The progressive networking of industrial plants provides an increasing amount of data that is available in operation. It is usually no longer possible for humans to oversee this amount of information and to draw knowledge from it. With the development of increasingly powerful processors, machine learning methods have come into focus for this application. In this project, the existing procedures, which are mostly based on physical models, are to be complemented in order to enable comprehensive monitoring. The focus is on nonlinear systems that are difficult to describe using physical models.
