Data-driven anomaly monitoring methods for multimode processes: overview and perspectives

Industrial processes usually need to function under multiple conditions because of changes in raw materials, setting points, and the external environment. Anomaly monitoring methods for multimode processes effectively ensure the safe operation of industrial systems, and they are a research hotspot of current process monitoring technology. Herein, anomaly monitoring methods for multimode processes are summarized, including overall modeling, adaptive modeling, hybrid modeling, and multi-model modeling methods. Research progress of multimode stationary processes and multimode nonstationary processes is then reviewed, and the advantages and disadvantages of these methods are analyzed. Finally, considering the characteristics of the practical industrial systems, the open problems in this field and the future development direction are summarized.