Abstract: Systems and methods for health monitoring of complex systems are disclosed. In one embodiment, a method includes receiving a plurality of signals indicative of observation states of plurality of operating variables, performing a combined probability analysis of the plurality of signals using a diagnostic model of a monitored system to provide a health prognosis of the monitored system, and providing an indication of the health prognosis of the monitored system. In some embodiments, the monitored system may be an onboard system of an aircraft.

Abstract: Described is a system for health prognosis of a component based on the use of a graphical probabilistic model. The model comprises a layer of at least one component node representing the health of a component, a layer of at least one health observation node representing a health observation, and a layer of at least one usage node representing a usage observation. Additionally, the system is configured to collect component failure data, which is used in generating normalized failure histograms. The histograms provide failure densities for component and health observation failures. The system also computes at least one parameter for the model using component and health observation failure densities. A component prognosis is computed based on present observation of system usage and health with a history of past observation using a standard reasoning engine.

Abstract: Systems and methods for health monitoring of complex systems are disclosed. In one embodiment, a method includes receiving a plurality of signals indicative of observation states of plurality of operating variables, performing a combined probability analysis of the plurality of signals using a diagnostic model of a monitored system to provide a health prognosis of the monitored system, and providing an indication of the health prognosis of the monitored system. In some embodiments, the monitored system may be an onboard system of an aircraft.