Safety risk analysis of hoisting construction of prefabricated buildings based on Dynamic Bayesian Network
To address the issues of multiple risk factors,high uncertainty,and dynamic changes in risk state during the construction of prefabricated building hoisting,a dynamic analysis method for safety risk during prefabricated building hoisting construction based on Dynamic Bayesian Networks is proposed.Firstly,according to the construction characteristics of prefabricated building hoisting and accident cause theory,15 safety risk analysis indexes of hoisting are proposed from four aspects:human,material,environment,and management.The safety risk index system of hoisting construction of a prefabricated building is constructed.Then,the time dimension is introduced to establish a Dynamic Bayesian Network model,the probability of network nodes is quantified by fuzzy theory and expert scoring method,and the conditional probability is modified by combining the Leaky Noisy-or Gate extended model.Finally,the bidirectional inference function of the dynamic Bayesian network is used to analyze the dynamic risk of the safety risk of the hoisting of the prefabricated building.The time series change curve of safety risk in hoisting construction of a certain prefabricated building is obtained by case analysis,and the key risk factors leading to hoisting accidents are obtained by reverse reasoning.The results show that the probability of a lifting accident occurring at the initial moment is 0.313,and the probability of hoisting risk occurring increases significantly with the increase of construction time.Through the comparison of the posterior probability,it is found that the assembly building hoisting mainly has a greater risk in 2 aspects:human and material.The hoisting safety supervisory staff configuration,on-site construction safety management level,prefabricated components quality level,and lifting equipment operation condition are the key factors leading to the occurrence of hoisting construction safety risk.The research results can provide a new way to analyze and effectively control the safety risk of prefabricated building hoisting construction.
NETL
NSTL
万方数据
维普
