Real-time fault diagnosis using knowledge-based expert system

Process Safety and Environmental Protection

Volumn 86, Issue 1 B, 2008, Pages 55-71

  Nan, Cen ^a   Khan, Faisal ^a   Iqbal, M Tariq ^a  

^a MEMORIAL UNIVERSITY OF NEWFOUNDLAND   (Canada)

Author keywords

Abnormal operation; Fault diagnosis; Fuzzy logic; G2 system; Process monitoring

Indexed keywords

ADMINISTRATIVE DATA PROCESSING; CONTROL SYSTEMS; DECISION SUPPORT SYSTEMS; ELECTRIC FAULT CURRENTS; ENGINEERS; EXPERT SYSTEMS; FORECASTING; FUZZY INFERENCE; FUZZY LOGIC; HEALTH; INDUSTRIAL APPLICATIONS; MANAGEMENT INFORMATION SYSTEMS; PROCESS ENGINEERING; PROCESS MONITORING;

ABNORMAL CONDITIONS; ADVANCED SOFTWARE (CO); CHEMICAL ENGINEERS; DESIGN SAFETY; FAULT DIAGNOSIS (FD); FAULT DIAGNOSIS METHOD; HIGH CONFIDENCE; KNOWLEDGE-BASED; KNOWLEDGE-BASED EXPERT SYSTEMS; OF SENSORS; OPERATING CONDITIONS; PROCESS COMPLEXITY; PROCESS CONDITIONS; PROCESS INDUSTRIES; REAL-TIME DATA; REAL-TIME FAULT DIAGNOSIS; SIMULATED DATA; SOFTWARE APPLICATIONS; WIDE-RANGE;

KNOWLEDGE BASED SYSTEMS;

EID: 46249094992     PISSN: 09575820     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.psep.2007.10.014     Document Type: Article

References (21)

1. Dash S., Maurya M.R., Venkatasubramanian V., and Rengaswamy R. Fuzzy-logic based trend classification for fault diagnosis of chemical processes. J Comput Chem Eng 27 3 (2003) 347-362
2. Dash S., Maurya M.R., and Venkatasubramanian V. A novel interval-halving framework for automated identification of process trends. AIChE J 50 1 (2004) 149-162
3. El-Shal S.M., and Morris A.S. A fuzzy expert system for fault detection in statistical process control of industrial processes. IEEE Trans Syst Man Cyber Part C: Appl Rev 30 2 (2000) 281-289
4. Gomm J.B. Adaptive neural network approach to on-line learning for process fault diagnosis. Trans Inst Meas Control 20 3 (1998) 144-152
5. Harris C.J., Hong X., and Gan Q. Adaptive Modeling Estimation and Fusion from Data (2002), Springer, New York
6. Janusz M., and Venkatasubramanian V. Automatic generation of qualitative description of process trends for fault detection and diagnosis. Eng Applic Artif Intell 4 5 (1991) 329
7. Jian'an L., Changjiang F., Xuemin S., Yuefei Z., and Haixia Z. Research of fault diagnosis expert system based on case reasoning for complex dynamic equipments. Proc Int Sym Test Meas 1 (2001) 369-372
8. John H. Model-based fault detection in information poor plants. Automatica J 30 6 (1994) 929-943
9. Lo C.H., Wong Y.K., and Rad A.B. Intelligent System for Process Supervision and Fault Diagnosis in Dynamic Physical Systems. IEEE Trans Ind Electron 53 2 (2006) 581-592
10. Maki Y., and Loparo K.A. Neural-network approach to fault detection and diagnosis in industrial processes. IEEE Trans Control Syst Technol 5 6 (1997) 529-541
11. Marcellus R.L. Evaluation of a nonstationary policy for statistical process control. Proceedings of the 1997 6th Annual Industrial Engineering Research Conference (1997) 89-94
12. Mendonca L.F., Sousa J.M.C., and Sá da Consta J.M.G. Fault detection and isolation of industrial processes using optimized fuzzy models. Proceedings of the IEEE International Conference on Fuzzy Systems (2005) 851-856
13. Mohamed L., and Ibrahim A.S. Model-based fault diagnosis via parameter estimation using knowledge based and fuzzy logic approach. Presented at IEEE MELECON 2002. Cairo, Egypt (2002)
14. Monsef H., Ranjbar A.M., and Jadid S. Fuzzy rule-based expert system for power system fault diagnosis. IEE Proc Gener Trans Distr 144 2 (1997) 186-192
15. Nan, C., Iqbal, M.T. and Khan, F.I., 2006, Modeling and simulating a micro steam power unit using G2 real-time expert system. Presented at IEEE NECEC 2006, St. Johns, Newfoundland, Canada.
16. Siegel D., Abidi K., and Anderson R. Abnormal Condition Management (2004), Gensym Corporation
17. Venkatasubramanian V., and Chan K. Neural network methodology for process fault diagnosis. AIChE J 35 12 (1989) 1993-2002
18. Wolfram A., Füssel D., Brune T., and Isermann R. Component-based multi-model approach for fault detection and diagnosis of a centrifugal pump. Proc Am Control Conf 6 (2001) 4443-4448
19. Xia Q., Rao M., Henricksson C., and Farzadeh H. Case-based reasoning for intelligent fault diagnosis and decision making in pulp processes. Pulp Paper Canada 98 2 (1997) 26-30
20. Zadeh L.A. Fuzzy logic. IEEE Comput 21 4 (1998) 83-93
21. Zhang J. Improved on-line process fault diagnosis through information fusion in multiple neural networks. Comput Chem Eng 30 3 (2006) 558-571