Simplified Machine Diagnosis Techniques Utilizing System Parameter Distance of ARMA Model

カテゴリ: 部門大会

論文No: MC6-9

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 Utilizing System Parameter Distance of ARMA Model

著者名: 竹安 数博(大阪府立大学)

著者名(英語): Kazuhiro Takeyasu()

キーワード: time series analysis|ARMA model|autocorrelation function|cumulants|diagnosis

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

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