基于径向基函数神经网络算法的汽轮发电机转子绕组匝间短路故障诊断  

Fault Diagnosis of Inter-turn Short Circuit in Turbogenerator Rotor Winding Based on Radial Basis Function Neural Network Algorithm

作　　者：周奇 吕飞 周煜晨 姚殷培 王驰 吴頔杰 ZHOU Qi;LV Fei;ZHOU Yuchen;YAO Yinpei;WANG Chi;WU Dijie(Guoneng Changyuan Hanchuan Power Generation Co.,Ltd.,Hanchuan 431600,China)

机构地区：[1]国能长源汉川发电有限公司,湖北汉川431600

出　　处：《电工技术》2024年第11期33-35,40,共4页Electric Engineering

摘　　要：转子绕组匝间短路是汽轮发电机的主要故障之一,对该故障的既有诊断方法仍有不足。在分析径向基函数神经网络基础上,提出一种基于该神经网络的汽轮发电机转子绕组匝间短路故障诊断方法。详细介绍了该方法的故障诊断流程,并对其进行了仿真验证。研究表明,该方法精度高且收敛速度快,可有效诊断汽轮发电机转子绕组匝间短路故障。The inter-turn short circuit of rotor winding is one of the main faults in turbogenerators,and there are still shortcomings in existing diagnostic methods for this fault.Based on the analysis of radial basis function neural networks,a fault diagnosis method for inter-turn short circuits in turbogenerator rotor windings is proposed based on this neural network.The fault diagnosis process of this method is outlined in detail in this paper,and simulation verification is conducted.The proposed method is found to have high accuracy and fast convergence speed,and can effectively diagnose inter-turn short circuit faults in turbogenerator rotor windings.

关 键 词：汽轮发电机 转子绕组匝间短路 故障诊断 径向基函数神经网络 MATLAB 

分 类 号：TM311[电气工程—电机]