Development of a rough set-based fuzzy neural network for online monitoring of microdrilling

A rough set-based fuzzy neural network has been developed in this study for online monitoring of microdrilling. By applying the rough set theory, we obtained reduced rule sets from data samples as the fuzzy neural network rules. Then the neural network model was designed based on the reduced rule sets. The number of the network fuzzy rules was reduced. Shortcomings in high-dimensional fuzzy neural network, such as huge structure, were overcome. Data that were sampled in real-time from the spindle motor three-phase currents were processed by the trained network to monitor the microdrill wear online. The experiment results show that if the threshold is properly selected, the microdrill breakage will be effectively prevented by the monitoring.