Researchers at CAPS and Georgia Tech collaborate to detect faults in superconducting cables using machine learning
In a new study, engineering researchers are developing a novel machine learning tool that may increase the reliability of high-temperature superconductor (HTS) power systems. The method finds early indicators of series faults in HTS cables.
High-temperature superconductor power systems can carry 100 times more electricity than conventional wires. They are lightweight and require less space to power electric aircraft and ships.

