Detecting Potential Risks of Emergency Events in Automated Warehousing Systems

In the unmanned warehousing such complex closed operation scene, various types of materials are stored. In most cases, the scene of the operation process to maintain efficient, stable state operation, but because the scene may be stored in the hazardous materials, and the road connection relationship, hidden cable pipeline complexity, is very likely to occur with the hazardous, proliferation, irreversible damage to the scene of the unexpected events. These emergencies will lead to the original scheduling operation process within the scene is blocked or even forced to terminate, resulting in unmanned warehousing scenarios of operational efficiency decline. Therefore, this paper proposes an unmanned warehousing contingency potential risk state detection algorithm based on GCDN, which can timely detect the potential risk state that occurs before the scene occurs a contingency, and allows the disposal team to dispose of it in advance, fundamentally preventing the occurrence of the contingency.