Fault detection in a batch process using a bayesian model

T. Nonaka, Yoshiyuki yamashita, Mutsumi Suzuki

研究成果: Article査読

3 被引用数 (Scopus)

抄録

Application of Bayesian dynamic modeling to fault detection is developed for a nonstationary batch process. In the modeling, the observed time series are expressed in several specific components such as local polynomial trend, observation noise and globally stationary autoregressive component. To illustrate the method, detection of a fault in an operation of a stirred vessel with a heater is presented.From the sequential probability ratio test of the model estimation error, the fault can be detected successfully with high sensitivity.

本文言語English
ページ(範囲)465-469
ページ数5
ジャーナルJOURNAL of CHEMICAL ENGINEERING of JAPAN
26
5
DOI
出版ステータスPublished - 1993

ASJC Scopus subject areas

  • 化学 (全般)
  • 化学工学(全般)

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