HeatTrack

Enhanced Reliability, Monitoring and Diagnostics of Complex Cooling Systems through Advanced Thermal Management

The project HeatTrack focuses on studying and developing optimization, monitoring and diagnostic methods and tools dedicated to complex industrial refrigeration systems.

The project develops a system-level methodology for designing cooling systems for electronics-sensitive industries.

Furthermore, cost savings, environmental impact and energy use of cooling systems are investigated to achieve optimal performance. Based on synthetic data, a diagnostic tool has been developed to detect early failures and identify abnormal operations within the cooling system and its components through data analysis and monitoring. When extended to real-world data, this innovation improves system reliability and prevents unexpected downtime.

Research on adaptive methods and tools based on machine learning and deep learning is also included in the project, enabling continuous assessment of health status, key operational events and remaining service life of cooling system components.