Study of synthesis identification in the cutting process with a fuzzy neural network

With the development of intelligent manufacturing systems, the requirements of the stability and reliability are increasingly more important, especially in the NC cutting process. The method of traditional and single working condition monitoring cannot be fully satisfied. In this paper, an artificial neural network with fuzzy logic, signal processing and other techniques is composed, and a method of synthesis identification and diagnosis of the working condition with a model of a compound fuzzy inference neural network has been tested and has yielded good result, so that the stability and reliability of on-line monitoring and diagnosis is rationally expected to be realized.