welding groove mapping: image acquisition and processing on shiny surfaces - visapp
TRANSCRIPT
Welding Groove Mapping:Image Acquisition and Processing on Shiny
SurfacesPresenter : Jônata T. Carvalho
Authors: Cristiano R. Steffens, Bruno Q. Leonardo, Sidnei Carlos S. Filho, Valquiria Hüttner, Vagner S. Rosa, Silvia Silva C. Botelho
Federal University of Rio Grande – FURGComputational Sciences Center – C3
11°International Conference on Computer Vision Theory and Applications - VISAPP 2016
Motivation
• Manual process affects the quality of the weldo Reworko Material wasteo Weak and breakable final producto Reproducibility and regularity
• The human sideo Welding is unhealthy – ergonomy, heat and fumeso Laborious and repetitive task
Prior approaches for welding process automation
• We can highlight three main approaches:oA combination of structured illumination laser and camera,
as used in Kawahara (1983), Drews et al. (1986), Liu (2010), Zhang et al. (2014) and De Xu (2004);
oA touch sensor based approach as in Kim and Na (2000);oTechniques where the arc current feedback is explored, as
in Dilthey and Gollnick (1998) and Halmøy (1999);
Typical Setup of a Linear Welding System
Figure 1 – Typical linear welding robot installation
The BUG-O MDS Welding Robot
• Robust Modular Roboto Rails and Carriageso Linear Weavero Pendulum Weaver
• Can be used on a large variety of surfaces• Able to make different welding seams• Weldor adjusts the linear rail and the parameters in runtime
The BUG-O MDS Welding Robot
Figure 2 – Bug-o MDS welding robotSource : BUG-O Systems
Proposed Vision-based Measurement System
Figure 8 – High-level architecture of a vision-based measurement system
Proposed Vision-based Measurement System
Figure 3 – Image acquisition setup Figure 4 – Welding groove properties
Machine Vision System
• Groove measurement and modeling
• Custom LED lighting system
• Terasic D5M Camera + Altera DE0-Nano FPGA
• Full control of the camera registers
• HW & SW integration
• USB and Bluetooth communication
• Embedded image processing
Machine Vision System
Figure 7 – Altera DE0-Nano FPGA.Source: Altera
Figure 6 – Terasic D5M CMOS Camera
Source: AlteraFigure 5 – Illumination
Debevec’s HDR image composition
Figura 9 – HDR Input images
Processing in the VBM System
Figura 10 – Single exposure Figura 11 – HDR composed
Figura 12 – Line segment detection Figura 13– Final groove modeling
Machine Vision System (SW)
• Contrast enhancemento Multi-exposure composition (Debevec)o Normalization and Histogram Equalization
• Noise reductiono Gaussian, Mean, Median
• Edge and line detectiono Canny + Hough, Fast LSD, Edlines, PPHT
• Heuristics
• Pixel to metric unit conversion
Controll System Implementation (HW)
Figure 14 – Overview of the digital control system
Results of the Measurement System (Best-Case)
Gap B - Plate Bottom Gap A - Plate TopMean Error Std. Dev. Mean Error Std. Dev.0.143mm 0.084mm 0.780mm 0.157mm
Figure 15 – Measured/position Figure 16 – Repeatability
Table 1 – Gaussian filtering + LSD by Von Gioi (2012)
Method Comparisson – Gap A
Figure 17 – Error and Std. Deviation in millimeters for Gap A (smaller is better)
Method Comparisson – Gap B
Figure 18 – Error and Std. Deviation in millimeters for Gap B (smaller is better)
Conclusion
• End-to-end embedded welding system prototype
• Integrates different techniques to perform dimensional measurement of thick steel plate bevel groove
• Computer Vision applied to reflective surfaces, without the need of structured light, polarized lenses or complex optical arrangements
• Extracted dimensions can be mapped in settings for the robotic welding equipment
Future Work
• Explore lighting options, noise suppression algorithms and image composition techniques to improve the system
• Bilateral and L0 gradient minimization filtering (not trivial to implement)
• Compare Debevec’s multi-exposure composition to other approaches that minimize the computational cost and are hardware-friendly
• Online application - mapping while welding
• Deep learning based image restoration
• Produce a general purpose welding workcell
Welding Groove Mapping:Image Acquisition and Processing on Shiny
Surfaces
Federal University of Rio Grande – FURGComputational Sciences Center – C3