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首页> 外文期刊>International Journal of Computer Integrated Manufacturing >Prediction, monitoring and control of surface roughness in high-torque milling machine operations
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Prediction, monitoring and control of surface roughness in high-torque milling machine operations

机译:高扭矩铣刨机运行中表面粗糙度的预测,监控和控制

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The development and testing of an application that will predict, monitor and control surface roughness are described. It comprises three modules for off-line roughness prediction, surface roughness monitoring and surface roughness control, and is especially designed for high-torque, high-power milling operations, which are widely used nowadays in the manufacture of wind turbine components. The application is tested in a milling machine with a high working volume. Due to the highly complex phenomena that generate surface roughness and the large number of factors that interact during the cutting process, models to calculate the average surface roughness parameter (Ra) are based on artificial neural networks (ANN) as they are especially suitable for modelling complex relationships between inputs and outputs.View full textDownload full textKeywordsmilling, surface roughness, artificial neural networks, process monitoring, cutting parametersRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/0951192X.2012.684717
机译:描述了预测,监视和控制表面粗糙度的应用程序的开发和测试。它包括用于离线粗糙度预测,表面粗糙度监测和表面粗糙度控制的三个模块,并且特别设计用于高扭矩,高功率的铣削操作,这些操作如今已广泛用于制造风力涡轮机部件。该应用程序在具有高工作量的铣床中进行了测试。由于产生表面粗糙度的高度复杂现象以及在切削过程中相互作用的众多因素,用于计算平均表面粗糙度参数(Ra)的模型基于人工神经网络(ANN),因为它们特别适合建模输入和输出之间的复杂关系。查看全文下载全文关键字铣削,表面粗糙度,人工神经网络,过程监控,切削参数相关var addthis_config = {ui_cobrand:“ Taylor&Francis Online”,services_compact:“ citeulike,netvibes,twitter,twitter,technorati,delicious ,linkedin,facebook,stumbleupon,digg,google,更多”,发布号:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/0951192X.2012.684717

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