A hybrid least-square QR decomposition （LSQR）-particle swarm optimization （LSQR-PSO） algorithm was devel- oped to estimate the three-dimensional （3D） temperature distributions and absorption coefficients simulta...A hybrid least-square QR decomposition （LSQR）-particle swarm optimization （LSQR-PSO） algorithm was devel- oped to estimate the three-dimensional （3D） temperature distributions and absorption coefficients simultaneously. The outgoing radiative intensities at the boundary surface of the absorbing media were simulated by the line-of-sight （LOS） method, which served as the input for the inverse analysis. The retrieval results showed that the 3D temperature distribu- tions of the participating media with known radiative properties could be retrieved accurately using the LSQR algorithm, even with noisy data. For the participating media with unknown radiative properties, the 3D temperature distributions and absorption coefficients could be retrieved accurately using the LSQR-PSO algorithm even with measurement errors. It was also found that the temperature field could be estimated more accurately than the absorption coefficients. In order to gain insight into the effects on the accuracy of temperature distribution reconstruction, the selection of the detection direction and the angle between two detection directions was also analyzed.展开更多
基金supported by the Major National Scientific Instruments and Equipment Development Special Foundation of China(Grant No.51327803)the National Natural Science Foundation of China(Grant No.51476043)the Fund of Tianjin Key Laboratory of Civil Aircraft Airworthiness and Maintenance in Civil Aviation University of China
文摘A hybrid least-square QR decomposition （LSQR）-particle swarm optimization （LSQR-PSO） algorithm was devel- oped to estimate the three-dimensional （3D） temperature distributions and absorption coefficients simultaneously. The outgoing radiative intensities at the boundary surface of the absorbing media were simulated by the line-of-sight （LOS） method, which served as the input for the inverse analysis. The retrieval results showed that the 3D temperature distribu- tions of the participating media with known radiative properties could be retrieved accurately using the LSQR algorithm, even with noisy data. For the participating media with unknown radiative properties, the 3D temperature distributions and absorption coefficients could be retrieved accurately using the LSQR-PSO algorithm even with measurement errors. It was also found that the temperature field could be estimated more accurately than the absorption coefficients. In order to gain insight into the effects on the accuracy of temperature distribution reconstruction, the selection of the detection direction and the angle between two detection directions was also analyzed.
