TY - JOUR
T1 - An optimization method of planar array capacitance imaging
AU - Pan, Zhao
AU - Wang, Shan
AU - Li, Pengcheng
AU - Zhang, Yuyan
AU - Wen, Yintang
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/8/15
Y1 - 2021/8/15
N2 - Planar array capacitance imaging technology is a kind of nondestructive testing technology applied to defect detection of composite materials. In the imaging process, the image quality is often poor due to the environment noise and the ill-posed of inverse problem solving. In this paper, an image reconstruction optimization method is proposed. Based on the analysis of the sensitive region of a single pair of electrodes and the contribution of capacitance value to each solution unit, an optimization matrix which is calculated by adjusting the contribution coefficient of each capacitance value to different solution units is proposed to optimize the sensitive field. Finally, simulation and experiment results are presented to show the effectiveness of the proposed method. Through the average relative error of each pixel of the reconstructed image before and after optimization, it can be seen that the error of reconstructed images at two different positions are reduced by an average of 3.22 % and 1.62 % respectively, while verified this method can effectively improve the reconstructed image and improve the anti-noise ability of the image.
AB - Planar array capacitance imaging technology is a kind of nondestructive testing technology applied to defect detection of composite materials. In the imaging process, the image quality is often poor due to the environment noise and the ill-posed of inverse problem solving. In this paper, an image reconstruction optimization method is proposed. Based on the analysis of the sensitive region of a single pair of electrodes and the contribution of capacitance value to each solution unit, an optimization matrix which is calculated by adjusting the contribution coefficient of each capacitance value to different solution units is proposed to optimize the sensitive field. Finally, simulation and experiment results are presented to show the effectiveness of the proposed method. Through the average relative error of each pixel of the reconstructed image before and after optimization, it can be seen that the error of reconstructed images at two different positions are reduced by an average of 3.22 % and 1.62 % respectively, while verified this method can effectively improve the reconstructed image and improve the anti-noise ability of the image.
KW - Anti-noise optimization matrix
KW - Image reconstruction
KW - Nondestructive testing
KW - Planar array capacitance sensor
UR - https://www.scopus.com/pages/publications/85104082961
U2 - 10.1016/j.sna.2021.112724
DO - 10.1016/j.sna.2021.112724
M3 - 文章
AN - SCOPUS:85104082961
SN - 0924-4247
VL - 327
JO - Sensors and Actuators A: Physical
JF - Sensors and Actuators A: Physical
M1 - 112724
ER -