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LSTM-based Anomal Motor Vibration Detection

机译:基于LSTM的ANOMAL电机振动检测

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摘要

Recently, drones are being used in various work sites and the scope of use thereof is gradually expanding. However, since there is no special abnormality detection system to predict the fall of a drone, it is always exposed to the risk of a fall. Therefore, in this paper, we proposed an algorithm that predicts abnormal behavior through Long Short Term Memory (LSTM) based on the motor vibration data collected from the drone to predict the abnormal motion of the drone.
机译:最近,在各种工作场所使用无人机,并且其范围逐渐扩展。 然而,由于没有特殊的异常检测系统来预测无人机的堕落,因此总是暴露于跌倒的风险。 因此,在本文中,我们提出了一种基于从无人机收集的电动机振动数据来预测通过长短短期存储器(LSTM)来预测异常行为的算法,以预测无人机的异常运动。

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