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Comparison of results for eccentric cage induction motor using Finite Element method and Modified Winding Function Approach

机译:偏心笼型感应电动机有限元法与修正绕组函数法的结果比较。

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Air-gap eccentricity is a fault that mainly affects large induction motors. In the worst case an eccentricity fault can result in a stator rotor rub thereby causing severe damage to the motor. As a result eccentricity fault detection has gained considerable significance. Of all detection schemes for this fault, Motor Current Signature Analysis (MCSA) is the most widely used technique. This scheme relies on identifying fault specific frequency component in the line current spectrum of the motor to identify the type of fault. The severity of the fault can be estimated by monitoring the magnitude of the characteristic frequency component. To characterize the fault severity an accurate model of induction motor has to be developed. Two models - Finite Element(FE) based model and Modified Winding Function Approach (MWFA) based model are used in this paper to estimate the magnitude of fault specific frequency components for different eccentricities at full load condition. The results obtained from the two methods are compared to find the suitability of MWFA based model in characterizing the fault severity.
机译:气隙偏心是主要影响大型感应电动机的故障。在最坏的情况下,偏心故障会导致定子转子摩擦,从而对电动机造成严重损坏。结果,偏心故障检测已具有相当重要的意义。在所有针对此故障的检测方案中,电动机电流签名分析(MCSA)是使用最广泛的技术。该方案依赖于在电动机的线电流频谱中识别故障特定的频率分量,以识别故障的类型。可以通过监视特征频率分量的大小来估计故障的严重程度。为了表征故障严重性,必须开发感应电动机的精确模型。本文使用两种模型-基于有限元(FE)的模型和基于改进绕线函数法(MWFA)的模型来估计满载条件下不同偏心率的故障特定频率分量的大小。比较从两种方法获得的结果,以发现基于MWFA的模型在表征故障严重性方面的适用性。

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