摘要
从小波分析中对函数逼近表示的不同角度,分别介绍了3种主要的小波网络,并对这3种小波网络的构成、网络模型和学习算法等进行了详细介绍和比较,给出了它们之间的本质区别。在此基础之上,对小波网络在电力系统故障信号分类和故障数据压缩方面的应用进行了讨论,给出的相应数字仿真结果表明,小波网络在电力系统故障信号处理方面的应用是完全可行的。
According to different aspects of function approximation with wavelet transformations in wavelet analysis, three main wavelet networks are respectively outlined. The detailed presentation and comparison of the architectures, models and learning algorithms of the three wavelet networks are carried out and the essential differences among them are described. On this basis, the application of wavelet network in the classification of power system fault signals and the fault data compression is researched and corresponding digital simulations are given. The simulation results show that it is feasible to apply wavelet network to power system fault signal processing.
出处
《电网技术》
EI
CSCD
北大核心
2003年第4期7-10,共4页
Power System Technology
基金
国家自然科学基金资助项目(59977019)。
关键词
小波网络
电力系统
故障
信号处理
Wavelet network
Adaptive wavelet network
Fault classification
Data compression
