Comparison of the Mollification Method, Wavelet Transform and Moving Average Filter for Reduction of Measurement Noise Effects in Inverse Heat Conduction Problems

This paper proposes a procedure to smooth temperature data by wavelet transform, moving average filter and the mollification method prior to utilizing the IHCP methods (i.e. the conjugate gradient method, the Tikhonov regularization method) for unknown heat ux estimation. The measured transient temperature data utilized in the solution may be obtained from locations inside the body or from locations on its inactive boundaries. Two case studies are used to investigate the eciency and accuracy of the mentioned procedure. The first case study is performed on a rectangular body. The second case study demonstrates the ability of the proposed method to estimate heat ux in a more complicated geometry. Smoothing measured data causes an increase in the accuracy and stability of the estimation.