基于砂粒平均切削深度的带磨削表面粗糙度预测

Junde Qi, Bing Chen
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引用次数: 4

摘要

表面粗糙度是一种被广泛应用于产品质量评价的指标。建立了基于磨粒平均切削深度的带磨削表面粗糙度预测模型。首先,在前人工作的基础上,提出了磨料颗粒最大切削深度的计算方法。在这个过程中,为了使原来的计算更加方便,进行了一些简化。其次,根据计算方法得到磨料颗粒的平均切割深度;最后,通过分析粗糙度与平均切削深度之间的关系,综合考虑磨削过程的静态和动态影响,建立了带磨削表面粗糙度的简单预测模型。实验结果表明,预测值与实测值吻合较好。该预测模型可作为选择磨料颗粒和工艺参数的理论依据,以获得良好的表面粗糙度。
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Surface Roughness Prediction Based on the Average Cutting Depth of Abrasive Grains in Belt Grinding
Surface roughness is a widely used index for product quality evaluation. In this paper, a prediction model of the surface roughness in belt grinding is developed based on the average cutting depth of abrasive grains. Firstly, a calculation method of the maximum cutting depth of abrasive grains is presented based on our previous work. In this process, some simplifications are made to make the original calculations more convenient. Secondly, the average cutting depth of the abrasive grains was obtained based on the calculation method. Finally, by analysing the relationship between the roughness and the average cutting depth, and taking the static and dynamic effects of grinding process into account, a simple prediction model for surface roughness in belt grinding is presented. Experiments were carried out and the results indicate a good agreement between the predicted values and experimental values. The prediction model can be used as the theoretical foundation for the selection of abrasive grains and the process parameters to achieve a good surface roughness.
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