电机与控制应用2024，Vol.51Issue(6)：1-11,11.DOI:10.12177/emca.2024.038
基于小波神经网络的六相永磁同步电机高阻连接状态感知策略
Sensing Strategy for High Resistance Connection State of Six-Phase PMSM Based on Wavelet Neural Network
摘要
Abstract
Six-phase permanent magnet synchronous motors have the ability of phase-deficient operation,thus precise prediction of their high resistance connection state must be made to ensure effective disconnection for faulty lines,prevent protection misoperation caused by system disturbances,and provide reliable criteria for fault-tolerant control.A mathematical model for complete decoupling of six-phase permanent magnet synchronous motor is established based on vector space decomposition,and its control system model is established.Motor signals in normal state and high resistance connection state are collected,and their energy distance features are extracted by wavelet packet decomposition,input to the back propagation neural network for offline training,and finally applied to sense development situation of high resistance connection state online under drastic conditions.Simulations are carried out based on Matlab,and the results show that the proposed strategy can effectively identify high resistance connection state,sensitively sense its development situation,send warning signals before the high resistance faults occur,and have certain robustness to drastic conditions.关键词
六相永磁同步电机/高阻连接/小波包分解/能量距/前向反馈神经网络Key words
six-phase permanent magnet synchronous motor/high resistance connection/wavelet packet decomposition/energy distance/back propagation neural network分类
信息技术与安全科学引用本文复制引用
陈少霞,高卓,姚钢,鲁涛,钱轶群..基于小波神经网络的六相永磁同步电机高阻连接状态感知策略[J].电机与控制应用,2024,51(6):1-11,11.基金项目
国家电网有限公司总部管理科技项目资助(5209KZ220002) （5209KZ220002）
国家自然科学基金(52077135)State Grid Corporation Limited Headquarters Management Technology Project Funding(5209KZ220002) （52077135）
National Natural Science Foundation of China(52077135) （52077135）
