混合增量建模在微加工过程表面粗糙度预测中的应用

F. Castaño, R. Haber, Raúl M. del Toro, Gerardo Beruvides
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引用次数: 5

摘要

本文介绍了一种混合增量建模策略(HIM)在微加工过程表面粗糙度实时估计中的应用。这个策略主要包括两个步骤。首先,建立了具有代表性的微加工过程混合增量模型。该模型的最终结果将输出描述为两个输入(Z轴上每齿进给二次元和振动平均二次元(rms))和输出(表面粗糙度Ra)的函数。其次,实时评估混合增量模型对表面粗糙度的预测效果。将计算过程嵌入到一个表面粗糙度实时监测系统中,对模型进行了实验验证。原型评估表明,估计表面粗糙度的成功率约为80%。这些结果为开发新一代微型部件表面粗糙度实时监测嵌入式系统和进一步在工业层面上的应用奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of hybrid incremental modeling for predicting surface roughness in micromachining processes
This paper presents the application of a hybrid incremental modeling strategy (HIM) for real-time estimation of surface roughness in micromachining processes. This strategy essentially consists of two steps. First, a representative hybrid incremental model of micromachining process is obtained. The final result of this model describes output as a function of two inputs (feed per tooth quadratic and vibration mean quadratic (rms) in the Z axis) and output (surface roughness Ra). Second, the hybrid incremental model is evaluated in real time for predicting the surface roughness. The model is experimentally tested by embedding the computational procedure in a real-time monitoring system of surface roughness. The prototype evaluation shows a success rate in the estimate of surface roughness about 80%. These results are the basement for developing a new generation of embedded systems for monitoring surface roughness of micro components in real time and the further exploitation of the monitoring system at industrial level.
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