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Naila Zareen
Universiti Teknologi Malaysia

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Fuzzy Neural Network for Classification Fault In Protection System Azriyenni Azriyenni; Mohd Wazir Mustafa; Naila Zareen
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 8: August 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i8.pp5969-5975

Abstract

Novel intelligent technique is a combination of fuzzy and neural network techniques that can be used to classify faults in electric power system protection. There have two problems in the protection system, which are: undesired tripping and fail to operate. Loss of power supply to relays and circuit breakers or failure in protective devices may cause failures in protection system. Construction of neural networks to explore fact to identify fault component is from control center. The objective of this paper is to develop novel concept for classification failures protection system are using Fuzzy Neural Network technique. Methodology consists of Neural Network and Fuzzy. The Neural network is also conscientious for estimating degree of membership in system components from corresponding area in classification of disorders. The input variables of neural network formed of binary numbers. Value of 1 indicates if fault occurs and value of 0 indicates no-fault occurs. Fuzzy relations will represent by fuzzy. These Fuzzy relations can be represented by fuzzy diagram consisting of three sets of node that would be considered to represent components, relays and circuit breakers.
Co-Authors Azriyenni Azhari Zakri Mohd Wazir Mustafa