Double-layer data model-driven plant-level chemical process monitoring method

The invention discloses a double-layer data model-driven plant-level chemical process monitoring method. Relationships between sub-modules are modeled by constructing a double-layer data statistical analysis model on the basis of blocking modeling, so that a plant-level process is globally monitored. Compared with the conventional other plant-level process monitoring methods, the method has the advantages that each unit of the process can be monitored in each sub-module, relationship information between the sub-modules of the plant-level process can be effectively combined, and the whole plant-level process is globally monitored by utilizing a second-layer data model, so that the monitoring performance of the plant-level chemical process is greatly improved, and the industrial automation of the plant-level process can be favorably expanded and implemented.