General Electric Company

Vetco Gray Inc.

Brandon Stephen Good

Charles Burton Theurer

Shaopeng Liu

Li Zhang

Adam Joseph McCann

Lynn Ann DeRose

Robert Lee Wallace

Jacob Berlier

Douglas Roy Forman

Judith Ann Guzzo

Bernard Patrick Bewlay

Guanghua Wang

Alberto Santamaria-Pang

Gyeong Woo Cheon

Todd Franklin Scarola

Bijan Chitsaz

David Grey Smith

Patricia Denise Mackenzie

Janet Sue Bennett

Christopher Donald Johnson

Huan Tan

Todd William Danko

Andrew Day

Craig Douglas Young

Joseph James Salvo

John Michael Lizzi

Younkoo Jeong

Benjamin Edward Beckmann

David Toledano

Nichole Lea Wood

Yang Zhao

Jeffrey Richardson Terry

Bernhard Joseph Scholz

Michael Orlando Cimini

Patrick Anthony Montelo

Morgan Fredric Intrator

Nicolas Auguste Constant Schieli

James Nelson Bratton

Morgan Frederic Intrator

Lee Roy LaPierre

Gregory Alan Richardson

Patricia MacKenzie

Hasan Imamus Saleheen

Francis Christopher Hann

Benjamin Edward Beekmann

Methods, apparatus, systems, and articles of manufacture are disclosed to autonomously detect thermal anomalies. Disclosed examples include an example apparatus to detect engine anomalies comprising: at least one memory; instructions in the apparatus; and processor circuitry to execute the instructions to: control a plurality of infrared cameras to capture a baseline image set, the baseline image set including at least two thermal images; generate emissivity data based on the baseline image set; provide the baseline image set and the emissivity data to an artificial intelligence model, the artificial intelligence model to generate a reconstructed image set; determine a difference between the baseline image set and the reconstructed image set; and in response to the difference exceeding a threshold, generate an alert indicating detection of an engine anomaly.

Methods and apparatus to autonomously detect thermal anomalies

Method, and corresponding system, for receiving and adaptively compressing sensor data for an operating manufacturing machine. The method includes determining the sensor data values at the working tool positions based on a time correlation of the values of the sensor data relative to time and the working tool positions relative to time. Tool control magnitude values relative to the working tool positions are determined based on the process data. The method further includes determining a magnitude differential, relative to the working tool positions, between the sensor data values and the tool control magnitude values. Scoring data is determined by applying a scoring function to the magnitude differential. The magnitude differential data is compressed based at least in part on the scoring data. The method further includes decompressing the magnitude differential data and determining the sensor data values versus the working tool positions based on the magnitude differential data.

Systems and methods for receiving sensor data for an operating additive manufacturing machine and adaptively compressing the sensor data based on process data which controls the operation of the machine

Improved gimbal systems, apparatus, articles of manufacture and associated methods are disclosed. Examples include a panel including a window, the window to define an aperture for a sensor; a platform to mount the sensor, the platform including a first pinion; a first stepper motor to move the first pinion about a first arched rack; a gimbal body including the first arched rack and a second pinion; and a second stepper motor to move the second pinion about a second arched rack, the second arched rack positioned orthogonally to the first arched rack.

Gimbal systems, apparatus, articles of manufacture and associated methods

Systems and methods for facilitating proximity detection and location tracking using a hub or bridge are disclosed. An example apparatus is to receive a message from a beacon at a second location within a proximity area of the apparatus, the message indicative of the second location and identifying the beacon; and relay the message to a location server to determine asset location.

Hardware system for active RFID identification and location tracking

Methods, apparatus, systems and articles of manufacture are disclosed to facilitate proximity detection and location tracking. An example method includes receiving messages collected by a badge in an environment, the messages including signal strength and a timestamp. The example method also includes assigning a location in the environment to the badge based on a first subset of the messages. The example method also includes identifying an asset in a second subset of the messages. The example method also includes updating a current location associated with the asset based on a relative proximity of the asset to the badge, wherein the current location corresponds to a first time and the updated location corresponds to a second time, and wherein a change in location between the current location and the updated location indicates movement of the asset in the environment.

