Prakash Rangasamy, Krishnaraj Vijayan, Zitoune Redouane, Sheikh-Ahmad Jamal
PSG College of Technology, Coimbatore 641004, India.
University Paul Sabatier, Toulouse 31300, France.
Materials (Basel). 2016 Sep 26;9(10):798. doi: 10.3390/ma9100798.
Carbon fiber reinforced polymers (CFRPs) have found wide-ranging applications in numerous industrial fields such as aerospace, automotive, and shipping industries due to their excellent mechanical properties that lead to enhanced functional performance. In this paper, an experimental study on edge trimming of CFRP was done with various cutting conditions and different geometry of tools such as helical-, fluted-, and burr-type tools. The investigation involves the measurement of cutting forces for the different machining conditions and its effect on the surface quality of the trimmed edges. The modern cutting tools (router tools or burr tools) selected for machining CFRPs, have complex geometries in cutting edges and surfaces, and therefore a traditional method of direct tool wear evaluation is not applicable. An acoustic emission (AE) sensing was employed for on-line monitoring of the performance of router tools to determine the relationship between AE signal and length of machining for different kinds of geometry of tools. The investigation showed that the router tool with a flat cutting edge has better performance by generating lower cutting force and better surface finish with no delamination on trimmed edges. The mathematical modeling for the prediction of cutting forces was also done using Artificial Neural Network and Regression Analysis.
碳纤维增强聚合物(CFRP)因其优异的机械性能可提升功能性能,已在众多工业领域得到广泛应用,如航空航天、汽车和航运业。本文针对CFRP的边缘修整进行了实验研究,采用了各种切削条件以及不同几何形状的刀具,如螺旋刀具、带槽刀具和毛刺型刀具。该研究包括测量不同加工条件下的切削力及其对修整边缘表面质量的影响。用于加工CFRP的现代切削刀具(铣刀或毛刺刀具),其切削刃和表面具有复杂的几何形状,因此传统的直接刀具磨损评估方法并不适用。采用声发射(AE)传感对铣刀的性能进行在线监测,以确定不同几何形状刀具的AE信号与加工长度之间的关系。研究表明,具有平切削刃的铣刀性能更佳,切削力更低,表面光洁度更好,修整边缘无分层现象。还利用人工神经网络和回归分析对切削力预测进行了数学建模。