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- 田村 雅之
- 東京ガス(株)技術研究所
書誌事項
- タイトル別名
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- Designing Empirical Diagnostic Rules for Plant Start-Up Monitoring Using Dynamic Time Warping
- プラント キドウジ ニ オケル ケイケンテキ シンダン ロジック ノ ドウテキ ジカン シンシュクホウ ニ ヨル セッケイホウ
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A novel design method of empirical if-then rules for diagnosis of plant start-up sequences is proposed. The rules dealt with in this paper take form of "If variable Y is out of the determined range when variable X becomes X_0, then raise alarm", which is one of the styles of rules commonly implemented in practical plant control logic. When sufficient number of normal and abnormal data is available, one can build empirical if-then rules for early detection of abnormal start-up sequences. Conventionally the rules are built by expert engineers based on their experiences, and inevitably in subjective way. Present paper proposes a design method which can objectively give an optimal rule. The first step of the proposed method is 'alignment' of data profiles using dynamic time warping. The second step is calculations of correlation ratios of data to find the best condition to distinguish normal and abnormal start-up sequences. A simulation study of a natural gas fueled plant is used as an example of applications of the proposed method.
収録刊行物
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- 日本機械学会論文集C編
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日本機械学会論文集C編 76 (767), 1649-1654, 2010
一般社団法人 日本機械学会
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詳細情報 詳細情報について
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- CRID
- 1390282681362726528
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- NII論文ID
- 110007682154
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- NII書誌ID
- AN00187463
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- ISSN
- 18848354
- 03875024
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- NDL書誌ID
- 10784193
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可