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Study of Mechanical and Sliding Wear Behavior of Al-25Zn alloy/SiC/Graphite Novel Hybrid Composites for Plain Bearing Application

机译:Al-25Zn合金/ SiC /石墨新型混合复合材料对铝合金应用的机械滑动磨损行为研究

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In this investigations, sliding wear performance of Al-25Zn based novel hybrid composites added with fixed weight percentage of graphite (3 wt.%) and varying weight percentage of silicon carbide (10, 20 and 30 wt.%) was investigated for various process factors such as specimen temperature, applied load, sliding speed and sliding distance using a pin on disc with EN24 disc as per Taguchi L16 array. For similar test conditions, the composite with 10 wt.% of silicon carbide shows the highest wear resistance and tensile strength; whereas the composite with 20 wt.% of SiC shows highest hardness. The specimen temperature is recognized as the dominating parameter for the sliding wear performance of the materials. Artificial Neural network and Regression model developed was found competent for the forecasting of wear performance. Confirmation experiment conducted with the optimum parameter combination also confirmed the accuracy of developed model. The observed wear mechanism is abrasion and adhesion. The major mechanisms of abrasive wear are recognized as ploughing, micro cutting and delamination.
机译:在该研究中,研究了用于各种过程的固定重量百分比(3重量%)的固定重量百分比和不同重量百分比(10,20,20和30重量%)的铝基杂交复合材料的滑动磨损性能。根据TAGUCHI L16阵列,使用销钉上的标本温度,施加载荷,滑动速度和滑动距离等因素使用en24盘。对于类似的试验条件,具有10重量%的复合材料。碳化硅的%含量最高,耐磨性和拉伸强度。虽然具有20重量%的复合材料。%的SiC的百分比显示出最高的硬度。试样温度被认为是用于材料的滑动磨损性能的主导参数。发现人工神经网络和回归模型得到了磨损性能预测的能力。用最佳参数组合进行的确认实验还证实了开发模型的准确性。观察到的磨损机构是磨损和粘附性。研磨磨损的主要机制被认为是犁,微切割和分层。

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