Research on Heat Treatment Control Technology of Machining Parts

Response to the call of the development of industry and agriculture of heat treatment technology, higher request is put forward. It has become the key technology that how can the temperature be controlled at good heating temperature. RBF neural network predictor optimized by the Adaptive fuzzy C - means clustering algorithm and BP neural network controller device are designed in the paper in order to overcome the traditional RBF network control problems. The output of the controller is better stabilized in a given value through the reasonable initialization of the three parameters of the RBF neural network predictor. Simulation shows that the fuzzy optimization network has better control effect to the original network control. It can not only save energy, but improve the efficiency of industrial and agricultural production.