摘要
针对电能质量的短时扰动的分类问题,提出了一种基于广义S变换和模糊模式识别的短时电能质量的分类方法。先对扰动信号作广义S变换得到模时频矩阵,再从该矩阵中提取4种统计量特征值,然后利用模糊模式识别方法的最大隶属度原则对扰动信号进行归类,从而实现对短时电能质量扰动信号的自动分类。仿真测试结果表明,该方法识别正确率高且对噪声不敏感,适用于实际应用。
A new approach of classification of short duration power quality disturbances using generalized S-transform and fuzzy pattern recognition is proposed. First, the generalized S-tranform is utilized to produce module matrixes of disturbances and then 4 simple statistical features are extracted from the matrixes. Finally, a fuzzy pattern recognition system is used for the classification of distrubances in which the maximal membership value is adopted. The simulation results show that the proposed classification method is an effective technique for building up a pattern recognition system of power disturbance signals and technique is feasible for real applications for its significant accuracy and immuning to noise.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2008年第22期20-24,共5页
Power System Protection and Control
基金
国家自然科学基金项目(50677015)~~
关键词
短时电能质量
S变换
模糊模式识别
分类
short duration power quality
generalized S-transform
fuzzy pattern recognition
classification
