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Prediction of slurry erosive wear behaviour of Al6061 alloy using a fuzzy logic approach

机译:使用模糊逻辑方法预测AL6061合金的浆料腐蚀行为

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Slurry erosive wear as a failure mechanism has significance in terms of dictating the performance of marine components. Experimental determination of this wear phenomenon for various materials in current naval applications is tedious, expensive and, in the majority of cases, not reliable. The standard experimental procedures in assessing the slurry erosive wear do not simulate the actual operating conditions. Researchers have been focusing on predictions of wear behaviour based on several hypotheses and mathematical models as a response to overcome the above mentioned obstacles. The fuzzy logic approach is a highly reliable analytical technique and therefore widely accepted and used. This paper discusses a fuzzy logic model to predict the slurry erosive wear behavior of cast aluminum 6061 (Al 6061) alloy pre and post heat treatment. The adopted fuzzy model employs hybrid-learning techniques involving a combination of both back-propagation and least-square method. Sand concentration, test duration, slurry rotation speed and impinging particle sizes served as inputs while slurry erosive wear losses were the outputs. The predicted values have been compared with published experimental data under various operating conditions. The predicted values of slurry erosive wear loss of cast aluminum 6061 alloy pre and post heat treatment are in close agreement with the experimental results.
机译:泥浆腐蚀磨损作为失效机制,就规定了海洋组分的性能而具有重要意义。实验测定当前海军应用中各种材料的这种磨损现象是乏味,昂贵的,并且在大多数情况下,不可靠。评估浆料腐蚀磨损的标准实验程序不会模拟实际操作条件。研究人员一直专注于基于几个假设和数学模型的磨损行为的预测,作为克服上述障碍的回应。模糊逻辑方法是一种高度可靠的分析技术,因此广泛接受和使用。本文讨论了一种模糊逻辑模型,以预测铸铝6061(Al 6061)合金前和后热处理的浆料腐蚀行为。采用的模糊模型采用混合学习技术,涉及反向传播和最小二乘法的组合。砂浓度,测试持续时间,浆料转速和撞击粒度施用为输入,而浆料腐蚀磨损损失是输出。将预测值与各种操作条件下的公开的实验数据进行了比较。铸铝6061合金前后热处理和后热处理的预测值与实验结果密切一致。

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