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Optimization and analysis for surface roughness of SiCp/Al metal matrix composite by micro-WEDM

机译:Micr-WEDM的SICP / Al金属基质矩阵表面粗糙度的优化与分析

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The material removal process of SiC/Al particulate (SiCp/Al) metal matrix composite by micro-wire electrical discharge machining (micro-WEDM) is influenced by many factors interaction, which makes the mathematical model of surface roughness (SR) be difficult to obtain effectively. To solve this problem, experimental study method is conducted under the constraint conditions. In this paper, a central composite design (CCD) testing with 3-factor and 5-level is carried out and SiCp/Al metal matrix composite machining test scheme is designed, and then second-order relational model is established between SR and main power parameters (open-circuit voltage, capacitance, and pulse duration) by using response surface methodology. Through multiple quadratic fitting, the quadratic regression mathematical model of SR is obtained. Constrains of actual machining condition upon the parameters are analyzed further. With the goal of reducing SR of SiCp/Al metal matrix composite by micro-WEDM, the parameters optimization model is established. Particle swarm optimization (PSO) algorithm and its procedure are designed to solve the model. Test proves that the algorithm could achieve optimized process parameters which satisfy multiple constraints rapidly and effectively.
机译:通过微导线电放电加工(Micro-WEDM)的SiC / Al颗粒状(SiCP / Al)金属基质复合材料的材料去除方法受许多因素相互作用的影响,这使得表面粗糙度(SR)的数学模型难以有效获得。为了解决这个问题,在约束条件下进行实验研究方法。在本文中,进行了3​​系数和5级的中央复合设计(CCD)测试,设计了SICP / Al金属矩阵复合加工测试方案,然后在SR和主电源之间建立二阶关系模型参数(开路电压,电容和脉冲持续时间)通过使用响应表面方法。通过多次二次拟合,获得了SR的二次回归数学模型。进一步分析了参数上的实际加工条件的约束。通过通过微内带减少SICP / Al金属矩阵复合材料的SR,建立了参数优化模型。粒子群优化(PSO)算法及其程序旨在解决模型。检验证明,该算法可以达到快速且有效地满足多个约束的优化过程参数。

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