Abstract: A device and a method for determining a portion of broken grain and/or non-grain components in a stream of harvested material is disclosed. The device includes a camera to generate images of the stream of harvested material and an evaluation unit to estimate the portion in an image supplied by the camera. The evaluation unit includes a first-order classifier to estimate a first parameter of the stream of harvested material, and a plurality of second-order classifiers assigned to various values of the first parameter to estimate the portion in a stream of harvested material that has the assigned parameter value. The evaluation unit, with assistance of the first-order classifier, estimates a value of the first parameter using a first number of images of the camera, and then selects the second-order classifier assigned to the value of the first parameter to estimate the portion with assistance of the selected second-order classifier.

Abstract: A method and a system for determining an indicator of processing quality of an agricultural harvested material using a mobile device is disclosed. A computing unit analyzes image data of a prepared sample of harvested material containing grain components and non-grain components in an analytical routine to determine the indicator of the processing quality of the agricultural harvested material. Further, the computing unit uses a trained machine learning model in the analytical routine to perform at least one step of determining the indicator of the processing quality of the agricultural harvested material and that the computing unit adjusts at least one machine parameter of the forage harvester based on the indicator of processing quality.

Abstract: A self-propelled combine for collecting and handling harvested material and a method for cleaning and/or referencing an optical measuring device of the self-propelled combine are disclosed. The self-propelled combine has a bypass device with an optical measuring device for determining harvested material properties of the partial flow of harvested material.

Abstract: A detection arrangement for detecting a wear status of a chopping knife arrangement of a chopping device provided for processing a product flow, wherein the chopping device has a revolving chopping drum receiving the chopping knife arrangement and at least one shear bar which cooperates with the chopping knives, with a sensor arrangement which has a magnetic exciter arrangement and a flux conducting device magnetically coupled thereto. The sensor arrangement provides a pole arrangement which forms at least one magnetic pole with a pole surface for conducting magnetic flux, wherein at least a portion of the chopping knife passes the pole arrangement during a rotation of the chopping drum. A voltage induced when a chopping knife arrangement passes the sensor arrangement forms the measured magnetic value, which is used by the evaluation unit to determine the state of wear of the chopping knife arrangement.

Abstract: A method and a system for determining an indicator of processing quality of an agricultural harvested material using a mobile device is disclosed. A computing unit analyzes image data of a prepared sample of harvested material containing grain components and non-grain components in an analytical routine to determine the indicator of the processing quality of the agricultural harvested material. Further, the computing unit uses a trained machine learning model in the analytical routine to perform at least one step of determining the indicator of the processing quality of the agricultural harvested material.

Abstract: A method and a system for determining an indicator of processing quality of an agricultural harvested material using a mobile device is disclosed. A computing unit analyzes image data of a prepared sample of harvested material containing grain components and non-grain components in an analytical routine to determine the indicator of the processing quality of the agricultural harvested material. Further, the computing unit uses a trained machine learning model in the analytical routine to perform at least one step of determining the indicator of the processing quality of the agricultural harvested material and that the computing unit adjusts at least one machine parameter of the forage harvester based on the indicator of processing quality.

Abstract: An agricultural work machine, in particular a harvester, has a header for performing agricultural work and having a control device which has at least one sensor unit for detecting a crop stream in and/or around the header and an image processing unit for processing images which are generated by the sensor unit based on the crop stream detected via sensor. The control device is configured to detect regions of like characteristics, components of the header and properties of the crop stream and is configured to use that which has been detected for open loop control and/or closed loop control of process sequences in the agricultural work machine.

Abstract: An agricultural harvesting machine, particularly a combine harvester or a forage harvester, has a supporting frame, a cutting mechanism, an inclined conveyor and a driver's cab. The cutting mechanism is arranged at the supporting frame by the inclined conveyor. The driver's cab is arranged at the supporting frame with the intermediary of at least one damper unit. At least one camera is arranged in an interior of the driver's cab. The camera is oriented to the cutting mechanism and/or to the inclined conveyor through a front windshield of the driver's cab. The camera is arranged in an operative area of a cleaning device of the front windshield so that a detection area of the camera can be optically acquired at least through a portion of the operative area of the cleaning device.

Abstract: A method and system for identifying lengths of a particle in a flow of harvested material comprising particles in an agricultural harvester is disclosed. The agricultural harvester has at least one work assembly for harvesting a crop or for processing harvested material of the crop and can be adjusted using machine parameters. The harvested material is transported as a flow of harvested material through the agricultural harvester while the agricultural harvester is operating. The agricultural harvester has a camera that takes images of the flow of harvested material, with a computing unit of the agricultural harvester analyzing the images of the flow of harvested material in an analytical routine thereby finding particle lengths of particles of the flow of harvested material that are an excess length.

Abstract: A method and system for identifying, using a computing unit, lengths of a particle in a material flow is disclosed. The computing unit is configured to analyze images of the material flow (13) in an analytical routine and to derive particle lengths of particles of the material flow contained in the images. The particle length derived in the analytical routine may comprise an excess length, with the analytical routine being based on a machine learning method trained to find or identify particles with the excess length.

Abstract: A system and method for determining a broken grain fraction of a quantity of grains is disclosed. The system includes at least one camera and a computing unit, with the camera configured to create an image of the quantity of grains, and with the computing unit configured to evaluate, using artificial intelligence, the image to determine broken grains in the image, and to determine, based on the broken grains, the broken grain fraction of the quantity of grains in the image.

