切削数据预测分析方法研究
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摘要
数据预测分析是切削数据库的重要功能之一,文中采用回归分析预测法、有限元分析方法与神经网络预测方法建立了切削力预测模型。通过切削实验验证了模型的准确性,并对不同模型的数据来源特点与预测精度进行了分析研究。获得的结果可以为预测模型的建立与预测方法的选择提供理论支撑。
Data predictive analysis is one of the important functions of cutting databases. The regression force prediction model, finite element analysis method and neural network prediction method are used to establish the cutting force prediction model. The accuracy of the model is verified by cutting experiments, and the data source characteristics and prediction accuracy of different models are analyzed. The obtained results can provide theoretical support for the establishment of prediction models and the selection of prediction methods.
Data predictive analysis is one of the important functions of cutting databases. The regression force prediction model, finite element analysis method and neural network prediction method are used to establish the cutting force prediction model. The accuracy of the model is verified by cutting experiments, and the data source characteristics and prediction accuracy of different models are analyzed. The obtained results can provide theoretical support for the establishment of prediction models and the selection of prediction methods.
引文
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[5]员天佑,刘金,李兴兰.数据挖掘技术在超精密光学制造中的应用[J].制造业自动化,2014(21):154-156.
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[10]王振旗,姚晓斌.基于GA-BP算法的光伏系统发电功率预测[J].计算机系统应用,2016,25(2):227-230.
[2] AN S, CHENG Y N, LIU X L, et al. Research on Cutter Location Optimization of Tapered Ball End Mill Finish Flank Milling Ruled Surface Blade[J]. Key Engineering Materials,2013, 589-590:421-426.
[3]宫爱红,陈和平,阮景奎,等.汽车模具高速铣削工艺参数优化及数据库系统的研究与开发[J].机床与液压,2007,35(1):196-198.
[4]李铁钢,范智广,王宛山.基于数据挖掘的切削参数优化[J].组合机床与自动化加工技术,2012(1):36-39.
[5]员天佑,刘金,李兴兰.数据挖掘技术在超精密光学制造中的应用[J].制造业自动化,2014(21):154-156.
[6]王雅轩,顼聪.数据挖掘技术的综述[J].电子技术与软件工程,2015(8):204-205.
[7]刘春艳,凌建春,寇林元,等.GA-BP神经网络与BP神经网络性能比较[J].中国卫生统计,2013, 30(2):173-176,181.
[8]边霞,米良.遗传算法理论及其应用研究进展[J].计算机应用研究,2010,27(7):2425-2429,2434.
[9]戴健伟,吉华,杨岗,等.基于GA_BP算法的化工设备设计人工时预测[J].计算机集成制造系统,2013,19(7):1665-1675.
[10]王振旗,姚晓斌.基于GA-BP算法的光伏系统发电功率预测[J].计算机系统应用,2016,25(2):227-230.