In　order　to　recognize　the　abnormal　pattern　of　control　chart　to　enhance　the　automation　level　of　quality　management　and　promote　E-management　of　manufacturing　enterprise,　in　this　paper　the　quality　data　generated　by　Monte　Carlo　simulation　is　coded　through　linear　transformation　to　improve　the　character　of　the　patterns,　and　then　the　two　kinds　of　neural　networks　are　applied　to　recognize　the　control　chart　patterns.　Through　analyzing　the　test　result,　the　application　strategy　of　control　chart　recognition　is　proposed.