Temperature field reconstruction algorithm based on Reflected Sigmoid radial basis function interpolation

Abstract:

The acoustic thermometry has a good application in the special temperature field environment. That is, the continuous distribution of temperature field can be reconstructed using the flight time spent on the finite ultrasonic propagation path. The least square method is one of the acoustic temperature field reconstruction algorithms, and the reconstructed temperature field will have the phenomenon of missing edge information using this method. In order to solve this problem, an algorithm based on Reflected Sigmoid radial basis function interpolation is proposed to reconstruct the twodimensional distribution of temperature without information loss. In this algorithm, the least square method is adopted to determine the temperature matrix and the ReflectedSigmoid function is used to interpolate the temperature field. The reconstruction results and error analysis of two typical single peak temperature field models show that the root mean square percentage error of the symmetrical single peak temperature field is 1.6% and the root mean square percentage error of the skewed single peak temperature field is 3.5% after complementing the edge of the temperature field.