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Prediction of the Cut Depth of Granitic Rocks Machined by Abrasive Waterjet (AWJ)

机译:磨料水射流(AWJ)加工的花岗岩岩石切割深度的预测

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摘要

In this paper, an experimental study on the cut depth, which is an important cutting performance indicator in the abrasive waterjet (AWJ) cutting of rock, was presented. Taguchi experimental design of an orthogonal array was employed to conduct the experiments. A variety of nine types of granitic rocks were used in the cutting experiments. The experimental data were used to assess the influence of AWJ operating variables on the cut depth. Using regression analysis, models for prediction of the cut depth from the operating variables and rock properties in AWJ machining of granitic rocks were then developed and verified. The results indicated that the cut depths decreased with increasing traverse speed and decreasing abrasive size. On the other hand, increase of the abrasive mass flow rate and water pressure led to increases in the cut depths. Additionally, it was observed that the standoff distance had no discernible effects on the cut depths. Furthermore, from the statistical analysis, it was found that the predictive models developed for the rock types had potential for practical applications. Verification of the models for using them as a practical guideline revealed a high applicability of the models within the experimental range used.
机译:本文提出了对切削深度的实验研究,切削深度是岩石磨料射流切割中的重要切削性能指标。使用Taguchi正交阵列的实验设计进行实验。切割实验中使用了多种9种类型的花岗岩。实验数据用于评估AWJ操作变量对切削深度的影响。然后,使用回归分析,开发和验证了用于根据花岗岩的AWJ加工中的操作变量和岩石特性预测切削深度的模型。结果表明,切削深度随行进速度的增加和磨料尺寸的减小而减小。另一方面,磨料质量流量和水压的增加导致切削深度的增加。此外,可以观察到,间隔距离对切削深度没有明显的影响。此外,从统计分析中发现,针对岩石类型开发的预测模型具有实际应用潜力。验证将其用作实际指南的模型表明,该模型在所使用的实验范围内具有很高的适用性。

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