Abstract
The corrosion of metals and the paint adhesion on metals is a result of the superposition of complex reactions on the surface, which depend on surface oxide thickness, its porosity and chemical composition. By means of diffuse reflectance spectroscopy and evaluation of the spectra by a Kohonen self-organizing map, it is possible to predict the future corrosion behaviour of low carbon steel. Combining a Kohonen map and an interpolation method in the output layer allows to determine the layer thickness of conversion layers on aluminium from their interference spectra. This offers a fast, reliable and on-line applicable tool to calculate the thickness of transparent surface layers on aluminium or other metals even in the range below 100 nm.
Keywords
- Radial Basis Function
- Diffuse Reflectance Spectrum
- Radial Basis Function Network
- Interference Spectrum
- Kohonen Network
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 1995 Springer-Verlag London Limited
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Kessler, W., Kessler, R.W. (1995). Kohonen Network as a Classifier and Predictor for the Qualification of Metal-Oxide-Surfaces. In: Hunt, K.J., Irwin, G.R., Warwick, K. (eds) Neural Network Engineering in Dynamic Control Systems. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-1-4471-3066-6_10
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