期刊名称：Indian Journal of Computer Science and Engineering
印刷版ISSN：2231-3850
电子版ISSN：0976-5166
出版年度：2016
卷号：7
期号：5
页码：208-218
出版社：Engg Journals Publications
摘要：This paper proposes an adaptive constraint based framework for fault detection of a complexthermal power plant system. In many complex systems, representation of precise and crisp constraintsuses formal specification languages such as Object Constraint Language (OCL). Here, a constraint basedneuro-fuzzy controller to tackle imprecise constrained objects is proposed. The proposed inferencesystem is used to identify the intensity of faults by mapping instance values against the constraints. Theimprecise constraints defined as fuzzy constraints are prioritized using fuzzy weights assigned to rules.Back-propagation algorithm is used to train and calibrate the controller to capture the dynamic behaviorof the system. The system is adopted into a coal-fired Thermal power plant system, which is controlled bydifferent parameters in a constrained environment. The output of the neuro-fuzzy inference system iscompared against actual plant site alarm that functions based on rule based system and has been foundthat the intensity of faults can be accurately determined.
