Abstract
Propulsion systems are exposed to environmental ingestion hazards that can cause significant damage and decrease performance. Particles are ingested in a wide range of flight environments that can cause immediate engine failure or long-term damage. An accurate measurement technique has been developed to quantify particle ingestion and aid engine health monitoring. This sensor utilizes scattering and extinction techniques along with machine learning models to measure particle characteristics based on a robust and versatile library. The capabilities of this sensor have been demonstrated using solid quartz particles on the Rolls-Royce M250-C20B particle ingestion turboshaft test engine. To the authors' knowledge, this work presents the first demonstration and validation of optical solid particle sensing in a turbine engine. CSPEC sand (Mil-E-5007C) was ingested for the validation test at two different feed rates using a sand feeder. The sand concentrations were 45 mg/m3 and 22 mg/m3. The sensor outputs the particle characteristics of aspect ratio (AR), size distribution (σ), Sauter mean diameter (D32), and the particle mass flowrate. The Sauter mean diameter and mass flowrate of ingested sand were calculated using the machine learning model outputs and validated by independent measurements. The sensor produced a 0.1 g/min RMS error compared to the validation measurement.
