[1]李小水,詹友基,贾敏忠.采用BP神经网络预测钻削灰铸铁的切削能耗[J].福建工程学院学报,2017,15(06):528-534.[doi:10.3969/j.issn.1672-4348.2017.06.005]
　Li Xiaoshui,Zhan Youji,Jia Minzhong.Prediction of cutting energy consumption in drilling gray iron by BP neural network[J].Journal of FuJian University of Technology,2017,15(06):528-534.[doi:10.3969/j.issn.1672-4348.2017.06.005]
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采用BP神经网络预测钻削灰铸铁的切削能耗()
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《福建工程学院学报》[ISSN:2097-3853/CN:35-1351/Z]

卷:
第15卷
期数:
2017年06期
页码:
528-534
栏目:
出版日期:
2017-12-25

文章信息/Info

Title:
Prediction of cutting energy consumption in drilling gray iron by BP neural network
作者:
李小水; 詹友基; 贾敏忠
福建工程学院机械与汽车工程学院
Author(s):
Li Xiaoshui;  Zhan Youji;  Jia Minzhong
School of Mechanical and Automotive Engineering, Fujian University of Technology
关键词:
BP神经网络;  钻削;  切削能耗;  三元回归
Keywords:
BP neural network;  drilling;  cutting energy consumption;  ternary regression
分类号:
TG5
DOI:
10.3969/j.issn.1672-4348.2017.06.005
文献标志码:
A
摘要:
采用BP神经网络建立灰铸铁钻削过程的切削能耗与切削参数之间的关系模型，并建立三元线性回归预测模型，对两种预测模型预测结果的准确性进行比对分析。考虑切削参数之间的交互作用建立三维表面图，对比分析钻削过程的切削能耗与切削参数的变化规律。结果表明，通过训练的BP神经网络在预测切削能耗方面具有更好的准确性，对钻削过程的切削能耗预测研究具有一定应用价值和指导意义。生产实际中，从减小切削能耗的角度分析，在满足加工质量的前提下，钻削灰铸铁时应优先选择较大的进给量和切削速度。
Abstract:
BP neural network was used to establish the relationship model of the cutting energy consumption and the cutting parameters in the drilling of gray cast iron. The ternary linear regression model was established to compare the accuracy of the prediction results of the two prediction models. The interactions among the cutting parameters were taken into consideration in establishing the three-dimensional surface graph, and the varied cutting energy consumptions and cutting parameters in the drilling process were compared and analyzed. Results show that the trained BP neural network has better accuracy in predicting the energy consumption of cutting, which has certain application value and provides guidance for the cutting energy consumption prediction of the drilling process. Under the premise of guaranteeing the processing quality, priority should be given to choosing a larger feed and cutting speed in order to reduce the cutting energy consumption when drilling gray cast iron.

参考文献/References:

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更新日期/Last Update: 2017-12-25