Safety accident analysis of power transmission and substation projects based on association rule mining

To achieve the sustainable development goals (SDGs) of power transmission and substation project construction, statistical analysis was used to provide an outline of safety accidents, the 4M1E method was applied for sorting out and analyzing the risk factors, and the Apriori algorithm was carried out for exploring the intrinsic interaction among risk factors based on association rule mining. The results showed that the safety accidents that happen in the construction of power transmission and substation projects were not much frequent, but deadly; the process of foundation construction and high fall was the most accident-prone process and injury type respectively. In addition, human behaviors were the foremost factors leading to accidents, and there was a strong correlation among the risk factors of low project management level, lack of safety awareness, and poor risk identification ability. For improving the security situation, measures should be taken for controlling human factors, performing flexible management, and strengthening safety training. In further research, more detailed and diversified accident reports and case data should be analyzed, and more consideration should be put on the weighted risk factor analysis to obtain more comprehensive and objective safety accident analysis results for power transmission and substation projects. This study highlights the risks in power transmission and substation project construction and introduces a novel method for better analyzing the intrinsic interaction among risk factors, which provides theoretical support for related departments to conduct sustainable safety management.