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首页> 外文期刊>Journal of Thermoplastic Composite Materials >Genetic Algorithm based Resistive Susceptor Design for Uniform Heating During the Induction Bonding Process
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Genetic Algorithm based Resistive Susceptor Design for Uniform Heating During the Induction Bonding Process

机译:基于遗传算法的感应结合过程中均匀加热的电阻感受器设计

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In this research workcut mesh design optimization for the induction bonding process using genetic algorithms (GAs)is investigated to solve the problem of nonuniform heating,which leads to nonuniform temperature fields and temperature grdients exceeding the process window required for bonding.Cut patterns in the metal mesh can redirect the magnetically induced electric currents generated thus changing the temperature distribution.In this work,the heat generation model for determinign current adn heat generation distribution for a given coi and mesh size,coded as a Mathematica function,was coupled with a simple genetic algorithm.Ths cost function to be minimized by the GA was the ratio of the maximum heat generation in the mesh to the minimum heat generation.Two studies were performed with the GA-based design optimization:the first with a six sided square mesh and the second using a ten sided square mesh.The best cut mesh designs obtained from the GA were compared with the globally optimal designs,where available,and with the baseline mesh.The GA could not reach the global optima due to the complex nature of the design search space.However,it was determined that the GA was able to redcue the variations in heat generation in the mesh for all cases and delivered significant improements over the baseline case in reasonable computational time,evaluating less than 2% of the possible cut mesh patterns.Thus the genetic algorithm based design optimization was proven to be a computationally efficient tool in the generation of good cut mesh designs for the induction bonding process.
机译:在这项研究中,研究人员使用遗传算法(GAs)对感应焊接过程的网格设计进行了优化,以解决加热不均匀的问题,从而导致温度场和温度梯度不均匀,超过了粘接所需的工艺范围。网格可以重定向产生的磁感应电流,从而改变温度分布。在这项工作中,用于确定给定coi和网格尺寸的电流和热量分布的热生成模型(编码为Mathematica函数)与简单的遗传算法结合通过GA最小化的成本函数是网格中最大热量与最小热量的比值。基于GA的设计优化进行了两项研究:第一项是六面正方形网格,第二项是第二种方法是使用十面正方形网格。将遗传算法获得的最佳切割网格设计与全局优化进行比较由于设计搜索空间的复杂性,遗传算法无法达到全局最优值。但是,可以确定遗传算法能够减少热源中热量的变化。在合理的计算时间内对所有情况都进行了网格划分,并在基线情况下提供了显着的改进,估计不到可能的切割网格样式的2%。因此,基于遗传算法的设计优化被证明是生成良好切割的一种计算有效的工具感应粘合过程的网格设计。

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