Study on tool wear identifying based on Fuzzy Neural Network

To detect gradual tool wear state online, this paper presents the methods of Wavelet Fuzzy Neural Network (WFNN), Regression Neural Network (RNN) and Sample Classification Fuzzy Neural Network (SC-FNN) by detecting cutting force, motor power of machine tool and AE signal respectively. Although these methods can be implemented, it is difficult to obtain comprehensive information of machining and exact value of tool wear when using single method of intelligent modeling and signal detecting. In order to solve this problem, fuzzy inference technique is adopted to fuse the recognized data. Emulation experiment is carried out by using Matlab software and this method is verified to be feasible. Experimental result indicates that by applying fuzzy data fusion, an exact tool wear forecast can be got rapidly.