系统仿真学报 ›› 2018, Vol. 30 ›› Issue (8): 3139-3145.doi: 10.16182/j.issn1004731x.joss.201808039

• 仿真应用工程 • 上一篇    下一篇

矢量控制系统中感应电机电流传感器故障诊断

孙凯1, 何柏娜1, SarahOdofin2, 谷雨3   

  1. 1.山东理工大学电气与电子工程学院,山东 淄博 255049;
    2. Faculty of Engineering and Environment,University of Northumbria, Newcastle, UK NE1 8ST;
    3. 北京信息科技大学自动化学院,北京 100192
  • 收稿日期:2016-09-22 出版日期:2018-08-10 发布日期:2019-01-08
  • 作者简介:孙凯(1970-),男,山东诸城,博士,副教授,研究方向为现代电力电子技术及电气传动;何柏娜(1977-),女,辽宁辽阳,博士,副教授,研究方向为高电压技术。
  • 基金资助:
    山东省高等学校科技计划(J14LN27)

Current Sensor Fault Diagnosis for Induction Motor in Vector Control System

Sun Kai1, He Baina1, Sarah Odofin2, Gu Yu3   

  1. 1. School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255049, China;
    2. Faculty of Engineering and Environment, University of Northumbria, Newcastle NE1 8ST, UK;
    3. School of Automation, Beijing Information Science & Technology University, Beijing 100192, China
  • Received:2016-09-22 Online:2018-08-10 Published:2019-01-08

摘要: 提出一种矢量控制系统中感应电动机电流传感器故障诊断方法。建立包含扰动和传感器故障的电动机状态空间数学模型,设计一个基于电动机状态空间数学模型的扩张状态观测器,并设计一个故障估计器,用以估计故障和系统状态。通过闭环系统特征值配置和遗传优化算法搜寻闭环反馈增益矩阵的最优值,提高估计精度和鲁棒性,利用Matlab仿真模型和实时数据进行仿真验证。

关键词: 故障诊断, 故障估计, 遗传算法, 传感器故障, 感应电动机, 矢量控制, 扩张状态观测器

Abstract: A current sensor fault diagnosis method of induction motor in vector control system is proposed. A state-space form including sensor faults and environmental disturbances/noises of induction machine is described. An augmented observer is designed to simultaneously estimate system states, and current sensor faults. To attenuate the effects from the environmental disturbances/noises, a genetic algorithm is employed to design observer gain by minimizing the estimation error against environmental disturbances and noises. A simulation model based on Matlab and real-data of the induction motor collected by experiment is utilized to validate the proposed methods, which show the efficiency of the proposed sensor fault diagnosis approaches. The proposed methods have great potential to improve the reliability of the real-time operation of the induction motor drive systems.

Key words: fault diagnosis, state estimation, genetic algorithm, sensor fault, induction motor, vector control, augmented observer

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