DocumentCode :
3247406
Title :
Partial Discharge Pattern Recognition of Molded Type Transformers Using Self Organizing Map
Author :
Chang, Wen-Yeau ; Yang, Hong-Tzer
Author_Institution :
Dept. of Electr. Eng., St. John´´s Univ., Taipei
fYear :
2006
fDate :
38869
Firstpage :
246
Lastpage :
249
Abstract :
In this paper, application of self organizing map (SOM) to recognize partial discharge (PD) patterns of molded type transformers (MTTs) is proposed. The PD patterns are measured by using a commercial PD detector. A set of features, used as operators, for each PD pattern are extracted through statistical tools. The proposed SOM classifier has the advantage of high robustness to the ambiguous patterns, which is useful in recognizing the PD patterns of electrical transformers. To verify the effectiveness of the proposed method, the classifier was tested on 120 sets of field-test PD patterns of MTTs. The test results show the proposed approach may achieve a quite satisfactory recognition of PD patterns
Keywords :
partial discharge measurement; pattern classification; power engineering computing; power transformer testing; self-organising feature maps; statistical analysis; MTT; PD measurement; SOM classifier; commercial PD detector; electrical transformers; feature extraction; field-test PD patterns; molded type transformers; partial discharge pattern recognition; robustness; self organizing map; statistical tools; Circuit testing; Detectors; Feature extraction; Fuzzy systems; Hybrid intelligent systems; Multi-layer neural network; Organizing; Partial discharges; Pattern recognition; Transformers; Molded Type Transformers; Partial Discharge; Pattern Recognition; Self Organizing Map;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Properties and applications of Dielectric Materials, 2006. 8th International Conference on
Conference_Location :
Bali
Print_ISBN :
1-4244-0189-5
Electronic_ISBN :
1-4244-0190-9
Type :
conf
DOI :
10.1109/ICPADM.2006.284163
Filename :
4062652
Link To Document :
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