Abstract: A system and methods for real-time model based vehicle structural anomaly detection are disclosed. A real-time measurement corresponding to a location on a vehicle structure during an operation of the vehicle is received, and the real-time measurement is compared to expected operation data for the location to provide a modeling error signal. A statistical significance of the modeling error signal to provide an error significance is calculated, and a persistence of the error significance is determined. A structural anomaly is indicated, if the persistence exceeds a persistence threshold value.

Abstract: A system and methods for real-time model based vehicle structural anomaly detection are disclosed. A real-time measurement corresponding to a location on a vehicle structure during an operation of the vehicle is received, and the real-time measurement is compared to expected operation data for the location to provide a modeling error signal. A statistical significance of the modeling error signal to provide an error significance is calculated, and a persistence of the error significance is determined. A structural anomaly is indicated, if the persistence exceeds a persistence threshold value.

Abstract: A system to launch and recover an Unmanned Aerial Vehicle (UAV) aircraft has a pole member attached to a deck of a ship. An arm member is attached to the pole member and extends away from the pole member in an approximately horizontal direction. The arm member is able to move rotationally and vertically on the pole member. An attachment mechanism is attached to a distal end of the arm member for holding and capturing the UAV aircraft. Momentum of the UAV aircraft causes the arm member to move rotationally around and vertically on the pole member when the UAV aircraft is coupled to the attachment mechanism.

Abstract: A system to launch and recover an Unmanned Aerial Vehicle (UAV) aircraft has a pole member attached to a deck of a ship. An arm member is attached to the pole member and extends away from the pole member in an approximately horizontal direction. The arm member is able to move rotationally and vertically on the pole member. An attachment mechanism is attached to a distal end of the arm member for holding and capturing the UAV aircraft. Momentum of the UAV aircraft causes the arm member to move rotationally around and vertically on the pole member when the UAV aircraft is coupled to the attachment mechanism.

Abstract: A method and system for detecting in-flight fault characteristics of flight control actuators is provided. Commands are sequentially sent to sets of actuators during flight in a manner that is expected to produce little or no net aircraft motion. The detection of motion indicates the possibility of a faulty actuator. If additional tests confirm the failure, the actuator is isolated and other actuators are compensated to adjust for the failed actuator, permitting continuation of safe and controllable fight by the flight crew and control for a safe landing. This isolation of the suspect failed actuator serves to prevent a possible upset of the aircraft control should the suspect actuator completely fail to a large offset condition, due to continued use during flight, a situation that may cause loss of control of the aircraft.

Abstract: A method and system for detecting in-flight fault characteristics of flight control actuators is provided. Commands are sequentially sent to sets of actuators during flight in a manner that is expected to produce little or no net aircraft motion. The detection of motion indicates the possibility of a faulty actuator. If additional tests confirm the failure, the actuator is isolated and other actuators are compensated to adjust for the failed actuator, permitting continuation of safe and controllable fight by the flight crew and control for a safe landing. This isolation of the suspect failed actuator serves to prevent a possible upset of the aircraft control should the suspect actuator completely fail to a large offset condition, due to continued use during flight, a situation that may cause loss of control of the aircraft.

Abstract: A fault diagnostics system for monitoring the operating condition of a host system, e.g., an aircraft, which includes a plurality of subsystems. The fault diagnostics system is preferably implemented in software running on a high-speed neural network processor. The fault diagnostics system constructs a neural network model of the performance of each subsystem in a normal operating mode and each of a plurality of different possible failure modes. The system preferably dynamically predicts the performance of each subsystem based upon the response of each of the neural network models to dynamically changing operating conditions, compares the actual performance of each subsystem with the dynamically predicted performance thereof in each of the normal and possible failure modes, and determines the operating condition of the host system on the basis of these comparisons.