The Boeing Company

University of Washington

John Jian Dong

Naveed Moayyed Hussain

Mark Nicholas Simpson

Roland Hinton

Michael J Duffy

Douglas Conrad Cameron, Jr

Mohammed Humayun Kabir

Alan Douglas Byar

Matthew Aaron Novick

Todd Clayton DePauw

Alexandru I Stere

Christina M Doty

Navid Zobeiry

Ashith Paulson Kunnel Joseph

Michael James Duffy

Doughlas C Cameron

A method is provided for monitoring a machine that is operable to perform a task. The method includes accessing a smart digital twin (SDT) of an instance of the machine, the SDT including discrete modules for storage of data and logic including models of the machine, requirements of the machine, and maintenance actions for the machine. The method includes performing data analytics on values of operating conditions of the machine to determine a state of the machine, using a model from the models of the machine and the logic. The state of the machine is compared to the requirements, and a maintenance action is identified based on the comparison and to cause a change in the state to maintain the requirements. The data of the SDT is updated to include identification of the maintenance action, and an indication of the maintenance action is output for performance on the machine.

Smart digital twin for monitoring a machine

Methods and systems are provided that facilitate the maintenance of levered landing gears by monitoring the condition of the stop pads of such landing gears. One embodiment provides for calibrating a sensor for measuring a condition of a stop joint formed by a first stop pad and a second stop pad of a levered landing gear against a nominal condition of at least one of the first stop pad and the second stop pad; monitoring, by the sensor, a current condition of the at least one of the first stop pad and the second stop pad from the nominal condition; determining whether a non-conformance from the nominal condition of the at least one of the first stop pad and the second stop pad has been detected by the sensor for the current condition; and in response to determining that the non-conformance has been detected, generating an alert.

Health monitoring of aircraft landing gear mechanical structures

A method, apparatus, system, and computer program products for managing a set of outliers in test data. A computer system analyzes a set of features derived from the test data using different outlier detection methods to generate a result of the set of outliers identified by the different outlier detection methods. The test data is obtained from testing a physical structure. The computer system determines a causality for the set of outliers in the result. The physical structure is retested with a set of changes determined using the causality identified for the set of outliers. The retesting generates new test data for the physical structure.

Outlier detection and management

Apparatus for controlling multi-rotor vehicle vibrations and related methods are disclosed herein. An example apparatus includes a vibration level detector to determine a vibration level of a frame of a vehicle based on data received from a sensor of the vehicle, the vehicle including a rotor. The apparatus includes a rotor operation analyzer to determine an operational parameter of the rotor based on the vibration level. The apparatus includes a communicator to transmit an instruction including the operational parameter to a controller of the rotor.

Apparatus for controlling multi-rotor vehicle vibrations and related methods

A method, apparatus, system, and computer program product for estimating material properties. Training data comprising results of testing samples for a set of materials over a range of loads applied to the samples is identified by a computer system. A machine learning model is trained by the computer system to output the material properties for materials in structures using the training data.

Material characterization system and method

A multi-rotor vehicle includes a plurality of electric motors and edge computing systems (ECSs). The electric motors are operatively coupled to respective rotors, and cause the respective rotors to rotate relative to the airframe. The ECSs are independent, distinct and distributed to the electric motors, each operatively coupled to a respective electric motor and thereby a respective rotor. Each ECS is configured to acquire and process sensor data for the respective rotor to determine rotor status information, and execute motor commands to control the respective electric motor and thereby the respective rotor. Each ECS is configured as an integrated flight computer and motor controller.

Multi-rotor vehicle with edge computing systems

A multi-rotor vehicle includes a plurality of electric motors and edge computing systems (ECSs). The electric motors are operatively coupled to respective rotors, and cause the respective rotors to rotate relative to the airframe. The ECSs are independent, distinct and distributed to the electric motors, each operatively coupled to a respective electric motor and thereby a respective rotor. Each ECS is configured to acquire and process sensor data for the respective rotor to determine rotor status information, and execute motor commands to control the respective electric motor and thereby the respective rotor. The ECSs are configured according to a model in which any of the ECSs is selectable as a primary ECS, and others of the ECSs are operable as secondary ECSs, the secondary ECSs configured to communicate respective rotor status information to the primary ECS, and the primary ECS configured to provide the motor commands to the secondary ECSs.

Growing community of inventors

Bothell, WA, United States of America

John Jian Dong