A knowledge-based supervision model for machine tools
The knowledge-based supervision system described is intended to detect cutter damages in milling machines, using x-axis and y-axis displacement signals. The model hierarchically integrates real-time signal processing algorithms in a knowledge-based processing environment where rules and objects coexist. A deeply coupled, numeric/symbolic model is developed. It incorporates physical models and empirical knowledge. It is implemented in a multiprocessor architecture.<<ETX>>