Aircraft Anomaly Prognostics

Ridgetop Group will leverage its proven Electromechanical Actuator (EMA) prognostics methodology to develop an advanced model-based actuator prognostic reasoner (MAPR). Ridgetop's concept is a self-contained, embedded prognostic reasoner with a passive connection to common avionic data busses. By monitoring actuator health in real time and providing early warning of incipient fault conditions, the proposed MAPR would enable condition based maintenance (CBM) of critical avionic flight control systems and support safer, more reliable next generation air transportation. The novel approach will effectively decouple the passive prognostic reasoner from the target flight control system, or actuator, and will support multiple avionic data bus interfaces, such as MIL-STD-1553, easing adoption, validation, integration, and support. Potentially, a single MAPR could monitor multiple flight control systems, reducing overall sensor costs. Furthermore, an embedded MAPR implementation with field upgradeable firmware would support evolving interface standards and prognostic health measurement capabilities. Finally, the proposed MAPR architecture is ideally suited for hardware-in-the-loop (HIL) testing, which dramatically accelerates technology readiness and commercial introduction.

Ridgetop is currently working with a large German automaker in applying power prognostics technology area for hybrid vehicle applications. This modeling approach is applicable to the next generation of hybrid and electric vehicles with EMA drive trains. Ridgetop is also working with Japanese automotive firms and subsystem suppliers. Firms working in the field of Integrated Vehicle Health Monitoring (IVHM) of precision critical robots with maintenance models can reduce downtime of assembly robots. Ridgetop has also met with engineers who design high speed subway train station turn-style ticket-taking machines and held discussions with key firms providing such equipment. In these cases, there is a strong return-on-investment (ROI) associated with minimizing unplanned downtime and the early detection of anomalies is critically important.

Electromechanical Actuator (EMA) systems can reduce weight in airborne vehicles. This modeling approach can be extended to any EMA system, including exploration robot limbs, thrust vector controllers, landing gear, and aircraft maneuvering control surfaces. Dynamic modeling that incorporates environmental conditions will reduce the likelihood of poor decisions based on bad sensors.

This is early/mid-stage (TRL 6) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.

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