Systems and methods of aircraft thrust management are provided. For example, a propulsion system for an aircraft comprises a fuel cell assembly comprising a fuel cell, a turbomachine, and a controller comprising memory and one or more processors. The memory stores instructions that, when executed by the one or more processors, cause the propulsion system to perform operations including receiving data indicative of a propulsion system thrust discrepancy and modifying an output of the fuel cell in response to receiving data indicative of the propulsion system thrust discrepancy. Modifying the fuel cell output may include modifying output products, an electrical power output, or both of the fuel cell to balance the thrust provided by the propulsion system.

A method, apparatus, system, and computer program product for managing a vapor cycle machine. Data is received for the vapor cycle machine in an aircraft. The data comprises a pressure, a temperature, and a speed for a set of compressors in the vapor cycle machine. A ratio of the pressure to the temperature is determined for the set of compressors that ran during a flight of the aircraft. A set of actions is performed when the ratio of the pressure to the temperature for the set of compressors that ran during the flight of the aircraft exceeds a threshold more than a selected number of times over a range of flights for the aircraft.

A method, apparatus, and system for managing sensor system for an aircraft. A presence of erroneous sensor data generated by a set of external sensors on an exterior of the aircraft is detected. A set of deployable sensors is deployed in response to the erroneous sensor data being received from the set of external sensors on the exterior of the aircraft when an undesired environmental condition adverse to the set of external sensors on the exterior of the aircraft is absent. Sensor data is received from the set of deployable sensors.

An aircrew automation system that provides a pilot with high-fidelity knowledge of the aircraft's physical state, and notifies that pilot of any deviations in expected state based on predictive models. The aircrew automation may be provided as a non-invasive ride-along aircrew automation system that perceives the state of the aircraft through visual techniques, derives the aircraft state vector and other aircraft information, and communicates any deviations from expected aircraft state to the pilot.

Aspects of the disclosure relate to identifying and responding to problem conditions for a fleet of aerial vehicles. This may include receiving at one or more processors of one or more server computing devices sensor feedback from an AV of the fleet. A problem condition may be identified using the sensor feedback. A mitigation response for the problem condition relating to a mission assigned to the aerial vehicle may be determined. The mitigation response may be sent to the AV in order to cause the aerial vehicle to maneuver according to the mitigation response and thereby automatically respond to the problem condition.

A method and a system for monitoring a mechanical system, the mechanical system including a lubrication system provided with a reservoir containing a lubricating liquid, with a lubrication circuit designed to lubricate the mechanical system, as well as with a particle detection device arranged in the lubrication circuit. The detection device makes it possible, in particular, to count the number of particles flowing through the lubrication circuit and/or the flow rate of the particles. Comparing that number or that flow rate with a first threshold makes it possible to determine a risk of damage affecting the mechanical system and to anticipate the maintenance or reinforced monitoring operations that possibly need to be performed.

An engine vibration monitoring and control system includes an aircraft autopilot and a flight management system (FMS). The FMS is in operable communication with the aircraft autopilot and is configured to determine when the aircraft autopilot is engaged and disengaged. The FMS is also adapted to receive vibration data from an engine vibration data source and is configured, upon determining that the aircraft autopilot is engaged, to: process the vibration data to determine when engine vibrations exceed one or more first thresholds, and when the engine vibrations exceed the one or more first thresholds, supply commands to the autopilot that cause the autopilot to take corrective actions to reduce the engine vibrations below the one or more first thresholds.

Systems and methods relate to electric propulsor fault detection. An exemplary system includes at least a first inverter configured to accept a direct current and produce an alternating current, a first propulsor, a first motor operatively connected with the first propulsor and powered by the alternating current, and at least a noise monitoring circuit electrically connected with the direct current and configured to detect electromagnetic noise and disengage the at least an inverter as a function of the electromagnetic noise.

According to an embodiment of the present disclosure, a method of training a machine learning model is provided. Input data is received from at least one remote device. A classifier is evaluated by determining a classification accuracy of the input data. A training data matrix of the input data is applied to a selected context autoencoder of a knowledge bank of autoencoders including at least one context autoencoder and the training data matrix is determined to be out of context for the selected autoencoder. The training data matrix is applied to each other context autoencoder of the at least one autoencoder and the training data matrix is determined to be out of context for each other context autoencoder. A new context autoencoder is constructed.

An impact detection device includes an impact detector, a wireless communication device, an energy storage device, an autonomous electrical energy generation device, a device for receiving energy by radio frequency, the device being configured to adopt the following two modes: a first mode, referred to as autonomous mode, in which the autonomous electrical energy generation device is configured to supply the impact detector and the wireless communication device; a second mode, referred to as external mode, in which the device for receiving energy by radio frequency is configured to supply the impact detector and the wireless communication device.