Research on Risk Management of Gas Safety based on Big Data

In order to solve the shortcomings of coal mine enterprises in gas safety management, according to the big data theory, a safety management analysis method is proposed. First, the behavioral safety theory is used to classify the causes of gas hazards. Then use the HDFS to storage the unsafe behavior and unsafe physical state that found by behavior observers, and finally use the MapReduce-based parallel FP-growth algorithm to find out the repeated and dangerous unsafe behaviors in daily operations, and form a Hadoop-based gas behavior security management model. The experimental results show that the model has certain practical reference value for the targeted implementation of gas safety management in coal mine enterprises. Through the unsafe behavior and physical state found, the shortcomings in safety management will be discover, it will help enterprises improve the safety management system. So it has certain prospects for improving the safety production culture of coal mine enterprises and reducing the occurrence of gas accidents.