The Boeing Company

Eric Lee Nicks

David Allan Followell

Javier Cortez

Nail Hanov

Liessman E Sturlaugson

John M Boggio

Jeffrey Alan Schmitz

James Robert Hamilton

Stephen G Dame

Jeanne C Maggiore

Timothy Joseph Wilmering

William E Wojczyk, Jr

Steven Matthew Gunther

Balaje T Thumati

Stephen P Jewett

Andrew Wall

Robert C Thompson

Peter G Rhodes

Ali K Babool

Thomas J Hollerich

James Michael Cress, Jr

Cedar Cloyd

A method includes training a model to identify anomalous portions of a test component using training images and labels that indicate anomalous portions of training components within the training images. The method also includes compressing a source image of the test component to generate a first input image having a first resolution and making a first determination of whether the first input image indicates that the test component is anomalous. The method also includes making a second determination, for each section of a second input image, of whether the section indicates that the test component is anomalous. The second input image has a second resolution that is greater than the first resolution. The method also includes providing an indication of whether the first input image indicates that the test component is anomalous and providing an indication of whether the second input image indicates that the test component is anomalous.

Methods and systems for inspecting components

A monitoring system and method are configured to detect a status of a door for a component on a vehicle. The monitoring system includes a sound sensor positioned within an auditory range of the door. The sound sensor detects sound energy generated in relation to a closed position of the door and an open position of the door. The sound sensor outputs a sound signal indicative of the sound energy. A monitoring control unit is in communication with the sound sensor. The monitoring control unit receives the sound signal and analyzes the sound signal to determine the status of the door.

Monitoring systems and methods for vehicles

A handle system for a vehicle is disclosed and includes a support structure defining a handle. The support structure is movable between a stowed position where the handle is inaccessible by a passenger and a deployed position where the handle is accessible by the passenger. The handle system also includes an actuator operably coupled to the support structure and configured to move the support structure between the stowed position and the deployed position. The handle system further includes one or more sensors configured to obtain data indicative of vehicle motion and a controller. The controller is configured to determine the vehicle exceeds a threshold rate of movement based on the data obtained by the one or more sensors. In response to determining the vehicle exceeds the threshold rate of movement, the controller instructs the actuator to move the support structure from the stowed position into the deployed position.

Deployable handle system for a vehicle

An apparatus for maintenance of an aircraft is provided. The apparatus accesses flight data for a flight of the aircraft and predicts and thereby produces a predicted state of the aircraft for a next flight of the aircraft based on the flight data. The apparatus deploys a similarity detection model to determine similarities between the flight data for the flight and a training set of flight data for previous flights of the aircraft. The similarities determined by the similarity detection model are values of independent variables of a classification model. The apparatus deploys the classification model to predict and thereby produce a predicted state of the aircraft for the next flight of the aircraft based on the values of the independent variables, and generates an alert when the predicted state of the aircraft is a fault state.

Maintenance of an aircraft via similarity detection and modeling

A vehicle includes a first system, a first sensor, a second sensor, and a processor. The first sensor is configured to generate first sensor data indicative of an operational status of the first system. The second sensor is configured to generate second sensor data associated with an adaptive performance metric adjustment criterion. The processor is configured to, in response to determining that the second sensor data satisfies the adaptive performance metric adjustment criterion, determine, based on the second sensor data, an adaptive performance metric to be compared to the first sensor data to identify anomalous behavior of the first system. The processor is further configured to compare the first sensor data to the adaptive performance metric and to generate a maintenance alert in response to determining that the first sensor data fails to satisfy the adaptive performance metric.

Vehicle anomalous behavior detection

A service trolley for inspecting an interior cabin of a vehicle including a plurality of seats is disclosed. The service trolley includes a container body supported by a plurality of wheels, at least one image capture device, and a control module in communication with the image capture device and a database. The image capture device is mounted to the container body and is positioned along an outer surface of the container body in a location relative to the interior cabin of the vehicle to view the plurality of seats. The database stores image data of the plurality of seats of the vehicle. The control module executes instructions to compare the image data stored in the database with the image of a specific seat to determine a presence of at least one defect on an exterior of a specific seat in the interior cabin of the vehicle.

Service trolley for inspecting an interior cabin of a vehicle

A system may include an air treatment assembly configured to deliver treated air to an enclosed space within a vehicle, at least one upstream sensor upstream from the air treatment assembly, and at least one downstream sensor downstream from the air treatment assembly. The upstream sensor(s) and the downstream sensor(s) are configured to detect at least one attribute of air, such as air pressure. An air treatment monitoring system is in communication with the sensors. The air treatment monitoring system receives one or more sensor signals from the sensors, and calculates an attribute differential (such as a pressure differential) based on the one or more signals.

