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Harmonic Order Tracking Analysis: A Novel Method for Fault Diagnosis in Induction Machines

机译:谐波阶次跟踪分析:感应电机故障诊断的一种新方法

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摘要

The diagnosis of induction machines using Fourier transform relies on tracking the frequency signature of each type of fault in the current's spectrum, but this signature depends on the machine's slip and the supply frequency, so it must be recomputed for each working condition by trained personnel or by diagnostic software. Besides, sampling the current at high rates during long times is needed to achieve a good spectral resolution, which requires large memory space to store and process the current spectra. In this paper, a novel approach is proposed to solve both problems. It is based on the fact that each type of fault generates a series of harmonics in the current's spectrum, whose frequencies are multiples of a characteristic main fault frequency. The tracking analysis of the fault components using the harmonic order (defined as the frequency in per unit of the main fault frequency) as independent variable instead of the frequency generates a unique fault signature, which is the same for any working condition. Besides, this signature can be concentrated in just a very small set of values, the amplitudes of the components with integer harmonic order. This new approach is introduced theoretically and validated experimentally.
机译:使用傅立叶变换对感应电机的诊断依赖于跟踪电流频谱中每种故障的频率特征,但是该特征取决于电机的转差率和供电频率,因此必须由受过训练的人员或在每种工作条件下对它进行重新计算。通过诊断软件。此外,为了获得良好的频谱分辨率,还需要长时间高速率采样电流,这需要很大的存储空间来存储和处理电流频谱。本文提出了一种新颖的方法来解决这两个问题。基于以下事实:每种类型的故障都会在电流频谱中生成一系列谐波,其频率是典型故障主频率的倍数。使用谐波次数(定义为主故障频率的单位频率)作为自变量而不是频率来跟踪故障分量,会生成唯一的故障特征,在任何工作条件下都是相同的。此外,该签名可以集中在很小的一组值上,这些分量的幅度具有整数谐波阶数。从理论上介绍了这种新方法,并通过实验进行了验证。

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