Methods and apparatus to facilitate proximity detection and location tracking

A sensor calibration system includes a plurality of sensors and a user interface configured to receive user-provided locations of at least two sensors of the plurality of sensors. The sensor calibration system further includes a motorized apparatus including a drive system, at least one detector, and a localization system. The sensor calibration system further includes a controller communicatively coupled to the user interface and the motorized apparatus. The controller is configured to determine a whether each of at least two sensors is a key sensor based on the user-provided locations. The controller is configured to determine a path for the motorized apparatus based on the user-provided locations. The controller is further configured to determine a position of each sensor based on the location of the motorized apparatus when each sensor is detected by the at least one detector. The controller is further configured to relate the location of the motorized apparatus and the position of each sensor to a common origin.

Systems and methods including motorized apparatus for calibrating sensors

Certain examples provide systems and methods to monitor and control hospital operational systems based on occupancy data and medical orders. An example healthcare workflow management and reasoning system includes a workflow engine including a first particularly programmed processor to monitor one or more medical orders from one or more hospital information systems to identify a condition indicating that a first patient in a first room is ready for a clinical activity such as discharge. The example healthcare workflow management and reasoning system includes a sensing component including a second processor to gather occupancy data regarding the first patient in the first room and transmit the occupancy data to the workflow engine. The example workflow engine controls one or more hospital operational systems to trigger cleaning of the first room, lighting settings for the first room, and transportation of a second patient to the first room based on occupancy data from the sensing component.

Methods and systems to sense situational awareness with a dual doppler and control for optimized operations

Method, and corresponding system, for iteratively distributing improved process parameters to a fleet of additive manufacturing machines. The method includes receiving sensor data from a sensor for a first machine of the fleet of machines. The method further includes comparing the sensor data values at the working tool positions of the plurality of layers to reference data values at the working tool positions for the plurality of layers to determine a set of comparison measures for the first machine. The method further includes selecting a machine from among the first machine and at least a second machine of the fleet of machines based at least in part on the comparison measures of each of the machines. The method further includes receiving, from the selected machine, process parameters of the selected machine; and transmitting at least part of the process parameters of the selected machine to other machines of the fleet.

Identifying and distributing optimal machine parameters within a fleet of additive manufacturing machines

In various example embodiments, a system and method for facilitating proximity detection and location tracking using a mobile wireless bridge are provided. The system includes a beacon badge, a beacon tag, and a real-time location services ('RTLS') server communicatively coupled to the beacon badge, such as via a wireless network or the like. The beacon tag broadcasts a beacon message receivable by the beacon badge. The beacon badge determines whether it is proximate to the beacon badge based on the signal strength of the received beacon message. The beacon badge further communicates identifying information contained with the received beacon message to the RTLS server. The RTLS server uses the identifying information to determine the proximate location of the beacon badge.

Wireless bridge hardware system for active RFID identification and location tracking

Method, and corresponding system, for receiving and processing sensor data for an additive manufacturing machine. The method includes determining values of the sensor data relative to time; and determining tool positions relative to time based on process data which controls operation of the additive manufacturing machine. The method further includes determining the sensor data values at the working tool positions based on a correlation of the values of the sensor data relative to time and the working tool positions relative to time. A representation of the sensor data values at the working tool positions is displayed by a user interface device.

Systems and methods for receiving sensor data for an operating additive manufacturing machine and mapping the sensor data with process data which controls the operation of the machine

The present disclosure relates to cell processing techniques. By way of example, a cell processing system may include a plurality of tracking devices coupled to a respective plurality of sample processing containers and storing sample identification information for a patient sample for use with sample processing devices configured to process the patient sample according to workflow steps of a processing protocol. A plurality of readers are configured to receive signals from the plurality of tracking devices. A controller may be coupled to the plurality of readers and configured to determine if the patient sample is processed according to the processing protocol based at least in part on the signals from the plurality of tracking devices.

Cell processing techniques

Method, and corresponding system, for producing an alert during manufacture of a part formed by a plurality of layers. The method includes determining the sensor data values at the working tool positions of each of the plurality of layers based on a correlation of the values of the sensor data relative to time and the working tool positions of each of the plurality of layers relative to time. During the manufacturing process, the sensor data values at the working tool positions of at least one of the plurality of layers are compared to reference data values at the working tool positions for the at least one layer to determine a comparison measure for the at least one layer. An alert is transmitted if the determined comparison measure of a layer is not within a defined range. A defined action is applied to the manufacturing process based on the transmitted alert.

Systems and methods for receiving sensor data for an operating manufacturing machine and producing an alert during manufacture of a part

Growing community of inventors

Schenectady, NY, United States of America

Brandon Stephen Good