Wenru Fan, Chi Wang^*

Structural Durability & Health Monitoring, Vol.14, No.4, pp. 303-314, 2020, DOI:10.32604/sdhm.2020.011009

Abstract Due to the widespread use of carbon fiber reinforced polymer/plastic (CFRP), the nondestructive structural health monitoring for CFRP is playing an increasingly essential role. As a nonradiative, noninvasive and nondestructive detection technique, planar electrical capacitance tomography (PECT) electrodes array is employed in this paper to reconstruct the damage image according to the calculated dielectric constant changes. The shape and duty ratio of PECT electrodes are optimized according to the relations between sensitivity distribution and the dielectric constant of different anisotropic degrees. The sensitivity matrix of optimized PECT sensor is more uniform as the result shows, because the sensitivity of insensitivity… More >

Caifeng Cheng^1,2, Deshu Lin^3,*

Journal on Internet of Things, Vol.2, No.1, pp. 47-54, 2020, DOI:10.32604/jiot.2020.09117

Abstract In this paper, the observation matrix and reconstruction algorithm of compressed sensing sampling theorem are studied. The advantages and disadvantages of greedy reconstruction algorithm are analyzed. The disadvantages of signal sparsely are preset in this algorithm. The sparsely adaptive estimation algorithm is proposed. The compressed sampling matching tracking algorithm supports the set selection and culling atomic standards to improve. The sparse step size adaptive compressed sampling matching tracking algorithm is proposed. The improved algorithm selects the sparsely as the step size to select the support set atom, and the maximum correlation value. Half of the threshold culling algorithm supports the… More >

I-Yao CHAN, Chein-Shan Liu, Weichung Yeih

The International Conference on Computational & Experimental Engineering and Sciences, Vol.20, No.2, pp. 53-54, 2011, DOI:10.3970/icces.2011.020.053

Abstract In this study, we adopt the fictitious time integration method to treat the image reconstruction problem. The distorted image is considered as a result of diffused data from the initial perfect image by using a nonlinear diffusion equation. The image reconstruction problem then becomes an inverse problem by using the data in the final time to recover the data in the initial time. This inverse problem is known as the backward in time nonlinear diffusion problem which is highly ill-posed. We propose to use the fictitious time integration method to tackle this highly ill-posed image reconstruction problem and it is… More >