应用PCD刀具铣削砂型的刀具磨损机理和预测模型

doi:10.3901/JME.2018.17.124

机械工程学报 ›› 2018, Vol. 54 ›› Issue (17): 124-132.doi: 10.3901/JME.2018.17.124

• 特邀专栏：智能制造装备 • 上一篇下一篇

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应用PCD刀具铣削砂型的刀具磨损机理和预测模型

单忠德¹, 朱福先^1,2

1. 机械科学研究总院先进成形技术与装备国家重点实验室北京 100044;
2. 江苏理工学院材料工程学院常州 213001

收稿日期:2017-10-08 修回日期:2018-01-19 出版日期:2018-09-05 发布日期:2018-09-05
通讯作者: 单忠德(通信作者),男,1970年出生,博士,研究员,博士研究生导师。主要研究方向为绿色制造工艺与装备、先进成形制造工艺及智能装备。E-mail:shanzd@cam.com.cn
作者简介:朱福先,男,1979年出生,博士研究生,副教授。主要研究方向先进成形制造工艺及智能装备。E-mail:jxzfx@jsut.edu.cn
基金资助:
国家杰出青年科学基金资助项目（51525503）。

Wear Mechanism and Prediction Model of Polycrystalline Diamond Tool in Milling Sand Mould

SHAN Zhongde¹, ZHU Fuxian^1,2

1. State Key Laboratory of Advanced Forming Technology and Equipment, China Academy of Machinery Science Technology, Beijing 100044;
2. School of Materials Engineering, Jiangsu University of Technology, Changzhou 213001

Received:2017-10-08 Revised:2018-01-19 Online:2018-09-05 Published:2018-09-05

摘要/Abstract

摘要： 针对无模铸造成形技术在铸型制作中的优势，基于聚晶金刚石（Polycrystalline diamond，PCD）刀具铣削砂型试验，研究了PCD刀具铣削砂型的磨损机理，构建了刀具磨损率的预测模型。使用扫描电镜观察了PCD刀具刀面磨损带的微观形貌，研究了刀具磨损随加工时间的变化规律和磨损机理。结果表明：在砂型加工过程中，凸起的砂粒对刀具表面的高频刻划和冲击导致刀具表面金刚石颗粒解理断裂和金刚石颗粒间黏结材料被刮除，从而造成金刚石颗粒脱落；刀具中的微观缺陷和砂型中的"硬点"造成刀具微崩刃。基于支持向量机（Support vector machines，SVM）回归分析算法，应用Matlab软件编译了PCD刀具相对加工量的磨损率回归程序，以正交试验结果为训练样本，构建了刀具磨损率预测模型。应用该模型预测了工艺参数对刀具磨损率的影响，为砂型高效加工的刀具磨损控制提供了依据。

关键词: PCD刀具, 磨损机理, 磨损预测模型, 无模铸造, 支持向量机

Abstract: For the advantage of patternless casting technology in mould making, the wear mechanism of PCD tool is studied and the prediction models of wear ratio are built based on the sand mould milling experiments with polycrystalline diamond (PCD) tool. The micro phase morphology of wear zone of PCD tool is observed by scanning electron microscopy, from which the change rule with the processing time and the wear mechanism are studied. The results show that the high frequency scrape and impact of the raised sand particles on the flank during the sand milling process lead to the cleavage fracture of diamond particles and the scraping of the bonding material among the PCD particles in the surface of the tool, which cause the diamond particles to fall off. Furthermore, the microscopic defects in the tool and the "hard spots" in the sand mould cause the cutter micro chipping. Based on support vector machine (SVM) regression analysis algorithm, Matlab is used to compile the regression program of the ratio of wear to milling volume to build the prediction model of wear ratio based on the orthogonal experimental results. The influence of process parameters on tool wear ratio are predicted with the model, which can provide the basis for the wear control of the tool with high efficiency processing sand mould.

Key words: patternless casting, PCD tool, support vector machine (SVM), wear mechanism, wear prediction model

中图分类号:

TH16

单忠德, 朱福先. 应用PCD刀具铣削砂型的刀具磨损机理和预测模型[J]. 机械工程学报, 2018, 54(17): 124-132.

SHAN Zhongde, ZHU Fuxian. Wear Mechanism and Prediction Model of Polycrystalline Diamond Tool in Milling Sand Mould[J]. Journal of Mechanical Engineering, 2018, 54(17): 124-132.

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应用PCD刀具铣削砂型的刀具磨损机理和预测模型

Wear Mechanism and Prediction Model of Polycrystalline Diamond Tool in Milling Sand Mould

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