Multiple ANNs Combined Scheme for Fault Diagnosis of Power Transformers

被引：0
|
作者：
Tian, Huixin [1 ]
Li, Kun [2 ]
Meng, Bo [1 ]
机构：
[1] Tianjin Polytech Univ, Elect Engn & Automat Dept, Tianjin, Peoples R China
[2] Tianjin Polytech Univ, Dept Management, Tianjin, Peoples R China
来源：
2011 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6 | 2011年
关键词：
Fault diagnosis; ELM; power transforers; ensemble technique; EXTREME LEARNING-MACHINE;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
It is very important to find the incipient faults of power transformers for keeping away from the further deterioration in modern power system. For enhancing the accuracy of fault diagnosis for power transformers, a multiple ANNs scheme is proposed in this paper. In this scheme, a novel ANN method ELM is used to establish the base classifier for its good performance and fast learning speed. Secondly, the several base classifiers based on single ELM will be combined by consulting ensemble techniques. And then a multiple ELMs method is obtained. The real gas records data from a power company is used to establish fault diagnosis system for power transformers based on the new multiple ELMs method. For comparison, the conventional method and other ANN method are used to build fault diagnosis models by the same data. The experiments demonstrate the new multiple ELMs method has the best performance in both learning ability aspect and generalization ability aspect for fault diagnosis of power transformers.
引用
收藏
页码：2557 / +
页数：2
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