Multivariate statistical process monitoring (SPM)has gained tremendous attention in both academic and industrial circles over the past two decades.Most of the existing statistical monitoring algorithms are established on the assumption that the monitored industrial processes work under single operating mode.However

in order to meet the demands of markets

multimode has become a significant feature of modern chemical industry.To meet the monitoring demands of multimode processes

a global monitoring strategy based on locality preserving projection (LPP)and Gaussian mixture model (GMM)is proposed.By integrating probability indices of each operating modes

the online monitoring is guaranteed to be continuous and uninterrupted.The efficiency and effectiveness of the novel monitoring strategy is verified though the Tennessee Eastman (TE)simulation platform.