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基于LVQ神經網絡的冷軋帶鋼表面缺陷分類方法

Classification of surface defects for Cold rolled strips based on LVQ neural network

  • 摘要: 將LVQ神經網絡用于冷軋帶鋼表面缺陷的自動分類中,解決了以往分類方法在多缺陷模式類型情況下耗時多和準確率低的問題.對現場采集到的14種主要缺陷類型進行了實驗.實驗結果表明,基于LVQ神經網絡的分類器訓練與分類的時間短,在多缺陷種類分類的過程中準確率能得到保證.

     

    Abstract: A new method which uses LVQ neural network in the automatic classification of surface defects for cold rolled strips was presented. The problems of long time and low accuracy in the classification of multi-defect pattern types with some traditional classification algorithms were resolved. Tested by 14 main defect types collected from online data, the results demonstrated that the method of surface defects for cold rolled strips based on LVQ neural network spent little time during training and classifying, and its accuracy could be assured on the recognition process of multi-defect pattern types.

     

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