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Detection of Eccentricity Faults in Five-Phase Ferrite-PM Assisted Synchronous Reluctance Machines

机译:检测五相铁氧体-PM辅助同步磁阻机中的偏心故障

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Air gap eccentricity faults in five-phase ferrite-assisted synchronous reluctance motors (fPMa-SynRMs) tend to distort the magnetic flux in the air gap, which in turn affects the spectral content of both the stator currents and the ZSVC (zero-sequence voltage component). However, there is a lack of research dealing with the topic of fault diagnosis in multi-phase PMa-SynRMs, and in particular, those focused on detecting eccentricity faults. An analysis of the spectral components of the line currents and the ZSVC allows the development of fault diagnosis algorithms to detect eccentricity faults. The effect of the operating conditions is also analyzed, since this paper shows that it has a non-negligible impact on the effectivity and sensitivity of the diagnosis based on an analysis of the stator currents and the ZSVC. To this end, different operating conditions are analyzed. The paper also evaluates the influence of the operating conditions on the harmonic content of the line currents and the ZSVC, and determines the most suitable operating conditions to enhance the sensitivity of the analyzed methods. Finally, fault indicators employed to detect eccentricity faults, which are based on the spectral content of the stator currents and the ZSVC, are derived and their performance is assessed. The approach presented in this work may be useful for developing fault diagnosis strategies based on the acquisition and subsequent analysis and interpretation of the spectral content of the line currents and the ZSVC.
机译:五相铁氧体辅助同步磁阻电动机(FPMA-Synrms)的气隙偏心故障倾向于使气隙中的磁通量扭曲,这反过来影响定子电流和ZSVC的光谱含量(零序电压成分)。然而,缺乏对多相PMA-Synrms中的故障诊断主题的研究,特别是那些重点检测偏心故障的主题。对线电流的光谱分量和ZSVC的分析允许开发故障诊断算法来检测偏心故障。还分析了操作条件的效果,因为本文表明,基于定子电流和ZSVC的分析,它对诊断的有效性和灵敏度具有不可忽略的影响。为此,分析了不同的操作条件。本文还评估了操作条件对线电流和ZSVC的谐波含量的影响,并确定最合适的操作条件,以增强分析方法的灵敏度。最后,推导出用于检测基于定子电流和ZSVC的光谱含量的偏心故障的故障指示,并评估它们的性能。本作工作中呈现的方法可用于基于采集和随后的分析和解释线电流和ZSVC的频谱内容的分析和解释来开发故障诊断策略。

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