光学精密工程2013，Vol.21Issue(4)：1062-1068,7.DOI:10.3788/OPE.20132104.1062
压缩感知在电容层析成像流型辨识中的应用
Application of compressed sensing to flow pattern identification of ECT
摘要
Abstract
In view of lower recognition rates of traditional methods in the flow pattern identification of Electrical Capacitance Tomography (ECT) , a identification method for the ECT based on Compressed Sensing (CS) was put forward. Firstly, measurement capacitance vectors obtained by an ECT system were normalized and represented as a sparse linear combination of training sample set in an over complete dictionary. Then,the random Gaussian matrix was taken as the measurement matrix to sample from the test and standard samples respectively,and the signal reconstruction algorithm based on the CS was used to solve the optimization problem of L0 norm for the sparse representation of each sample on the training sample set. The linear correlation coefficient between the sparse solutions of samples to be tested and the standard samples are calculated to determine the classification of flow pattern. The simulation experiment results of typical flow patterns indicate that the flow pattern identification rates under absence of noise,and signal to Noise Ratios(SNRs) of 40 db and 20 db are 100%, 99. 25% and 98. 12% respectively. It concluds that the flow pattern identification method proposed has high ef- ficiency and accuracy and a good noise immunity, which also provides a new method for the flow pattern identification of ECT.关键词
电容层析成像/压缩感知/流型辨识/稀疏表示/相关系数Key words
Electrical Capacitance Tomography(ECT)/ Compressed Sensing(CS)/ flow pattern identification/ sparse representation/ correlation coefficient分类
信息技术与安全科学引用本文复制引用
吴新杰,黄国兴,王静文..压缩感知在电容层析成像流型辨识中的应用[J].光学精密工程,2013,21(4):1062-1068,7.基金项目
辽宁省自然科学基金资助项目(No.20102082) （No.20102082）
