Defect detection and classification system for automatic analysis of digital radiography images of PM parts
Defect detection and classification system for automatic analysis of digital radiography images of PM parts
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DOI：
10.1179/0032589914z.000000000151
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发表时间：
2014-02
影响因子：
1.4
通讯作者：
Maxim Ponomarev;C. Selcuk;T. Gan;M. Amos;I. Nicholson;M. Iovea;M. Neagu;B. Stefanescu;G. Mateiasi
中科院分区：
文献类型：
--
作者：
Maxim Ponomarev;C. Selcuk;T. Gan;M. Amos;I. Nicholson;M. Iovea;M. Neagu;B. Stefanescu;G. Mateiasi
数字射线照相技术是一种很有前途的粉末冶金（PM）零件无损检测工具，其中透射X射线被记录以生成用于先进缺陷检测系统的数据。该系统的一个重要组成部分是X射线图像模式识别的数据处理平台。结合先进的降噪技术，对比度增强和图像分割。讨论了感兴趣区域中图像的配准算法，例如尺度不变特征变换（SIFT）。现代模式识别方法，如平滑，矩表示，图像对齐和光流对特征分类进行了评估。拟议的缺陷检测和分类能力，自动分析的数字射线照相图像从粉末冶金零件可能允许集成到多视图检测系统，这应该加强质量控制的粉末冶金制造和生产环境。能够以当前生产线的速度工作的缺陷检测系统对PM制造商和用户都具有极大的兴趣。
Digital radiography is a promising non-destructive testing tool for powder metallurgy (PM) parts, in which transmitted X-rays are recorded to generate data for an advanced defect detection system. An important part of this system is the data processing platform for pattern recognition in X-ray images. Combinations of advanced techniques for noise reduction, contrast enhancement and image segmentation are employed. Algorithms of registration for images in regions of interest are discussed, e.g. the scale invariant feature transform (SIFT). Modern pattern recognition methodologies such as smoothing, moment representation, image alignment and optical flow towards feature classification are evaluated. The proposed defect detection and classification capability for automatic analysis of digital radiographic images from PM parts potentially allows integration into multiple-view inspection systems, which should enhance quality control in the PM manufacturing and production environment. Defect detection systems able to work at the speed of current production lines are of great interest to both PM manufacturers and users.