Prediction Of Elevator Accident Types Based On Radial Basis Function Neural Network

Since the reform and opening up,China's urbanization has been advancing,high-rise buildings have been emerging,and the use of elevators has been growing.With the continuous increase of elevator input,elevator accidents have never been reduced,and once the elevator accidents occur,often accompanied by personal casualties.There are many factors leading to elevator accidents.In the safety management of elevators,especially the unsafe behavior of people is difficult to control,and there are many uncertainties.Therefore,although the production level of elevators is constantly improving,elevator accidents are still common,seriously threatening the life safety of the urban population.Studying the occurrence law of elevator accidents,analyzing the causes of elevator accidents and predicting the types of elevator accidents are effective means to prevent the occurrence of elevator accidents and reduce property losses.With the continuous development of big data technology,it is of great significance for elevator safety management to make full use of elevator accident data to prevent the occurrence of elevator accidents.By fully mining,statistics and analysis of the recorded elevator accident data provided by the Inspection and Inspection Institute of Chinese Special Equipment,this paper expounds the occurrence law of elevator accident with time,link,rated load and rated speed.Using RBF neural network,six indexes of elevator accident occurrence month,elevator accident occurrence time(hour),elevator accident occurrence link,rated load of elevator,rated speed of elevator operation and the cause of elevator accident are determined as input parameters.The prediction model of elevator accident type is established,and the accuracy is verified by the data of test group.The results show that compared with other methods,the accident type prediction model based on RBF neural network method has good accuracy,can accurately predict the type of elevator accidents,and plays a positive role in enterprise elevator safety management.