The invention relates to an elevator fault early-warning method based on the Internet of Things technology and a coupled graph neural network. The elevator fault early-warning method based on the Internet of Things technology and the coupled graph neural network comprises the following steps: a, acquiring data in an elevator car in real time, and transmitting the collected data to a cloud; b, preprocessing the data, and carrying out feature extraction; and c, utilizing a pre-trained coupled graph neural network model for analyzing the data acquired in real time at the cloud, and carrying out early-warning on elevator faults in advance. According to the invention, early-warning for the elevator faults is realized in advance through the coupled neural network model, and therefore the elevator fault early-warning method has higher accuracy and precision compared with a traditional mode under the conditions that data are unbalanced and fault data are few.

    本发明涉及一种基于物联网技术和耦合图神经网络的电梯故障预警方法,包括以下步骤:a、实时采集电梯轿厢内的数据,并将采集的数据传输至云端;b、对数据进行预处理,并进行特征提取;c、利用预先训练的耦合图神经网络模型在云端对实时采集的数据进行分析,并对电梯故障进行提前预警。本发明利用耦合神经网络模型实现电梯故障的提前预警,这样,在数据不平衡,故障数据较少的情况下,比传统方式具有更高的准度和精度。


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    Title :

    Elevator fault early-warning method based on Internet of Things technology and coupled graph neural network


    Additional title:

    基于物联网技术和耦合图神经网络的电梯故障预警方法


    Contributors:
    ZHU SHUAI (author) / HUANG ZHONGPING (author) / LI ZHUANG (author) / JIA CHUNHUA (author) / WU LEILEI (author) / CAI WEIWEI (author)

    Publication date :

    2021-05-07


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    B66B Aufzüge , ELEVATORS




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