摘要(英) |
This paper proposes a new framework for the AI discrimination of present machine, which is based on the vibration variation of the machine known as decay coefficient. By calculating the machine’s decay coefficient, we can determine the current state and behavior of the machine, and calculate the machine’s condition according to the different state and behavior. Since the calculation of the decay coefficient is based on the variation of the vibration rather than the total value of the vibration, the calculation model can be applied to different machines.
The aforementioned theory is verified by simulated and actual data. The effect of a single variable on the decay coefficient is tested by simulating the change of sampling rate, decay rate and vibration period, and applied to the actual motor operation. However, after the data is calculated by its decay coefficient, the five stages of travel with different behaviors are visible to the naked eye. Therefore, this paper not only provides a method to identify the vibration status of the machine, but also makes the vibration data more readable and meaningful through this method. As such, the limit of the vibration period between 2~180 seconds and the sensor sampling period will not exceed 750ms for any machine. |
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