基于数据挖掘的电梯振动数据异常监控系统设计

Design of Elevator Vibration Data Abnormal Monitoring System Based on Data Mining

针对已有的电梯振动数据无法实时在线采集、处理的问题,利用数据挖掘技术,设计了电梯振动数据异常监控系统。该系统搭建电梯振动数据采集、分析系统框架,对发现电梯在运行过程中的异常振动数据进行模块化设计,通过挖掘电梯振动相关数据的最大频繁项,找出电梯各项数据的潜在联系。因此,电梯振动数据异常监控系统能够实时在线发现电梯的异常振动数据,有效分析电梯振动产生的原因,并提出相应的解决方案。

In view of the problem that the existing elevator vibration data can not be collected and processed online in real time,this paper uses data mining technology to design the elevator vibration data abnormal monitoring system.The system builds the framework of the elevator vibration data acquisition and analysis system,and modularizes the abnormal vibration data found during the operation of the elevator.In addition,by mining the most frequent items of elevator vibration related data,find out the potential connection of elevator data.Therefore,the elevator vibration data abnormal monitoring system can find the abnormal vibration data of the elevator on-line in real time,can effectively analyze the causes of the elevator vibration,and put forward the corresponding solutions.