Systems and methods for monitoring an air treatment assembly of a vehicle

Methods, apparatus, systems, and articles of manufactures for aircraft cabin temperature control using temperature data from mobile electronic devices are described herein. An example mobile electronic device described herein includes a transceiver to receive a climate characteristic value measured by a personal mobile electronic device in a cabin of an aircraft and a cabin air manager to calculate an updated climate characteristic setting for an environmental control system (ECS) of the aircraft based on a current climate characteristic setting of the ECS and the climate characteristic value.

Aircraft cabin climate control using data from mobile electronic devices

A method of determining a seat back status of a passenger seat in a vehicle. The method includes monitoring a seat back orientation sensor coupled to a seat back of the passenger seat and monitoring a reference orientation sensor coupled at a fixed position within the vehicle. The seat back orientation sensor determines an orientation of the seat back relative to Earth, and the reference orientation sensor determines an orientation of the vehicle relative to Earth. The method further includes determining an orientation of the seat back relative to the vehicle based on a comparison between the orientation of the seat back and the orientation of the vehicle relative to Earth, and transmitting seat back orientation data, of the seat back relative to the vehicle, to a remote monitoring unit, wherein the remote monitoring unit is configured to display a first notification when the seat back is not fully upright.

System and method of determining a seat back status of a passenger seat in a vehicle

A method and apparatus for managing health of a motor in an aircraft is presented. A first group of motor parameters and a second group of external bias parameters in sensor data received from a sensor system associated with the aircraft in which the first group of motor parameters is for an environment affected by operation of the motor in the aircraft and the second group of external bias parameters modifies an effect of the first motor group of motor parameters in identifying a health of the motor is monitored. The health of the motor is identified based on the first group of motor parameters and the second group of external bias parameters. An action is performed based on the health of the motor identified, wherein a controller enables increasing a confidence level in indicating the health of the motor.

Motor health management apparatus and method

A computer-implemented method, environmental control system (ECS) for an aircraft, and system are provided. Air temperatures at the inlet and outlet of a ram air duct for an ECS are measured. Also, air temperatures at outlets from one or more heat exchangers arranged in the ram air duct are measured. The temperatures are typically measured when the aircraft is on the ground and when aircraft engines supplying air to the ECS are operating at idle. Shortly thereafter, the heat exchangers are manually inspected to determine a level of actual fouling (e.g., dirt, dust, or other debris accumulated on heat exchanger surfaces). A supervised machine learning or other statistical analysis is performed on the measured temperatures and associated actual fouling levels to develop a model that predicts an amount of heat exchanger fouling, based on the temperature measurements. An alert can be output if the predicted fouling exceeds a fouling threshold.

Model-based method and system to detect heat exchanger fouling

A component monitoring system is configured to indirectly monitor an operative health status of an operative component. The component monitoring system includes an ambient condition sensor within a chamber, an operative component coupled to the chamber. The ambient condition sensor is configured to sample an ambient condition within the chamber when the operative component is active. The ambient condition sensor is configured to output ambient condition data indicative of the ambient condition detected by the ambient condition sensor. At least one control unit is in communication with the ambient condition sensor. The control unit(s) is configured to indirectly determine the operative health status of the operative component through an analysis of the ambient condition data.

Systems and methods for monitoring operative components of a vehicle based on ambient conditions

A method to provide prognosis and diagnosis of environmental control system maintenance. The method including imaging, with at least one imaging unit, in real time at least one portion of an environmental control system in operation, wherein real time images register a dynamic feature of a dynamic predetermined characteristic of the at least one portion of the environmental control system, comparing, with a controller, the real time images of the at least one portion of the environmental control system with stored images of the at least one portion of the environmental control system in operation to identify a change in the dynamic feature of the dynamic predetermined characteristic of the at least one portion of the environmental control system, and determining, with the controller, whether an abnormality exists in the at least one portion of the environmental control system based on the identified change in the dynamic feature between the real time images and the stored images of the at least one portion of the environmental control system.

System and method for environmental control system diagnosis and prognosis

A data acquisition node for coupling to a system of a vehicle includes a processor coupled to a communication interface. The processor is configured to transition from a sleep mode to a start-up detect mode after an imminent-event message is received at the communication interface. The communication interface is substantially deactivated while in the start-up detect mode. The processor also is configured to monitor sensor data from at least one sensor while in the start-up detect mode. The at least one sensor is operable to generate a signal that is representative of a physical characteristic of the system.

Data acquisition node and method of operating same

A method of allocating objects within a plurality of storage bins including monitoring motion within the plurality of storage bins, wherein each storage bin of the plurality of storage bins includes a profile sensor coupled therein, and activating the profile sensor coupled within a first storage bin. The profile sensor activated based on detection of motion within the first storage bin. The method also includes determining, with the profile sensor, an available capacity within the first storage bin, and transmitting an indication of the available capacity within the first storage bin.

Growing community of inventors

O'Fallon, MO, United States of America

Eric Lee Nicks