For the prevention and control of gas explosion disaster risk in the coal mine, the risk index system was established to patter recognition of gas explosion. Interval linear data normalization method was put forward to reduce the information loss in the process of computing by using the risk patter cut-off of indexes. The risk index was weighted with interval data of multiple comparison method. According to dynamic time warping (DTW), the 5 weighted reference sequence was constructed by using the indexes risk patter cut-off which was normalized, and the weighted sequence was constructed to be identified for the unknown risk patter sample. And then, disaster risk pattern recognition model was established based on DTW which obtaining risk pattern by the shortest dynamic time warping distance of the weighted reference sequence and to be identified weighted sequence. The pattern recognition example was gave that based on 14 indicators of gas explosion disaster risk, and the risk identification results were in good agreement with the actual situation. Results show that, DTW model of risk patter recognition has good identification ability for explosion disaster risk model, which will be a new way to study the pre-control of gas explosion disaster risk in coal mines.