書誌事項
- タイトル別名
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- Anomaly Detection Method Using Information of Operation Pattern
- ウンテン パターン ジョウホウ オ リヨウ シタ イジョウ ケンチ ギジュツ
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An anomaly detection method based on multi-dimensional time-series sensing data has been developed on the purpose of enabling condition based maintenance. The proposed method generates normal state models using the learning data selected by the plant operation information and detects anomaly based on the distance between the model and the data. Local sub-space classifier is applied for normal state model and adequate threshold is calculated using learning data. The proposed method was evaluated using 4 datasets of time-series sensing data obtained from real equipments. It was confirmed that anomaly signs several days before equipment faults was detected properly while false detection hardly occurred.
収録刊行物
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- 電気学会論文誌C(電子・情報・システム部門誌)
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電気学会論文誌C(電子・情報・システム部門誌) 133 (10), 1998-2006, 2013
一般社団法人 電気学会
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詳細情報 詳細情報について
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- CRID
- 1390001204609204736
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- NII論文ID
- 10031200991
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- NII書誌ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL書誌ID
- 024946887
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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