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基于故障传播与因果关系的故障溯源方法及其在牵引传动控制系统中的应用

尹进田 谢永芳 陈志文 彭涛 杨超

尹进田, 谢永芳, 陈志文, 彭涛, 杨超. 基于故障传播与因果关系的故障溯源方法及其在牵引传动控制系统中的应用. 自动化学报, 2020, 46(1): 47−57 doi: 10.16383/j.aas.c190257
引用本文: 尹进田, 谢永芳, 陈志文, 彭涛, 杨超. 基于故障传播与因果关系的故障溯源方法及其在牵引传动控制系统中的应用. 自动化学报, 2020, 46(1): 47−57 doi: 10.16383/j.aas.c190257
Yin Jin-Tian, Xie Yong-Fang, Chen Zhi-Wen, Peng Tao, Yang Chao. Fault tracing method based on fault propagation and causality with its application to the traction drive control system. Acta Automatica Sinica, 2020, 46(1): 47−57 doi: 10.16383/j.aas.c190257
Citation: Yin Jin-Tian, Xie Yong-Fang, Chen Zhi-Wen, Peng Tao, Yang Chao. Fault tracing method based on fault propagation and causality with its application to the traction drive control system. Acta Automatica Sinica, 2020, 46(1): 47−57 doi: 10.16383/j.aas.c190257

基于故障传播与因果关系的故障溯源方法及其在牵引传动控制系统中的应用

doi: 10.16383/j.aas.c190257
基金项目: 国家自然科学基金(61490702, 61773407, 61621062, 61803390, 61751312), 国家杰出青年科学基金(61725306), 轨道交通节能控制与安全监测湖南省重点实验室(2017TP1002), 湖南省科技厅科技计划项目(2016TP1023), 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)资助
详细信息
    作者简介:

    尹进田:中南大学自动化学院博士研究生. 2004年获得湖南工程学院学士学位. 主要研究方向为牵引传动控制系统故障仿真与诊断. E-mail: yinjintian0115@163.com

    谢永芳:中南大学自动化学院教授. 1999年获得中南大学博士学位. 主要研究方向为复杂工业过程建模与控制, 分散鲁棒控制, 故障诊断. E-mail: yfxie@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. 本文通信作者. E-mail: zhiwen.chen@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. E-mail: chaoyang@csu.edu.cn

Fault Tracing Method Based on Fault Propagation and Causality With Its Application to the Traction Drive Control System

Funds: Supported by National Natural Science Foundation of China (61490702, 61773407, 61621062, 61803390, 61751312), National Science Foundation for Distinguished Young Scholars of China (61725306), Key Laboratory of Energy Saving Control and Safety Monitoring for Rail Transportation (2017TP1002), Science and Technology Project of Hunan Science and Technology Agency (2016TP1023), Program of Joint Pre-research Foundation of the Chinese Ministry of Education (6141A02022110), General Program of Equipment Pre-research Field Foundation of China (61400030501), and Postdoctoral Foundation (2018M643000)
  • 摘要: 针对故障溯源问题, 提出一种基于故障传播与因果关系的故障溯源方法. 该方法首先建立体现时空特性的系统故障传播模型; 其次利用Granger因果关系技术判定不同观测点信号间的因果关系, 确定适合提取信号故障特征用于故障诊断的观测点; 然后提取系统运行时这些观测点故障特征和故障传播时间; 最后同故障传播模型中对应观测点的时空特性相匹配, 从而确定故障类型与位置, 实现故障溯源. 所提方法在高速列车牵引传动控制系统半实物仿真平台上进行了实验验证, 结果表明该方法可行有效.
    1)   收稿日期 2019-03-27    录用日期 2019-09-24 Manuscript received March 27, 2019; accepted September 24, 2019 国家自然科学基金 (61490702, 61773407, 61621062, 61803390, 61751312), 国家杰出青年科学基金 (61725306), 轨道交通节能控制与安全监测湖南省重点实验室 (2017TP1002), 湖南省科技厅科技计划项目 (2016TP1023), 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) 资助 Supported by National Natural Science Foundation of China (61490702, 61773407, 61621062, 61803390, 61751312), National Science Foundation for Distinguished Young Scholars of China (61725306), Key Laboratory of Energy Saving Control and Safety Monitoring for Rail Transportation (2017TP1002), Science and Technology Project of Hunan Science and Technology Agency (2016TP1023), Program of Joint Pre-research Foundation of the Chinese Ministry of Education (6141A02022110), General Program of Equipment Pre-research Field Foundation of China (61400030501), and Postdoctoral Foundation (2018M643000)
    2)   本文责任编委 董海荣 Recommended by Associate Editor DONG Hai-Rong 1. 中南大学自动化学院 长沙 410083    2. 邵阳学院多电源地区电网运行与控制湖南省重点实验室 邵阳 422000 1. School of Automation, Central South University, Changsha 410083    2. Hunan Provincial Key Laboratory of Grids Operation and Control on Multi-Power Sources Area, Shaoyang University, Shaoyang 422000
  • 图  1  方法整体流程图

    Fig.  1  Integrated flowchart of the proposed method

    图  2  牵引传动控制系统观测点示意图

    Fig.  2  Schematic diagram of observation point of traction drive control system

    图  3  牵引传动控制系统主电路拓扑图

    Fig.  3  Main circuit topology diagram of traction drive control system

    图  4  硬件在环半实物仿真平台

    Fig.  4  Semi-physical simulation platform of hardware-in-the-loop

    图  5  观测点电流信号间Granger因果关系

    Fig.  5  Granger causality between the current signals at different observation points

    图  6  不同观测点电流时域波形

    Fig.  6  Current time domain waveforms at different observation points

    图  7  不同观测点电流频谱图

    Fig.  7  Current spectrum of different observation points

    表  1  不同观测点故障特征频率值(Hz)

    Table  1  Fault feature frequency value at different observation points (Hz)

    电网
    频率$ f $
    电机定子电流
    频率$ f_1 $
    转差率$ s $观测点1电流故障
    特征频率$ (1\pm2s)f_1 $
    观测点2电流故障
    特征频率$ 2sf_1 $
    观测点3电流故障
    特征频率$ 2sf_1 $
    观测点4电流故障特征频率$ (4n\pm1)f\pm2sf_1 $
    50131.10.0172126.4/135.64.54.545.5/54.5
    145.5/154.5
    245.5/254.5
    下载: 导出CSV
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  • 收稿日期:  2019-03-27
  • 录用日期:  2019-09-24
  • 刊出日期:  2020-01-21

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