Institute for Energy Engineering, Universitat Politècnica de València, Cmno. de Vera s/n, 46022 Valencia, Spain.
Sensors (Basel). 2018 Jul 18;18(7):2340. doi: 10.3390/s18072340.
The development of advanced fault diagnostic systems for induction machines through the stator current requires accurate and fast models that can simulate the machine under faulty conditions, both in steady-state and in transient regime. These models are far more complex than the models used for healthy machines, because one of the effect of the faults is to change the winding configurations (broken bar faults, rotor asymmetries, and inter-turn short circuits) or the magnetic circuit (eccentricity and bearing faults). This produces a change of the self and mutual phase inductances, which induces in the stator currents the characteristic fault harmonics used to detect and to quantify the fault. The development of a machine model that can reflect these changes is a challenging task, which is addressed in this work with a novel approach, based on the concept of partial inductances. Instead of developing the machine model based on the phases' coils, it is developed using the partial inductance of a single conductor, obtained through the magnetic vector potential, and combining the partial inductances of all the conductors with a fast Fourier transform for obtaining the phases' inductances. The proposed method is validated using a commercial induction motor with forced broken bars.
通过定子电流开发感应电机的先进故障诊断系统需要准确和快速的模型，这些模型能够模拟机器在故障情况下的稳态和暂态运行。这些模型比健康机器使用的模型复杂得多，因为故障的一个影响是改变绕组配置（断条故障、转子不对称和匝间短路）或磁路（偏心和轴承故障）。这会导致自感和互感相的变化，从而在定子电流中感应出用于检测和量化故障的特征故障谐波。开发能够反映这些变化的电机模型是一项具有挑战性的任务，本工作提出了一种新的方法，基于部分电感的概念。该方法不是基于相线圈来开发电机模型，而是使用通过磁矢量势获得的单个导体的部分电感来开发，并通过快速傅里叶变换组合所有导体的部分电感来获得相电感。使用带有强制断条的商用感应电机对所提出的方法进行了验证。
