Systems monitoring based on dynamic classification with SVDD

In this paper, we address the problem of system monitoring and faults detection using classification-based approach. The main is to follow online evolutions which can occur on the diagnosed system in the course of time. In data classification, the functioning modes are represented with a set of similar patterns called classes. These classes change their intrinsic characteristics and they are likely to be dynamic. Indeed, over the time, new data may be incorporated into the informative model and some others can be likewise discarded. In this paradigm, we propose a dynamic classification method based on modified version of the Support Vector Domain Description (SVDD). Thanks to added insertion/removal procedure, the employed SVDD supports evolving data and maintains dynamically the descriptive model. The proposed approach is applied afterwards on a hydraulic system consisting of three interconnected tanks.