Modelling and Multi-objective Optimization of Elastic Abrasive Cutting of C45 and 42Cr4 Steels

I. Aleksandrova, A. Stoynova, A. Aleksandrov
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引用次数: 1

Abstract

Elastic abrasive cutting is a new high-performance method to produce workpieces made of materials of different hardness, which ensures lower wear of cut-off wheels and higher quality machined surfaces. However, the literature referring to elastic abrasive cutting is scarce; additional studies are thus needed. This paper proposes a new approach for modelling and optimizing the elastic abrasive cutting process, reflecting the specifics of its particular implementation. A generalized utility function has been chosen as an optimization parameter. It appears as a complex indicator characterizing the response variables of the elastic abrasive cutting process. The proposed approach has been applied to determine the optimum conditions of elastic abrasive cutting of С45 and 42Cr4 steels. To solve the optimization problem, a model of the generalized utility function reflecting the complex influence of the elastic abrasive cutting conditions has been developed. It is based on the findings of the complex study and modelling of the response variables of the elastic abrasive cutting process (cut-off wheel wear, time per cut, cut piece temperature, cut off wheel temperature and workpiece temperature) depending on the conditions of its implementation (compression force F exerted by the cut-off wheel on the workpiece, workpiece rotational frequency nw, cut off wheel diameter ds). By applying a genetic algorithm, the optimal conditions of elastic abrasive cutting of С45 and 42Cr4 steels: ds = 120 mm; F = 1 daN; nw = 63.7 min–1 and nw = 49.9 min–1, respectively for С45 and 42Cr4 steels, have been determined. They provide the best match between the response variables of the elastic abrasive cutting process.
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C45和42Cr4钢弹性磨料切削建模及多目标优化
弹性磨料切削是一种高性能的加工不同硬度材料工件的新方法,它能保证较低的截齿磨损和较高的加工表面质量。然而,关于弹性磨料切削的文献很少;因此需要进一步的研究。本文提出了一种新的方法来建模和优化弹性磨料切割过程,反映了其具体实施的细节。选择广义效用函数作为优化参数。它是表征弹性磨料切削过程响应变量的复杂指标。应用该方法确定了С45和42Cr4钢的弹性磨料切削的最佳条件。为了解决这一优化问题,建立了反映弹性磨料切削条件复杂影响的广义效用函数模型。它是基于对弹性磨料切割过程的响应变量(切断轮磨损、每次切割时间、切割片温度、切断轮温度和工件温度)的复杂研究和建模的结果,这些响应变量取决于其实施条件(切断轮对工件施加的压缩力F、工件旋转频率nw、切断轮直径ds)。应用遗传算法得到С45和42Cr4钢弹性磨料切削的最优条件为:ds = 120 mm;F = 1 daN;确定了С45和42Cr4钢的nw = 63.7 min-1和nw = 49.9 min-1。它们提供了弹性磨料切削过程响应变量之间的最佳匹配。
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