Vora, Nishith ; Tambe, Sanjeev S. ; Kulkarni, Bhaskar D. (1997) Counterpropagation neural networks for fault detection and diagnosis Computers & Chemical Engineering, 21 (2). pp. 177-185. ISSN 0098-1354
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Official URL: http://linkinghub.elsevier.com/retrieve/pii/009813...
Related URL: http://dx.doi.org/10.1016/0098-1354(95)00259-6
Abstract
This paper shows the application of a counterpropagation neural network (CPNN) to detect single faults and their magnitudes. The performance of CPNN has been evaluated by considering a variety of faults occurring in a nonisothermal continuous stirred tank reactor (CSTR). The results presented here indicate that CPNN provides an attractive alternative to error-back-propagation (EBP) networks due to its faster learning ability for fault detection and diagnosis.
| Item Type: | Article |
|---|---|
| Source: | Copyright of this article belongs to Elsevier Science. |
| ID Code: | 17344 |
| Deposited On: | 16 Nov 2010 08:09 |
| Last Modified: | 06 Jun 2011 09:32 |
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