Diagnosis of rotor asymmetries in induction motors: A steady state approach using rotating frame references

Francisco Vedreño Santos , Lucia Frosini , Daniel Moriñigo Sotelo
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Abstract

The diagnostic of electrical machines is of paramount importance, particularly with the Motor Current Signature Analysis (MCSA) method. MCSA stands out as a potent and non-intrusive tool for evaluating the condition of electric motors. This paper introduces an innovative approach for the diagnosis of rotor asymmetries, broken rotor bars, in induction machines operating in steady state directly fed from the grid, emphasising the decomposition of line currents within specific rotating frames. A novel methodology is proposed, and its results are meticulously compared with those obtained through the conventional Fast Fourier Transform (FFT) diagnostic technique. In particular, the newly introduced methodology exhibits enhanced sensitivity, surpassing the capabilities of conventional FFT. Additionally, the innovative approach is proven to be capable of quantifying the increase in fault harmonics in correlation with the load on the machine, aligning with the results observed through conventional FFT analysis. The findings strongly indicate that this pioneering technique offers a more robust and reliable means of diagnosing induction machines when compared to the traditional FFT method, by enhancing sensitivity and providing a nuanced understanding of fault harmonic variations with load changes.
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感应电动机转子不对称的诊断:一种使用旋转框架参考的稳态方法
电机的诊断是至关重要的,特别是电机电流特征分析(MCSA)方法。MCSA作为一种评估电动机状况的有效且非侵入性的工具脱颖而出。本文介绍了一种创新的方法来诊断转子不对称,转子断条,在稳定状态下直接从电网供电的感应电机,强调在特定的旋转框架内的线路电流的分解。提出了一种新的方法,并将其结果与传统的快速傅里叶变换(FFT)诊断技术进行了细致的比较。特别是,新引入的方法显示出更高的灵敏度,超过了传统FFT的能力。此外,该创新方法被证明能够量化与机器负载相关的故障谐波的增加,与传统FFT分析观察到的结果一致。研究结果强烈表明,与传统的FFT方法相比,这种开创性的技术通过提高灵敏度和提供对故障谐波随负载变化的细微理解,提供了一种更强大、更可靠的诊断感应电机的方法。
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