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Surface Roughness Model Based on Force Sensors for the Prediction of the Tool Wear

机译:基于力传感器的表面粗糙度模型对刀具磨损的预测

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摘要

In this study, a methodology has been developed with the objective of evaluating the surface roughness obtained during turning processes by measuring the signals detected by a force sensor under the same cutting conditions. In this way, the surface quality achieved along the process is correlated to several parameters of the cutting forces (thrust forces, feed forces and cutting forces), so the effect that the tool wear causes on the surface roughness is evaluated. In a first step, the best cutting conditions (cutting parameters and radius of tool) for a certain quality surface requirement were found for pieces of UNS . Next, with this selection a model of surface roughness based on the cutting forces was developed for different states of wear that simulate the behaviour of the tool throughout its life. The validation of this model reveals that it was effective for approximately 70% of the surface roughness values obtained.
机译:在这项研究中,已经开发出一种方法,其目的是通过测量在相同切削条件下由力传感器检测到的信号来评估车削过程中获得的表面粗糙度。这样,在加工过程中获得的表面质量与切削力的几个参数(推力,进给力和切削力)相关,因此可以评估刀具磨损对表面粗糙度的影响。第一步,为UNS件找到了满足一定质量表面要求的最佳切削条件(切削参数和刀具半径)。接下来,通过这种选择,针对不同的磨损状态,开发了基于切削力的表面粗糙度模型,该模型模拟了刀具在整个使用寿命中的行为。该模型的验证表明,它对获得的大约70%的表面粗糙度值有效。

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