A hardware implementation of hierarchical Neural Networks for real-time quality control systems in industrial applications

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 de...

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Hauptverfasser: Baratta, Daniela, Bo, Gian Marco, Caviglia, Daniele D., Valle, Maurizio, Canepa, Giovanni, Parenti, Riccardo, Penno, Carla
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung: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.
ISSN:0302-9743
1611-3349
DOI:10.1007/BFb0020319