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    机器视觉技术在评定DWTT试样断口中的应用

    Application of Machine Vision Technology in Evaluating the Fracture Surface of DWTT Specimens

    • 摘要: 结合管线钢DWTT试样断口剪切面积分数pSA指标的评定步骤与要求,介绍了机器视觉识别与图像测量分析技术的实践应用.其中有效净截面的确定,大画幅、大景深、高分辨率成像系统以及Gabor滤波器-聚类分析图像处理技术是机器视觉技术的关键.实际应用结果表明:采用机器视觉自动图像测量技术,可显著提高pSA指标的评测效率和结果的可重复性.

       

      Abstract: Towards the standardized procedure and requirement for rating the percent of shear area,i.e.pSA of DWTT specimens from pipeline steels,the machine vision technology and its application in the measurement and analysis from fractorgraphy image were introduced.The definition of valid measuring area for rating pSA,imaging system with large field of vision,large focus depth and high resolution,and suitable image analyzing and treatment algorithm as Gabor filter-cluster analysis are crucially relevant to the high quality of machine vision for rating pSA.The practical application results show that rating of pSA index could be performed more efficiently and reproducibly with the help of automatic measurement on images by machine vision technology.

       

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