Aiming at the problem that batch data synchronization in unequal-length batch process monitoring fails to fully exploit local information

this paper proposes a variable grouping dynamic time warping-multiway canonical variate analysis (VGDTW-CVA) algorithm for unequal-length batch process fault detection. First

the mutual information matrix is used to describe the correlation between variables of unequal-length batch process

and all the variables are divided into serval groups based on mutual information matrix. Then use the DTW algorithm to synchronize each variable group separately

and integrate the synchronized variable groups into a complete 3D data set. Finally

MCVA method is utilized to establish dynamic monitoring model for online monitoring of batch production process. The simulation results on the penicillin simulation system show that the VGDTW-MCVA has better monitoring effect for the unequal-length batch production process.