Video Interpolation-Based Multi-Source Data Fusion Method for Laser Processing Melt Pool
Source abstract
Abstract
In additive manufacturing processes, the metal melt pool is decisive for processing quality. A single sensor is incapable of fully capturing its physical characteristics and is prone to data inaccuracies. This study proposes a multi-sensor monitoring solution integrating an off-axis infrared thermal camera with an on-axis high-speed camera to address this issue; a multi-source data pre-processing procedure has been designed, a multi-source data fusion method based on video frame interpolation has been developed, and a self-supervised training strategy based on transfer learning has been introduced. Experimental results indicate that the proposed data fusion method can eliminate temperature anomalies caused by single emissivity and droplet splashing, generating highly credible fused data and significantly enhancing the stability of metal additive manufacturing and the quality of parts.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Image Fusion Techniques · Advanced Image Processing Techniques · Image Enhancement Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Key Laboratory of Featured Metal Materials and Life-Cycle Safety for Composite Structures, Guangxi University, Nanning 530004, China
Institute of Laser Intelligent Manufacturing and Precision Processing, School of Mechanical Engineering, Guangxi University, Nanning 530004, China
Funding
National Key R&D Program of China · Key R&D Program of Guangxi Province · Guangxi Natural Science Foundation
References (33)
Show source-provided references
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