Intelligent tool condition monitoring in milling operation
One of the most important features of the modern machining system in an `unmanned` factory is to change tools that have been subjected to wear and damage. An integrated system composed of multi-sensors, signal processing device and intelligent decision making plans is a necessary requirement for automatic manufacturing process. An intelligent tool wear monitoring system for milling operation will be introduced in this report. The system is equipped with four kinds of sensors, signal transforming and collecting apparatus and microcomputer. A unique ANN (artificial neural network) driven fuzzy pattern recognition algorithm has been developed from this research. It can fuse the information from multiple sensors and has strong learning and noise suppression ability. This lead to successful tool wear classification under a range of machining conditions.
- Research Organization:
- Southampton Inst., Systems Engineering Faculty (United Kingdom)
- OSTI ID:
- 649572
- Report Number(s):
- AD-A-347671/XAB; TRN: 82430380
- Resource Relation:
- Other Information: PBD: 1998
- Country of Publication:
- United States
- Language:
- English
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