Abnormality Detection of Cast-Resin Transformers Using the Fuzzy Logic Clustering Decision Tree
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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-05-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/10/2546 |
| _version_ | 1797567709266837504 |
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| author | Chin-Tan Lee Shih-Cheng Horng |
| author_facet | Chin-Tan Lee Shih-Cheng Horng |
| author_sort | Chin-Tan Lee |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T19:46:20Z |
| format | Article |
| id | doaj.art-0e97e32ffab54f3991ed5d74f59b7d6d |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T19:46:20Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-0e97e32ffab54f3991ed5d74f59b7d6d2023-11-20T00:46:34ZengMDPI AGEnergies1996-10732020-05-011310254610.3390/en13102546Abnormality Detection of Cast-Resin Transformers Using the Fuzzy Logic Clustering Decision TreeChin-Tan Lee0Shih-Cheng Horng1Department of Electronic Engineering, National Quemoy University, Kinmen 892009, TaiwanDepartment of Computer Science & Information Engineering, Chaoyang University of Technology, Taichung 413310, TaiwanFailures 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.https://www.mdpi.com/1996-1073/13/10/2546cast-resin transformersabnormal defectspartial dischargepattern recognitionhierarchical clusteringdecision tree |
| spellingShingle | Chin-Tan Lee Shih-Cheng Horng Abnormality Detection of Cast-Resin Transformers Using the Fuzzy Logic Clustering Decision Tree Energies cast-resin transformers abnormal defects partial discharge pattern recognition hierarchical clustering decision tree |
| title | Abnormality Detection of Cast-Resin Transformers Using the Fuzzy Logic Clustering Decision Tree |
| title_full | Abnormality Detection of Cast-Resin Transformers Using the Fuzzy Logic Clustering Decision Tree |
| title_fullStr | Abnormality Detection of Cast-Resin Transformers Using the Fuzzy Logic Clustering Decision Tree |
| title_full_unstemmed | Abnormality Detection of Cast-Resin Transformers Using the Fuzzy Logic Clustering Decision Tree |
| title_short | Abnormality Detection of Cast-Resin Transformers Using the Fuzzy Logic Clustering Decision Tree |
| title_sort | abnormality detection of cast resin transformers using the fuzzy logic clustering decision tree |
| topic | cast-resin transformers abnormal defects partial discharge pattern recognition hierarchical clustering decision tree |
| url | https://www.mdpi.com/1996-1073/13/10/2546 |
| work_keys_str_mv | AT chintanlee abnormalitydetectionofcastresintransformersusingthefuzzylogicclusteringdecisiontree AT shihchenghorng abnormalitydetectionofcastresintransformersusingthefuzzylogicclusteringdecisiontree |