Edge chipping mechanism and failure time prediction on carbide cemented tool during drilling of CFRP/Ti stack
Edge chipping mechanism and failure time prediction on carbide cemented tool during drilling of CFRP/Ti stack
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CFRP/Ti 叠层钻削过程中硬质合金刀具的崩刃机制和失效时间预测
DOI：
10.1007/s00170-017-0017-7
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发表时间：
2017-01
影响因子：
3.4
通讯作者：
Ma Zhenbo
中科院分区：
文献类型：
--
作者：
Wang Ben;Yin Wendian;Wang Minghai;Zheng Yaohui;Li Xiaopeng;Ma Zhenbo
为了研究硬质合金刀具在CFRP/Ti叠层复合材料钻孔过程中的刃崩问题，进行了钻孔实验，并提出了刀具失效模型。分析了推力、钻削温度和刀具磨损情况。建立了刃口崩刃的刀具受力模型和刀具失效模型。在此基础上，建立了崩刃失效时间预测模型。在建立预测模型时考虑了钻削温度、维氏硬度和切削速度等因素。结果表明，粘着磨损对崩刃有很大影响。刀具前刀面的粘着磨损损伤导致前刀面载荷的变化和初始裂纹的产生。在剪应力的作用下，裂纹从前刀面开始，然后扩展到后刀面，导致刀具刃口崩刃。钛合金与硬质合金之间的亲和作用和热残余应力是导致刀具刃口崩刃的两个关键因素。在粘结相内部或在硬质相和粘结相之间的边界处容易发生撕裂。随着钻削温度的升高，硬质合金的硬度会逐渐降低。失效时间的预测结果与实验结果基本一致，验证了预测模型的有效性。
To investigate the edge chipping during drilling of the CFRP/Ti stack with carbide cemented tools, a drilling experiment was carried out and a tool failure model was proposed. Thrust force, drilling temperature, and tool wear were analyzed. A tool stressing model and a tool failure model of edge chipping were constructed respectively. On the basis of these, the prediction model on the edge chipping was established to forecast the failure time. Drilling temperature, Vickers hardness, and cutting speed were considered during the prediction model building. The results demonstrate that adhesive wear has a great influence on the edge chipping. The damage of adhesive wear for tool rake face leads to the load variation on rake face and the initial crack. Under the action of shear stress, the crack starts at rake face and then expands to the flank face, resulting in tool edge chipping. The affinity interaction (between titanium alloy with carbide cemented) and the thermal residual stress are two critical factors for tool edge chipping. Tear easily occurs inside the binding phase or at the boundary between hard phase and binder phase. As the drilling temperature increases, the hardness of the carbide cemented will gradually decrease. The prediction result of failure time is similar to the experimental result, and the effectiveness of the prediction model is verified.
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影响因子：
5
作者：
T. Deng;M. Bingley;M. Bradley;S. R. D. Silva
通讯作者：
T. Deng;M. Bingley;M. Bradley;S. R. D. Silva
DOI：
10.1115/msec2015-9364
发表时间：
2015-06
期刊：
--
影响因子：
--
作者：
Dave Kim;A. Beal;P. Kwon
通讯作者：
Dave Kim;A. Beal;P. Kwon
影响因子：
5
作者：
Xin Wang;P. Kwon;C. Sturtevant;Dave Kim;Jeff Lantrip
通讯作者：
Xin Wang;P. Kwon;C. Sturtevant;Dave Kim;Jeff Lantrip
影响因子：
2.7
作者：
Pengfei Zhang;N. Churi;Z. Pei;C. Treadwell
通讯作者：
Pengfei Zhang;N. Churi;Z. Pei;C. Treadwell
DOI：
10.1007/s00170-016-8512-9
发表时间：
2016-02
期刊：
The International Journal of Advanced Manufacturing Technology
影响因子：
--
作者：
Jinyang Xu;M. El Mansori
通讯作者：
Jinyang Xu;M. El Mansori