Abstract
In this paper a real-time quality control system for steel industry is presented. The system implements the surface defect classification of steel strips in flat rolled mills in real-time. To achieve reliable classification accuracy the system implements a MLP_based hierarchical neural network. A dedicated hardware implementation has been designed and manufactured to meet the realtime constraints of the application. An ASIC neural chip directly implements the neural network and it is integrated on a custom high speed co-processor board, compatible with many commercial carrier board. The entire system has been tested with data coming from the plant.
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© 1997 Springer-Verlag Berlin Heidelberg
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Baratta, D. et al. (1997). A hardware implementation of hierarchical Neural Networks for real-time quality control systems in industrial applications. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020319
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DOI: https://doi.org/10.1007/BFb0020319
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