LAPSE:2023.23159
Published Article

LAPSE:2023.23159
Abnormality Detection of Cast-Resin Transformers Using the Fuzzy Logic Clustering Decision Tree
March 27, 2023
Abstract
Failures of cast-resin transformers not only reduce the reliability of power systems, but also have great effects on power quality. Partial discharges (PD) occurring in epoxy resin insulators of high-voltage electrical equipment will result in harmful effects on insulation and can cause power system blackouts. Pattern recognition of PD is a useful tool for improving the reliability of high-voltage electrical equipment. In this work, a fuzzy logic clustering decision tree (FLCDT) is proposed to diagnose the PD concerning the abnormal defects of cast-resin transformers. The FLCDT integrates a hierarchical clustering scheme with the decision tree. The hierarchical clustering scheme uses splitting attributes to divide the data set into suspended clusters according to separation matrices. The hierarchical clustering scheme is regarded as a preprocessing stage for classification using a decision tree. The whole data set is divided by the hierarchical clustering scheme into some suspended clusters, and the patterns in each suspended cluster are classified by the decision tree. The FLCDT was successfully adopted to classify the aberrant PD of cast-resin transformers. Classification results of FLCDT were compared with two software packages, See5 and CART. The FLCDT performed much better than the CART and See5 in terms of classification precisions.
Failures of cast-resin transformers not only reduce the reliability of power systems, but also have great effects on power quality. Partial discharges (PD) occurring in epoxy resin insulators of high-voltage electrical equipment will result in harmful effects on insulation and can cause power system blackouts. Pattern recognition of PD is a useful tool for improving the reliability of high-voltage electrical equipment. In this work, a fuzzy logic clustering decision tree (FLCDT) is proposed to diagnose the PD concerning the abnormal defects of cast-resin transformers. The FLCDT integrates a hierarchical clustering scheme with the decision tree. The hierarchical clustering scheme uses splitting attributes to divide the data set into suspended clusters according to separation matrices. The hierarchical clustering scheme is regarded as a preprocessing stage for classification using a decision tree. The whole data set is divided by the hierarchical clustering scheme into some suspended clusters, and the patterns in each suspended cluster are classified by the decision tree. The FLCDT was successfully adopted to classify the aberrant PD of cast-resin transformers. Classification results of FLCDT were compared with two software packages, See5 and CART. The FLCDT performed much better than the CART and See5 in terms of classification precisions.
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Keywords
abnormal defects, cast-resin transformers, decision tree, hierarchical clustering, partial discharge, pattern recognition
Subject
Suggested Citation
Lee CT, Horng SC. Abnormality Detection of Cast-Resin Transformers Using the Fuzzy Logic Clustering Decision Tree. (2023). LAPSE:2023.23159
Author Affiliations
Lee CT: Department of Electronic Engineering, National Quemoy University, Kinmen 892009, Taiwan [ORCID]
Horng SC: Department of Computer Science & Information Engineering, Chaoyang University of Technology, Taichung 413310, Taiwan
Horng SC: Department of Computer Science & Information Engineering, Chaoyang University of Technology, Taichung 413310, Taiwan
Journal Name
Energies
Volume
13
Issue
10
Article Number
E2546
Year
2020
Publication Date
2020-05-17
ISSN
1996-1073
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Original Submission
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PII: en13102546, Publication Type: Journal Article
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LAPSE:2023.23159
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https://doi.org/10.3390/en13102546
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Mar 27, 2023
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