Project Details
Researchers use airborne sensors and machine learning to measure risk to different components of the electric grid and monitor their functioning. The Grid Communications and Security Group develops and tests sensor packages for deployment on drones, high-altitude balloons, and high-altitude, long endurance aircraft. The group has its own drone flight operations team.
This airborne sensing capability can be used to find faulty or damaged power electronics equipment or transmission lines. Thermal, audio and radio frequency sensors can detect fire risks such as electrical arcing, particularly in remote areas that are difficult to access.
The Grid Communications and Security Group combines development of drone-mounted thermal and audio sensors with machine learning algorithms to analyze sensor readings and flag anomalies. The results enable utilities and emergency responders to prevent wildfires by recognizing failing or overheated equipment early; track wildfires as they move; and reduce wildfire damage to the electric grid.
Researchers have also assessed sensor platforms for different wildfire-related applications, such as search and rescue. Using aerial sensors for some detection and tracking tasks reduces risk to wildland firefighters. The project could potentially save lives and homes in addition to preventing regional blackouts.
