基于粒子群优化的五相永磁同步电机匝间短路建模与故障诊断

Jian-wei Yang, M. Dou, Zhiyong Dai, Dongdong Zhao, Zhen Zhang
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引用次数: 6

摘要

多相永磁同步电动机广泛应用于容错控制领域。其中一个重要的容错控制问题是故障诊断。在现有的大多数文献中,故障诊断主要集中在三相永磁同步电动机上。提出了一种基于粒子群优化(PSO)的五相永磁同步电机匝间短路故障诊断模型和方法。本文主要有两个方面的贡献:1)通过分析永磁同步电动机的电阻、电感和磁通等物理参数,建立了五相永磁同步电动机ITSC故障的数学模型。2)提出了一种基于粒子群算法的参数估计方法,该方法引入与ITSC比相关的适应度函数,将故障参数识别问题重新定义为极值求问题,用于跟踪实际ITSC比,检测五相永磁同步电机的故障级别。仿真结果对所提出的模型和故障诊断方法进行了初步验证。
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Modeling and fault diagnosis of inter-turn short circuit for five-phase PMSM based on Particle Swarm Optimization
Multiphase PMSMs are widely used in fault-tolerant control applications. And one of the important fault-tolerant control problems is fault diagnosis. In most existing references, the fault diagnosis always focuses on three-phase PMSM. In this paper, a novel model and a fault diagnosis method of inter-turn short circuit (ITSC) fault for five-phase PMSM based on particle swarm optimization (PSO) are presented. There are two contributions in this paper: 1) By analyzing the physical parameters of the PMSM, such as resistance, inductance and flux, the mathematic model of ITSC fault for five-phase PMSM is established. 2) A parameter estimation method based on PSO algorithm, which introduces a fitness function related to the ITSC ratio and reformulates the fault parameters identification problem as the extreme seeking problem, is proposed to track the actual ITSC ratio and detect the fault level for five-phase PMSM. Simulation results provide preliminary verification of the proposed model and fault diagnosis method.
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