| 在线支持向量机在数控铣床刀具磨损预测建模中的应用 |
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| 引用本文： | 李雪梅,丁力行,陈嘉澍. 在线支持向量机在数控铣床刀具磨损预测建模中的应用[J]. 现代制造工程, 2011, 0(7) |
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| 作者姓名： | 李雪梅 丁力行 陈嘉澍 |
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| 作者单位： | 仲恺农业工程学院机电工程学院,广州,510225 |
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| 摘 要： | 刀具磨损的自动监测是现代制造技术的关键技术之一,是保证自动化加工顺利进行的前提之一.在实际生产当中,对刀具磨损的检测,不能停机检测而只能采取在线的间接监测方法.提出一种基于在线支持向量机的数控铣床刀具磨损的预测方法.结果表明,所提方法具有参数调整时间快、泛化能力强的优点,可以比较准确地监控刀具磨损.
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| 关 键 词： | 在线支持向量机 刀具磨损 预测建模 |
The application of online support vector machine to tool wear prediction modeling of digital control milling machine |
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| LI Xue-mei,DING Li-xing,CHEN Jia-shu. The application of online support vector machine to tool wear prediction modeling of digital control milling machine[J]. Modern Manufacturing Engineering, 2011, 0(7) |
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| Authors: | LI Xue-mei DING Li-xing CHEN Jia-shu |
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| Affiliation: | LI Xue-mei,DING Li-xing,CHEN Jia-shu(School of Mechanical and Electrical Engineering,Zhongkai University of Agriculture and Engineering,Guangzhou 510225,China) |
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| Abstract: | The automatic monitoring of tool wear is one of the key technologies of modern manufacturing technology as well as one premise to ensure the automatic processing to go on well.In actual production,the detection of tool wear should employ indirect online monitoring instead of stop detection.Presents a tool wear prediction method of digital control milling machine based on online support vector machine.The result shows that the presented method with quick parameter adjustment time and good generalization abil... |
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| Keywords: | online support vector machine tool wear prediction modeling |
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