Film Defects of Lithium Battery Recognition Based on Brightness and One-against-All Support Vector Machine

Gong Chen; Xi Fang Zhu; Qing Quan Xu; An Cheng Xu; Hui Yang

doi:10.4028/www.scientific.net/AMM.462-463.155

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 462-463Film Defects of Lithium Battery Recognition Based...

Film Defects of Lithium Battery Recognition Based on Brightness and One-against-All Support Vector Machine

Abstract:

Lithium battery film on-line defect recognition system is realized based on industrial charge-coupled device (CCD) to improve quality. Otsu algorithm is adopted for threshold instead of traditional method. Area of defect is sorted to get the largest defect and geometry and projective is extracted from image. Film defects of lithium battery recognition is realized based on Brightness Judgment and One-against-all support vector machine (OAA-SVM). Experiment results show that these methods are effective and feasible, the accuracy can reach 90%.

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Periodical:

Applied Mechanics and Materials (Volumes 462-463)

Pages:

155-158

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.462-463.155

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Online since:

November 2013

Authors:

Gong Chen*, Xi Fang Zhu, Qing Quan Xu, An Cheng Xu, Hui Yang

Keywords:

Lithium Battery, Recognition, Support Vector Machine (SVM), Threshold

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* - Corresponding Author

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