A rapid image acquisition method for external defect inspection of battery can

During the manufacturing process, battery cans may have appearance defects such as scratches, dents, and stains. The reliability of the battery will be reduced if these defects are not detected. Machine vision based inspection methods have high inspection accuracy and stability, gradually replacing manual inspection. The efficiency of machine vision inspection method is constrained by the efficiency of image acquisition. In this paper, an image acquisition method based on magnet roller is proposed, which can realize the rapid loading and unloading of the battery cans and the high-speed image acquisition. The efficiency of the inspection system has increased from 140 per minute to 240, and the inspection accuracy reaches 99.6%.

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Publication Details

Journal
Scientific Reports
Published
2026-05-18
DOI
https://doi.org/10.1038/s41598-026-53774-z
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
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article

A rapid image acquisition method for external defect inspection of battery can

Pengfei Ji, Wei Yang, Chunfeng Huang
Scientific Reports
Industrial Vision Systems and Defect Detection
article

A rapid image acquisition method for external defect inspection of battery can

Pengfei Ji, Wei Yang, Chunfeng Huang
article en

Abstract

During the manufacturing process, battery cans may have appearance defects such as scratches, dents, and stains. The reliability of the battery will be reduced if these defects are not detected. Machine vision based inspection methods have high inspection accuracy and stability, gradually replacing manual inspection. The efficiency of machine vision inspection method is constrained by the efficiency of image acquisition. In this paper, an image acquisition method based on magnet roller is proposed, which can realize the rapid loading and unloading of the battery cans and the high-speed image acquisition. The efficiency of the inspection system has increased from 140 per minute to 240, and the inspection accuracy reaches 99.6%.

Scientific Reports
Henan University of Technology (CN), Anyang Institute of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 5%
Industrial Vision Systems and Defect Detection
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