RBF approach for trajectory interpolation in self-organizing map based condition monitoring

Self-organizing map trajectory interpolation using radial basis functions is proposed for process condition monitoring. Self-organizing maps are a powerful means to visualize the state of a process. However, a quantization process takes place when input vectors are mapped onto the grid (output) space. The discrete nature of the output space gives rise to a considerable loss of information which is particularly harmful to detect incipient faults which are often revealed by drifts or slight changes in the state trajectory. A continuous projection from the input space onto the SOM grid space using RBF-based interpolation is proposed and tested with experimental data