计量学报2024，Vol.45Issue(5)：671-677,7.DOI:10.3969/j.issn.1000-1158.2024.05.09
基于压缩感知的AT温度场重建算法
Reconstruction Algorithm of AT Temperature Field Based on Compressed Sensing
摘要
Abstract
To improve the temperature field reconstruction ability of acoustic tomography(AT),an AT temperature field reconstruction algorithm based on compressed sensing(CS-AT algorithm)was proposed.The algorithm utilizes signal sparsity to reduce the amount of data to be solved and reduce the difficulty of solving inverse problems.Firstly,selected an appropriate dictionary and constructed a framework based on CS for the forward and inverse problem of temperature field reconstruction by AT.Then,the orthogonal matching pursuit(OMP)algorithm was used for CS reconstruction to obtain the solution of the temperature field reconstruction in the sparse domain.Finally,transformed it back to the original domain and interpolated it to 37 × 37 pixel fine temperature distribution using cubic splines.Through numerical simulation,for kinds of models temperature fields(average temperature,single peak,bimodal,and four peak)were reconstructed using the classical least squares method(LSM)and CS-AT algorithm under noisy and non-noisy conditions respectively.Average temperature,single peak,and double peak actual temperature fields were reconstructed on an independently developed experimental system.Simulation and experiments have shown that CS-AT algorithm can effectively reduce temperature field reconstruction errors.Under the four peak temperature field,the highest reconstruction error of CS-AT algorithm is only 25.5％of LSM.关键词
温度测量/声学层析成像/温度场重建/压缩感知/正交匹配追踪Key words
temperature measurement/acoustic tomography/temperature field reconstruction/compressed sensing/OMP分类
通用工业技术引用本文复制引用
魏元焜,颜华,周英钢..基于压缩感知的AT温度场重建算法[J].计量学报,2024,45(5):671-677,7.基金项目
国家自然科学基金(61372154) （61372154）
辽宁省博士科研启动基金(201601157) （201601157）
