集员卡尔曼滤波器在电机故障诊断中的应用

Application of set-membership Kalman filter in motor fault diagnosis

中文关键词  故障诊断  伺服电机  集员卡尔曼滤波器  中心对称多面体

英文关键词  fault diagnosis  servo motor  set-membership Kalman filter  zonotope

中文摘要

      本文针对伺服电机提出了一种基于集员卡尔曼滤波器的故障诊断方法并进行了实际应用. 首先, 基于运动学关系和数据驱动技术构建了伺服电机的综合系统动态. 之后, 针对电机的位置–速度模型设计了一个中心对称多面体卡尔曼滤波器来检测位置传感器和速度传感器是否发生故障. 同时, 针对电机的力矩–速度模型设计了一个中心对称多面体卡尔曼滤波器来检测力矩执行器故障和速度传感器故障. 然后, 基于上述的两个中心对称多面体卡尔曼滤波器提出了一种故障隔离律, 可以定位出伺服电机故障部件的位置. 最后, 通过一个实际的伺服电机实验平台对所提出方法进行了应用, 并验证了其可行性与有效性

英文摘要

      This paper proposes a fault diagnosis approach for servo motor based on set-membership Kalman filter and realizes the practical application. Firstly, the integrated dynamic system of servo motor is constructed via the kinematic relationship and data-driven techniques. A zonotopic Kalman filter is then designed for the motor position–velocity model to determine whether the position sensor and velocity sensor are faulty. Meanwhile, a zonotopic Kalman filter is synthesized for the motor torque–velocity model to detect the torque actuator fault and velocity sensor fault. After that, a fault isolation law is proposed with the aid of the presented two zonotopic Kalman filter, which can locate the faulty component of servo motor. Finally, the proposed approach is applied to a practical servo motor experimental platform, and its viability and validity are verified.