We try to give a quantitative and global discrimination function by studying mb/MS data using Fisher method that is a kind of pattern recognition methods. The reliability of the function is also analyzed. The results show that this criterion works well and has a global feature, which can be used as first-level filtering criterions in event identifi- cation. The quantitative and linear discrimination function makes it possible to identify events automatically and achieve the goal to react the events quickly and effectively. We try to give a quantitative and global discrimination function by studying mb / MS data using Fisher method that is a kind of pattern recognition methods. The reliability of the function is also analyzed. The results show that this criterion works well and has a global feature , which can be used as first-level filtering criterions in event identifi- cation. The quantitative and linear discrimination function makes it possible to identify events automatically and achieve the goal to react the events quickly and effectively.