Feature Extraction for a Conditioning Monitoring System in a Bottling Process.

We present an approach for feature extraction in the context of condition monitoring of a bottling process. A special focus lies on the characterisation and evaluation of liquid textures. The approach will feed into a sensor and information fusion system to monitor a bottling process. Requirements like real-time capabilities, data reduction and resource limitations necessitate a fusion approach which capture physical effects of different sensors, extract appropriate features and combine them into one state for the complete filling process. Special attention is paid to the feature extraction of the visual sensor signals to monitor the filling level, the amount of foam and the degree of turbulence in the liquid.