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首页> 外文期刊>Electric power systems research >Detection and estimation of demagnetization faults in permanent magnet synchronous motors
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Detection and estimation of demagnetization faults in permanent magnet synchronous motors

机译:永磁同步电动机退磁故障的检测与估计

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摘要

This paper presents a symbolic dynamic method for health monitoring of permanent magnet synchronous motors (PMSMs), which involves abstraction of a qualitative description from a dynamical system representation of the PMSM. The underlying algorithms rely on state-space embedding of the PMSM's output line current and discretization of the resultant pseudo-state and input spaces. System identification is achieved through inference of the PMSM's dynamical system behavior, and the deviation of the system's output behavior from the nominal expected behavior yields a measure of the estimated fault. A special-purpose test bed has been designed and fabricated for experimental validation of the health monitoring algorithm via controlled accelerated deterioration of magnetization in the PMSM. The performance of the proposed algorithm has been compared with that of a classical motor current signature analysis (MCSA) procedure as well as with a benchmark particle filter for fault detection in PMSMs.
机译:本文提出了一种用于永磁同步电动机(PMSM)健康监测的符号动态方法,该方法涉及从PMSM的动态系统表示中提取定性描述。底层算法依赖于PMSM输出线电流的状态空间嵌入以及所得伪状态和输入空间的离散化。通过推断PMSM的动态系统行为来实现系统识别,并且系统输出行为与标称预期行为的偏差会产生估计故障的度量。设计并制造了一种专用测试床,用于通过PMSM中受控的磁化加速劣化来对健康监控算法进行实验验证。该算法的性能已与经典电动机电流签名分析(MCSA)程序以及用于PMSM中故障检测的基准粒子滤波器进行了比较。

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