Amazon
Airframe Health Monitoring System
The student team worked to develop and demonstrate the capability and benefits of a health monitoring system for a UAS airframe. They used onboard sensors and flight data to determine airframe health, predict maintenance intervals and diagnose off nominal airframe behavior. The team examined the existing sensing capability of a drone to determine potential benefits of health monitoring, explored additional sensing capabilities and the added capability of a monitoring system, and down-selected and developed a system capable of tracking the performance of an airframe component through one lifecycle.
Faculty Adviser(s)
Erik Hurlen, Associate Teaching Professor, Aeronautics & Astronautics
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