In order to ensure environment safety of underground mine

a minimum-distance clustering fusion algorithm is put forward to overcome measurement error and system error of sensor

and achieve data-level fusion of underground environment information

compared with other mentioned references

fusion precision is improved.On this basis

probabilistic neural network classifier is designed to carry on decision-level fusion on data-level fusion result and achieve grade safety partition of underground mine environment.Practice shows that the two-step fusion methods are feasible and effective in underground mine environment monitoring system.