基于大数据闸门启闭机健康状态分析方法的研究

Research on Health Status Analysis Method of Gate Hoist Based on Big Data

为提高闸门启闭机智能监控系统对设备运行状态分析的能力和效率,提出了一种基于大数据闸门启闭机的健康状态分析新方法,先依据闸门启闭机运行监测的实时数据和历史数据,分析设备的运行强度、故障情况、状态参数及特征量权重;再将启闭机的状态特征在某一时期内监测得到的正常值作为标准值或健康值(区间),建立相对评价标准,通过比较实际值与标准值,找出启闭机的运行状况特征异常点;并在此基础上建立了评价指标体系,采用层次分析法定量分析了各指标权重,给出了启闭机的健康状态模糊综合评价方法,增强了闸门启闭机智能监控系统的设备运行状态分析功能。

In order to improve the ability and efficiency of an intelligent monitoring system for analyzing the operating status of a gate hoist, a new health status analysis method of a gate hoist based on big data was proposed. Firstly, according to the real-time data and historical data of a gate hoist operation monitoring, the operation intensity, fault conditions, status parameters and state-characteristic weights of the equipment were analyzed. Then, a relative evaluation standard was established based on the normal value of the same state characteristic from monitoring the same hoist in a certain period as the standard value or healthy value(interval). The abnormal values of the state characteristics could be found by comparing the actual monitoring values and the standard values. Finally, an evaluation index system was constructed, and the weight of each index was quantitatively analyzed by using analytic hierarchy process. A fuzzy comprehensive evaluation method of the hoist health status was given. The equipment operation status analysis function of a gate hoist intelligent monitoring system was enhanced.