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CFRP制孔过程中轴向力自适应控制仿真及实验研究

Simulation and Experimental Study on Axial Force Adaptive Control in CFRP Hole-making Process
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摘要 钻削轴向力的大小和碳纤维增强树脂基复合材料(Carbon fiberrein-forced plastic, CFRP)制孔质量的好坏密切相关,为合理调控轴向力来减少制孔缺陷,开展了CFRP制孔过程中轴向力的自适应控制仿真及实验研究。首先,开展CFRP钻削试验,对轴向力及制孔质量进行了定量研究。其次,根据CFRP钻入、稳定钻削及钻出阶段不同加工特性建立了轴向力三阶段模型。最后,基于模糊逻辑及所建模型进行了轴向力自适应控制仿真及实验研究。结果表明:利用模糊逻辑控制算法结合CFRP加工特性,对制孔过程中轴向力进行智能调控是可行的;此外,根据仿真信息调控轴向力可有效降低制孔缺陷、提升孔壁质量。该研究为大厚度碳纤维复合材料制孔过程中轴向力的智能调控提供了新的思路。 The axial force of drilling is closely related to the quality of CFRP hole-making.In order to reasonably control the axial force to reduce hole-making defects,the simulation and experimental study on the axial force adaptive control in CFRP hole-making process were carried out.Firstly,the axial force and hole-making quality were quantitatively studied through CFRP drilling experiments.Secondly,a three-stage axial force model was established by considering the different machining characteristics of CFRP in the drilling entry stage,steady drilling stage and drilling out stage.Finally,the simulation and experimental study on the axial force adaptive control was carried out based on the three-stage model and fuzzy logic.The results show that it is feasible to control the axial force intelligently by using the fuzzy logic control algorithm and combining with CFRP processing characteristics.In addition,adjusting the axial force according to the simulation information can effectively reduce the hole-making defects and improve the hole wall quality.It provides a new idea for intelligent control of axial force in hole-making process of large thickness carbon fiber composites.
作者 詹迪雷 李鹏南 邱新义 牛秋林 李树健 ZHAN Dilei;LI Pengnan;QIU Xinyi;NIU Qiulin;LI Shujian(School of Mechanical Engineering,Hunan University of Science and Technology,Xiangtan 411201,Hu'nan,China)
出处 《机械科学与技术》 CSCD 北大核心 2024年第3期474-482,共9页 Mechanical Science and Technology for Aerospace Engineering
基金 国家自然科学基金项目(51775184,51975208) 国家自然科学青年科学基金项目(52105442)。
关键词 CFRP制孔 分层 仿真 模糊控制 CFRP hole-making delamination simulation fuzzy control
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