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On-line Residual Life Prediction Including Outlier Elimination for Condition Based Maintenance

発表形態:
原著論文
主要業績:
主要業績
単著・共著:
共著
発表年月:
2012年03月
DOI:
会議属性:
指定なし
査読:
有り
リンク情報:

日本語フィールド

著者:
Satoru Goto and Kenta Tsukamoto
題名:
On-line Residual Life Prediction Including Outlier Elimination for Condition Based Maintenance
発表情報:
International Journal of Innovative Computing, Information and Control 巻: 8 号: 3(B) ページ: 2193-2202
キーワード:
On-line prediction, Outlier elimination, Deterioration prediction, Residual life prediction, Condition based maintenance
概要:
抄録:
A method of on-line residual life prediction is proposed for condition based maintenance of industrial equipment. With on-line monitoring of condition of the indus- trial equipment, the residual life is evaluated by using on-line prediction of the equipment deterioration. The deterioration prediction is based on an on-line identification of the mathematical model of deterioration process. To improve the accuracy of the deteriora- tion prediction, outlier elimination technique is introduced. The proposed method was applied to actual data of rotating equipment in a thermal power plant and the results verified the effectiveness of the proposed method.

英語フィールド

Author:
Satoru Goto and Kenta Tsukamoto
Title:
On-line Residual Life Prediction Including Outlier Elimination for Condition Based Maintenance
Announcement information:
International Journal of Innovative Computing, Information and Control Vol: 8 Issue: 3(B) Page: 2193-2202
Keyword:
On-line prediction, Outlier elimination, Deterioration prediction, Residual life prediction, Condition based maintenance
An abstract:
A method of on-line residual life prediction is proposed for condition based maintenance of industrial equipment. With on-line monitoring of condition of the indus- trial equipment, the residual life is evaluated by using on-line prediction of the equipment deterioration. The deterioration prediction is based on an on-line identification of the mathematical model of deterioration process. To improve the accuracy of the deteriora- tion prediction, outlier elimination technique is introduced. The proposed method was applied to actual data of rotating equipment in a thermal power plant and the results verified the effectiveness of the proposed method.


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