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Research on method of reconstructing temperature field of silicon melt based on eigenfunction interpolation

机译:基于特征函数插值的硅熔体温度场重构方法研究

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Traditional single point detection of temperature of the thermal field in the single crystal furnace can't get the temperature distribution inside the silicon melt. In this paper, TDR-120 semiconductor silicon single crystal furnace is taken as the research object, and a method of reconstructing temperature field of silicon melt based on eigenfunction interpolation is proposed. The paper takes the finite element method to get the eigenfunctions based on the heat conduction equation. According to the contribution of the eigenfunctions to the reconstruction of the temperature field, the partial eigenfunctions with larger contribution are selected by the threshold function, which are used as a set of basis to reconstruct the temperature field. And the weight coefficients are estimated using the temperature of multiple monitoring points. Then, the temperature distribution in the area under study is obtained by solving the inverse problem. Moreover, aiming at the influence of temperature monitoring points on the reconstruction accuracy, the multipopulation genetic algorithm is used to optimize the placement of sensor monitoring points for measuring the temperature on the free liquid surface so as to improve the reconstruction accuracy of the temperature field. Simulation results show the effectiveness of the proposed method.
机译:传统的单晶炉热场温度单点检测无法获得硅熔体内部的温度分布。本文以TDR-120半导体硅单晶炉为研究对象,提出了一种基于特征函数插值的硅熔体温度场重构方法。本文采用有限元方法,基于热传导方程获得本征函数。根据本征函数对温度场重建的贡献,通过阈值函数选择贡献较大的部分本征函数,将其作为重建温度场的基础。并使用多个监控点的温度估算权重系数。然后,通过求解反问题来获得研究区域内的温度分布。此外,针对温度监测点对重建精度的影响,采用多种群遗传算法优化了传感器监测点在自由液面上测量温度的位置,从而提高了温度场的重建精度。仿真结果表明了该方法的有效性。

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