3D surface defect analysis and evaluation

2008 ◽  
Author(s):  
B. Yang ◽  
M. Jia ◽  
G. J. Song ◽  
L. Tao ◽  
K. G. Harding
Keyword(s):  
Surface Defect ◽  
Defect Analysis ◽  
Analysis And Evaluation ◽  
3D Surface

Fast 3D surface defect detection with fringe projection

2020 ◽  
Author(s):  
Jiaming Qian ◽  
Shijie Feng ◽  
Yixuan Li ◽  
Tianyang Tao ◽  
Qian Chen ◽  
...  
Keyword(s):  
Defect Detection ◽  
Surface Defect ◽  
Fringe Projection ◽  
3D Surface ◽  
Surface Defect Detection

Surface Defect Analysis by Using a Novel Backside XTEM Sample Preparation Method

2006 ◽  
Author(s):  
Jian-Shing Luo ◽  
Lang-Yu Huang ◽  
Wen-Lon Gu ◽  
Jeremy D. Russell
Keyword(s):  
Sample Preparation ◽  
Specific Surface ◽  
Surface Defect ◽  
Surface Defects ◽  
Preparation Method ◽  
Defect Analysis ◽  
Sample Preparation Method ◽  
Tem Analysis ◽  
Site Specific ◽  
Electron Spectrometry

Abstract This paper demonstrates a novel method of XTEM sample preparation for site-specific surface defect analysis using backside polishing. Analysis of three different types of site-specific surface defects was demonstrated using a novel backside XTEM sample preparation method. The details of the backside XTEM sample preparation method and some examples are reported in this paper. Comparing to Auger electron spectrometry (AES) results on similar defects, more detailed and precise information is observed using TEM analysis with this method. It is therefore a complementary technique to traditional AES analysis on surface defects for contamination with atomic level concentration. From the results, the sample preparation method can produce a clean, pristine surface that is well characterized and could be reproduced, successfully.

scholarly journals An Intelligent and Confident System for Automatic Surface Defect Quantification in 3D

2015 ◽  
Vol 649 ◽  
pp. 46-53 ◽  
Author(s):  
Mitul Tailor ◽  
Jon Petzing ◽  
Michael Jackson
Keyword(s):  
Point Cloud ◽  
Surface Defect ◽  
Visual Analysis ◽  
Surface Defects ◽  
Metal Plate ◽  
Measuring Instruments ◽  
Point Cloud Data ◽  
Defect Analysis ◽  
Cloud Data ◽  
Defect Quantification

Automatic surface defect inspection within mass production of high-precision components is growing in demand and requires better measurement and automated analysis systems. Many manufacturing industries may reject manufactured parts that exhibit even minor defects, because a defect might result in an operational failure at a later stage. Defect quantification (depth, area and volume) is a key element in quality assurance in order to determine the pass or failure criterion of manufactured parts. Existing human visual analysis of surface defects is qualitative and subjective to varying interpretation. Non-contact and three dimensional (3D) analyses should provide a robust and systematic quantitative approach for defect analysis. Various 3D measuring instruments generate point cloud data as an output, although they work on different physical principles. Instrument’s native software processing of point cloud data is often subject to issues of repeatability and may be non-traceable causing significant concern with data confidence.This work reports the development of novel traceable surface defect artefacts produced using the Rockwell hardness test equipment on flat metal plate, and the development of a novel, traceable, repeatable, mathematical solution for automatic defect detection and quantification in 3D. Moreover, in order to build-up the confidence in automatic defect analysis system and generated data, mathematical simulated defect artefacts (soft-artefact) have been created. This is then extended to a surface defect on a piston crown that is measured and quantified using a parallel optical coherence tomography instrument integrated with 6 axis robot. The results show that surface defect quantification using implemented solution is efficient, robust and more repeatable than current alternative approaches.

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