SBIR/STTR Award attributes
Gas turbine engines with prolonged exposure to sand and dust are susceptible to component and performance degradation and ultimately engine failure. Our proposed sensor will use an innovative hybrid and complimentary discrimination approach to incorporate material identification along with capability of size, size distributions, and concentration while maintaining the same form factor of the current sensor platform. We will use a systematic test matrix to characterize and demonstrate advanced prototype sensors’ capabilities. Our sensor can be integrated into an engine health management system to allow early warning of excessive dust loading and enhance durability of an aeroturbine engine.