Abstract
In this paper we propose a method for complex process visualization using a continuous mapping from the space of measurements or features of the process onto a continuous visualization space. To construct this mapping we suggest a continuous extension of the self organizing map using a kernel regression approach. We also describe a method for continuous condition monitoring based on the proposed continous mapping. We finally illustrate the proposed method with experimental data from an induction motor working in different fault conditions.
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Zhuo Meng and Yoh-Han Pao. Visualization and self-organization of multidimensional data thorough equalized ortogonal mapping. IEEE Transactions on Neural Networks, 11(4):1031–1038, July 2000.
David J.H. Wilson and George W. Irwin. RBF principal manifolds for process monitoring. IEEE Transactions on Neural Networks, 10(6):1424–1434, November 1999.
Teuvo Kohonen, Erkki Oja, Olli Simula, Ari Visa, and Jari Kangas. Engineering applications of the self-organizing map. Proceedings of the IEEE, 84(10):1358–1384, october 1996.
Esa Alhoniemi, Jaakko Hollmén, Olli Simula, and Juha Vesanto. Process monitoring and modeling using the self-organizing map. Integrated Computer Aided Engineering, 6(1):3–14, 1999.
Jianchang Mao and Anil K. Jain. Artificial neural networks for feature extraction and multivariate data projection. IEEE Transactions on Neural Networks, 6(2):296–316, March 1995.
Teuvo Kohonen. Self-Organizing Maps. Springer-Verlag, 1995.
Donald F. Specht. A general regression neural network. IEEE Transactions on Neural Networks, 2(6):568–576, November 1991.
Simon Haykin. Neural Networks, a Comprehensive Foundation. Prentice-Hall, Inc., 1999.
C. M. Bishop, M. Svensen, and C. K. I. Williams. GTM: a principled alternative to the self-organizing map. In C. von der Malsburg, W. von Seelen, J. C. Vorbruggen, and B. Sendhoff, editors, Artificial Neural Networks—ICANN 96. 1996 International Conference Proceedings, pages 165–70. Springer-Verlag, Berlin, Germany, 1996.
Helge Ritter. Parametrized self-organizing maps. In S. Gielen and B. Kappen, editors, Proc. ICANN’93, International Conference on Artificial Neural Networks,Amsterdam, pages 568–577, Berlin, 1993. Springer Verlag.
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Díaz, I., Diez, A., Vega, A.A.C. (2001). Complex Process Visualization through Continuous Feature Maps Using Radial Basis Functions. In: Dorffner, G., Bischof, H., Hornik, K. (eds) Artificial Neural Networks — ICANN 2001. ICANN 2001. Lecture Notes in Computer Science, vol 2130. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44668-0_62
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DOI: https://doi.org/10.1007/3-540-44668-0_62
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