简介概要

Fault diagnosis and process monitoring using a statistical pattern framework based on a self-organizing map

来源期刊:中南大学学报(英文版)2015年第2期

论文作者:SONG Yu(宋羽) JIANG Qing-chao(姜庆超) YAN Xue-feng(颜学峰)

文章页码:601 - 609

Key words:statistic pattern framework; self-organizing map; fault diagnosis; process monitoring

Abstract: A multivariate method for fault diagnosis and process monitoring is proposed. This technique is based on a statistical pattern (SP) framework integrated with a self-organizing map (SOM). An SP-based SOM is used as a classifier to distinguish various states on the output map, which can visually monitor abnormal states. A case study of the Tennessee Eastman (TE) process is presented to demonstrate the fault diagnosis and process monitoring performance of the proposed method. Results show that the SP-based SOM method is a visual tool for real-time monitoring and fault diagnosis that can be used in complex chemical processes. Compared with other SOM-based methods, the proposed method can more efficiently monitor and diagnose faults.

详情信息展示

Fault diagnosis and process monitoring using a statistical pattern framework based on a self-organizing map

SONG Yu(宋羽), JIANG Qing-chao(姜庆超), YAN Xue-feng(颜学峰)

(Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education
(East China University of Science and Technology), Shanghai 200237, China)

Abstract:A multivariate method for fault diagnosis and process monitoring is proposed. This technique is based on a statistical pattern (SP) framework integrated with a self-organizing map (SOM). An SP-based SOM is used as a classifier to distinguish various states on the output map, which can visually monitor abnormal states. A case study of the Tennessee Eastman (TE) process is presented to demonstrate the fault diagnosis and process monitoring performance of the proposed method. Results show that the SP-based SOM method is a visual tool for real-time monitoring and fault diagnosis that can be used in complex chemical processes. Compared with other SOM-based methods, the proposed method can more efficiently monitor and diagnose faults.

Key words:statistic pattern framework; self-organizing map; fault diagnosis; process monitoring

<上一页 1 下一页 >

相关论文

  • 暂无!

相关知识点

  • 暂无!

有色金属在线官网  |   会议  |   在线投稿  |   购买纸书  |   科技图书馆

中南大学出版社 技术支持 版权声明   电话:0731-88830515 88830516   传真:0731-88710482   Email:administrator@cnnmol.com

互联网出版许可证:(署)网出证(京)字第342号   京ICP备17050991号-6      京公网安备11010802042557号