Novel fault diagnosis strategy for batch chemical processes

WANG Zhenheng; ZHAO Jinsong; LI Changlei

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Novel fault diagnosis strategy for batch chemical processes

更新时间：2025-12-10

- Novel fault diagnosis strategy for batch chemical processes
- CIESC Journal Issue 11, Pages: 2837-2842(2008)
- 作者机构：
  
  1. 北京化工大学信息科学与技术学院
  2. 清华大学化学工程系
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Online First：05 November 2008，
  
  Published：05 November 2008
- 稿件说明：
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WANG Zhenheng, ZHAO Jinsong, LI Changlei. Novel fault diagnosis strategy for batch chemical processes[J]. CIESC Journal, 2008, (11): 2837-2842.
DOI：

WANG Zhenheng, ZHAO Jinsong, LI Changlei. Novel fault diagnosis strategy for batch chemical processes[J]. CIESC Journal, 2008, (11): 2837-2842. DOI：

摘要

间歇过程的在线故障诊断近年来受到了越来越多的关注，目前比较通用的方法主要是多变量统计的方法。然而在实际过程尤其是多阶段的间歇过程中故障诊断效果往往不够理想，误诊率比较高。为解决上述问题，本文基于动态轨迹分析（DLA）和在线的动态时间规整方法（DTW），将二者的优点有效地结合在一起提出了一种在线故障诊断策略，提高了故障诊断效率和准确性。青霉素发酵过程的在线故障诊断应用实例表明该方法具有比较好的诊断效果。

Abstract

The online fault diagnosis for batch processes has received increasing attention.The most popular method is multivariate statistical methods (MSM)

such as multiway principal component analysis (MPCA) and multiway partial least square (MPLS).Abnormal events can be detected by calculating the T2 and SPE values of the sensor data without the need to build first principal based mechanism models while fault diagnosis is realized by employing contribution plot.In industrial applications to batch processes

especially to multiphase batch processes，however

contribution plot analysis is not always accurate and reliable

and the rate of wrong diagnosis is unfavorably high.To solve the aforementioned problem

a novel fault diagnosis strategy was proposed by combining dynamic locus analysis (DLA) and online dynamic time warping (DTW).The efficiency and accuracy of fault diagnosis were improved.The utility of the new fault diagnosis strategy was demonstrated through the penicillin fermentation case study.

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