Nonlinear temperature field reconstruction using acoustic tomography

Acoustic tomography is considered to be a promising technique for temperature field monitoring, with the advantage of non-invasive, low cost, high temporal resolution and ease of use. However, in combustion process, the gradient of the temperature field could be relatively large, therefore the commonly used straight ray acoustic tomography may not be able to provide accurate quantitative temperature field estimation due to refraction effect. In this paper, bent ray model and nonlinear reconstruction algorithm is applied, which allows the sound propagation trajectories and temperature distribution being reconstructed iteratively from the time-of-flight (TOF) measurements. Based on local linearity assumption, each reconstruction iteration consists of two steps, the ray tracing step to calculate the ray trajectories from the obtained temperature field estimation, and the linear reconstruction step, which utilizes the SIRT method to update the temperature field estimation. The feasibility and effectiveness of the developed methods are validated in simulation study. Results show that the proposed method can improve the reconstruction quality compared to the conventional straight ray acoustic tomography.