【摘要】 切削状态监控是实现机械加工过程自动化的关键技术,切削力信号的实时信息能够反映切削过程特别是刀具状态的变化。文章利用车削实验方法系统测量了外圆车刀在不同磨损状态下的切削力信号,利用频谱分析方法得到了相应的切削力功率谱。实验结果表明,在切削力频谱中总存在一组特征频率,其频率及谱值与刀具的磨损状态密切相关。在正常磨损阶段,该谱值随磨损程度增大而增大,因而可根据谱值的大小及变化规律预测刀具的磨损程度。因此该方法丰富了切削力监控技术的内容,进一步提高了监控的准确性。更多还原

【Abstract】 Cutting monitoring is the key to achieving manufacturing automation.The real-time cutting force signals can indicate the cutting tool state during the cutting process.In the present paper,the cutting force signals under different cutting tool wear stages were systematically measured by turning experiments and the power spectrums of the cutting force signals at different wear stages were analyzed.It is proved that there exists a set of characteristic frequencies for a certain cutting process.The characteristic frequencies and their power spectrums have close relations with cutting tool wear states.At the normal wear stage,the values of the power spectrum increase with the increase of wear level.Thus,the cutting tool wear can be predicted by the variation of the power spectrums.So the proposed method improves the cutting monitoring technology as well as the monitoring precision.更多还原