Deep Learning-Based Classification of Defects in Induction Brazed Copper Joints Using Infrared Thermal Imaging for Enhanced Joint Quality Monitoring

This project will develop a new system that uses infrared cameras and artificial intelligence to automatically detect defects in copper joints made by induction brazing, a process widely used in heat pump manufacturing. By capturing and analyzing the heat patterns that appear during brazing, the system can quickly identify problems such as cracks or poor filler flow without the need for expensive and time-consuming testing. The collaboration between the University of Manitoba and the University of Aveiro will combine expertise in smart manufacturing and brazing technologies to create a prototype real-time monitoring tool. This will help industry partners improve the quality and safety of heat pumps, reduce costly rework, and support the transition to more energy-efficient and sustainable heating and cooling systems.

Faculty Supervisor:

Ahmad Naser

Student:

Partner:

University of Aveiro

Discipline:

Engineering

Sector:

Advanced Manufacturing; Artificial Intelligence

University:

University of Manitoba

Program: