Abstract: A precise mass balance model is the basis of data rectification.However, the streams of material in industrial processes change dynamically due to frequently occurring scheduling events.A new method was proposed to update the mass balance model in view of application.Bayesian network was used, its structure was selected according to expert’s experiences and its variables were trained by historical data.Consequently, scheduling events were identified based on diagnostic function of Bayesian network, and an updated simplified model was finally established.In this way, the feasibility of data rectification was enhanced.And simulation results demonstrated the efficiency of the proposed method.