This study proposed a damage identification method compared with the existing ones,based on relative curvature difference and frequency perturbation theory,showing sensitivity to local damage by changes in the curvatu...This study proposed a damage identification method compared with the existing ones,based on relative curvature difference and frequency perturbation theory,showing sensitivity to local damage by changes in the curvature mode and high recognition accuracy of frequencies.Considering the relative curvature difference as a damage index,numerical simulation is used for a simply supported beam under single and multiple damage conditions for different damage degrees.The damage is located according to the curvature mode curves,and the damage degree is qualitatively determined.Based on the perturbation theory,the damage equations are established by the changes between frequencies before and after damage,and the damage localization and degree are verified and determined.Effectiveness of the proposed method for identifying damage at different conditions is numerically investigated.This method potentially promotes the development of damage identification of beam structures.展开更多
Image super-resolution methods-based existing edge indicating operators—namely Gauss curvature,mean curvature and gradient-cannot effectively identify the edges,ramps and flat regions and suffer from the loss of fine...Image super-resolution methods-based existing edge indicating operators—namely Gauss curvature,mean curvature and gradient-cannot effectively identify the edges,ramps and flat regions and suffer from the loss of fine textures.To address these issues,this paper presents a fractional anisotropic diffusion equation based on a new edge indicator,named fractional-order difference curvature,which can characterize the intensity variations in images.We introduce the frequency-domain definition for fractional-order derivative by the Fourier transform,which is easy to implement numerically.The new edge indicator is better than the existing edge indicating operators in distinguishing between ramps and edges and can better handle the fine textures.Comparative results for natural images validate that the proposed method can yield a visually pleasing result and better values of MSSIM and PSNR.展开更多
基金This study is supported by the National Natural Science Foundation of China under Grant No.51278420the Natural Science Foundation of Shaanxi Province under Grant No.2017JM5021.
文摘This study proposed a damage identification method compared with the existing ones,based on relative curvature difference and frequency perturbation theory,showing sensitivity to local damage by changes in the curvature mode and high recognition accuracy of frequencies.Considering the relative curvature difference as a damage index,numerical simulation is used for a simply supported beam under single and multiple damage conditions for different damage degrees.The damage is located according to the curvature mode curves,and the damage degree is qualitatively determined.Based on the perturbation theory,the damage equations are established by the changes between frequencies before and after damage,and the damage localization and degree are verified and determined.Effectiveness of the proposed method for identifying damage at different conditions is numerically investigated.This method potentially promotes the development of damage identification of beam structures.
基金This work was supported by National Natural Science Foundation of China(No.61701060)Major Project of Fundamental Science and Frontier Technology Research of Chongqing CSTC(Grant Nos.cstc2015jcyjBX0124 and cstc2015jcyjBX0090)+1 种基金Chongqing Research Program of Basic Research and Frontier Technology(No.cstc2017jcyjAX0007)Scientific and Technological Research Program of Chongqing Municipal Education Commission(No.KJ1600410).
文摘Image super-resolution methods-based existing edge indicating operators—namely Gauss curvature,mean curvature and gradient-cannot effectively identify the edges,ramps and flat regions and suffer from the loss of fine textures.To address these issues,this paper presents a fractional anisotropic diffusion equation based on a new edge indicator,named fractional-order difference curvature,which can characterize the intensity variations in images.We introduce the frequency-domain definition for fractional-order derivative by the Fourier transform,which is easy to implement numerically.The new edge indicator is better than the existing edge indicating operators in distinguishing between ramps and edges and can better handle the fine textures.Comparative results for natural images validate that the proposed method can yield a visually pleasing result and better values of MSSIM and PSNR.