中国电机工程学报Issue(4)：866-872,7.DOI:10.13334/j.0258-8013.pcsee.2015.04.013
一种广义S变换及模糊SOM网络的电能质量多扰动检测和识别方法
Detection and Classification of Power Quality Multi-disturbances Based on Generalized S-transform and Fuzzy SOM Neural Network
摘要
Abstract
To solve the problem of detecting and classifying power quality multi-disturbances, this paper proposed a new method based on the generalized S-transform and the fuzzy self-organizing maps (SOM) neural network to extract features and to recognize the disturbance patterns. As to all kinds of the disturbance voltage signals, especially the superposition of two kinds of voltage disturbances, the generalized S-transform is used to extract multi-disturbance time-frequency features. Then, the average square-sum of S-transform amplitudes are used to train the fuzzy SOM neural network, and the new collected data are tested using the trained fuzzy SOM neural network. Simulation and experiment results show that the generalized S-transform can detect power quality multi-disturbance effectively, and the fuzzy SOM neural network can classify it accurately. The problem of voltage super imposed disturbance classification can be resolved successfully from both qualitative and quantitative ways.关键词
电能质量检测/多扰动检测/S变换/广义S变换/SOM神经网络Key words
power quality detection/multi-disturbance detection/S-transform/generalized S-transform/SOM neural network分类
信息技术与安全科学引用本文复制引用
尹柏强,何怡刚,朱彦卿..一种广义S变换及模糊SOM网络的电能质量多扰动检测和识别方法[J].中国电机工程学报,2015,(4):866-872,7.基金项目
国家杰出青年科学基金项目(50925727)；国家自然科学基金项目(60876022)；国防预研重大项目(C1120110004)。Project supported by the National Natural Science Foundation for Distinguished Young Scholars of China (50925727) （50925727）
Project supported by National Natural Science Foundation of China (60876022) （60876022）
The National Defense Advanced Research Project (C1120110004) （C1120110004）
