The use of Kohonen self-organizing maps in process monitoring

Process monitoring and fault diagnosis have been studied widely in recent years, and the number of industrial applications with encouraging results has grown rapidly. In the case of complex processes a computer aided monitoring enhances operators' possibilities to run the process economically. In this paper a fault diagnosis system is described and some application results from the Outokumpu Harjavalta smelter are discussed. The system monitors process states using neural networks (Kohonen self-organizing maps, SOM) in conjunction with heuristic rules, which are also used to detect equipment malfunctions.