The invention relates to an elevator comprehensive fault early warning method based on multi-dimensional Internet of Things atlas big data. The method comprises the following steps that S1, the multi-dimensional big data related to elevator operation is collected based on the multi-dimensional Internet of Things; S2, a data map network of an elevator is constructed based on the multi-dimensional big data fusion; S3, each node in the data atlas network is subjected to dimension reduction processing, and the data atlas network subjected to the dimension reduction processing is subjected to specification processing to generate a training model; S4, the multidimensional big data is taken as input, a fault type is taken as output, and the training model is subjected to offline training to acquire the training model with the optimal judgment result as a prediction model; and S5, operation data of the current operation elevator is acquired and is used as input to carry out fault prediction onthe elevator through the prediction model and output risk early warning. According to the elevator comprehensive fault early warning method, for the high-risk elevator, the detection and the maintenance can be carried out in advance before a comprehensive fault occurs, and preventive measures are taken to reduce the elevator fault to occur, so that casualties are reduced.
本发明涉及一种基于多维物联网图谱大数据的电梯综合故障预警方法,包括:S1.基于多维物联网采集与电梯运行相关的多维大数据;S2.基于所述多维大数据融合构建一个所述电梯的数据图谱网络;S3.对所述数据图谱网络中各节点进行降维处理,对降维处理后的所述数据图谱网络进行规约处理生成训练模型;S4.以所述多维大数据为输入,以故障类型为输出,对所述训练模型进行离线训练,获取判断结果最佳的所述训练模型为预测模型;S5.获取当前运行电梯的运行数据,并作为输入以所述预测模型对所述电梯进行故障预测,并输出风险预警。可以针对高风险的电梯,在综合性故障发生之前,做到提前检测维修,防患于未然,以减少电梯故障发生,从而减少人员伤亡。
Elevator comprehensive fault early warning method based on multi-dimensional Internet of Things atlas big data
一种基于多维物联网图谱大数据的电梯综合故障预警方法
2020-07-10
Patent
Electronic Resource
Chinese
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