A Non-intrusive Intelligent Monitoring Method for Elevator State

Abstract

A non-intrusive intelligent monitoring method for elevater state was established. In this method, the acceleration signal is initialized by Weiszfeld algorithm, and the acceleration signal is decomposed into vertical component and horizontal component. The dynamic characteristics of elevator are estimated by Kalman filter. The vibration analysis of horizontal component is carried out and the baseline of normal operation is established. The sensor is calibrated automatically according to the operation characteristics of elevator. According to the unscented Kalman filter fused with simultaneous localization and mapping (SLAM), the sensor information is coupled to track the real-time position of elevator. The effectiveness and robustness of the method were verified in actual operation. The problem of position error accumulation was basically solved without the installation of beacon. This method has low cost and strong universality, and has certain practical significance for promoting the on-demand maintenance of elevator.

Keywords

• real time r condition monitor
• information fusion
• unscented kalman filter
• sensor
• auto calibration
• non-intrusive
• elevator state