Rtx Corporation

Raytheon Technologies Corporation

Danbing Seto

Edward Thomas Rocco

Zaffir A Chaudhry

Coy Bruce Wood

Liang Tang

David L Lincoln

Gregory S Hagen

Scott Goyette

Jeremiah C Lee

Allan J Volponi

Joshua Adams

Sheridon Everette Haye

Yan Chen

Ramesh Rajagopalan

Janet Shaw

Robert H Luppold

Lichu Zhao

An in-situ system for a gas turbine engine blade inspection including a sensor system configured to capture images of a forward surface of at least one gas turbine engine blade; a processor coupled to the sensor system, the processor configured to determine damage to the at least one gas turbine engine blade based on video analytics; and a tangible, non-transitory memory configured to communicate with the processor, the tangible, non-transitory memory having instructions stored therein that, in response to execution by the processor, cause the processor to perform operations comprising receiving, by the processor, data for the forward surface of at least one gas turbine engine blade from the sensor system; determining, by the processor, a rotational speed of a fan; and determining, by the processor, a fan synchronization.

Optical in-situ inspection system

An assembly for an aircraft propulsion system includes a propulsor section, an imaging device, a plurality of light sources, and a controller. The propulsor section includes a propulsor. The propulsor includes a plurality of propulsor blades. The imaging device is disposed in the propulsor section. The imaging device includes a camera. The plurality of light sources are disposed in the propulsor section. The controller includes a processor in communication with a non-transitory memory storing instructions, which instructions when executed by the processor, cause the processor to: control the plurality of light sources to direct light to the plurality of propulsor blades, control the camera to capture image data of each propulsor blade of the plurality of propulsor blades, and identify a presence or an absence of damage for each propulsor blade of the plurality of propulsor blades using the image data.

Propulsor blade imaging assembly for an aircraft propulsion system

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.

Water pressure and quantity monitoring for hydrogen steam injected and inter- cooled turbine engine

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.

Water condition monitoring for hydrogen steam injected and inter-cooled turbine engine

Water pressure and quantity monitoring for hydrogen steam injected and inter-cooled turbine engine

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.

Oil debris monitor to detect mechanical failures in high noise environments

An engine parameter estimation tuning system includes an engine parameter estimator unit and a gas path analysis (GPA) unit. The engine parameter estimator unit includes an onboard model (OBM) configured to output estimated parameters based on operation of a gas turbine engine. The gas path analysis (GPA) unit includes a performance health monitor unit configured to adjust a long-term deterioration parameter independently from adjustment of a short-term tuning parameter to tune one or more targeted estimation parameters included in the estimated engine parameter. In this manner, the engine parameter estimation tuning system can realize the different time scales associated with uncertainties in an engine and accommodate them separately so that the estimated engine parameters become much more accurate.

Tuning engine parameter estimator using gas path analysis data

A method for fault diagnosis of a bearing includes detecting, using an oil debris monitor (ODM) sensor, ODM data corresponding to an amount of debris flowing downstream from the bearing. The method also includes detecting, using a vibration sensor, vibration data corresponding to vibration of the bearing during use. The method also includes determining, by a controller, a vibration stage flag corresponding to a severity of damage of the bearing based on the vibration data. The method also includes determining, by the controller, a severity level of the damage of the bearing based on a combination of the vibration stage flag and the ODM data. The method also includes outputting, by an output device, the severity level.

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Avon, CT, United States of America

Danbing Seto