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Mathematical Modeling of Multiple Quality Characteristics of a Laser Microdrilling Process Used in Al7075/SiC_p Metal Matrix Composite Using Genetic Programming

机译:基于遗传编程的AL7075 / SIC_P金属基质复合材料中使用的激光微滴处理的多种质量特征的数学建模

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The conventional method for machining metal matrix composites (MMCs) is difficult on account of their excellent characteristics compared with those of their source materials. Modern laser machining technology is a suitable noncontact method for machining operations of advanced engineering materials due to its novel advantages such as higher productivity, ease of adaptation to automation, minimum heat affected zone (HAZ), green manufacturing, decreased processing costs, improved quality, reduced wastage, removal of finishing operations, and so on. Their application includes hole drilling in an aircraft engine components such as combustion chambers, nozzle guide vanes, and turbine blades made up of MMCs which meet quality standards that determine their suitability for service use. This paper presents a derived mathematical model based on evolutionary computation methods using multivariate regression fitting for the prediction of multiple characteristics (circularity, taper, spatter, and HAZ) of neodymium: yttrium aluminum garnet laser drilling of aluminum matrix/silicon carbide particulate (Al/SiCp) MMCs using genetic programming. Laser drilling input factors such as laser power, pulse frequency, gas pressure, and pulse width are utilized. From a training dataset, different genetic models for multiple quality characteristics were obtained with great accuracy during simulated evolution to provide a more accurate prediction compared to empirical correlations.
机译:由于与它们的源材料相比,难以实现金属基质复合材料(MMCS)的常规方法。现代激光加工技术是一种合适的非接触式方法,用于加工先进的工程材料的运营方法,因为其新颖的优势,如更高的生产率,简单适应自动化,最小热影响区域(HAZ),绿色制造,加工成本,提高质量,提高质量减少浪费,去除整理操作等。它们的应用包括飞机发动机部件中的孔钻孔,例如燃烧室,喷嘴导向叶片和由MMC构成的涡轮机叶片,其满足质量标准,这些标准确定它们适合使用的服务使用。本文提出了一种基于进化计算方法的衍生数学模型,其使用多元回归拟合预测钕(圆形,锥度,飞溅和HAZ)的钕:铝基铝基/碳化硅颗粒的Yttrium铝石榴石激光钻孔(Al / SICP)MMC使用遗传编程。使用激光钻孔输入因子,如激光功率,脉冲频率,气体压力和脉冲宽度。从训练数据集中,在模拟演进过程中以极高的精度获得了多种质量特征的不同遗传模型,以提供与经验相关相比更准确的预测。

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  • 来源
    《Modelling and simulation in engineering》 |2019年第1期|1024365.1-1024365.15|共15页
  • 作者单位

    Umm Al Qura Univ Coll Engn & Islamic Architecture Dept Mech Engn Al Abdiah 24231 Makkah Saudi Arabia;

    Umm Al Qura Univ Coll Engn & Islamic Architecture Dept Mech Engn Al Abdiah 24231 Makkah Saudi Arabia;

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