Research on the causes of earthwork foundation pit collapse based on Fault tree and Bayesian network

Abstract

With the rapid development of the construction industry, construction safety accidents frequently occur. Among these accidents, earthwork foundation pit collapse, as a subset of construction accidents, often causes significant casualties and economic losses due to the self-weight of collapsed materials and the extensive area affected. The purpose of this study is to identify the causes of construction safety and collapse accidents and their relationships in order to facilitate effective supervision and prevention during the construction process. Firstly, text mining is conducted on historical construction safety accident reports using R language tools and the TF-IDF algorithm to obtain keywords related to accident causative factors. Then the risk factors are analyzed to establish the basic event, intermediate event, and top event of the accident, to construct a fault tree of casualties caused by earthwork foundation pit collapse accidents and analyze the structural importance of risk factors. Finally, the fault tree is transformed to a Bayesian network using image mapping and numerical mapping to enable the analysis of node sensitivity and the prediction of top event probability to provide scientific reference for safety accident prediction and prevention.