Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/80474
DC Field | Value | |
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dc.title | Fuzzy expert system for fault diagnosis in power systems | |
dc.contributor.author | Chang, C.S. | |
dc.contributor.author | Chen, J.M. | |
dc.contributor.author | Liew, A.C. | |
dc.contributor.author | Srinivasan, D. | |
dc.contributor.author | Wen, F.S. | |
dc.date.accessioned | 2014-10-07T02:57:56Z | |
dc.date.available | 2014-10-07T02:57:56Z | |
dc.date.issued | 1997 | |
dc.identifier.citation | Chang, C.S.,Chen, J.M.,Liew, A.C.,Srinivasan, D.,Wen, F.S. (1997). Fuzzy expert system for fault diagnosis in power systems. International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications 5 (2) : 75-81. ScholarBank@NUS Repository. | |
dc.identifier.issn | 09691170 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/80474 | |
dc.description.abstract | Fault diagnosis of power system plays a crucial role in power system monitoring and control that ensures a stable supply of electrical power to consumers. In the case of multiple faults or incorrect operation of protective devices, fault diagnosis requires judgment of complex conditions of various levels, especially considering the unavoidable uncertainties that occur during operation involving the fault location and other information available. This paper presents a methodology for fault diagnosis for complex electrical power systems, which is based on fuzzy logic and expert system to deal with the uncertainties. Expert knowledge concerning normal and faulted operation is acquired via knowledge acquisition techniques. A fuzzy logic expert system for fault diagnosis of power system is developed which uses as input status change of the operated circuit breakers and relays. The fuzzy expert system requires much less memory space to store active databases than those used by conventional expert systems. The fuzzy expert system first identifies a short list of possible fault sections and deals with one possible fault section at a time. It then conducts inference to determine the most likely fault sections and the associated fault section sequences. Several study cases are given in this paper to demonstrate salient features of the proposed method. | |
dc.source | Scopus | |
dc.subject | Fault diagnosis | |
dc.subject | Fuzzy expert system | |
dc.subject | Power systems | |
dc.type | Article | |
dc.contributor.department | ELECTRICAL ENGINEERING | |
dc.description.sourcetitle | International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications | |
dc.description.volume | 5 | |
dc.description.issue | 2 | |
dc.description.page | 75-81 | |
dc.description.coden | IJEIE | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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