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http://dx.doi.org/10.21219/jitam.2022.29.6.013

Analysis of Secondary Battery Based on Image Processing of Computed Tomography  

Jea-Seok Oh (Department of Robotics Engineering, Hoseo University)
Sang-Yeol Lee (Department of Mechanical Engineering, Hansung University)
Yoon-Gi Yang (Department of Information Telecommunication Engineering, The University of Suwon)
Keun-Ho Rew (Department of Robotics Engineering, Hoseo University)
Publication Information
Journal of Information Technology Applications and Management / v.29, no.6, 2022 , pp. 13-21 More about this Journal
Abstract
In this study, we presented a method to inspect the mechanical defects of 4680 type lithium-ion batteries through image processing method. The raw X-ray images are filtered with CLAHE, then Radon inverse transformations are calculated to reconstruct 3D computed tomography of the battery. Using Haar-cascade, the ROI is targeted automatically, and the template matchings are applied twice. The variations of contrast between template and background show the appropriate values for detecting tabs. It was shown that the proposed algorithm can detect all the tab inside the battery and the distances between tabs. Finally, we successfully found the geometrical defects of battery.
Keywords
Secondary battery; Computed tomography; Machine vision; Failure detection;
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