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文章摘要
一种基于深度神经网络的直流充电桩故障诊断方法
A fault diagnosis method for DC charging pile based on deep neural network
Received:July 26, 2019  Revised:September 03, 2019
DOI：10.19753/j.issn1001-1390.2021.06.021
中文关键词: 直流充电桩  状态监测  故障诊断  深度神经网络  整流控制
英文关键词: 
基金项目:
Author NameAffiliationE-mail
Zhao Xiang NARI Group Corporation（State Grid Electric Power Research Institute） zhaoxiang@sgepri.sgcc.com.cn 
Chen Liangliang NARI Group Corporation（State Grid Electric Power Research Institute） 13851729510@126.com 
Li Mingzhen* School of Electrical Engineering and Automation, Wuhan University li-mingzhen@qq.com 
Zhou Chengke School of Electrical Engineering and Automation, Wuhan University c.zhou@gcu.edu.uk 
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中文摘要:
      针对直流充电桩故障多发的现状，提出一种基于深度神经网络的直流充电桩故障诊断方法，利用对整流器输出电压的监测实现充电桩故障实时诊断。首先，利用电路仿真软件对直接电流控制系统、同步PI电流控制和一种旋转坐标系解耦控制等典型的控制策略在正常运行、功率器件故障、控制元件故障等运行状态下进行仿真，得到了720组输出电压波形数据。将这些输出电压波形数据作为数据输入对深度神经网络进行训练，得出了基于数据指针向量的故障诊断判据。结果表明，该方法可正确实现直流充电桩的故障诊断，模型的计算误差满足要求。
英文摘要:
      
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