Honeywell International Inc.

Honeywell G.m.b.h.

Raj Mohan Bharadwaj

Kyusung Kim

Darryl Busch

Andrew Peter Vechart

Megan L Hawley

Piyush Ranade

Kwong Wing Au

David Lazarovich

Paul Frederick Dietrich

David Daniel Lilly

Ranjana Ghosh

Abraham Reddy

Dinkar A Mylaraswamy

Vibhor L Bageshwar

Dwayne Michael Benson

Daniel P Johnson

Joel N Bock

Eric Blumer

Mike S Koerner

Onder Uluyol

David B Goldstein

George Daniel Hadden

Subhabrata Ganguli

Suresh Sundarraj

Craig L Schimmel

Vidhyashankaran Ramamoorthy Iyer

John Linert

Phil Scandura

Craig Schimmel

Darryl G Busch

George D Hadden

A method in an aircraft of using prognostic indicators for aircraft maintenance includes retrieving aircraft health data for a plurality of aircraft components wherein the aircraft health data includes at least one of mechanical systems condition indicator (CI) data, vibration spectrum data, resampled time-domain (RTD) data, and RTD spectrum data. The method includes estimating component health status information for the plurality of aircraft components using a plurality of prognostic modules wherein each prognostic module is configured to generate health status information for at least one of the aircraft components, the health status information includes at least one of a current health indicator and a prognostic indicator. The method also includes storing the component health status information for the aircraft components in a database onboard the aircraft, and causing the display of the health status information for the specific component on an aircraft display.

System and method of using mechanical systems prognostic indicators for aircraft maintenance

Disclosed are methods, systems, and non-transitory computer-readable mediums for detecting and avoiding loss of separation between vehicles. A first method may include training a vehicle interaction machine learning model to predict future vehicle interactions based on identified vehicle interactions and an identified risk of encounter between two or more selected vehicles. A second method may include obtaining real-time data associated with a vehicle-of-interest; evaluating the real-time data associated with the vehicle-of-interest to form encounter models; monitoring the encounter models with a model access function of the vehicle interaction machine learning model to detect real-time anomalies; and in response to detecting a real-time anomaly, transmitting an alert. A third method may include obtaining trajectory information; analyzing the trajectory information to determine whether a trajectory is a new trajectory type or whether the trajectory is a member of a new interaction; updating training data for the vehicle interaction machine learning model.

Method and system for detecting and avoiding loss of separation between vehicles and updating the same

A computer-implemented method for predicting material properties in an Additive Manufacturing (AM) process is provided. The method comprises: receiving sensor data during the build of a metallic component using the AM process wherein the sensor data includes time-series temperature data of a surface of the metallic component recorded by a photodiode and time-series temperature data of a surface of the metallic component recorded by a pyrometer; receiving ICME (Integrated Computational Materials Engineering) model output data for building the component wherein the ICME model output data includes predicted melt pool dimensions time-series data, predicted melt temperature time-series data, and predicted defects forming as a result of melt pool evolution and movement; and estimating using the received sensor data and the received ICME model output data one or more material properties associated with the metallic component using a material property prediction module configured to predict one or more of the material properties.

System and method for additive manufacturing process monitoring

An environmental control system (ECS) includes a controller; and a mode selector in communication with the controller and configured to select at least one of a plurality of modes. The mode is based on one of: number of occupants in an environment; activity of the occupants in the environment; destination of the environment; and performance of an engine that moves the environment. The controller is configured to change an ECS load on the system based upon the selected mode.

ECO mode ECS logic

An inertial navigation system (INS) includes a primary inertial navigation system (INS) unit configured to receive accelerometer measurements from an accelerometer and angular velocity measurements from a gyroscope. The primary INS unit is further configured to receive global navigation satellite system (GNSS) signals from a GNSS sensor and to determine a first set of kinematic state vectors based on the accelerometer measurements, the angular velocity measurements, and the GNSS signals. The INS further includes a secondary INS unit configured to receive the accelerometer measurements and the angular velocity measurements and to determine a second set of kinematic state vectors of the vehicle based on the accelerometer measurements and the angular velocity measurements. A health management system is configured to compare the first set of kinematic state vectors and the second set of kinematic state vectors to determine faults associated with the accelerometer or the gyroscope based on the comparison.

Systems and methods for determining inertial navigation system faults

A program product for determining an obstruction in an air circuit for an environmental control unit having a motor is provided. The program product comprises a program and a non-transitory, computer-readable storage medium. The program is configured to at least facilitate obtaining a load current of the motor, determining a state of the motor, generating a comparison, and determining the obstruction using the load current and the comparison. The comparison is generated by comparing the load current to a first plurality of values if the motor is in a steady state, and by comparing the load current to a second plurality of values if the motor is in a transient state. The non-transitory, computer-readable storage medium stores the program.

Motor current based air circuit obstruction detection

A system and method for determining the response capabilities of a control effector are provided. Command data and sensor data associated with the control effector are processed to generate control effector health data representative of control effector health. The control effector health data are processed in a reasoned. The reasoned is configure to selectively indict and clear one or more faults, determine one or more failures that cause indicted faults, and determine, based on the one or more determined failures, a usable range of control effector commands to which the control effector can respond.

Control effector health capabilities determination reasoning system and method

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.

Methods for optimizing diagnostics reasoner models

Methods and apparatus are provided for determining whether a built-in-test fault code (BITFC) data sequence generated by a built-in-test (BIT) of a particular module of a complex system is indicative of an actual fault condition. A regression function is generated for the particular module based on stored BITFC data sequences generated by the BIT and stored repair data for that module from a fault history database. Later, during operation of the particular module, the BIT generates a new BITFC data sequence. A processor can then load the new BITFC data sequence and execute the regression function with respect to the new BITFC data sequence to determine whether the new BITFC data sequence is indicative of an actual fault condition at the particular module or is indicative of a false fault condition at the particular module.

Methods systems and apparatus for determining whether built-in-test fault codes are indicative of an actual fault condition or a false alarm

A computer implemented method and system includes using information provided from sensors to monitor a wind turbine generator and provide signals representative of operation of the wind turbine generator, extracting signal level features from the signals, extracting model based features from the signals, calculating signal based conclusions, model based conclusions and spectral feature reinforcement based conclusions, and fusing the conclusions to provide a fault detection indication.

Wind turbine generator fault diagnostic and prognostic device and method

A testbed for testing health of software includes an input model, a hardware model, and a resource modeler. The input model represents an input system used in conjunction with the software. The hardware model represents one or more hardware components used in conjunction with the software. The resource modeler is coupled to the input model and the hardware model, and is configured to estimate effects on the software of conditions of the hardware components, the input system, or both.

Software health management testbed

Methods and systems are provided for improving the repair efficacy of a repair action using inferred feedback. The method comprises downloading a repair procedure, which has a probability of success for correcting the fault code. Repair action data is input into to the computing device and is tracked and correlated with the downloaded procedure. The method then adjusts a probability of success of the repair procedure in clearing the fault code generated by the complex system based at least on the correlation. The system comprises a means for receiving repair data, a means for tracking repair action data taken, a means for correlating the tracked repair action and the repair data, and a means for updating a probability of success of the repair action based at least in part on the correlation of the repair data, the repair action data and the operating status of the complex system.

Automatic determination of success of using a computerized decision support system

A method for determining an obstruction in an air circuit, the air circuit having a fan and a motor that drives the fan, includes the steps of obtaining a load current of a motor coupled to the air circuit, comparing the load current to a predetermined value, and determining the obstruction using the load current and the predetermined value.

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.

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Maple Grove, MN, United States of America

Raj Mohan Bharadwaj