Application of RBF neural network based on ENN2 clustering in Fault Diagnosis

被引：2

作者：

Wen, Tianzhu ^{[1
]}

Xu, Aiqiang ^{[1
]}

Liu, Chunxia ^{[1
]}

Li, Nan ^{[2
]}

机构：

[1] Naval Aeronaut & Astronaut, Yantai, Peoples R China

[2] PLA 91395, Beijing, Peoples R China

来源：

2014 SIXTH INTERNATIONAL CONFERENCE ON INTELLIGENT HUMAN-MACHINE SYSTEMS AND CYBERNETICS (IHMSC), VOL 2 | 2014年

关键词：

fault diagnosis; RBF neural network; ENN2; clustering; extension theory; unsupervised learning;

D O I：

10.1109/IHMSC.2014.120

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Radial basis function (RBF) neural network is widely used in engineering with its powerful advantage in solving nonlinear problems. But the number of hidden layer as well as the center and standard deviation of radial basis function are difficult to get, so RBF neural network based on ENN2 is proposed to solve the fault diagnosis problem. Firstly, the structure of RBF neural network is introduced; afterwards, the learning algorithm of RBF neural network is analyzed, the center and standard deviation of RBF in hidden layer are obtained by clustering method of extension neural network type 2(ENN2), meanwhile the weight matrix between hidden layer and output layer are calculated by generalized inverse method. Ultimately, the method is used to solve fault diagnosis problem, the results show that it has the advantages of simple structure, fast learning speed and high diagnostic accuracy.

引用

页码：71 / 74

页数：4

共 50 条

[21] The Research on Fault Diagnosis of Building Electrical System Based on RBF Neural Network
Wu, Qian
Wang, Yahui
Zhang, Long
Shen, Li
[J]. PROCEEDINGS OF 2013 CHINESE INTELLIGENT AUTOMATION CONFERENCE: INTELLIGENT AUTOMATION, 2013, 254 : 9 - 19
[22] The Gas Regulator Fault Diagnosis Based on PCA-RBF Neural Network
Wang Yahui
Zhang Fucheng
Chen Fangwen
[J]. 2017 20TH INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS), 2017,
[23] Fault Diagnosis of Wireless Sensor Based on ACO-RBF Neural Network
Liu Rui-fang
[J]. ICCSIT 2010 - 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY, VOL 2, 2010, : 248 - 251
[24] Rolling bearing fault diagnosis based on wavelet packet and RBF neural network
Sun Fang
Wei Zijie
[J]. Proceedings of the 26th Chinese Control Conference, Vol 5, 2007, : 451 - 455
[25] Research on Fault Diagnosis of a Certain Launch Vehicle Based On RBF Neural Network
Wang, Sai
Cao, Ji-ping
Huang, Rui
Lei, Ning
[J]. INTERNATIONAL CONFERENCE ON MECHANICAL, ELECTRONIC AND INFORMATION TECHNOLOGY (ICMEIT 2018), 2018, : 139 - 146
[26] Fault diagnosis for embedded system based on RBF neural network optimized by PSO
Zhai, Zhihua
Du, Guangchao
[J]. 2012 INTERNATIONAL CONFERENCE ON INTELLIGENCE SCIENCE AND INFORMATION ENGINEERING, 2012, 20 : 130 - 133
[27] Fault Diagnosis of Gear Based on Singular Value Decomposition and RBF Neural Network
Zhang, Qi
Zhao, Wei
Xiao, Shun Gen
[J]. 2017 2ND INTERNATIONAL CONFERENCE ON FRONTIERS OF SENSORS TECHNOLOGIES (ICFST), 2017, : 470 - 474
[28] Fault Diagnosis and Application Based on SOM Neural Network
Zhang, Hang
Liu, Wencheng
Wu, Yongjian
Liu, Sheng
[J]. 2ND INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND INDUSTRIAL AUTOMATION (ICITIA 2017), 2017, : 42 - 49
[29] Research on rotor fault diagnosis of asynchronous Motor based on RBF neural network
Ge, Qiang
Xu, Liang-Liang
[J]. PROCEEDINGS OF FIRST INTERNATIONAL CONFERENCE OF MODELLING AND SIMULATION, VOL V: MODELLING AND SIMULATION IN MECHANICS AND MANUFACTURE, 2008, : 373 - 378
[30] An expert system for farm machinery fault diagnosis based on RBF neural network
Nie Caili
Liu Shuxia
[J]. PROCEEDINGS OF THE 2007 INTERNATIONAL CONFERENCE ON AGRICULTURE ENGINEERING, 2007, : 389 - 393

← 1 2 3 4 5 →