基于模糊神经网络的同步发电机转子匝间短路预测  

Forecasting Shorted Turns in Generator Rotor Windings Using Fuzzy Neural Networks

作　　者：刘靖[1] 刘念[1] 王海田[1] 党晓强[1] 

机构地区：[1]四川大学电气信息学院,四川成都610065

出　　处：《东方电气评论》2003年第1期52-55,共4页Dongfang Electric Review

摘　　要：模糊神经网络是模糊逻辑与神经网络相结合而构成的,具备了模糊技术和神经网络技术的优点,从而被应用于电力系 统故障诊断中,是一种使用方便的处理系统。基于模糊神经网络对同步发电机转子匝间短路故障预测进行研究。经过训练后的 模糊神经网络。在对发电机转子匝间短路故障进行预测时,有较高的准确性和有效性。Fuzzy neural network is made up of fuzzy logic and neural network, which has.the merits of fuzzy technology and neural network technology, so this kind of management system can be used widely in diagnosing fault in power system. And this method is studied in forecasting inter-turn shorted turns in rotor windings of generator herein. Once trained, the proposed model is verified by a field test, whose results show that it is quite accurate and efficient. Fuzzy neural networks; Synchronous machine; Shorted turns; Rotor

关 键 词：模糊神经网络 同步发电机 转子 匝间短路 预测 

分 类 号：TM341[电气工程—电机] TP183[自动化与计算机技术—控制理论与控制工程]