EE 2616 will develop a non-invasive, self-powered system for detecting anomalies in HVAC Rooftop Units (RTUs). The system collects data from split-core current transformers and Type-K thermocouples installed on compressor power lines and refrigerant lines. Using these inputs, a custom fault detection algorithm -developed with ME 2616 team - compares real- time operating data to ideal performance baselines to identify abnormal conditions such as low refrigerant charge, line restrictions, short cycling, and condenser fouling. The system runs on a Raspberry Pi and uses an LTE modem for wireless data logging, remote monitoring, and real-time fault notifications, enabling a shift from reactive to preventative maintenance.

Our team collaborated with Mechanical Engineering 16 on this project.