Data-driven Artificial System of parallel emergency management for petrochemical plant

A data-driven system of parallel emergency management is designed to manage production safety emergencies caused by natural or human-induced disasters in the petrochemical plant, combining with the parallel management theory based on ACP (Artificial Systems, Computational Experiment, and Parallel Execution) approach. Data is acquired by use of techniques including video monitoring and detection, which is the premise of building Artificial System. Based on mass data of the key state variables, Artificial System is designed by using fuzzy expert system and other intelligent modeling algorithms. Finally, the parallel emergency solution is provided for emergency management in one case of ethylene plant, and it can make a great improvement to the emergency management of the plant.