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Parametric Optimization of Electrochemical Honing of Helical Gears by Response Surface Methodology and Genetic Algorithm

机译:响应面法和遗传算法螺旋齿轮电化学珩磨的参数优化

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Finishing is crucial for maximizing the service life and overall in-service performance of gears. This paper presents the parametric optimization of Electrochemical Honing (ECH) of helical gears using Response Surface Methodology (RSM) and Genetic Algorithm (GA) to predict the surface quality of gear teeth profile. A three factors three levels Box Behnken Design (BBD) of Response Surface Methodology (RSM) has been designed to investigate and analyze the effects of input variables: voltage, rotating speed and electrolyte concentration on measures of process performances: percentage improvement in average and maximum surface roughness (PIR_a/PIR_(tm)) value. Typical ranges of input parameters were investigated and regression models were developed and used respectively as constraints and objective function for parametric optimization using GA. The results established the feasibility of using the process to improve the surface quality of gear teeth profile.
机译:精加工对于最大化使用寿命和齿轮的整体服务性能至关重要。本文介绍了使用响应面法(RSM)和遗传算法(GA)来预测齿轮齿轮廓的表面质量的螺旋齿轮的电化学珩磨(ECH)的参数优化。响应面方法(RSM)的三个因素三级盒BECNKEN设计(BBD)旨在调查和分析输入变量的影响:电压,转速和电解质浓度对过程性能测量的影响:平均值和最大值百分比改善表面粗糙度(PIR_A / PIR_(TM))值。研究了典型的输入参数范围,并分别为使用GA的参数优化的约束和目标函数来开发和使用回归模型。结果建立了使用该过程改善齿轮齿轮廓的表面质量的可行性。

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