Machining　status　monitoring　technique　by　multi-sensors　can　acquire　and　analyze　the　machining　process　information　to　implement　abnormity　diagnosis　and　fault　warning.　Statistical　quality　control　technique　is　normally　used　to　distinguish　abnormal　fluctuations　from　normal　fluctuations　through　statistical　method.　In　this　paper　by　comparing　the　advantages　and　disadvantages　of　the　two　methods,　the　necessity　and　feasibility　of　integration　and　fusion　is　introduced.　Then　an　approach　that　integrates　multi-sensors　status　monitoring　and　statistical　process　control　based　on　artificial　intelligent　technique,　internet　technique　and　database　technique　is　brought　forward.　Based　on　virtual　instrument　technique　the　author　developed　the　machining　quality　assurance　system　-　MoniSysOnline,　which　has　been　used　to　monitoring　the　grinding　machining　process.　By　analyzing　the　quality　data　and　AE　signal　information　of　wheel　dressing　process　the　reason　of　machining　quality　fluctuation　has　been　obtained.　The　experiment　result　indicates　that　the　approach　is　suitable　for　the　status　monitoring　and　analyzing　of　machining　process.