Abstract: A propulsion system for an aircraft is disclosed and includes a water recovery system and a water monitoring system. The water recover system includes a condenser that is arranged along the core flow path and is configured to extract water from an exhaust gas flow. The water monitoring system includes a sensor and a controller programed to determine a condition of water and generate a prompt based on information communicated from the at least one sensor.

Abstract: A propulsion system for an aircraft includes a hydrogen fuel system, a water recovery system and a water pressure and quantity monitoring system. The water recovery system uses a condenser to extract water from an exhaust gas flow. The water pressure and quantity monitoring system measures water pressures and quantities at various locations in the water recovery system to assess the health and efficiency of the water recovery/supply system and the propulsion system.

Abstract: A propulsion system for an aircraft includes a hydrogen fuel system, a water recovery system and a water pressure and quantity monitoring system. The water recovery system uses a condenser to extract water from an exhaust gas flow. The water pressure and quantity monitoring system measures water pressures and quantities at various locations in the water recovery system to assess the health and efficiency of the water recovery/supply system and the propulsion system.

Abstract: A propulsion system for an aircraft is disclosed and includes a water recovery system and a water monitoring system. The water recover system includes a condenser that is arranged along the core flow path and is configured to extract water from an exhaust gas flow. The water monitoring system includes a sensor and a controller programed to determine a condition of water and generate a prompt based on information communicated from the at least one sensor.

Abstract: A method to effectively utilize an oil debris monitor to provide advanced warning to mechanical system failures in a high noise system by adapting detection and annunciation algorithms to the background noise in a system that includes collecting I and Q channel data from a sensor; processing the I and Q channel data to both calculate a noise based (RMS adjusted) detection threshold and to identify a ferrous and nonferrous signal; processing the ferrous and nonferrous signals to determine signal peaks above the RMS adjusted detection threshold; adjusting a detection threshold if more signal peaks observed than allowable particles in a given time window; transmitting the detection threshold previously determined to particle detection, rate limit adjustment, detectability algorithms, and estimated mass loss accumulation.

Abstract: A method for fault identification for a gas turbine engine includes receiving sensor data from at least one health monitoring sensor of a health monitoring system for a gas turbine engine; utilizing a pre-filter to filter the sensor data and obtain filtered data based on a plurality of signatures of fault conditions of the health monitoring system and the gas turbine engine; utilizing at least one transfer function to extract features from the filtered sensor data based on the plurality of signatures; utilizing a machine learning technique to analyze the extracted features, and determine whether any of the extracted features are indicative of a fault condition in the health monitoring system or the gas turbine engine; and based on the analysis indicating the presence of a fault condition, providing a fault detection notification. A health monitoring system for a gas turbine engine is also disclosed.

Abstract: A method for actively calculating and monitoring the oil debris monitor phase angle includes sensing a noise from an in-line oil debris monitor sensor in an oil flow path, generating a polar plot of an I and Q channel data from only the noise. Linear regression of noise is then utilized from the I and Q channel data for calculating a slope of regression form the linear regression and converting the slope to a phase angle.

Abstract: An oil debris monitoring sensor includes a multiple of passages within the housing, each of the multiple of passages surrounded by a set of coils to detect a particle. A method for determining a presence of a particle in a system includes a) installing a single sensor in-line with an oil flow path; b) communicating oil through a multiple of passages within the housing of the single sensor; c) detecting a particle through the single sensor; and d) isolating the particle to one of the multiple of passages within the sensor housing.

Abstract: An oil debris monitoring sensor includes a multiple of passages within the housing, each of the multiple of passages surrounded by a set of coils to detect a particle. A method for determining a presence of a particle in a system includes a) installing a single sensor in-line with an oil flow path; b) communicating oil through a multiple of passages within the housing of the single sensor; c) detecting a particle through the single sensor; and d) isolating the particle to one of the multiple of passages within the sensor housing.

