基于实际切深的薄壁件加工变形误差的预测

Fast Prediction of Static Form Errors in Peripheral Milling of Thin-Walled Workpieces Using Real Cutting Depth

在切削力作用下,刀具/工件的变形是影响薄壁件加工精度与质量的关键因素,而控制最大变形在允许误差范围之内,是表面误差预测的最终目的。以立铣加工为对象,提出了一种根据实际径向切深预测薄壁件加工表面最大变形误差的高效计算方法。在切削力分类的基础上通过定义切削力分析指标,考虑刀具/工件系统的变形,通过集中力作用位置的计算及实际切深的修正,得到了基于切削力曲线形状特征的实际切深的计算方法,并应用于薄壁件最大变形的预测中。以典型航空铝合金材料为对象,通过合理安排实验,并与数值计算结果对比,验证了最大变形误差算法的正确性及有效性。该方法基于切削力信号,不必进行有限元计算,效率高,可用于切削过程在线监控系统中,进行加工超差在线预测和控制。

Existing methods for predicting form errors^[1-4] are, in our opinion, too tedious and timeconsuming, leading to inefficiency in peripheral milling of thin-walled workpieces. We now present a fast and efficient method for making such prediction. In the full paper, we explain our fast and efficient method in detail; in this abstract, we just add some pertinent remarks to listing the two topics of explanation： （1） the analysis of milling process and the classification of forces and （2） the calculation of actual cutting depth of flexible cutting system; in topic 1, we utilize eqs. （1） through （4）, taken from the open literature, to classify cutting forces into ten types, shown in Fig. 3 in the full paper; the two subtopics of topic 2 are the determination of the maximum deflection of thin-wall under cutting（subtopic 2.1） and the calculation of actual cutting depth and maximum form errors（subtopic 2.2）; in subtopic 2. 1, we point out thatδL（max）, the maximum deflection, is either δw（max）, the maximum deflection mainly caused by the decrease of rigidity of workpiece, orδc（max）, the maximum deflection mainly caused by the deformation of cutter, whichever is bigger; in subtopic 2.2, based on the force indices extracted from the cutting force shape characteristics, we derive eqs. （6） though （11） in the full paper and eqs. （13） through （18） in the full paper for calculating actual cutting depth and maximum form errors. We performed tests, whose results are given in Fig. 10 in the full paper; these results show that deviations of calculated form errors from those measured are less than 16. 2%. We also performed the comparison of speed of prediction of form errors of peripheral milling of thin-walled workpieces for our method with that for Tsai’s method. ^[3] Using Pentium IV PC, we found that our fast and efficient method requires only 3 s as compared with 780 s required by Ref. 3＇s method.