Research on Cause of Coal Face Accident Based on Topic Model Mining
Fanqiang Meng, Chunxia Li · Social Science Research Frontiers · 2022
As the first production site of coal, mining working face is the place where coal mine accidents occur frequently. In order to avoid or reduce the occurrence of accidents, it is necessary to eliminate and discover the hidden danger of accidents in mining face in time. However, in the past, the cause of accidents mainly adopts the method of qualitative analysis, and lacks the effective analysis model of the cause of accidents, so that the potential value of a large number of hidden danger data of accidents has not been applied. Therefore, the LDA topic mining algorithm is used to build the accident cause topic mining model, and the Perplexity index is used to determine the best number of topics, and the semantic network graph is used to analyze the internal relationship between the hidden dangers of accidents, which directly reflects the main accident cause and the correlation between the cause factors of coal mining face. Taking 18925 accident hidden danger data of a mine in Shandong Province from August 2013 to September 2019 as an example, the topic of accident causes was extracted by mining the topic model, and the semantic network diagram was drawn. The social network analysis method was applied to analyze the association relationship between the factors of accident hidden danger. The results show that management defects, unsafe behavior of personnel, unsafe state of equipment and unsafe state of environment are the main factors leading to coal face accidents, and their interaction leads to the occurrence of accidents.