Title:causal Analysis Of Falling Accidents In Building Construction At Heights Based On Fault Tree And Bayesian Network.

In the process of urban development,the construction industry has always been one of the pillar industries in my country.However,in large-scale construction activities,the frequent safety accidents in construction projects have caused a large number of personal accidents and property losses,which has adversely affected social stability and economic growth.Through the analysis of construction engineering accidents,different types of accidents can be found in their own unique cause mechanisms.According to the annual accident statistics,the highest frequency of occurrence is the accidental accident,and the degree of casualties caused by personnel are the most serious.Therefore,in-depth discussing the cause mechanism of the accident and the corresponding security control strategy is of great significance to reduce the number of accidents in the high place and improve the level of construction safety management in my country.This article uses the faulty tree and Bayesian network method to analyze the cause of the fall accident,mainly divided into the following four parts:(1)Elapse the concept of a high fall accident,as well as related theories of accidents,fault trees,and Bayesian networks,laying the theoretical foundation for the following.The analysis of the survey report of construction accidents from 311 has formed four perspectives of "people-material-tube-ring",and an index system is constructed.(2)Taking a high place to fall as the top-level incident.In the four dimensions of personnel,object factors,management factors,and environmental factors,the subdivisions are 8 intermediate events and 25 detailed indicators to build and analyze the accident of the accident.Failure tree model.(3)Use the corresponding relationship between the two models to transform.With the help of Netica software,build the Bayesian network model and analyze,and compare the analysis results of the two models.The results show that the main cause of the secondary indicators is object factors;in the fourth-level indicators,"habitual violations","excessive force","physical imbalance","safety device failure or incomplete","no security protection measures are not good","no security protection measures are not good" Implementation "," inadequate security education ",and" poor on-site supervision "are the main causes.(4)Taking the "5.23" height accident as an example,Bayesian network based on the builtin height falling accident,Bayesian network,started a fault diagnosis,and inspected the parts that could cause accidents in order.Assign the effective conditions of the test results to the Bayesian network,and update the model data at the same time.After 6 failure diagnosis,the cause of the occurrence effectively avoided the accidental falling accident.The diagnostic results are consistent with the model prediction results,which verify the feasibility of the failure diagnosis of the Bayesian network model failure diagnosis of the height fall accident.