Simplified Machine Diagnosis Techniques Using ARMA Model of Absolute Deterioration Factor

カテゴリ: 部門大会

論文No: MC6-7

グループ名: 【C】平成19年電気学会電子・情報・システム部門大会講演論文集

発行日: 2007/09/04

タイトル(英語): Simplified Machine Diagnosis Techniques Using ARMA Model of Absolute Deterioration Factor

著者名: 石井 康夫(Hankyu Corporation)

著者名(英語): Yasuo Ishii(Hankyu Corporation)

キーワード: ARMA model|diagnosis|autocorrelation function|cumulants|absolute deterioration factor

要約(日本語): In order to diagnose machines accurately, the method of calculating Kurtosis or Bicoherence was utilized. Calculating system parameter distance was also utilized to apply time series data to Autoregressive (AR) model or Autoregressive Moving Average (ARMA) model.
In this paper, simplified method of calculating autocorrelation function is introduced and is utilized for ARMA model identification. Furthermore, absolute deterioration factor such as Bicoherence is introduced. Machine diagnosis can be executed by this simplified method of calculating system parameter distance. Useful results were obtained.

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