Optimum parameters for fault detection and diagnosis system of batch reaction using multiple neural networks

被引：22

作者：

Tan, W. L. ^{[1
]}

Nor, N. M. ^{[1
]}

Abu Bakar, M. Z. ^{[1
]}

Ahmad, Z. ^{[1
]}

Sata, S. A. ^{[1
]}

机构：

[1] Univ Sci Malaysia, Sch Chem Engn, Seberang Prai Selatan 14300, Penang, Malaysia

来源：

JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES | 2012年 / 25卷 / 01期

关键词：

Fault; Batch; Multiple neural networks; Diagnosis system;

D O I：

10.1016/j.jlp.2011.08.002

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

Batch process usually differs from the continuous process because of its time-varying variables and the process parameters. An early detection and isolation of faults in the process will help to reduce the process upsets and keep it safe and reliable. This paper discusses on the application of multi-layer perceptron neural network in detecting various faults in batch chemical reactor based on an esterification process that involves the reaction of ethanol and acetic acid catalyzed by sulfuric acid. A multilayer feed forward neural network with double hidden layers has been used in the neural network architecture. The detection was based on the different patterns generated between normal and faulty conditions. An optimum network configuration was found when the network produced the minimal error with respect to the training, testing and data validation. (C) 2011 Elsevier Ltd. All rights reserved.

引用

页码：138 / 141

页数：4

共 50 条

[31] Induction motor fault detection and diagnosis using supervised and unsupervised neural networks
Premrudeepreechacharn, S
Utthiyoung, T
Kruepengkul, K
Puongkaew, P
IEEE ICIT' 02: 2002 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY, VOLS I AND II, PROCEEDINGS, 2002, : 93 - 96
[32] Leakage fault detection of pneumatic pipe system using neural networks
Zhang, S
Asakura, T
Hayashi, S
SICE 2003 ANNUAL CONFERENCE, VOLS 1-3, 2003, : 2482 - 2487
[33] Diagnosis of mechanical pumping system using neural networks and system parameters analysis
Tai-Ming Tsai
Wei-Hui Wang
Journal of Mechanical Science and Technology, 2009, 23 : 124 - 135
[34] Diagnosis of mechanical pumping system using neural networks and system parameters analysis
Tsai, Tai-Ming
Wang, Wei-Hui
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2009, 23 (01) : 124 - 135
[35] Infrared flame detection system using multiple neural networks
Huseynov, Javid J.
Baliga, Shankar
Widmer, Alan
Boger, Zvi
2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6, 2007, : 608 - +
[36] An Integrated Intrusion Detection System by Using Multiple Neural Networks
Liu, Guisong
Wang, Xiaobin
2008 IEEE CONFERENCE ON CYBERNETICS AND INTELLIGENT SYSTEMS, VOLS 1 AND 2, 2008, : 724 - 729
[37] Bearing Fault Detection Using Neural Networks
Hajar, Mayssa
Khalil, Mohamad
2012 2ND INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTATIONAL TOOLS FOR ENGINEERING APPLICATIONS (ACTEA), 2012, : 57 - 60
[38] A expert system of fault diagnosis based on neural networks
He, Q
Yang, K
Du, DM
Zhou, XX
SYSTEMS INTEGRITY AND MAINTENANCE, PROCEEDINGS, 2000, : 166 - 171
[39] Adaptive neural-networks-based fault detection and diagnosis using unmeasured states
Liu, C. -S.
Zhang, S. -J.
Hu, S. -S.
IET CONTROL THEORY AND APPLICATIONS, 2008, 2 (12): : 1066 - 1076
[40] Gas leakage fault detection of pneumatic pipe system using neural networks
Zhang, S
Asakura, T
Hayashi, S
JSME INTERNATIONAL JOURNAL SERIES C-MECHANICAL SYSTEMS MACHINE ELEMENTS AND MANUFACTURING, 2004, 47 (02) : 568 - 573

← 1 2 3 4 5 →