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An improved electromechanical spectral signature for monitoring gear-based systems driven by an induction machine

机译:一种改进的机电频谱特征,用于监视由感应电机驱动的基于齿轮的系统

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Even under normal operating conditions, Gear-based systems naturally generate four particular frequencies: the input and output mechanical speeds as well as the gear meshing and the hunting tooth frequencies. Thereby, through amplitude monitoring of these components and their harmonics, the gear state can be easily monitored and successfully assessed. Based on this fact, this paper discusses the fitness of the vibration data and the load torque (mechanical signature) to detect these frequencies. Furthermore, when the system is driven by an induction machine these frequencies will affect the stator currents. Thus, the appropriateness of the spectral analyzing techniques based such amounts as alternate for monitoring gear-based systems will also be discussed. Moreover, for improving the sensitivity detection of these particular frequencies an original preprocessing technique is proposed and its effectiveness is evaluated for spectral analysis of mechanical as well as electrical experimental data.
机译:即使在正常运行条件下,基于齿轮的系统也自然会产生四个特定的频率:输入和输出机械速度以及齿轮啮合和棘轮频率。由此,通过对这些部件及其谐波的振幅监控,可以容易地监控并成功评估齿轮状态。基于这一事实,本文讨论了振动数据的适应性和用于检测这些频率的负载转矩(机械特征)。此外,当系统由感应电机驱动时,这些频率将影响定子电流。因此,还将讨论基于频谱分析技术的适当性,例如用于监视基于齿轮的系统的替代量。此外,为了提高对这些特定频率的灵敏度检测,提出了一种原始的预处理技术,并对其有效性进行了机械和电气实验数据的频谱分析。

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