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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yang Qiping Xue Wude Lan Zhida |
| Copyright Year | 2005 |
| Description | Author affiliation: Shanghai Inst. of Electr. Power (Yang Qiping; Xue Wude) |
| Abstract | This paper introduces artificial intelligence system method and describes the developing and application in transformer fault diagnosis. An artificial intelligent system (TFDAI) design includes selection of input, network topology, synaptic connection weights, two-passageway, and output. This paper introduces the new intelligence technology in the transformer fault diagnosis -TFDAI System. TFDAI based data processing and diagnostic techniques are described in detail. It consists of expert system (ES ), artificial neural network (ANN), guide-rule, two-passageway and their characteristics are presented. This paper mentions the two-passageway structure of the artificial intelligence system and with practical examples. ES and ANN are connected by the two-passageway effectively. It states that artificial intelligence system for transformer early hidden faults achieves the possibility and accuracy of primary diagnosis |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 215571 |
| Page Count | 5 |
| File Format | |
| ISBN | 0780391144 |
| DOI | 10.1109/TDC.2005.1546920 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2005-08-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Artificial Intelligence (AI) Two-passageway Artificial neural networks Oil insulation Dissolved gas analysis Artificial neural network (ANN) Power transformers Petroleum Fault diagnosis Transformer fault diagnosis Gas insulation Intelligent systems Artificial intelligence Expert system (ES) Power transformer insulation |
| Content Type | Text |
| Resource Type | Article |
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