Because industrial process is often under changes, it is necessary to reconcile the measurement of the dynamic process. There are many problems in the present dynamic data reconciliation methods, such as low calculation efficiency, difficulty of treatment for the reconciliation of input variables. Based on the analysis of the characteristic of dynamic data reconciliation, an integral approach is presented which integrates finite clement collocation method, filtering technique and robust method. The finite element collocation method can reduce the amount of discrete model constrained equations to decrease the problem complexity without any loss of measurement information. The filtering technique can eliminate random errors in input variables effectively and no lag or signal distortion will be introduced. Monte Carlo method is used to test the efficiency of the robust method for gross error detection. The calculation results show that the integral approach can improve the calculation efficiency greatly and can deal with the gross error of abnormal type properly.