書誌事項
- タイトル別名
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- Fault Diagnosis System of Electromagnetic Valve Using Neural Network Filter
- ニューラル ネットワーク フィルタ オ モチイタ クウキアツ デンジベン ノ オンキョウ コショウ シンダン
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This paper is concerned with the gas leakage fault detection of electromagnetic valve using a neural network filter. In modern plants, the ability to detect and identify gas leakage faults is becoming increasingly important. The main difficulty in detecting gas leakage faults by sound signals lies in the fact that the practical plants are usually very noisy. To solve this difficulty, a neural network filter is used to eliminate background noise and raise the signal noise ratio of the sound signal. The background noise is assumed as a dynamic system, and an accurate mathematical model of the dynamic system can be established using a neural network filter. The predicted error between predicted values and practical ones constitutes the output of the filter. If the predicted error is zero, then there is no leakage. If the predicted error is greater than a certain value, then there is a leakage fault. Through application to practical pneumatic systems, it is verified that the neural network filter was effective in gas leakage detection.<br>
収録刊行物
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- 日本原子力学会和文論文誌
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日本原子力学会和文論文誌 7 (3), 186-193, 2008
一般社団法人 日本原子力学会
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詳細情報
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- CRID
- 1390282680163951488
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- NII論文ID
- 10021307502
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- NII書誌ID
- AA11643165
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- ISSN
- 21862931
- 13472879
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- NDL書誌ID
- 9629307
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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
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- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可