Process State and Progress Visualization Using Self-Organizing Map
The self-organizing map (SOM)  is used in data analysis for resolving and visualizing nonlinear relationships in complex data. This paper presents an application of the SOM for depicting state and progress of a real-time process. A self-organizing map is used as a visual regression model for estimating the state configuration and progress of an observation in process data. The proposed technique is used for examining full-scope nuclear power plant simulator data. One aim is to depict only the most relevant information of the process so that interpretating process behaviour would become easier for plant operators. In our experiments, the method was able to detect a leakage situation in an early stage and it was possible to observe how the system changed its state as time went on.
KeywordsTraining Data Process Variable Component Plane Reactor Shutdown Boiling Water Reactor
Unable to display preview. Download preview PDF.
- Simula, O., Vesanto, J., Vasara, P., Helminen, R.R.: Self-organizing map in industry analysis. In: Industrial Applications of Neural Networks, pp. 87–112. CRC Press, Boca Raton (1999)Google Scholar
- Alhoniemi, E., Hollmén, J., Simula, O., Vesanto, J.: Process monitoring and modeling using the self-organizing map. Integrated Computer-Aided Engineering 6, 3–14 (1999)Google Scholar
- Sirola, M., Lampi, G., Parviainen, J.: SOM based decision support in failure management. International Scientific Journal of Computing 3, 124–130 (2005)Google Scholar
- Paulsen, J.L.: Design of Process Displays based on Risk Analysis Techniques. PhD thesis, The Technical University of Denmark and Risø National Laboratory, Roskilde, Denmark (2004)Google Scholar
- Pershagen, B.: Light Water Reactor Safety. Pergamon Press, Stockholm (1989)Google Scholar
- Vesanto, J.: Data Exploration Process Based on the Self-Organizing Map. PhD thesis, Helsinki University of Technology, Espoo, Finland (2002)Google Scholar