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石墨颗粒增强金属基复合材料能够提供更好的切削加工性能和摩擦性能。用灰度模糊算法优化Al-SiC-Gr混合金属基复合材料的加工参数,以获得到具有优秀综合性能的材料。当混合金属基复合材料中SiC-Gr的质量分数分别为5%、7.5%和10%时,对应的拉伸强度分别为170、210和204 MPa。另外,与另外2种材料相比,Al-10%(SiC-Gr)复合材料具有更好的切削加工性能。与其他的灰度技术相比,灰度模糊逻辑算法在输出方面提高了推理的合理性,降低了不确定性。实验结果表明,在设置的相同加工参数下,与其他的灰度技术相比,灰度模糊逻辑算法的推理合理性从0.619提高到0.891,且同时保证材料具有更好的综合性能。
Graphite Particle Reinforced Metal Matrix Composites provide better machinability and friction properties. The gray-scale fuzzy algorithm is used to optimize the processing parameters of Al-SiC-Gr mixed metal matrix composites to get the material with excellent comprehensive performance. When the mass fraction of SiC-Gr in the mixed metal matrix composites are 5%, 7.5% and 10% respectively, the corresponding tensile strengths are 170, 210 and 204 MPa respectively. In addition, Al-10% (SiC-Gr) composites have better machinability compared to the other two materials. Compared with other gray-level techniques, the gray-level fuzzy logic algorithm improves the rationality of reasoning and reduces the uncertainty in output. The experimental results show that under the same processing parameters, the reasoning rationality of gray-level fuzzy logic algorithm is improved from 0.619 to 0.891 compared with other gray-level techniques, and at the same time, the material has better comprehensive performance.