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首页> 外文期刊>The International Journal of Advanced Manufacturing Technology >Improving prediction accuracy of thermal analysis for weld-based additive manufacturing by calibrating input parameters using IR imaging
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Improving prediction accuracy of thermal analysis for weld-based additive manufacturing by calibrating input parameters using IR imaging

机译：通过使用红外成像校准输入参数，提高基于焊接的增材制造的热分析预测精度

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摘要

In experiments, it is usually difficult to accurately determine simulation input parameters such as heat source parameters, material properties at high temperature, etc. The uncertainty of such input parameters is responsible for the large error of thermal simulation for weld-based additive manufacturing. In this paper, a new approach is presented to calibrate uncertain input parameters. The approach is based on the solution of the inverse heat conduction problem of small-scale five-layer deposition and the application of the infrared (IR) imaging technique. The calibration of heat source parameters involves a multivariate optimization search using the pattern search method, whereas the calibration of the combined radiation and convection model includes a number of one-dimensional searches using the Fibonacci search method. Based on an in-depth analysis of IR images, thermal characteristics such as mean layer temperature and cooling rate are selected as the comparison results and included in cost functions. Lastly, the validity of the approach is demonstrated by a simulation case of 15-layer deposition with calibrated input parameters. The comparison between the simulated and experimental results verifies the improved prediction accuracy.
机译：在实验中，通常很难准确确定模拟输入参数，例如热源参数，高温下的材料性能等。此类输入参数的不确定性是造成基于焊接的增材制造的热模拟误差很大的原因。本文提出了一种新的方法来校准不确定的输入参数。该方法基于解决小规模五层沉积的逆热传导问题和红外（IR）成像技术的应用。热源参数的校准涉及使用模式搜索方法的多元优化搜索，而辐射与对流组合模型的校准包括使用斐波那契搜索方法的许多一维搜索。基于对红外图像的深入分析，选择平均层温度和冷却速率等热特性作为比较结果，并将其包括在成本函数中。最后，该方法的有效性通过带有校准输入参数的15层沉积的模拟案例得到证明。仿真结果和实验结果之间的比较验证了改进的预测精度。

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