Development Of Remote Fault Diagnosis Center Of Reaction-Regeneration System Of Fluid Catalytic Cracking

The rapid development of the domestic economy, the constant rising of social demand, increasing stricture of environmental regulations, all have made it more and more important for the petroleum refining industry to maintain a safe, efficient, sustainable and stable production. As the leading part of petroleum refining industry, the safety of FCC production becomes particularly important. As the core of FCC unit, reaction-regeneration system is often an accident-prone part. The development of its fault diagnostic tools is very essential. In this paper, a remote fault diagnosis center of reaction-regeneration system of FCC is developed using VC++ and Access as programming tools, using the network video server to transmit real-time process images via the Internet, combining expert system with fuzzy diagnosis method, against reaction-regeneration systems of three actual devices. This center consists of three modules which are process accounting module, fault diagnosis module and auxiliary function module.First, the development status of FCC is introduced and several typical reaction-regeneration system processes are described. The concept, classification of diagnosis technology and typical diagnosis methods are presented. The application in today’s chemical industry is introduced later.Then, the processes of three actual devices this paper involved are described. The theory of expert system and fuzzy reasoning are described thoroughly. For one particular set of device, seven kinds of typical failure of the reaction-regeneration system are summarized consulting process experts. They are associated with nineteen kinds of fault symptoms and related process parameters forming seven fault diagnosis rules.Finally, based on demand analysis of the center, functional design and detailed design process are described thoroughly. For the actual device, the implementation process is introduced in the order of three modules with the corresponding screenshot interfaces given.The result shows that the system is able to accumulate expert knowledge for fault diagnosis. On the basis of ensuring real-time fault diagnosis, this system works well with the cost greatly reduced. It has a strong practical value.