Abstract: An agricultural work machine has a crop collection arrangement for separating and collecting crops from field vegetation, which crop collection arrangement has at least one crop cutting device, a crop conveying device arranged downstream thereof and a crop intake device arranged downstream thereof, and having a control device which has at least one sensor unit for optically detecting a crop flow, an image processing unit for processing images which are generated by the sensor unit based on the optically detected crop flow, and a data output unit for displaying the images processed by the image processing unit. The image processing unit generates a velocity characteristic map and a directional change characteristic map based on the images generated by the sensor unit. The two characteristic maps are utilized jointly or each individually by the control device to control processes in the agricultural work machine and/or in the crop collection arrangement.

Abstract: A device and a method for determining a portion of broken grain and/or non-grain components in a stream of harvested material is disclosed. The device includes a camera to generate images of the stream of harvested material and an evaluation unit to estimate the portion in an image supplied by the camera. The evaluation unit includes a first-order classifier to estimate a first parameter of the stream of harvested material, and a plurality of second-order classifiers assigned to various values of the first parameter to estimate the portion in a stream of harvested material that has the assigned parameter value. The evaluation unit, with assistance of the first-order classifier, estimates a value of the first parameter using a first number of images of the camera, and then selects the second-order classifier assigned to the value of the first parameter to estimate the portion with assistance of the selected second-order classifier.

Abstract: A forage harvester is disclosed. The forage harvester has at least one work assembly for processing harvested material of a crop, which includes grain components. In operation, the harvested material is transported in a harvested material flow along a harvested material transport path through the forage harvester. The forage harvester further includes a corn cracker as a work assembly and a control assembly that includes an optical measuring system. The optical measuring system has a camera for recording image data of the harvested material, with the camera being positioned after the corn cracker. The control assembly, using an image recognition routine, determines image regions assigned to a comminuted grain component in the image data, determines geometric properties of the assigned comminuted grain components based on the image regions, and determines an indicator of a processing quality of the comminuted grain components from the geometric properties.

Abstract: A forage harvester is disclosed. The forage harvester has a work assembly for harvesting a crop and for processing harvested material of the crop, which includes grain components and non-grain components. In operation, the harvested material is transported in a harvested material flow along a harvested material transport path through the harvesting machine. The forage harvester also has a control assembly that includes an optical measuring system arranged on the harvested material transport path. The optical measuring system has a camera for recording image data of the harvested material of the harvested material flow. The control assembly, using an image recognition routine, determines image regions assigned to a non-grain component in the image data, determines geometric properties of the assigned non-grain components based on the image regions, and determines an indicator of a structural percentage of the harvested material from the geometric properties.

Abstract: An optical measuring device for the spectral measurement of a sample is disclosed. The optical measure device includes an integrating cavity that has a diffusely reflective interior in order to render the light in the integrating cavity diffuse, a light source that is configured to emit light of a predetermined wavelength range into the integrating cavity, and a sensor that is configured to receive light from the integrating cavity, wherein the integrating cavity comprises an optical opening, and wherein the optical measuring device is provided and configured to measure a sample located outside of the integrating cavity directly in front of the optical opening.

Abstract: An agricultural harvesting machine, with at least one work assembly and a monitoring assembly, is disclosed. The agricultural harvesting machine transports harvested material in a harvested material flow along a harvested material transport path. The monitoring assembly includes an measuring system positioned on the harvested material transport path and an evaluation device configured to determine at least one harvested material parameter. The measuring system includes a first passive optical sensor that senses image data indicative of visible light in a first section and a second non-passive non-optical sensor that senses data in a second section that at least partly overlaps the first section. The evaluation device correlates the image data for the overlapping section from the first optical sensor and the data from the second optical sensor and determines, based on the correlation, at least one harvested material parameter.

Abstract: An agricultural harvesting machine, with at least one work assembly and a monitoring assembly, is disclosed. The agricultural harvesting machine transports harvested material in a harvested material flow along a harvested material transport path. The monitoring assembly includes an optical measuring system positioned on the harvested material transport path and an evaluation device configured to determine at least one harvested material parameter. The optical measuring system includes a first optical sensor that senses spatially-resolved image data indicative of visible light in a first section and second optical sensor that senses image data indicative of invisible light in a second section that at least partly overlaps the first section. The evaluation device correlates the image data for the overlapping section from the first optical sensor and from the second optical sensor and determines, based on the correlation, at least one harvested material parameter.

Abstract: A combine harvester has at least one header for cutting plants to be harvested with the aid of the combine harvester, a feeder for conveying the cut plants in the direction of a threshing mechanism, and a threshing mechanism, with the aid of which fruits can be removed from the cut plants in such a way that the fruits are then present separately from plant residue of the plants. The feeder comprises a revolvingly driveable conveying unit and a conveyor channel within which the cut plants can be conveyed with the conveying unit. The feeder interacts with a measuring unit in the form of a sensor unit that contactlessly detects material feed height of plants conveyed with the aid of the feeder in the conveyor channel.

Abstract: A driver assistance system of an agricultural work machine constructed as forage harvester, wherein the agricultural work machine comprises a header for gathering crop, a chopping device having a chopping drum and chopping knives for comminuting the crop, and a monitoring device operable to generate a signal containing information about the wear status of the respective chopping knife and/or about the distance of the cutting edge of a chopping knife from a shear bar. This information is compared with a reference value, and the agricultural work machine has activation devices for activating and deactivating a knife grinding process and means for change of position of the shear bar. The monitoring device is integrated in the driver assistance system so that the driver assistance system automatically detects when a knife grinding process or a change of position of the shear bar must be activated or deactivated.