基于径向基函数神经网络的CFRP切削力预测

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碳纤维增强树脂基复合材料(CFRP)加工中基体相极易因切削力过大而破坏,并迅速扩展至加工表面以下而形成损伤。为了准确预测其切削力并加以控制,基于实验切削力数据建立了人工神经网络切削力模型,预测了不同纤维角度、切削深度和刀具角度下加工CFRP的切削力变化规律,并完成了不同刀具角度及切削参数下典型纤维角度CFRP单向板的直角切削实验,对预测模型进行验证,其预测精度可达85%以上。结合成屑过程在线显微观测结果可知:纤维角度是影响CFRP切削力的主要因素,0°~135°范围内,切屑形成方式为切断型和开裂后弯断型;切削力随纤维角度增大呈先减小后增大的趋势,135°时最大,随切削深度增加,切削力总体呈增大趋势。 In the CFRP process, the matrix phase is easily damaged by excessive cutting force and rapidly spreads below the machined surface to cause damage. In order to accurately predict and control the cutting force, an artificial neural network cutting force model was established based on experimental cutting force data to predict the cutting force variation of CFRP under different fiber angles, cutting depth and tool angle, And cutting parameters of the typical fiber angle CFRP one-way plate rectangular cutting experiments to verify the prediction model, the prediction accuracy of up to 85%. According to the on-line microscopic observation results of the chip formation process, the fiber angle is the main factor affecting the cutting force of CFRP. The chip formation mode is the cut-off type and the post-crack bending type in the range of 0 ° -135 °. The cutting force increases with the fiber angle It is the first to reduce and then increase the trend of the largest 135 °, with the increase of cutting depth, the cutting force generally showed an upward trend.
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