Monitoring Chemical Accidents in Industrial Complexes Using Tower-Installed Infrared System for Remote Chemical Detection and Long-Range Video Surveillance System

Abstract

Chemical industrial complexes are extensive, complex structures with large-scale chemical facilities where large quantities of various chemical substances are handled. Detection equipment must be installed in high locations to monitor these industrial complexes and detect chemical accidents from a distance. In previous studies, individual monitoring equipment was temporarily installed on the ground, on a rooftop, or on a vehicle to detect chemical accidents from a distance. In this study, however, the industrial complex chemical accident monitoring system was developed by combining different technologies and was installed on a tower. For the Yeosu National Industrial Complex (which functioned as a test bed), 70m-high steel towers were built. Additionally, an infrared system for remote chemical detection (SIGIS-2, Bruker) and a long-range video surveillance system (TORUSS-LR2000, Globalsystems) were installed at the top of steel towers to monitor the entire industrial complex. The target substances to be monitored in real time by the infrared system for remote chemical detection were selected, and the monitoring sections were classified to enable each piece of equipment to distinguish the scanned areas. To improve the accuracy of the detection results, the information about the actual handled substances and respective facilities of the sites in the industrial complex was inserted into the database of the system and then connected to the sections. During the three-month test operation, various chemical substances (including 1,3-butadiene, methanol, methylamine, ethyl acetate, ammonia, and vinyl chloride) were detected at each section in 20,034 cases, and the detection results were consistent with the inserted actual information. The accumulated detection data shows that the detection frequency of a specific chemical substance was high in each section. This can be used as a basis for modifying the threshold of the anomaly detection model, thereby improving the accuracy of the system. Therefore, this system can detect and evaluate the leakage of chemical substances and the occurrence of fires or smoke through large-scale scans 24 h per day. Furthermore, it can be used for the early detection of and effective responses to chemical accidents in industrial complexes.