微特电机 ›› 2021, Vol. 49 ›› Issue (6): 58-60.

• 读者园地 • 上一篇    下一篇

异步电动机故障仿真与诊断研究

赵乾麟1, 赵屹1, 方炳平1, 游张平1,2   

  1. 1.浙江乾麟缝制设备有限公司,丽水 323000;
    2.丽水学院 机械工程系,丽水 323000
  • 收稿日期:2021-03-10 出版日期:2021-06-28 发布日期:2021-06-22
  • 作者简介:赵乾麟(1962—),男,本科,高级工业设计师,研究方向为电机数字化设计与制造。
  • 基金资助:
    浙江省自然科学基金项目(LY20E050002);浙江省基础公益研究计划项目(LGG18E050001)

Research on Fault Simulation and Diagnosis of Asynchronous Motor

ZHAO Qian-lin1, ZHAO Yi1, FANG Bing-ping1, YOU Zhang-ping1,2   

  1. 1. Zhejiang Qianlin Sewing Equipment Co., Ltd., Lishui 323000, China;
    2. Department of Mechanical Engineering, Lishui University, Lishui 323000, China
  • Received:2021-03-10 Online:2021-06-28 Published:2021-06-22

摘要: 针对异步电动机传统故障诊断方法存在的问题,基于Simulink平台建立异步电动机故障仿真模型,应用人工神经网络开展故障诊断研究。在Simulink平台上选取仿真模块,设置单相短路(A相、B相、C相)、两相短路(AB、AC、BC)等6种接地短路故障类型,设定仿真参数,并进行仿真分析;建立异步电动机BP神经网络诊断模型;提取异步电动机故障特征量,经预处理后,送入BP神经网络模型进行训练与仿真测试。仿真结果表明该方法对于异步电动机的故障诊断是有效的、可行的。

关键词: 异步电动机, Simulink, 故障仿真, 故障诊断, 神经网络

Abstract: Aiming at problems of traditional fault diagnosis methods forasynchronous motors, a fault simulation model of asynchronous motor was set up based on Simulink platform, and fault diagnosis research was carried out based on artificial neural network and this simulation model.Select the simulation module on the Simulink platform, set up six types of ground short circuit faults (A phase short circuit, B phase short circuit, C phase short circuit, AB two-phase short circuit,AC two-phase short circuit, BC two-phase short circuit), set parameters, and carry out the simulation.The BP neural network diagnosis model of asynchronous motor was established. The faultcharacteristic quantity of asynchronous motor was extracted. After preprocessing, it was fed into the BP neural network model for training and simulation test. The simulation results show that the proposed method is effective and feasible for fault diagnosis of asynchronous motor.

Key words: asynchronous motor, Simulink, fault simulation, fault diagnosis, neural network

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