一种非侵入式电梯运行状态智能监测方法  

A Non-intrusive Intelligent Monitoring Method for Elevator State

作　　者：杨昱 王千山 李雪鹏 许增 李海芳 YANG Yu;WANG Qianshan;LI Xuepeng;XU Zeng;LI Haifang(College of Information and Computer, Taiyuan University of Technology, Jinzhong 030600, China)

机构地区：[1]太原理工大学信息与计算机学院,山西晋中030600

出　　处：《太原理工大学学报》2021年第6期920-927,共8页Journal of Taiyuan University of Technology

基　　金：国家自然科学基金资助项目(61976150);赛尔网络下一代互联网技术创新项目资助(NGII20181206);山西省重点研发计划项目资助(201803D31038)。

摘　　要：设计了一种非侵入式电梯运行状态智能监测方法。该方法通过Weiszfeld算法初始化重力加速度,将加速度信号分解为竖直分量和水平分量,使用卡尔曼滤波估计电梯的动力学特征,对水平分量进行振动分析并建立正常运行的基线,结合电梯的运行特性对传感器进行自动矫正。采用融合同步定位与建图技术(SLAM)的无迹卡尔曼滤波算法进行传感器信息耦合,跟踪电梯的实时位置。在实际运行中验证了该方法的有效性和鲁棒性,在不安装信标的前提下基本解决了电梯位置误差积累的问题。设计的非侵入式电梯状态智能监测方法成本低、普适性强,对推进电梯的按需维保有一定的现实意义。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.

关 键 词：实时状态监测 信息融合 无迹卡尔曼滤波 传感器 自动矫正 非侵入式 电梯运行 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]