Deere & Company

Carnegie Mellon University

Zachary Pezzementi

Herman Herman

Carlos Vallespi-Gonzalez

Aaron J Bruns

James Joseph Phelan

John M Hageman

Stephen R Corban

Carl Knox Wellington

Cristian Dima

Scott Miller

Joan Campoy

Victor S Sierra

Trenton Tabor

Jonathan Chang

Hanke Boesch

Cason Robert Male

William D Todd

A grain tailings elevator for a combine harvester includes a an elevator housing having an interior containing a conveyor arrangement configured to transport grain tailings through the elevator housing to a discharge outlet. The elevator housing has a side wall with a window to the interior of the elevator housing. A camera having a camera housing containing an image sensor is mounted to the side wall of the elevator housing over the window with the image sensor in registration with the window. The image sensor is trained on the conveyor arrangement and configured to image the grain tailings transported by the conveyor arrangement through the elevator housing.

Grain quality control system and method

A method and system for controlling the quality of harvested grains include capturing, by one or more image sensors, one or more images of material at a sampling location within a grain elevator of the combine harvester. The captured images are defined by a set of image pixels represented by image data and having a classification feature indicative of grain or non-grain material. One or more controllers receive the image data associated with the one or more images captured by the image sensor(s) and select a sample image defined by a subset of image pixels of the set of image pixels. The controller(s) apply a convolutional neural network (CNN) algorithm to the image data of the subset of image pixels of the selected sample image to determine the classification feature. The controller(s) analyze the determined classification feature to adjust an operational parameter of the combine harvester.

A method and non-transitory computer-readable medium capture an image of bulk grain and apply a feature extractor to the image to determine a feature of the bulk grain in the image. For each of a plurality of different sampling locations in the image, based upon the feature of the bulk grain at the sampling location, a determination is made regarding a classification score for the presence of a classification of material at the sampling location. A quality of the bulk grain of the image is determined based upon an aggregation of the classification scores for the presence of the classification of material at the sampling locations.

Grain quality monitoring

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Pittsburgh, PA, United States of America

Zachary Pezzementi