Name
Abstract | ||
|---|---|---|
In order to improve efficiency and precision of nondestructive testing, a nondestructive flaw detection system based on intelligent robot is described. The developed system on 4-dof industrial robot can perform detection in three-dimensional space and the adaptive-network-based fuzzy inference system has been adopted to improve inspection adaptability. A color image segmentation algorithm and an improved adaptive region growing algorithm were proposed and proved to be effective in defect detection. Actual results indicate that the developed system has advantages of good stability and high precision. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-02937-0_14 | Studies in Computational Intelligence |
Keywords | Field | DocType |
nondestructive flaw detection,machine vision,robot | Adaptability,Computer vision,Machine vision,Computer science,Intelligent robots,Nondestructive testing,Industrial robot,Color image segmentation,Artificial intelligence,Robot,Fuzzy inference system | Conference |
Volume | Issue | ISSN |
226 | 14 | 1860-949X |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chen Zhi-Guo | 1 | 1 | 2.04 |
| XU Wen-bo | 2 | 2 | 2.44 |