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Microcontroller Realization of an Induction Motors Fault Detection Method based on FFT and Statistics of Fractional Moments

机译:微控制器实现了基于FFT和统计分数时刻的统计故障检测方法

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Induction Motors (IM) are the most widely used motors in industry. Although this type of machines is very reliable, different faults may occur. It is extremely important to detect faults at the earliest stages to reduce financial and energy losses and to overcome catastrophic accidents. Monitoring of mechanical vibrations and electrical currents are widely applied for that purpose. Recently, an effective method for fault detection and identification combining Fast Fourier Transform (FFT) and Statistics of Fractional Moments (SFM), thereby called FFT+SFM, was proposed by some of the authors. This paper shows how the FFT+SFM method can be implemented in microcontroller-based systems for real-time condition monitoring of IM. The method is optimized with respect to microcontroller features and hence it’s implemented on a microcontroller. The optimized method is implemented by a C-code algorithm that is run on a microcontroller from the STM32F722 series by STMicroelectronics. The execution time and results of each algorithm iteration are measured to show the efficiency and effectiveness of the proposed algorithm. Results prove that the realization of the FFT+SFM method can be used in real-time condition monitoring systems of IM.
机译:感应电动机(IM)是工业中最广泛使用的电机。虽然这种类型的机器非常可靠,但可能发生不同的故障。在最早的阶段检测故障是非常重要的,以减少金融和能源损失,并克服灾难性事故。为此目的广泛地应用机械振动和电流监测。最近,一些作者提出了一种有效的故障检测和识别方法,以及分数矩阵(SFM)的统计数据,从而称为FFT + SFM。本文显示了如何在基于微控制器的系统中实现FFT + SFM方法,以实现IM的实时条件监控。该方法针对微控制器特征进行了优化,因此它在微控制器上实现。优化方法由C代码算法实现,该算法在STMicroelectronics的STM32F722系列上的微控制器上运行。测量每个算法迭代的执行时间和结果以显示所提出的算法的效率和有效性。结果证明了FFT + SFM方法的实现可用于IM的实时状态监测系统。

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