基于神经网络的冷轧带钢表面缺陷检测

Surface Defects Inspection of Cold Rolled Strips Based on Neural Network

带钢表面缺陷是影响带钢质量的重要因素,对带钢进行表面缺陷检测对提高带钢质量具有重要意义。传统人工检测的方法往往不能得到令人满意的检测结果。为此,提出了采用基于前馈神经网络(FFN)的方法对在线带钢的表面缺陷进行检测,检测结果令人满意,表明了该方法的有效性。

Defects on the surface of steel strips are main factors to evaluate quality of steel strips, and surface inspection is of great importance to improve quality of steel strips. Traditional surface inspection by human inspectors is far from satisfactory. In this paper, an approach to detect real-time surface defects of steel strips based on feed-forward neural network（FFN） is discussed. The experiments show that the method is effective.