Diagnosis of eccentricity based on the Hilbert transform of the startup transient current

R. Puche-Panadero, J. Pons-Llinares, J. Roger-Folch, M. Pineda-Sánchez
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引用次数: 18

Abstract

The Hilbert Transform (HT) can improve the resolution of motor current signature analysis (MCSA), especially at very low slip, because it converts the supply frequency into a continuous component, which can be easily removed to better detect fault harmonics. This paper proposes its application also during speed transients, with two key advantages: first, it allows an easy filtering of the transient current component corresponding to the supply frequency, and, second, the HT allows for the generation of the Hilbert Spectrum, as a replacement of the Fourier Spectrum in the case of non-stationary signals, like those that appear in a transient regime. The performance of the proposed method is compared with other methods as the Discrete Wavelet Transform (DWT), and is validated through simulation with a mathematical model and experimental analysis of a 1.1 kW three-phase squirrel-cage commercial induction motor with eccentricity.
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基于启动瞬态电流希尔伯特变换的偏心诊断
希尔伯特变换(HT)可以提高电机电流特征分析(MCSA)的分辨率,特别是在非常低的转差下,因为它将电源频率转换为连续分量,可以很容易地去除它以更好地检测故障谐波。本文还提出了它在速度瞬态期间的应用,具有两个关键优点:首先,它允许对与电源频率相对应的瞬态电流分量进行轻松滤波,其次,HT允许在非平稳信号的情况下生成希尔伯特谱,作为傅立叶谱的替代,例如那些出现在瞬态状态的信号。将该方法与离散小波变换(DWT)等方法的性能进行了比较,并通过1.1 kW偏心三相鼠笼型商用异步电动机的数学模型仿真和实验分析验证了该方法的有效性。
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