Fault Detection in a Batch Process Using a Bayesian Model

JOURNAL OF CHEMICAL ENGINEERING OF JAPAN

Yoshiyuki Yamashita¹  Mutsumi Suzuki¹  Toshiyuki Nonaka¹ 

[1] Department of Biochemistry and Engineering, Tohoku University

关键词: Process System;    Fault Detection;    Batch Process;    Time Series Analysis;    Bayesian Statistics;    State Space Method;    Hypothesis Test;   

DOI  :  10.1252/jcej.26.465

来源: Maruzen Company Ltd

【 摘 要 】

References(12)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.

【 授权许可】

Unknown