Study and Application of Case-based Extension Fault Diagnosis for Chemical Process

Your Location：

Home >

Browse articles >

过程系统工程与过程安全 | Updated：2026-01-06

- Study and Application of Case-based Extension Fault Diagnosis for Chemical Process
- Study and Application of Case-based Extension Fault Diagnosis for Chemical Process
- 中国化学工程学报（英文版） 2013年21卷第4期页码：366-3751004-9541
- Affiliations：
  
  College of Information Science & Technology, Beijing University of Chemical Technology,Beijing,China,100029
- Author bio：
- Funds：
- DOI：10.1016/S1004-9541(13)60484-X
  中图分类号：
- 纸质出版：2013
- Accepted：
Scan QR Code
彭荻, 徐圆, 朱群雄. Study and Application of Case-based Extension Fault Diagnosis for Chemical Process[J]. 中国化学工程学报（英文版）, 2013,21(4):366-3751004-9541.

PENG Di, XU Yuan, ZHU Qunxiong . Study and Application of Case-based Extension Fault Diagnosis for Chemical Process[J]. Chin.J.Chem.Eng., 2013, 21(4): 366-375.
彭荻, 徐圆, 朱群雄. Study and Application of Case-based Extension Fault Diagnosis for Chemical Process[J]. 中国化学工程学报（英文版）, 2013,21(4):366-3751004-9541. DOI： 10.1016/S1004-9541(13)60484-X.

PENG Di, XU Yuan, ZHU Qunxiong . Study and Application of Case-based Extension Fault Diagnosis for Chemical Process[J]. Chin.J.Chem.Eng., 2013, 21(4): 366-375. DOI： 10.1016/S1004-9541(13)60484-X.

In chemical processes

fault diagnosis is relatively difficult due to the incomplete prior-knowledge and unpredictable production changes. To solve the problem

a case-based extension fault diagnosis (CEFD) method is proposed combining with extension theory

in which the basic-element model is used for the unified and deep fault description

the distance concept is applied to quantify the correlation degree between the new fault and the original fault cases

and the extension transformation is used to expand and obtain the solution of unknown faults. With the application in Tennessee Eastman process

the result indicates that CEFD method has a flexible fault representation

objective fault retrieve performance and good ability for fault study

providing a new way for diagnosing production faults accurately.

浏览量

Downloads

CSCD

文章被引用时，请邮件提醒。

Submit

工具集

关联资源

Fault Diagnosis in Chemical Process Based on Self-organizing Map Integrated with Fisher Discriminant Analysis

Towards generalizable fault diagnosis: Learning invariant features across varying fault severities

Sample-optimized adaptive perceptual enhanced graph neural network based fault identification in industrial processes

SmdaNet: A hierarchical hard sample mining and domain adaptation neural network for fault diagnosis in industrial process

Physically-consistent-WGAN based small sample fault diagnosis for industrial processes