Acoustic Cameras for Health Monitoring of Next-Generation Aircraft

Persimia proposes to develop a new type of acoustic-based health monitoring system for next-generation aircraft. The system will leverage microphone arrays throughout the aircraft to detect and pinpoint anomalies in the fuel system (for liquid hydrogen-powered aircraft) or electrical or propulsive components (in electric or fuel cell-powered aircraft). The two main components of the system will be the microphones themselves, and a machine learning algorithm that will process the data and identify anomalies. Importantly, the acoustic processing algorithm will leverage data not only from the microphone arrays, but also from the flight computer so that the acoustic background at different thrust settings and flight conditions can be accounted for. The project seeks to develop acoustic fault detection systems for aircraft that can be applied to electrically-driven, fuel cell-driven, and eventually liquid hydrogen-powered aircraft. By mounting microphones in appropriate locations, different components of the system can be monitored, and thus the same overall concepts of acoustic monitoring combined with filtering and anomaly detection can be applied to fault detection for an electric motor, and leak detection for a liquid hydrogen tank. The overall goal, therefore, is to develop acoustic fault detection technology for aircraft so that it can be widely applied as the industry evolves toward new types of sustainable fuel sources. Phase I funding will be used to develop microphone array designs for fault detection in both eVTOL aircraft and liquid hydrogen-powered aircraft. The team will also identify the structure of fault detection algorithms, create simple lab-based experimental case studies, and engage in initial customer outreach. The market for this technology could be aircraft OEMs, the military, NASA, and others interested in implementing fault detection on next-generation aircraft.