Sensor Fusion of Acoustic Emission and Cutting Force for Tool Wear Monitoring during Composite Materials Machining

Sensor fusion for tool wear monitoring during machining of different plastic matrix fibre reinforced composite materials was carried out through the detection and analysis of cutting force and acoustic emission signals. Orthogonal cutting tests were performed using two different tool states: fresh and worn. Decision making on tool condition was achieved through a supervised neural network approach, using diverse back-propagation feed-forward neural network configurations, trained and testing with sensor fusion feature vectors.