Abstract: Entity extraction is performed using a voting ensemble approach to enhance the accuracy and effectiveness of entity extraction processes. Voting ensemble weights are stored. In turn, a prediction value for a first entity is determined from multiple models that are specifically trained for entity extraction. A plurality of first entity prediction values is obtained. The model with the highest prediction value among the plurality of first entity prediction values is then selected.

Abstract: A method for optimizing a diagnostic reasoner model, for use in connection with a diagnostic system for testing a system under test of an aircraft, includes the steps of querying for a plurality of primary indicators, further querying for a plurality of supplemental indicators, and updating the diagnostic reasoner model based at least in part on the supplemental indicators. The primary indicators identify one or more potential faults in the system under test. Each supplemental indicator provides information either validating or invalidating a particular primary indicator or association of primary indicators.

Abstract: A system and method are provided for supplying electromechanical actuator (EMA) health status information to a control system. A determination is made as to whether the EMA has experienced a fault. If the EMA has experienced a fault, a fault-based position limit and a fault-based rate limit of the EMA are determined, based on the fault. A design position limit and a design rate limit of the EMA are supplied. An updated position limit of the EMA is determined based on at least the design position limit and the fault-based position limit, and an updated rate limit of the EMA is supplied based on at least the design rate limit and the fault-based rate limit.

Abstract: A system and method are provided for supplying electromechanical actuator (EMA) health status information to a control system. A determination is made as to whether the EMA has experienced a fault. If the EMA has experienced a fault, a fault-based position limit and a fault-based rate limit of the EMA are determined, based on the fault. A design position limit and a design rate limit of the EMA are supplied. An updated position limit of the EMA is determined based on at least the design position limit and the fault-based position limit, and an updated rate limit of the EMA is supplied based on at least the design rate limit and the fault-based rate limit.

Abstract: A method for optimizing a diagnostic reasoner model, for use in connection with a diagnostic system for testing a system under test of an aircraft, includes the steps of querying for a plurality of primary indicators, further querying for a plurality of supplemental indicators, and updating the diagnostic reasoner model based at least in part on the supplemental indicators. The primary indicators identify one or more potential faults in the system under test. Each supplemental indicator provides information either validating or invalidating a particular primary indicator or association of primary indicators.

Abstract: A non-linear, semi-parametric neural network-based adaptive filter is utilized to determine the dynamic speed of a rotating rotor within an induction motor, without the explicit use of a speed sensor, such as a tachometer, is disclosed. The neural network-based filter is developed using actual motor current measurements, voltage measurements, and nameplate information. The neural network-based adaptive filter is trained using an estimated speed calculator derived from the actual current and voltage measurements. The neural network-based adaptive filter uses voltage and current measurements to determine the instantaneous speed of a rotating rotor. The neural network-based adaptive filter also includes an on-line adaptation scheme that permits the filter to be readily adapted for new operating conditions during operations.

Abstract: A non-linear, semi-parametric neural network-based adaptive filter is utilized to determine the dynamic speed of a rotating rotor within an induction motor, without the explicit use of a speed sensor, such as a tachometer, is disclosed. The neural network-based filter is developed using actual motor current measurements, voltage measurements, and nameplate information. The neural network-based adaptive filter is trained using an estimated speed calculator derived from the actual current and voltage measurements. The neural network-based adaptive filter uses voltage and current measurements to determine the instantaneous speed of a rotating rotor. The neural network-based adaptive filter also includes an on-line adaptation scheme that permits the filter to be readily adapted for new operating conditions during operations.