Power Quality Disturbances Events Recognition Based on S-Transform and Probabilistic Neural Network

被引：0
|
作者：
Huang, Nantian [1 ,2 ]
Liu, Xiaosheng [1 ]
Xu, Dianguo [1 ]
Qi, Jiajin [3 ]
机构：
[1] Harbin Inst Technol, Dept Elect Engn, Harbin 150006, Peoples R China
[2] Jinan Inst Chem Technol, Coll Informat & Control Engn, Jinan, Peoples R China
[3] State Grid Corp China, Hangzhou Elect Power Bur, Hangzhou, Zhejiang, Peoples R China
来源：
LIFE SYSTEM MODELING AND INTELLIGENT COMPUTING, PT I | 2010年 / 97卷
基金：
美国国家科学基金会;
关键词：
power quality (PQ); power quality disturbances; S-transform; probabilistic neural network; AUTOMATIC CLASSIFICATION;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Power quality (PQ) events recognition is the most important research area of power quality control. A novel high performance classification system based on S-transform and probabilistic neural network is proposed in this paper. Firstly, S-transform processes the original PQ signals into a complex matrix named S-matrix. The time and frequency features of disturbances signal are extracted from the S-matrix. Then, the selected subset of features is used as the input vector of the classifier. Finally, the probabilistic neural network classifier is trained and tested by the simulated simples. The simulation results show the effectiveness of the new approach.
引用
收藏
页码：207 / +
页数：2
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