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Fuzzy Ontology Reasoning for Power Transformer Fault DiagnosisSAMIRMI, F. D. , TANG, W. , WU, Q.
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fault diagnosis, ontology, fuzzy sets, multi-agent systems, power transformer
power(13), systems(12), fuzzy(8), agent(8), ontology(7), multi(6), diagnosis(6), transformers(5), system(5), fault(5)
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About this article
Date of Publication: 2015-11-30
Volume 15, Issue 4, Year 2015, On page(s): 107 - 114
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.04015
Web of Science Accession Number: 000368499800014
SCOPUS ID: 84949971675
This paper presents a novel fuzzy ontology reasoner for power transformer fault diagnosis under a multi-agent framework. The developed ontology provides a comprehensive knowledge base as part of a multi-agent system to enable imprecision reasoning. It is the first time that a fuzzy ontology model is developed for accurate power transformer fault diagnosis. It aims to develop an improved ontology model for transformer fault diagnosis by applying the fuzzy ontology. The proposed technique deals with the imprecision situation using the fuzzy ontology, in order to build an ontology-based knowledge representation for accurate power transformer fault diagnosis. The proposed system is tested with actual transformer online data to demonstrate the functionality of the developed fuzzy ontology, which can identify the faults that are unidentifiable using a basic ontology model, and this can significantly improve the overall accuracy for transformer fault diagnosis under a multi-agent framework.
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 Vibration Based Broken Bar Detection in Induction Machine for Low Load Conditions, MATIC, D., KANOVIC, Z., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 1, Volume 17, 2017.
Digital Object Identifier: 10.4316/AECE.2017.01007 [CrossRef] [Full text]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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