摘要
针对电梯运行过程中状态异常情况的不确定性问题,研究并实现了一种基于嵌入式系统的电梯运行状态监测方案。通过使用内部已集成了卡尔曼滤波的九轴加速度传感器来获取实时加速度状态,利用平滑滤波的方式对加速度数据进行二次平滑处理,通过建立状态模型的方法将电梯的运行状态模拟出来,利用LoRa技术将实时状态数据上传至服务器,服务器经过处理后显示出来。试验表明,该设计能将电梯的上行、下行、停止及停层状态良好的模拟出来,停层高度误差在0.28%~1.14%,对电梯维护控制系统(MCS)具有一定的现实意义。
Aiming at the uncertainty of abnormal status in elevator operation,a kind of elevator operation status monitoring scheme based on embedded system is studied and implemented.By using a nine-axis acceleration sensor with Kalman filter integrated internally to obtain real-time acceleration state;the second smoothing processing of acceleration data is carried out by means of smoothing filtering;by establishing the state model to simulate the elevator's running state;using LoRa technology and real-time state data is uploaded to the server,which is displayed after processing.The test shows that the design can simulate the elevator's up-going,down-going,stop-floor and stop-floor conditions,and the height error of the stop-floor is between 0.28%and 1.14%,which has certain practical significance for the elevator maintenance control system(MCS).
作者
郝真鸣
葛卫华
郝晋渊
李兵兵
孙丹丹
冉宁
Hao Zhenming;Ge Weihua;Hao Jinyuan;Li Bingbing;Sun Dandan;Ran Ning(College of Electronic Informational Engineering,Hebei University,Baoding071002,China;HBU/UCLAN School of Media,Communication and Creative Industries,Hebei University,Baoding071002,China)
出处
《电子测量与仪器学报》
CSCD
北大核心
2019年第8期187-193,共7页
Journal of Electronic Measurement and Instrumentation
基金
河北省引进留学人员项目(C20190319)
河北省自然科学基金(F2019201088)
国家自然科学基金(61903119)资助项目
