Research On Key Risk Identification Of Coal Mine Based On Complex Network

Coal energy has always been an important part of our country's energy development,and it will provide a very strong guarantee for the economic development of our country to ensure the safe development of the coal industry.It has been the focus research direction for domestic scholars to find out key risk factors in coal mine accidents by the analysis of coal mine accidents.At present,scholars at home and abroad have obtained many achievements in safety technology,method model,system construction,risk assessment and so on.However,the identification of risk factors before coal mine accidents and the research on statistical investigations of coal mine accidents are still in the primary stage.The paper extracts risk factors leading to coal mine accidents through the statistical study of coal mine accidents in Shanxi Province and constructs the matrix of coal mine risk factors.Then the complex network model is established.One of the innovations of this paper is the use of complex network model to analyze the risk factors of coal mines.The paper first introduces the development history and research status of accident causation theory in coal mine.Then,the paper researches coal mine accidents statistically based on the basic theory of complex network and relevant statistical characteristics,and identifies the risk factors that are likely to cause coal mine accidents.The risk factor matrix of the coal mines is constructed based on the identified risk factors.The paper constructs complex network models of risk factors according to the types of coal mine accidents,and the overall complex network model of coal mines is also constructed.Finally,the research obtains key risk factors of different accident types by analyzing the complex network models.At the same time,the paper analyzes the overall complex network model of risk factors,identifies key risk factors from the different statistical characteristics and provides related measures to prevent accidents according to key risk factors.