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Milling force identification from acceleration signals using regularization method based on TSVD in peripheral milling

机译:使用基于TSVD在外围铣削中的正规化方法铣削力识别

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Milling forces are important signals that can be used to monitor the condition of machine operating and milling process In general,milling forces can be measured by special equipment,for example,Kistler dynameters.However,dynameters are very expensive and require particular geometry of workpiece,which causes that dynameters are limited in research laboratories rather than actual production.In this paper,a force identification method in frequency domain,the regularization method based on the truncated singular value decomposition(TSVD),is employed for milling force reconstruction using acceleration signals in peripheral milling process The two acceleration sensors are mounted on the spindle box in the feed and cross-feed directions for reconstructing the milling forces.The regularization method based on TSVD is adopted for inverse problem in force identification because of its high identification accuracy,which can possess ill-conditioned matrixes well.Finally,the method is validated by numerical simulation and cutting experiments.In the experiment,the milling forces and acceleration signals from spindle box are acquired synchronously.Then,the frequency response functions between milling tool nose and acceleration sensors in the feed and cross-feed directions are obtained by impact tests.With the acceleration signals and frequency response functions,the milling forces can be reconstructed.Identified results show that the calculated forces and the measured forces are in good agreement on the whole,which verify the effectiveness of the employed method on milling force identification
机译:铣削力是重要的信号,可用于监测机器操作和铣削过程的情况一般,可以通过特殊设备测量铣削力,例如Kistler Dynemeters。但是,动力计非常昂贵,需要特定的工件几何形状,这导致动力计在研究实验室而不是实际生产中的限制。本文采用了使用加速信号的频域中的力识别方法,基于截断的奇异值分解(TSVD)的正则化方法用于使用加速信号进行铣削力重建外围铣削处理的两个加速度传感器安装在进料和交叉进给方向上的主轴盒上,用于重建铣削力。由于其高识别精度,采用了基于TSVD的正则化方法,因为它可以具有不良矩阵。最后,该方法验证数值模拟和切割实验。在实验中,同步获取铣削力和来自主轴箱的加速信号。然后,通过冲击试验获得铣削工具鼻子和加速度传感器之间的频率响应功能。利用加速信号和频率响应函数,可以重建铣削力。识别的结果表明,计算的力和测量力与整体吻合良好,这验证了采用方法对铣削力识别的有效性

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