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Drilling Temperature Model of High-Manganese Steel Based on BP Neural Network

The drilling of hard-to-cut high manganese steel materials is a difficulty in the field of machining. Research method for drilling temperature which has been commonly used is experimental method. The method has long-time and the high-cost drawbacks. Adopting error back neural network technology and using Matlab and C language programming method, in this paper neural network prediction model of drilling temperature is established on the base of limited training data. In comparison with the experimental temperature data, the result shows that the model prediction error is within 5%. Effective prediction and simulation has been achieved on the temperature of the high manganese steel drilling.