Title :
A knowledge-based supervision model for machine tools
Author :
Yoon, Taehwan ; Principe, Jose C.
Author_Institution :
Dept. of Electr. Eng., Florida Univ., Gainesville, FL, USA
Abstract :
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
Keywords :
knowledge based systems; machine tools; manufacturing computer control; cutter damages; empirical knowledge; knowledge-based processing environment; knowledge-based supervision model; machine tools; milling machines; multiprocessor architecture; numeric/symbolic model; physical models; real-time signal processing algorithms; Acoustic sensors; Feature extraction; Force sensors; Machine tools; Monitoring; Real time systems; Semiconductor device measurement; Sensor phenomena and characterization; Signal processing; Signal processing algorithms;
Conference_Titel :
Computer Software and Applications Conference, 1989. COMPSAC 89., Proceedings of the 13th Annual International
Conference_Location :
Orlando, FL
Print_ISBN :
0-8186-1964-3
DOI :
10.1109/CMPSAC.1989.65182