Abstract: A method to effectively utilize an oil debris monitor to provide advanced warning to mechanical system failures in a high noise system by adapting detection and annunciation algorithms to the background noise in a system that includes collecting I and Q channel data from a sensor; processing the I and Q channel data to both calculate a noise based (RMS adjusted) detection threshold and to identify a ferrous and nonferrous signal; processing the ferrous and nonferrous signals to determine signal peaks above the RMS adjusted detection threshold; adjusting a detection threshold if more signal peaks observed than allowable particles in a given time window; transmitting the detection threshold previously determined to particle detection, rate limit adjustment, detectability algorithms, and estimated mass loss accumulation.

Abstract: A method to effectively utilize an oil debris monitor to provide advanced warning to mechanical system failures in a high noise system by adapting detection and annunciation algorithms to the background noise in a system that includes collecting I and Q channel data from a sensor; processing the I and Q channel data to both calculate a noise based (RMS adjusted) detection threshold and to identify a ferrous and nonferrous signal; processing the ferrous and nonferrous signals to determine signal peaks above the RMS adjusted detection threshold; adjusting a detection threshold if more signal peaks observed than allowable particles in a given time window; transmitting the detection threshold previously determined to particle detection, rate limit adjustment, detectability algorithms, and estimated mass loss accumulation.

Abstract: A method for determining the presence of a particle while actively calculating and monitoring oil debris monitor phase angle in an oil system including collecting I and Q channel data from an oil debris monitor sensor, performing a fast Fourier transform on the I and Q channel data, extracting a shape from the fast Fourier transform, and determining whether a particle is present from the shape.

Abstract: An oil debris monitoring sensor includes a multiple of passages within the housing, each of the multiple of passages surrounded by a set of coils to detect a particle. A method for determining a presence of a particle in a system includes a) installing a single sensor in-line with an oil flow path; b) communicating oil through a multiple of passages within the housing of the single sensor; c) detecting a particle through the single sensor; and d) isolating the particle to one of the multiple of passages within the sensor housing.

Abstract: A method for determining the presence of a particle while actively calculating and monitoring oil debris monitor phase angle in an oil system including collecting I and Q channel data from an oil debris monitor sensor; determining whether the I and Q data is symmetric; processing the I and Q channel data to identify a ferrous and nonferrous signal in response to the I and Q data being symmetric; processing the ferrous and nonferrous signals to determine if a particle is present; determining a symmetry factor from the I and Q channel data in response to the particle being present and confirming that the particle is present from the symmetry factor.

Abstract: A method to effectively utilize an oil debris monitor to provide advanced warning to mechanical system failures in a high noise system by adapting detection and annunciation algorithms to the background noise in a system that includes collecting I and Q channel data from a sensor; processing the I and Q channel data to both calculate a noise based (RMS adjusted) detection threshold and to identify a ferrous and nonferrous signal; processing the ferrous and nonferrous signals to determine signal peaks above the RMS adjusted detection threshold; adjusting a detection threshold if more signal peaks observed than allowable particles in a given time window; transmitting the detection threshold previously determined to particle detection, rate limit adjustment, detectability algorithms, and estimated mass loss accumulation.

Abstract: A method for actively calculating and monitoring the oil debris monitor phase angle includes sensing a noise from an in-line oil debris monitor sensor in an oil flow path, generating a polar plot of an I and Q channel data from only the noise. Linear regression of noise is then utilized from the I and Q channel data for calculating a slope of regression form the linear regression and converting the slope to a phase angle.

Abstract: A method for determining the presence of a particle while actively calculating and monitoring oil debris monitor phase angle in an oil system including collecting I and Q channel data from an oil debris monitor sensor, performing a fast Fourier transform on the I and Q channel data, extracting a shape from the fast Fourier transform, and determining whether a particle is present from the shape.

Abstract: A method for determining the presence of a particle while actively calculating and monitoring oil debris monitor phase angle in an oil system including collecting I and Q channel data from an oil debris monitor sensor; determining whether the I and Q data is symmetric; processing the I and Q channel data to identify a ferrous and nonferrous signal in response to the I and Q data being symmetric; processing the ferrous and nonferrous signals to determine if a particle is present; determining a symmetry factor from the I and Q channel data in response to the particle being present and confirming that the particle is present from the symmetry factor.