Laser & Optoelectronics Progress, Volume. 59, Issue 8, 0815012(2022)
Multiresolution Feature Extraction of Surface Topography in Metal Fatigue Damage Process
Fig. 1. Flow chart of surface topography feature extraction in fatigue damage process
Fig. 2. Schematic diagram of 2-layer decomposition of surface topography
Fig. 3. Specimen size
Fig. 4. Experimental system
Fig. 5. Diagram of specimen surface pretreatment area
Fig. 6. 3D topography of each fatigue damage stage[18]
Fig. 7. Decomposition of gray images of each fatigue damage stage. (a) Fatigue cycle: 0; (b) fatigue cycles: 2000; (c) fatigue cycles: 4000; (d) fatigue cycles: 6000; (e) fatigue cycles 8000; (f) fatigue cycles 10000
Fig. 8. Contrast curves at the highest layer
Fig. 9. Correlation curves at the highest layer
Fig. 10. Characteristic parameter curves at the highest layer. (a) Energy; (b) homogeneity
Fig. 11. Mean value curves of contrast at the highest layer
Fig. 12. Mean value curves of correlation at the highest layer
Fig. 13. Mean value curves of energy at the highest layer
Fig. 14. Mean value curves of homogeneity at the highest layer
Fig. 15. Damage prediction results
|
Get Citation
Copy Citation Text
Tao Liu, Zhiqiang Yin, Jingfa Lei, Fangbin Wang. Multiresolution Feature Extraction of Surface Topography in Metal Fatigue Damage Process[J]. Laser & Optoelectronics Progress, 2022, 59(8): 0815012
Category: Machine Vision
Received: Aug. 17, 2021
Accepted: Oct. 13, 2021
Published Online: Apr. 11, 2022
The Author Email: Liu Tao (liutao19841015@163.com)