Design Of Construction Elevator Health Evaluation And Remote Monitoring System Based On IGA-BPNN

As the main manned and cargo mechanical equipment in the construction of high-rise buildings,the construction hoist directly determines the efficiency and safety of high-rise building construction.With the advent of the Internet of Things and the "Industry 4.0" era,the need for healthy and intelligent management of construction elevators is becoming increasingly urgent.Therefore,a universal remote monitoring system is designed for various types of construction elevators distributed in different places.And further conduct in-depth data mining on the data collected by the monitoring platform.By establishing an effective health evaluation model,evaluating the operating status of equipment,and giving scientific guidance on equipment maintenance and updating,it has important theoretical and practical significance for ensuring the safety of high-rise buildings.This project constructed a scientific and complete elevator health evaluation index system.On this basis,a construction elevator health evaluation model based on Improved Genetic Algorithm Back Propagation Neural Network(IGA-BPNN)was proposed.A cross-platform remote monitoring system compatible with multiple industrial communication protocols was designed,and based on the data collected by the remote monitoring platform,the IGA-BPNN evaluation model was trained and verified.The research contents of this topic are as follows:(1)Construct a construction elevator health evaluation index system based on the fusion of multiple algorithms.Starting from the man-machine-environment system engineering,40 health evaluation index factors were selected.Each index was quantitatively analyzed based on Relief F,Pearson and FAHP algorithms.12 health evaluation indexes with larger weights were selected as the input of the IGA-BPNN model.The health level of the elevator was divided based on the triangular fuzzy number.(2)Construct a construction hoist health evaluation model based on IGA-BPNN.Build a health evaluation model based on BPNN,analyze the optimization performance of particle swarm optimization(PSO),wolf pack algorithm(WPA),and genetic algorithm(GA)for BP parameters,and select the GA algorithm with the best optimization effect to optimize BPNN.And considering the shortcomings of GA algorithm that is easy to fall into local optimum when dealing with multi-peak problems,it is further optimized to build a construction elevator health evaluation model based on IGA-BPNN.Through example analysis,the convergence speed of the IGA-BPNN algorithm is faster,and the accuracy rate of health level prediction can reach 97%,which is 6 percentage points higher than that of GA-BPNN.(3)Design a multi-protocol integration cross-platform information transmission system.Develop and design programmable DTU,realize normal communication between DTU and hardware equipment and information transmission system,realize Modbus protocol,Profibus protocol,Profinet protocol and the conversion between RS485 bus protocol and MQTT protocol,and solve the problem of different construction elevator control hardware equipment and Information exchange issues between remote monitoring systems.(4)Design and construction elevator remote monitoring platform.The remote monitoring platform for construction elevators is designed based on IOT technology to realize the functions of real-time data collection,data storage,information traceability and health evaluation prediction analysis of different types of construction elevator control systems and data addresses.