Research of the Transformer Fault Diagnosis Expert System based on ESTA and Deep Learning Neural Network programmed in MATLAB

被引：0

作者：

Cui, Qiming ^{[1
]}

Liang, Kai ^{[1
]}

Gao, Hongyu ^{[2
]}

Chen, Guodong ^{[2
]}

Wang, Naiyu ^{[2
]}

Jin, Shaoyu ^{[1
]}

Zhong, Changqing ^{[1
]}

Cui, Shuting ^{[3
]}

Sun, Daojun ^{[1
]}

Fang, Jie ^{[4
]}

Han, Chengwei ^{[1
]}

Xu, Bin ^{[1
]}

An, Yuhong ^{[5
]}

Xu, Minghu ^{[6
]}

机构：

[1] State Grid Liaoning Anshan Power Supply Co, Anshan 114001, Peoples R China

[2] State Grid China Technol Coll, Tai An 271000, Shandong, Peoples R China

[3] Eastern Michigan Univ, Ypsilanti, MI 48197 USA

[4] State Grid Weinan Power Supply Co, Weinan 714200, Peoples R China

[5] State Grid Liaoning Dalian Training Ctr, Dalian 116023, Peoples R China

[6] State Grid Liaoning Elect Power Supply Skills Tra, Jinzhou 121001, Peoples R China

来源：

PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON CIVIL, TRANSPORTATION AND ENVIRONMENT | 2016年 / 78卷

关键词：

Expert System; ESTA; Deep Belief Network; BP Neural Network; MATLAB; Transformer Fault Diagnosis;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Some procedures or functions had be added to an ESTA (Expert System Shell for Text Animation) so that the ESTA and MATLAB can communicate via some data files. On this basis, a deep learning-DBN(Deep Belief Network) and two BP(back propagation) artificial neural network based on the MATLAB programming were researched by using directly DGA (Dissolved Gas Analysis) and characteristic gas method in transformer oil chromatographic analysis. The transformer fault diagnosis expert system based on a three ratio and characteristic gas method of DGA and ESTA including the DBN and two BP artificial neural network programmed in MATLAB had be created. The basic application shows the effectiveness of the expert system.

引用

页码：772 / 778

页数：7

共 7 条

[1]

[边莉 Bian Li], 2014, [电力系统保护与控制, Power System Protection and Control], V42, P146

[2]

Prolog Development Center, 2001, EST DOC

[3]

Shi Feng, 2009, MATLAB NEURAL NETWOR

[4]

Wan Yiqin, 2007, THESIS

[5]

Wu Jinghong, 2001, ZHEJIANG HYDROTECHNI, V4, P62

[6]

XU YF, 2006, MICROCOMPUTER APPL, V22, P41

[7]

Zhao Minhao, 2013, DATA FUSION BASED DE

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