Force model of high-manganese steel drilling based on artificial neural network

摘要：

The drilling of hard-to-cut high manganese steel materials is a difficulty in the field of machining. Research method which has been commonly used is experimental method. This method has time-wasting and high-cost disadvantages. In this paper, adopting error back neural network technology and using Matlab and C language programming method, neural network prediction model of drilling force and torque is established based on limited training data. Its comparison with the experimental data, the model prediction error is within 5％. Effective prediction and simulation has been achieved on the force and torque of the high manganese steel drilling.

关键词： Artificial neural network drilling force model high-manganese steel

作者: Yang Liang Xu Li

作者单位: School of Mechanical Engineering Dalian Jiaotong University Dalian , CHN School of Mechanical Engineering Dalian Jiaotong University Dalian, CHN

会议类型: 国际会议

会议名称: 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

会议地点: 厦门

会议语种:英文

页码: 253-257

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）