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首页> 外文期刊>The International Journal of Advanced Manufacturing Technology >Experimental and predictive study by multi-output fuzzy model of electrical discharge machining performances
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Experimental and predictive study by multi-output fuzzy model of electrical discharge machining performances

机译:电气放电性能多输出模糊模型的实验和预测研究

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摘要

The nature of electrical discharge machining makes it difficult to predict or even measure machining performance, which is why great attention has been paid to methodologies for measuring these performances. In this work, an experimental approach for measuring machining electrical discharge performance and geometric errors was presented. This can improve the authenticity of the parameters measured. A technique for identifying machining parameters using a multi-output system based on fuzzy logic has been proposed. The objective was to determine the influence of machining parameters on the machining performance and associated geometric errors. It is shown that the fuzzy model is capable of giving results providing a good correlation between the real and predicted values. The average error of the model was approximately 1.51% for material removal rate, 3.386% for tool wear rate, 2.924% for wear rate, 5.285% for surface roughness, 4.004% for radial overcut, 4.381% for circularity, and 2.937% for cylindricity.
机译:电气放电加工的性质使得难以预测甚至测量加工性能,这就是为什么由于用于测量这些性能的方法来支付众所周知的原因。在这项工作中,提出了一种测量加工电放电性能和几何误差的实验方法。这可以改善测量的参数的真实性。提出了一种基于模糊逻辑的多输出系统识别加工参数的技术。目的是确定加工参数对加工性能和相关几何误差的影响。结果表明,模糊模型能够在真实和预测值之间提供良好的相关性。材料去除率的平均误差大约为1.51%,对于刀具磨损率为3.386%,对于磨损率为2.924%,表面粗糙度为5.285%,径向过度的4.04%,圆柱度为4.381%,圆柱形为2.937%。 。

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