structural)
Feature extraction
Failure modes
Neural networks
Testing
Genetic algorithms

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

引用此文

Yang, H. C., Tieng, H., & Chen, S. F. (2011). Automatic feature selection and failure diagnosis for bearing faults. 於 SICE 2011 - SICE Annual Conference 2011, Final Program and Abstracts (頁 235-239). [6060609] (Proceedings of the SICE Annual Conference). Society of Instrument and Control Engineers (SICE).
Yang, Haw Ching ; Tieng, Hao ; Chen, Shih Fang. / Automatic feature selection and failure diagnosis for bearing faults. SICE 2011 - SICE Annual Conference 2011, Final Program and Abstracts. Society of Instrument and Control Engineers (SICE), 2011. 頁 235-239 (Proceedings of the SICE Annual Conference).
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title = "Automatic feature selection and failure diagnosis for bearing faults",
abstract = "This study develops a novel dual-stage diagnosis scheme for accelerating bearing failure diagnosis. The schema integrates the intelligent methods, i.e., genetic algorithm, k-nearest neighbors, and neural network, in the featuring and modeling stages to automatically select the significant features from various feature candidates for modeling bearing failure modes. After applying the scheme to classify two cases of bearing faults, the mean training time for model diagnosis is reduced to 8.1{\%} that of using a neural network model. In this work, case 1 indicates that training and testing accuracies of seven failure modes are 98.8{\%} and 94.5{\%}, respectively; in addition, case 2 shows that the training and testing accuracies are 96.2{\%} and 91.8{\%} while using the top seven features.",
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Yang, HC, Tieng, H & Chen, SF 2011, Automatic feature selection and failure diagnosis for bearing faults. 於 SICE 2011 - SICE Annual Conference 2011, Final Program and Abstracts., 6060609, Proceedings of the SICE Annual Conference, Society of Instrument and Control Engineers (SICE), 頁 235-239, 50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011, Tokyo, Japan, 11-09-13.

Automatic feature selection and failure diagnosis for bearing faults. / Yang, Haw Ching; Tieng, Hao; Chen, Shih Fang.

SICE 2011 - SICE Annual Conference 2011, Final Program and Abstracts. Society of Instrument and Control Engineers (SICE), 2011. p. 235-239 6060609 (Proceedings of the SICE Annual Conference).

研究成果: Conference contribution

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Yang HC, Tieng H, Chen SF. Automatic feature selection and failure diagnosis for bearing faults. 於 SICE 2011 - SICE Annual Conference 2011, Final Program and Abstracts. Society of Instrument and Control Engineers (SICE). 2011. p. 235-239. 6060609. (Proceedings of the SICE Annual Conference).