LaserMon Toolbox
Sensor fusion technique for laser-based 3D print monitoring, including scripts for spatiotemporal data synchronization;
Description:
This repository provides code templates for high-speed sensor fusion in laser-based additive manufacturing. It demonstrates how to fuse data from slow, high-resolution sensors with fast, low-resolution sensors using an adaptive weight model, running at 100 kHz. The code is intended as a template for adaptation to specific use cases.
The repository includes:
Preprocessing: Scripts for synchronizing sensor data and calibrating cameras.
Training: Code for adaptive weight models and creating training sets.
Inference: C code for high-speed inference with detailed comments.
Two use cases are covered: metal laser powder bed fusion (SLM) and polymer selective laser sintering (SLS).
More information:
Enrichment project: Improve the 3D printing stability & performance of laser-based polymer manufacturing
Responsible Research Lead: Dries Verhees (Research engineer - FM), Brian Booth (Research associate - UGent), Pieter-Jan Delvaux (Research engineer) and Stijn Helsen (Research engineer)
Authors: Brian Booth (UGent)
Programming Language: C & Python
Link to the repository: GitHub - bgbooth/LaserMon: LaserMon - Templates for edge-AI sensor fusion for laser-based additive manufacturing
Categories: Sensor fusion, additive manufacturing and adaptive weight model