Caterpillar Inc.

Other

Perkins Engines Company Limited

Caterpillar Global Mining Equipment LLC

Raymond Alan Wise

Lawrence Andrew Mianzo

Tod Andrew Oblak

John Michael Plouzek

Shawn Nainan Mathew

Daniel Paul Adler

Rex Aaron Glover

Peter Joseph Petrany

Samuel Alec Roberts

Michael Flatman

Thomas Henry Abel

Brian C Crow

An example wear detection system receives a plurality of images from a plurality of sensors associated with a work machine. Individual sensors of the plurality of sensors have respective fields-of-view different from other sensors of the plurality of sensors. The wear detection system identifies a first region of interest and second region of interest associated with the at least one GET. The wear detection system determines a first set of image points and a second set of images points for the at least one GET based on geometric parameters associated with the GET. The wear detection system determines a wear level or loss for the at least one GET based on the GET measurement.

Ground engaging tool wear and loss detection system and method

Changes in ambient light intensity are detected by processing image data from an image capture device to determine, iteratively, a signal-to-noise ratio of the image data. The signal-to-noise ratio is a ratio of average to variance of pixel values for some of the pixels forming the image. A control output is generated, based on the signal-to-noise ratio, that is responsive to changes in ambient light intensity. The control output is used control a light source of a vehicle.

Vehicle lighting control using image processing of changes in ambient light intensity

A system and method for dust mitigation in an environment with high amounts of debris is disclosed. The system may include an optical device disposed within an interior volume of an enclosure. A positive flow of clean air may be maintained into an air input aperture of the enclosure, around the optical device, over a lens of the optical device, and out a lens aperture of the enclosure. The system may be affixed to a piece of equipment, machine, or similar structure via a positionable or pivotable mount.

Dust mitigation for optical devices

An example wear detection system receives first image data related to at least one ground engaging tool (GET) of a work machine from one or more sensors at a first time instance in a dig-dump cycle of the work machine. The wear detection system processes the first image data to determine a first wear measurement and first wear level for the at least one GET. The wear detection system determines whether the first wear level is indicative of a GET replacement condition. The wear detection system generates an alert when the first wear level is indicative of the GET replacement condition. The wear detection system receives second image data related to the at least one GET a second time instance different from the first time instance when the first wear level is not indicative of the GET replacement condition and determines a second wear measurement and second wear level for the at least one GET. The wear detection system generates an alert indicative of the first wear level and the second wear level based on determining that the first wear level and the second wear level are indicative of the GET replacement condition.

An example wear detection system receives a left image and a right image of a bucket of a work machine having at least one ground engaging tool (GET). The example system identifies a first region of interest from the left image corresponding to the GET and a second region of interest from the right image corresponding to the GET. The example system also generates a left-edge digital image corresponding to the first region of interest and a right-edge digital image corresponding to the second region of interest. Further, the example system determines a sparse stereo disparity between the left-edge digital image and the right-edge digital image, and also determines a wear level or loss for the at least one GET based on the sparse stereo disparity.

An example wear detection system receives first imaging data from one or more sensors associated with a work machine. The first imaging data comprises data related to at least one ground engaging tool (GET) of the work machine. The example system identifies a region of interest including data of the at least one GET within the first imaging data. Based on the identified region of interest, the example system controls a LiDAR sensor to capture second imaging data capturing the at least one GET that is of higher resolution than the first imaging data. The example system generates a three-dimensional point cloud of the at least one GET based on the second imaging data and determines a wear level or loss for the at least one GET based on the three-dimensional point cloud.

An adjustable bedframe assembly for enhancing comfort and spinal alignment includes a plurality of legs that is coupled to and extends from a frame to support the frame on a substantially horizontal surface. A first plate that is coupled to a head rail and a pair of opposing side rails of the frame extends from the head rail to proximate to a midline of the pair of opposing side rails. A second plate that is pivotally coupled to the first plate extends to proximate to a foot rail of the frame so that the second plate and the first plate are configured to support a mattress. An actuator that is coupled to the second plate is positioned to selectively pivot the second plate relative to the first plate. The second plate is configured to selectively lower and raise a section of the mattress that is positioned on the second plate.

Growing community of inventors

Metamora, IL, United States of America

Raymond Alan Wise