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首页> 外文期刊>Advances in Electrical and Computer Engineering >Reassigned Short Time Fourier Transform and K-means Method for Diagnosis of Broken Rotor Bar Detection in VSD-fed Induction Motors
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Reassigned Short Time Fourier Transform and K-means Method for Diagnosis of Broken Rotor Bar Detection in VSD-fed Induction Motors

机译:重新分配的短时傅立叶变换和K均值方法在VSD馈电异步电动机转子断条检测中的诊断

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Over the years induction motors have established an uncanny knack for providing a plethora of utilities in the industry, where the fault monitoring and detection has become necessary. Several techniques could be applied for the monitoring and identification of broken rotor bars when the motor is fed by a variable speed drive (VSD). Nevertheless, many of these methodologies detect this fault and other failures in the steady state condition, but this monitoring grow into more complicated analysis during the startup transient condition owing to the large number of harmonics, which the VSD insert to the current signal. The novelty of the proposed methodology is the application of the reassignment during the startup transient and the steady state conditions to identify one broken rotor bar in the induction motor. The proposed methodology is experimented with both, real and synthetic signals. The problems that Short Time Fourier Transform (STFT), shows for the identification of broken rotor bars are exhibited. The proposed methodology includes an automatic diagnosis (K-means algorithm), where the signal energy is used. The results show that the Reassigned Short Time Fourier Transform (RSTFT) technique and K-means methods are appropriated for the effective monitoring and diagnosis of one broken rotor bar in the induction motor during the startup and steady state conditions of operation.
机译:多年来,感应电动机已经建立了一个不可思议的诀窍,可以在需要故障监视和检测的行业中提供大量实用程序。当电动机由变速驱动器(VSD)供电时,可以采用多种技术来监视和识别损坏的转子条。尽管如此,这些方法中的许多方法都可以在稳态条件下检测到此故障和其他故障,但是由于VSD插入到电流信号中的谐波数量众多,因此在启动瞬态条件期间,这种监视变得更加复杂。所提出的方法的新颖性是在启动瞬态和稳态条件期间应用重新分配以识别感应电动机中的一根损坏的转子条。所提出的方法已在真实信号和合成信号上进行了实验。出现了短时傅立叶变换(STFT)所显示出的用于识别转子条损坏的问题。所提出的方法包括使用信号能量的自动诊断(K-means算法)。结果表明,重新分配的短时傅立叶变换(RSTFT)技术和K-means方法适用于在启动和稳态运行条件下有效监测和诊断感应电动机中一根断线的转子。

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