A decentralized fuzzy inference method for solving the two-dimensional steady inverse heat conduction problem of estimating boundary condition
A decentralized fuzzy inference method for solving the two-dimensional steady inverse heat conduction problem of estimating boundary condition
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DOI：
10.1016/j.ijheatmasstransfer.2011.01.032
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发表时间：
2011-06
影响因子：
5.2
通讯作者：
Guangjun Wang;Lina Zhu;Hong Chen
中科院分区：
文献类型：
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作者：
Guangjun Wang;Lina Zhu;Hong Chen
本文提出了一种求解二维稳态逆热传导问题的新方法——分散模糊推理（DFI）法。首先，设计了一组分散模糊推理单元，并根据每个测量位置的实测温度与计算温度的差异对每个模糊推理单元进行模糊推理。用有限差分法求解直接热传导问题，得到了计算温度。然后，对模糊推理单元的推理结果进行加权，得到未知边界温度的补偿值。用补偿值不断更新猜测温度来估计未知边界温度。采用不同的初始猜测值、测点个数和测量误差进行了数值实验。比较DFI方法和Levenberg-Marquardt （L-M）方法的结果，可以得出DFI方法是有效的。
This paper addresses a new technique for solving the two-dimensional steady inverse heat conduction problem, which named decentralized fuzzy inference (DFI) method. First of all, a group of decentralized fuzzy inference units are designed, and the fuzzy inference for each fuzzy inference unit is conducted which bases on the difference between the measured and the computed temperature at each measuring location. The computed temperatures are obtained by solving the direct heat conduction problem with the finite difference method. And then, inference results of fuzzy inference units are weighted to yield compensation values of the unknown boundary temperatures. The unknown boundary temperatures are estimated by updating guess temperatures continuously with compensation values. Numerical experiments are carried out with different initial guesses, the number of measuring points and measurement errors. Comparing results of DFI method and Levenberg–Marquardt (L–M) method, we can conclude that DFI method is valid.