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Non-invasive Method for Elevator’s Movement Monitoring Based on MEMS Sensor and Kalman Filter

机译:基于MEMS传感器和卡尔曼滤波的电梯运动监测无创方法。

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Elevator has been indispensable in modern cities, yet a great number of elevator-related accidents have caused considerable harm to people's welfare. In response to the situation, this paper proposes a non-invasive method for elevator's movement monitoring using MEMS sensor and Kalman filter. Specifically, the method could automatically determine elevator's status and use Kalman filter to yield accurate estimation of elevator's displacement, especially short range displacement, without intervening elevator's operation. The method could potentially be used in a considerable range of scenarios, such as automatic mechanical anomaly detection and monitoring of daily or weekly usage pattern for power conservation and information services.
机译:电梯在现代城市中是必不可少的,但是与电梯相关的大量事故却对人们的福利造成了相当大的伤害。针对这种情况,本文提出了一种采用MEMS传感器和卡尔曼滤波器的无创方法来监测电梯的运动。具体地,该方法可以自动确定电梯的状态并且使用卡尔曼滤波器来产生对电梯的位移,特别是短程位移的准确估计,而无需干预电梯的操作。该方法可能会在相当多的场景中使用,例如自动机械异常检测和监视每日或每周使用模式的节电和信息服务。

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