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
文摘针对LSQR(least square QR-factorization)算法在求解电阻抗层析成像(electrical impedance tomography,EIT)逆问题时,由于矩阵维数高、计算量大而导致重建速度较慢的问题,提出基于小波多分辨分析的LSQR算法(wavelet multi-resolution based least square QR-factorization,WALSQR)。该方法将EIT的图像重建过程投影到低维的尺度空间进行,通过提取有效信息减少数据计算量,明显提高了图像重建速度。同时由于去除了噪声和冗余信息,保证了成像质量。本文将SALSQR方法分别应用于二维、三维EIT成像实验,证明其有效性,并为三维动态EIT图像重建算法的研究奠定了基础。
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.
