Use of moving average filter for regularization of the transfer function based on Green's function method (TFBGF) to solve an IHCP

摘要

Most techniques for inverse problems minimize the least squares error function between the calculated and measured temperature to estimate the heat flux in the IHCP. In this work, we apply the method of the transfer function based on Green's functions (TFBGF). Unlike the optimization techniques, TFBGF is a technique that uses deconvolution of the measured temperature and the heat transfer function of the system to estimate the unknown heat flux in a forward way.However, due to the presence of the inherent experimental uncertainties, some regularization methods may be necessary to add stability to the inverse solution. The regularization procedure proposed here is the moving average filters. Since the convolution has a filter characteristic, it has the advantage of being able to be implemented easily and incorporated to TFBGF method. In this work, an experimental procedure is designed to demonstrate the ability and technical robustness of TFBGF method with the regularization considering temperature data in regions of low sensitivity and high experimental uncertainty.