A review on risk management driven by big data in coal mine accidents
In order to clarify the research progress of intelligent risk management in coal mines,the research status of data-driven coal mine safety risk management models was comprehensively analyzed.The prediction methods and analysis models for coal mine safety risk assessment were also reviewed.Firstly,the intelligent risk management was defined,and the scope of analysis was determined by searching relevant literature.Then,the research status,existing problems and development trend of accident big data were reviewed from three aspects:data-driven analysis method,coal mine safety risk assessment model and coal mine big data prediction and early warning platform.The results show that the theory and application framework of data-driven risk analysis in the field of coal mine safety has been basically formed,but it still cannot meet the needs of risk assessment and emergency management.In the application of early warning platform,a unified and general basic framework of big data analysis platform for coal mine safety production has been formed,but its application and promotion in production practice are far from enough.In the future,it is necessary to construct the comprehensive risk assessment model to study the risk of coal mining,starting from improving data quality and integrating dynamic and static multi-source data.Besides,the application of data-driven analysis in production practice should also be strengthened.These works can promote the transformation of coal mine safety risk management mode from empiricism to data-driven,and realize the informatization and intelligence of coal mine safety risk management.
万方数据
维普
