A conceptual study of utilizing compressive-sensing-based fan noise mode detection for aeroengine prognostic and health management

In this paper, a concept about the aeroengine fan health monitoring approach is proposed based on the compressive-sensing-based acoustic mode detection method. Utilizing only a few acoustic sensors, possible accidents inducing the change of the fan noise mode spectrum can be inferred. To enable such a concept, the array design strategy and optimization method are first studied by maximizing the incoherence of the so-called sensing matrix. The performance of the designed array is examined in both simulation and experimental studies. Then, the idea of fan noise monitoring is conceptually demonstrated in wind tunnel tests by taking into account possible accidental scenarios with foreign body intrusions. The simulation and experimental results suggest that under such circumstances remarkable changes appear in the azimuthal mode spectrum from fan noise. Finally, it is demonstrated that the fan noise variation can be successfully detected by the compressive sensing method with just six sensors. In this way, the foreign body intrusion can be further diagnosed through the combination of compressive sensing and mode detection. Overall, the results confirm the potential capability of the proposed concept for future aeroengine health monitoring applications.