location: Current position: Home >> Scientific Research >> Paper Publications

基于径向基函数神经网络的CFRP切削力预测

Hits:

Date of Publication:2022-10-10

Journal:复合材料学报

Affiliation of Author(s):机械工程学院

Issue:3

Page Number:516-524

ISSN No.:1000-3851

Abstract:In machining of carbon fiber reinforced polymer (CFRP), the matrix phase is easy to fail due to the excessive cutting force, which extends to the underneath of machining surface and forms damage rapidly. For the precise prediction and control of cutting force, we established an artificial neural network cutting force model based on the experimental cutting force data to predict the cutting force change rule in machining CFRP under different fiber orientations, cutting depths and tool angles. Orthogonal cutting experiments on CFRP unidirectional laminate of typical fiber orientation with different tool angles and cutting parameters were conducted to verify the predicting model, and the predicting precision is up to 85%. Combined with the online microscopic prediction results of chip forming process, it is concluded that the fiber orientation is the primary factor affecting the cutting forces of CFRP, as varies from 0° to 135°, chip formation ways include the crushing-dominated failure type and bending failure type; the cutting force firstly decreases and then increases as the fiber orientation angle increases, and is maximum at 135°; the cutting force increases generally as cutting depth increases. © 2016, BUAA Culture Media Group Ltd. All right reserved.

Note:新增回溯数据

Pre One:基于彩色编码的副油箱风洞模型位姿测量方法

Next One:基于径向基函数神经网络的碳纤维增强树脂基复合材料切削力预测