Tool condition monitoring in cutting processes using hybrid neural network based sensor fusion strategy

This paper presents a study on tool condition monitoring in metal cutting processes using hybrid neural networks based sensor fusion strategy. Various sensing techniques are combined and used to select suitable monitoring indices. Several models are proposed to establish the relationship between tool conditions and monitoring indices. The proposed approach is built progressively by examining monitoring indices from various aspects and making monitoring decision step by step. Compared to others monitoring schemes, the results indicate a significant improvement and a good reliability in identifying the various tool conditions regardless of the variation in cutting parameters.