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Fault Diagnosis of Misaligned Hall-effect Position Sensors in Brushless DC Motor Drives Using a Goertzel Algorithm

机译:使用Goertzel算法诊断无刷直流电动机驱动器中未对准霍尔效应位置传感器的故障

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In this study, defective Brushless DC (BLDC) motor drives with misplaced Hall-effect position sensors are investigated. Since position sensor misplacement results in increased torque ripple, vibrations, audible noise, and reduced system efficiency, a robust technique for the diagnosis of the defect is required. Considering the commonly used sensors in BLDC motor drives, the DC-link current frequency spectrum is exploited to reveal the position sensor misalignment and the severity of the defect. Thus, frequency-domain analysis and, especially, the increment of the additional harmonic components of the DC-link current is investigated as potential fault signature. Moreover, the second order Goertzel Algorithm is proposed for fast fault identification due to its distinct features compared to the conventional signal processing techniques. Therefore, different scenarios are investigated to identify the effectiveness of both the selected harmonic components and the diagnostic method in highlighting the defect and its severity.
机译:在这项研究中,研究了带有错误位置的霍尔效应位置传感器的有缺陷的无刷直流(BLDC)电动机驱动器。由于位置传感器的位置不当会导致转矩脉动,振动,可听见的噪声增加,并降低系统效率,因此需要一种可靠的技术来诊断缺陷。考虑到BLDC电机驱动器中常用的传感器,可以利用直流母线电流频谱来揭示位置传感器的未对准和缺陷的严重性。因此,将频域分析,尤其是直流母线电流的附加谐波分量的增量作为潜在的故障特征进行了研究。此外,由于二阶Goertzel算法与常规信号处理技术相比具有鲜明的特征,因此提出了用于快速故障识别的算法。因此,研究了不同的情况,以识别所选谐波分量和诊断方法在突出缺陷及其严重性方面的有效性。

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