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Transient analysis of the external magnetic field via MUSIC methods for the diagnosis of electromechanical faults in induction motors

机译:通过MUSIC方法对外部磁场进行瞬态分析,以诊断感应电动机中的机电故障

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In the induction motor predictive maintenance area there is a continuous search for new techniques and methods that can provide additional information for a more reliable determination of the motor condition. In this context, the analysis of the external magnetic field has drawn the interest of many researchers. The simplicity, low cost and potential of this technique makes it attractive for complementing the diagnosis provided by other well-established methods. More specifically, the study of this quantity during transient operation of the motor (e.g. under the starting) has been recently proposed as a valuable tool for the diagnosis of certain electromechanical faults. Despite this fact, the research in this approach is still incipient and the employed signal processing tools must be still optimized for a better visualization of the fault components and, therefore, for a better determination of the machine condition. This paper presents an advanced algorithm based on MUSIC for enhancing the visualization of the harmonics caused by different motor failures in the electromotive force signals induced by the external magnetic field. Two faults are considered in the work: rotor problems and misalignments. Also, different positions of the external coil sensor are studied. The results prove the potential of the MUSIC algorithm for the reliable diagnosis of electromechanical faults.
机译:在感应电动机预测性维护领域,人们不断寻找可以提供更多信息以更可靠地确定电动机状况的新技术和方法。在这种情况下,对外部磁场的分析引起了许多研究人员的兴趣。该技术的简单性,低成本和潜力使其对补充其他公认的方法提供的诊断具有吸引力。更具体地,最近提出了在电动机的瞬态操作期间(例如,在启动下)对该量的研究,作为用于诊断某些机电故障的有价值的工具。尽管如此,这种方法的研究仍处于起步阶段,必须仍然对所使用的信号处理工具进行优化,以更好地显示故障组件,从而更好地确定机​​器状况。本文提出了一种基于MUSIC的高级算法,用于增强由外部磁场感应的电动势信号中不同电机故障引起的谐波的可视化。工作中考虑了两个故障:转子问题和不对中。此外,还研究了外部线圈传感器的不同位置。结果证明了MUSIC算法对于机电故障的可靠诊断的潜力。

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