Thesis Format
Monograph
Degree
Master of Engineering Science
Program
Mechanical and Materials Engineering
Supervisor
Tutunea-Fatan, Ovidiu-Remus
2nd Supervisor
Bordatchev, Evgueni
Affiliation
National Research Council of Canada
Co-Supervisor
Abstract
Surface polishing by laser remelting is a developing surface finishing method utilizing the heat of a laser to create a moving melt pool, resulting in a more uniform surface topography. The melt pool's stability significantly influences the process's effectiveness, as instability leads to the formation of non-uniformities and reduced uniformity. To monitor the melt pool state, two coaxially mounted thermographic cameras, sensitive to short-wave infrared (SWIR) and near-infrared (NIR) wavelengths, were integrated into the laser scanner-based polishing system for data collection. Analysis revealed that the NIR range captured a wider range of process dynamics due to the scanner optics' effects on transmitted melt pool emission. Using the NIR data, novel classification methods capable of identifying melt pool stability and undesired surface features were developed and demonstrated in an industry-relevant process monitoring program. This enables the estimation of surface non-uniformities for tracking, parameter adjustments, and correction, enhancing surface polishing precision.
Summary for Lay Audience
Surface polishing by laser remelting is a developing material finishing technique for achieving a smoother and more uniform surface finish. This method uses a focused laser beam to create a small, moving melt pool that redistributes the material, resulting in an improved surface. However, the uniformity of the final surface heavily relies on the stability of the rapid melting and solidification occurring. Fluctuations can lead to undesirable surface features, affecting the overall quality of the polished surface. To monitor and detect the state of the laser remelting process, thermographic information related to material temperature can be used. In this study, two thermographic cameras were added to the system of mirrors and lenses that direct the laser beam to capture process data with high resolution. These cameras were sensitive to two different wavelength ranges, the short-wave infrared (SWIR) and the near-infrared (NIR). Methods of analysis were used to evaluate the remelted surface for non-uniformities, and the thermographic data for regions of instability. Both sets of information could then be compared to identify correlations. After analyzing the data, it was found that the NIR range was more effective at capturing comprehensive process information potentially due to the system’s optical components limiting the SWIR information. Using the recorded NIR data, a classification method capable of identifying melt pool and surface formation stability was created using the total intensity of each captured frame. In real-time, the system identifies regions of the surface affected by melt pool instabilities, enabling non-uniformity tracking, quick adjustments of process parameters, or feature correction to achieve a more uniform and improved surface topography.
Recommended Citation
Beyfuss, Daniel, "Experimental analysis and online monitoring/classification of surface formation uniformity and laser remelting process stability using NIR and SWIR emission imaging" (2023). Electronic Thesis and Dissertation Repository. 9508.
https://ir.lib.uwo.ca/etd/9508