This article independently designed an elevator experimental platform and introduced digital twin technology to address the limitations of IoT monitoring elevators,thus establishing a digital twin elevator braking performance prediction and evaluation system.By deploying sensors to monitor the multi-dimensional data of the elevator itself,and dynamically collecting real-time data from the elevator based on an intelligent gateway,a high-fidelity model of the elevator has been built,achieving bidirectional mapping and dynamic interaction between the physical entities and twins of the elevator;Based on the elevator prediction model and combined with the PCA-RF-LSTM time series data regression algorithm,timely analysis and fault prediction of elevator performance have been made;Building a decision-making system in elevator application services,utilizing multidimensional data fusion analysis of elevator physical and virtual entities,as well as developing analysis technologies such as fault diagnosis,remote operation and maintenance,and accident tracing,this paper attempts to predict the fault and safety evaluation of elevator braking performance.
关键词
物联网/数字孪生/预测模型/安全评价
Key words
Internet of Things/Digital twin/Predictive model/Safety evaluation
维普
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