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高速列车牵引整流器多类故障联合诊断方法

陶宏伟 彭涛 杨超 陈志文 桂卫华

陶宏伟, 彭涛, 杨超, 陈志文, 桂卫华. 高速列车牵引整流器多类故障联合诊断方法. 自动化学报, 2019, 45(12): 2294−2302 doi: 10.16383/j.aas.c190258
引用本文: 陶宏伟, 彭涛, 杨超, 陈志文, 桂卫华. 高速列车牵引整流器多类故障联合诊断方法. 自动化学报, 2019, 45(12): 2294−2302 doi: 10.16383/j.aas.c190258
Tao Hong-Wei, Peng Tao, Yang Chao, Chen Zhi-Wen, Gui Wei-Hua. Joint fault diagnosis method of multiclass faults for traction rectifier in high-speed train. Acta Automatica Sinica, 2019, 45(12): 2294−2302 doi: 10.16383/j.aas.c190258
Citation: Tao Hong-Wei, Peng Tao, Yang Chao, Chen Zhi-Wen, Gui Wei-Hua. Joint fault diagnosis method of multiclass faults for traction rectifier in high-speed train. Acta Automatica Sinica, 2019, 45(12): 2294−2302 doi: 10.16383/j.aas.c190258

高速列车牵引整流器多类故障联合诊断方法

doi: 10.16383/j.aas.c190258
基金项目: 国家自然科学基金(61490702, 61773407, 61621062, 61803390), 轨道交通节能控制与安全监测湖南省重点实验室(2017TP1002), 装备预研教育部联合基金(6141A02022110), 装备预研领域基金(61400030501), 博士后基金(2018M643000), 湖南省研究生科研创新项目(CX20190064, CX2018B041)资助
详细信息
    作者简介:

    陶宏伟:中南大学自动化学院博士研究生. 2014年获得中南大学学士学位. 主要研究方向为电力电子系统建模, 故障诊断与容错控制. E-mail: hongwei.tao@csu.edu.cn

    彭涛:中南大学自动化学院教授. 2005年获得中南大学博士学位. 主要研究方向为复杂系统的故障诊断与容错控制. E-mail: pandtao@csu.edu.cn

    杨超:中南大学自动化学院博士研究生. 2014年获得重庆科技学院学士学位. 主要研究方向为牵引传动控制系统的故障诊断与健康监测. 本文通信作者. E-mail: chaoyang@csu.edu.cn

    陈志文:中南大学自动化学院讲师. 2016年获得德国杜伊斯堡 − 埃森大学博士学位. 主要研究方向为基于模型和数据驱动的故障诊断技术. E-mail: zhiwen.chen@csu.edu.cn

    桂卫华:中国工程院院士, 中南大学自动化学院教授. 1981年获得中南矿冶学院硕士学位. 主要研究方向为复杂工业过程建模, 优化与控制应用, 故障诊断与分布式鲁棒控制. E-mail: gwh@csu.edu.cn

Joint Fault Diagnosis Method of Multiclass Faults for Traction Rectifier in High-speed Train

Funds: Supported by National Natural Science Foundation of China (61490702, 61773407, 61621062, 61803390), Key Laboratory of Energy Saving Control and Safety Monitoring for Rail Transportation (2017TP1002), Program of Joint Pre-research Foundation of the Chinese Ministry of Education (6141A02022110), General Program of Equipment Pre-research Field Foundation of China (61400030501), Postdoctoral Foundation (2018M643000), and Hunan Provincial Innovation Foundation For Postgraduate (CX20190064, CX2018B041)
  • 摘要: 提出了一种高速列车牵引整流器多类故障联合诊断方法. 首先, 基于三电平牵引整流器开路故障分析, 建立整流器所有功率器件开路故障以及正常运行的状态空间模型并构建相应状态观测器. 然后, 基于正常状态观测器进行故障检测, 检测到故障后, 基于故障观测器区分功率器件开路故障和网侧电流传感器故障, 进而诊断出功率器件开路故障位置和网侧电流传感器故障类型. 实时仿真结果验证了本文方法的正确性和有效性.
  • 图  1  三电平整流器拓扑结构

    Fig.  1  Topology of three-level rectifier

    图  2  三电平整流器开关等效电路

    Fig.  2  Switching equivalent circuit of three-level rectifier

    图  3  不同运行情况下三电平整流器开关等效电路

    Fig.  3  Switching equivalent circuit of three-level rectifier in different operation conditions

    图  4  多类故障联合诊断方法流程图

    Fig.  4  Flowchart of joint fault diagnosis method for multiclass faults

    图  5  实时仿真平台

    Fig.  5  Real-time simulation platform

    图  6  $S_{a1}$开路故障诊断结果

    Fig.  6  Results of fault diagnosis when open-circuit fault occurs in $S_{a1}$

    图  7  网侧电流传感器增益故障诊断结果

    Fig.  7  Results of fault diagnosis when gain fault occurs in grid current sensor

    图  8  网侧电流传感器偏移故障诊断结果

    Fig.  8  Results of fault diagnosis when offset fault occurs in grid current senso

    图  9  网侧电流传感器漂移故障诊断结果

    Fig.  9  Results of fault diagnosis when drift fault occurs in grid current sensor

    表  1  $ H(k) $与故障位置的关系

    Table  1  Relationship of $ H(k) $ and fault loaction

    $ H(k) $故障位置
    255电流传感器
    254$ S_{a1} $
    253$ S_{a2} $
    251$ S_{a3} $
    247$ S_{a4} $
    236$ S_{b1} $
    223$ S_{b2} $
    191$ S_{b3} $
    127$ S_{b4} $
    下载: 导出CSV

    表  2  变流器参数

    Table  2  Parameter of converter

    参数符号
    网侧电压有效值$u_{N}$1500 V
    变压器电感$L_{N}$2 mH
    变压器电阻$R_{N}$0.2 $\Omega$
    直流环节电压$u_{1},u_{2}$1 300 V
    支撑电容$C_{1},C_{2}$1 600 mF
    下载: 导出CSV

    表  3  牵引电机参数

    Table  3  Parameter of traction motor

    参数符号
    定子电阻$R_{s}$0.15 $\Omega$
    定子电感$L_{ls}$1.42 mH
    转子电阻$R_{r}$0.16 $\Omega$
    转子电感$L_{lr}$0.6 mH
    互感$L_{m}$25.4 mH
    额定电压$U_{\rm{rate}}$2 000 V
    额定频率$f_{\rm{rate}}$140 Hz
    额定转速$n_{\rm{rate}}$4 140 r/min
    额定输出功率$P_{\rm{rate}}$300 kW
    额定转差率$s_{\rm{rate}}$1.4 %
    下载: 导出CSV
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  • 收稿日期:  2019-03-27
  • 录用日期:  2019-07-30
  • 刊出日期:  2019-12-01

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