NDLI: The fault diagnosis algorithm for transformer based on Extenics and rough set theory

Content Provider	IEEE Xplore Digital Library
Author	Shu Hong-chun Hu Ze-jiang Sun Shi-yun Yang Qing
Copyright Year	2008
Description	Author affiliation: Kunming Univ. of Sci. & Technol., Kunming (Shu Hong-chun)
Abstract	As one of the most important equipments to guarantee power gird operating safely and stably, the fault diagnosis of transformer has most important sense. Since the general diagnosis methods such as DGA and attributes' reduction of rough set haven't enough precision for transformer's fault diagnosis, Extenics and rough set theory are brought into diagnosing the fault of transformer. Using attribute predigesting method in rough set theory to classify the attribute term which needed by each fault diagnosis. Then building matter element model for transformer's fault diagnosis. Using DGA testing datum to be attribute set and the transformer's standard fault model to be the decision set for transformer's fault diagnosis. Utilize association function from Extenics to count each fault degree. Define the fault accepting rule to get transformer's fault. Use this method to diagnose one fault transformer and the diagnosis result matched case of fact fault. Apply this method to diagnose 76 DGA testing data and the right ratio of diagnostic result is better than IEC method.
Starting Page	1269
Ending Page	1272
File Size	508350
Page Count	4
File Format	PDF
ISBN	9787900714138
DOI	10.1109/DRPT.2008.4523602
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-04-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	DRPT
Subject Keyword	Fault diagnosis Set theory Dissolved gas analysis Testing IEC Power system modeling Power system faults Power system reliability Gases Helium Rough Set Transformer Fault Diagnosis Extenics Matter Element Model
Content Type	Text
Resource Type	Article

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