Application of a Radial Basis Function (RBF) Neural Network for fault diagnosis in a HVDC system

被引：84
|
作者：
Narendra, KG
Sood, VK
Khorasani, K
Patel, R
机构：
[1] Concordia Univ, Dept Elect & Comp Engn, Montreal, PQ H3G 1M8, Canada
[2] Hydro Quebec, Varennes, PQ J3X 1S1, Canada
来源：
IEEE TRANSACTIONS ON POWER SYSTEMS | 1998年 / 13卷 / 01期
基金：
加拿大自然科学与工程研究理事会;
关键词：
Radial Basis Function; Neural Networks; HVDC system; fault diagnosis;
D O I：
10.1109/59.651633
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：
The application of a Radial Basis Function (RBF) Neural Network (NN) for fault diagnosis in a HVDC system is presented in this paper. To provide a reliable preprocessed input to the RBF NN, a new pre-classifier is proposed. This pre-classifier consists of an adaptive filter (to track the proportional values of the fundamental and average components of the sensed system variables), and a signal conditioner which uses an expert Knowledge Base (KB) to aid the pre-classification of the signal. The proposed method of fault diagnosis is evaluated using simulations performed with the EMTP package.
引用
收藏
页码：177 / 183
页数：7
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