In order to solve the problem that the error evaluation delay and the size and roundness of workpiece can not meet the processing requirements at the same time in online measurement. First this paper proposes an online fusion control method for the size and roundness error of workpiece, which can not only improve the processing efficiency, but also improve the consistency of workpiece quality. Then, the Long Short-Term Memory(LSTM) is used to predict the workpiece information of online measurement, and the error is calibrated according to the predicted value. The LSTM is used to predict the workpiece information in real time, and the process parameters are adjusted in time when the prediction value is out of the theoretical boundary to avoid error accumulation. Finallyr the online grinding measurement experiment based on the LSTM is designed and carried out, and the relationship between the dimension of input tensor and the prediction accuracy is analyzed through the experimental results. The results show that the LSTM can accurately predict the grinding size sequence and roundness sequence, and has good universality. The small batch machining is carried out according to the experimental results. Statistical analysis shows that the grinding accuracy is significantly improved by using the fusion prediction and calibration method.