音響信号のニュートラルネットワークによるディーゼル機関の異常検出 Abnormal Sound Detection by Neural Network in the Diesel Engine

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This paper describes the method to detect the abnormal engine condition by means of an algorithm of the neural network, which is modeled upon information processing capability of the operater.<BR>The 4-cycle diesel engine is used in this experimental study. As for kinds of engine abnormalities, the leak of the gas from the exhaust pipe and the abnormal combustion depending on F.O. cut are taken as an example.<BR>The neural network is composed of the units and the weights which link between units. When the engine is operated by the normal condition, the spectrum data of the radiation sounds from the engine are put in the input layer in the neural network. By learning those data, the weights are formed between units. We judge whether the engine is the normal condigion by using this neural network. Under the normal condition, the correct recognition rate is almost 80% or over both the exhaust leak experiment and the fuel cut experiment. On the other, in case of the abnormal condition, the correct recognition rate is 20% or less in two kinds of experiments. For the results mentioned above, this method using the neural network could satisfactory detect two kinds of abnormal condition.

収録刊行物

  • 日本舶用機関学会誌  

    日本舶用機関学会誌 32(3), 206-214, 1997-03-01 

    The Japan Institute of Marine Engineering

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各種コード

  • NII論文ID(NAID)
    10002041453
  • NII書誌ID(NCID)
    AN00196373
  • 本文言語コード
    JPN
  • 資料種別
    ART
  • ISSN
    03883051
  • NDL 記事登録ID
    4160262
  • NDL 雑誌分類
    ZN24(科学技術--運輸工学--船舶)
  • NDL 請求記号
    Z16-747
  • データ提供元
    CJP書誌  CJP引用  NDL  J-STAGE 
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