Application of RBF Neural Network Optimized Based on K-means Cluster Algorithm in Fault Diagnosis

被引：0

作者：

Ren, Zhangao ^{[1
]}

Chen, Jianchun ^{[2
]}

Ye, Liwen ^{[2
]}

Wang, Cong ^{[2
]}

Liu, Yun ^{[1
]}

Zhou, Weihua ^{[1
]}

机构：

[1] State Grid Hunan Elect Power Co Ltd, State Grid Hunan Elect Power Co Ltd Res Inst, Changsha, Hunan, Peoples R China

[2] Huazhong Univ Sci & Technol, Sch Elect & Elect Engn, State Key Lab Adv Electromagnet Engn & Technol, Wuhan, Hubei, Peoples R China

来源：

2018 21ST INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS) | 2018年

关键词：

RBF neural network; Improved K-means cluster lgorithm; fault diagnose;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Radial Basis Function(RBF) neural network based on K-means cluster algorithm is widely used in intelligent fault diagnose with its good performance for nonlinear problems. However, the selection of initial center and number of hidden layer neurons is random. In this paper, a neural network based on improved K-means cluster algorithm with data density is proposed to solve this problem. The improved algorithm is applied to synchronous condenser's historical data. Simulation results prove the feasibility of the improved algorithm.

引用

页码：2492 / 2496

页数：5

共 7 条

[1] A Fast and Efficient Method for Training Categorical Radial Basis Function Networks
Alexandridis, Alex
Chondrodima, Eva
Giannopoulos, Nikolaos
Sarimveis, Haralambos
[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2017, 28 (11) : 2831 - 2836
[2] A DSP-based FFT-analyzer for the fault diagnosis of rotating machine based on vibration analysis
Betta, G
Liguori, C
Paolillo, A
Pietrosanto, A
[J]. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2002, 51 (06) : 1316 - 1322
[3] LOCALIZATION OF WINDING SHORTS USING FUZZIFIED NEURAL NETWORKS
ELSHARKAWI, MA
MARKS, RJ
OH, S
HUANG, SJ
KERSZENBAUM, I
RODRIGUEZ, A
[J]. IEEE TRANSACTIONS ON ENERGY CONVERSION, 1995, 10 (01) : 140 - 146
[4] ANN BASED PATTERN-CLASSIFICATION OF SYNCHRONOUS GENERATOR STABILITY AND LOSS OF EXCITATION
SHARAF, AM
LIE, TT
[J]. IEEE TRANSACTIONS ON ENERGY CONVERSION, 1994, 9 (04) : 753 - 759
[5] Tian S. P., COMPUTER ENG DESIGN, V32, P268
[6] Induction machine fault detection using SOM-based RBF neural networks
Wu, ST
Chow, TWS
[J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2004, 51 (01) : 183 - 194
[7] Wu Y. C., 2017, WIRELESS PERS COMMUN, V21, P1

← 1 →