...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Key Engineering Materials >Detection and Recognition of Steel Ball Surface Defect Based on MATLAB
【24h】

Detection and Recognition of Steel Ball Surface Defect Based on MATLAB

机译：基于MATLAB的钢球表面缺陷检测与识别

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Taking MATLAB as the experimental platform, the detection and recongnition method of steel ball surface defect is put forward. With the method, we could determine whether there are surface defects or not, and identify the types of defects. The process of detection and recognition is as follows: Firstly, two-time wavelet de-noising treatment of the steel ball image is achieved by means of ecomposition, quantization of threshold and recongnition of Sym4 wavelet function, afterward, many collected noise of the steel ball image is reduced effectively. Secondly, the de-noised image is preprocessed and then we can calibrate the boundary of the defects accurately, which is used to extract the characteristic parameters of defects. Thirdly, the types of defects of steel ball are judged, and the process of pattern recognition is reasonablely designed by putting forward the shape parameter F. combined with the characteristic parameters of the defects. Lastly, the feasibility and validity of the detection and recongnition algorithm arc verified by lots of analysis about experimental results especially the analysis on the experimental results comparing with the given data.
机译：以MATLAB为实验平台，提出了钢球表面缺陷的检测与识别方法。使用该方法，我们可以确定是否存在表面缺陷，并确定缺陷的类型。检测和识别的过程如下：首先，通过对钢球图像进行合成，阈值量化和Sym4小波函数的识别，实现了对钢球图像的二次小波去噪处理，其后，大量采集到的钢噪声球像有效减少。其次，对降噪后的图像进行预处理，然后可以准确地校准缺陷的边界，以提取缺陷的特征参数。第三，判断钢球的缺陷类型，结合缺陷的特征参数，提出形状参数F.，合理设计图案识别过程。最后，通过对实验结果的大量分析，特别是对实验结果与给定数据的比较分析，验证了检测识别算法的可行性和有效性。

著录项

  • 来源
    《Key Engineering Materials》 |2009年第2009期|603-608|共6页
  • 作者

    Yongzhi Lin; Xianli Liu; Haiying Han; Yiwen Wang; Peng Wang;

  • 作者单位

    Mechanical & Power Engineering College, Harbin University of Science &Technology, Harbin, China, 150080;

    Mechanical & Power Engineering College, Harbin University of Science &Technology, Harbin, China, 150080;

    Mechanical & Power Engineering College, Harbin University of Science &Technology, Harbin, China, 150080;

    Mechanical & Power Engineering College, Harbin University of Science &Technology, Harbin, China, 150080;

    Mechanical & Power Engineering College, Harbin University of Science &Technology, Harbin, China, 150080;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    wavelet de-noising; defect detection; pattern recognition; shape parameter; MATLAB;

    机译：小波去噪缺陷检测;模式识别;形状参数的MATLAB;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号