Flame 3D temperature field reconstruction based on Damped LSQR-LMBC

Abstract

Light field camera can solve the problems of complex optical path and difficult synchronous trigger of radiation temperature measurement multi camera system, which has some unique advantages in three-dimensional temperature reconstruction of radiation imaging. The LSQR is a classical algorithm for solving the least square problem based on large sparse matrix. When the algorithm is used to reconstruct three-dimensional temperature field, it depends on the initial value of temperature, and the reconstruction accuracy is not ideal when the signal-to-noise ratio is low. In this paper, a damped LSQR-LMBC reconstruction algorithm is proposed. By adding a damped regularization term into the LSQR method, the anti noise performance of flame three-dimensional temperature field reconstruction is improved. By combining the LMBC algorithm, the absorption coefficient and three-dimensional temperature field are solved at the same time. In the numerical simulation part, with the gradual reduction of signal-to-noise ratio, the reconstruction effect of Damped LSQR turns more stable than LSQR. When the signal-to-noise ratio reaches 13.86 dB, the reconstruction accuracy is improved by about 30%. The average reconstruction error of damped LSQR-LMBC is 6.63%. The three-dimensional temperature field distribution of butane flame is consistent with the characteristic of radiation flame combustion. Compared with the temperature measurement data of thermocouple, the relative error is about 6.8%.