RBF神经网络在谐波检测中的应用  

Application of RBF neural networks in harmonic detection

作　　者：曹长修[1] 钱基业[1] 何立新[2] 

机构地区：[1]重庆大学自动化学院,重庆400044 [2]重庆大学电气工程学院,重庆400044

出　　处：《国外电子测量技术》2007年第1期46-47,70,共3页Foreign Electronic Measurement Technology

摘　　要：有源电力滤波器补偿性能与所采用的谐波检测方式有很大的依赖关系,现有的检测方法存在精度不高、对电网频率变化比较敏感、自适应能力不强的缺点。本文提出基于RBF神经网络的谐波检测方法,具有较高的运算速度、较高的检测谐波精度,以及较强的自适应能力。The compensating capability of active power filter has relation with the way of harmonic detection, but the existing methods of harmonic detection have some disadvantages, such as the lower harmonic precision, sensitive to the change of the power system frequency, lower self-adaptive capability. This paper put forward a method of harmonic detection based on the RBF neural networks which can engage precise detection with high speed and self-adaptive capability.

关 键 词：RBF神经网络 谐波检测 有源电力滤波器 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]