Case Research on Improving the Precision of Cell Quality Detection by 3D Reconstruction Measurement Algorithm
This paper introduces the solutions for three kinds of scenarios in the OH detection and Gap detection of cells by X-Ray optical imaging technology,such as the image is blurred and can not be distinguished by quality inspection,OH detection and Gap detection can not be completed at the same time,and ultra-thick cell detection is abnormal.In this paper,X-Ray high dynamic range image enhancement algorithm solves the problem of image blur.The 3D reconstruction measurement algorithm is used to realize the synchronization of OH detection and Gap detection,and it fuses Gap features to improve the OH detection precision.Aiming at the online quality inspection of ultra-thick cells,AI algorithm is used to increase the original image information,improve the quality of image preprocessing,and enhance the profile of ultra-thick cell electrode sheets and the characteristics of electrode sheet end points,and it solves the problem of signal attenuation caused by X-Ray penetration of ultra-thick cells.These solution are application of"Time-sharing Stroboscopic 3D Reconstruction Measurement Algorithm"to solve the problem that the simple optical algorithm can not quantify the height of the defect morphologically.