Abstract: A forage harvester with at least one work assembly is disclosed. The forage harvester has a corn cracker to process grain components and a driver assistance system. The driver assistance system controls the corn cracker by adjusting the machine parameters of the corn cracker. In particular, the driver assistance system has an optimization model which includes a multidimensional characteristic map that represents a relationship between a processing quality of the grain components and at least three parameters that comprise an input parameter representing a current harvesting process state and at least one machine parameter of the corn cracker as an output parameter. Thus, the driver assistance system determines the output parameter in the control routine during the harvesting process based on the varying input parameter from the optimization model and adjusts it in the corn cracker to achieve a uniform given processing quality of the grain components during the harvesting process.

Abstract: A system for determining a crop edge and a self-propelled harvester using the system for automatic control are disclosed. The system comprises a camera that generates optical information of a front environment of the harvester. The system further includes a computing unit that analyzes the images using artificial intelligence so that a planted area of a field on which a plant crop is located may be delimited from a remaining residual area of the field, thereby determining the plant crop. In turn, the computing unit is further configured to determine the crop edge of the plant crop based on the determination of the plant crop and to automatically control the harvester based on the determination of the crop edge.

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 forage harvester is disclosed that includes a blade sharpening and shear bar adjusting device, a monitoring device configured to cyclically generate information on the state of the cutterhead chopping glades and the distance of the shear bar to the cutting edge, and a control unit. The control unit evaluates the information provided by the monitoring device about the state of wear of the chopping blades and the distance, compares it with a limit value for the state of wear and/or the distance, where the limit value forms a lower limit for an optimum range to be maintained by the blade sharpening and shear bar adjusting device, of the instantaneous cutting sharpness of the chopping blades or of the distance and, when the limit value is reached, automatically triggers a sharpening process and/or of a shear bar adjustment by the blade sharpening and shear bar adjusting device.

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: A forage harvester with at least one work assembly is disclosed. The forage harvester has a corn cracker to process grain components and a driver assistance system. The driver assistance system controls the corn cracker by adjusting the machine parameters of the corn cracker. In particular, the driver assistance system has an optimization model which includes a multidimensional characteristic map that represents a relationship between a processing quality of the grain components and at least three parameters that comprise an input parameter representing a current harvesting process state and at least one machine parameter of the corn cracker as an output parameter. Thus, the driver assistance system determines the output parameter in the control routine during the harvesting process based on the varying input parameter from the optimization model and adjusts it in the corn cracker to achieve a uniform given processing quality of the grain components during the harvesting process.

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: 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 self-propelled forage harvester is disclosed. The forage harvester includes a feed device, a chopping device comprising a cutterhead equipped with cutting blades and a shear bar for comminuting harvested material, a drive, and a driver assistance system for controlling at least the chopping device. The driver assistance system includes a memory for saving data and a computing device for processing the data saved in the memory, wherein the chopping device and the driver assistance system in combination form an automatic chopping system in that the computing device continuously determines a compaction of the comminuted harvested material using harvested material parameters during a harvesting process in order to autonomously ascertain and specify a cutting length to be adapted for maintaining nearly constant compactability.

Abstract: A forage harvester has multiple working elements for carrying out a crop handling process, a drive system which is divided into a main drive train that includes mechanically driven working elements, and an auxiliary drive train that includes hydraulically driven working elements, a driver assistance system which comprises a memory for storing data and a computing device for processing data stored in the memory, as well as a graphical user interface. The working elements consist of at least one adjustable crop handler, at least one actuator system for adjusting and/or actuating the crop handler, and a control unit for controlling the actuator system. The working element is designed as an automatic adjuster whose mode of operation can be optimized by the driver assistance system. The driver assistance system feeds a throughput-proportional load signal, which can be determined by at least one sensor system, to the particular automatic adjuster.

Abstract: A self-propelled forage harvester is disclosed. The forage harvester includes a feed device, a chopping device comprising a cutterhead equipped with cutting blades and a shear bar for comminuting harvested material, a drive, and a driver assistance system for controlling at least the chopping device. The driver assistance system includes a memory for saving data and a computing device for processing the data saved in the memory, wherein the chopping device and the driver assistance system in combination form an automatic chopping system in that the computing device continuously determines a compaction of the comminuted harvested material using harvested material parameters during a harvesting process in order to autonomously ascertain and specify a cutting length to be adapted for maintaining nearly constant compactability.

Abstract: A rechopper for chopped crop includes first and second rollers having axially parallel rotational axes, peripheral surfaces disposed opposite one another delimiting a comminution gap and truncated-cone shaped sections. The truncated cone-shaped sections have a base surface (G, G?), a top surface (D, D?) and peripheral surfaces extending at a slant relative to the rotational axis of the respective roller. The base surface (G, G?) and the top surface (D; D;) disposed on the first roller and the second roller have diameters that vary in an alternating manner as viewed in an axial direction (R).

Abstract: A corn header (4) for a forage harvester for harvesting stalked crop includes a set of cutting and intake conveyor mechanisms for cutting the crop in a substantially horizontal direction. A separating mechanism for separating the crop in a substantially vertical direction is positioned on at least one side of the corn header, laterally next to the cutting and intake conveyor mechanisms.

Abstract: A method for operating a forage harvester includes steps of capturing images of chopped material produced in the forage harvester using a camera, identifying images of kernel-type particles in the images, sorting the images of the kernel-type particles into at least two size fractions and determining a cardinality of the size fractions.

Abstract: A rechopper for chopped crop includes first and second rollers having axially parallel rotational axes, peripheral surfaces disposed opposite one another delimiting a comminution gap and truncated-cone shaped sections. The truncated cone-shaped sections have a base surface (G, G?), a top surface (D, D?) and peripheral surfaces extending at a slant relative to the rotational axis of the respective roller. The base surface (G, G?) and the top surface (D; D;) disposed on the first roller and the second roller have diameters that vary in an alternating manner as viewed in an axial direction (R).

Abstract: A corn header (4) for a forage harvester for harvesting stalked crop includes a set of cutting and intake conveyor mechanisms for cutting the crop in a substantially horizontal direction. A separating mechanism for separating the crop in a substantially vertical direction is positioned on at least one side of the corn header, laterally next to the cutting and intake conveyor mechanisms.

Abstract: An agricultural harvesting machine includes different working units, an input and display unit, a memory and evaluation unit, and a control device for influencing adjustable operating parameters of the working units, at least one set criterium being stored in the memory and evaluation unit, and, based on at least one crop material parameter and/or operating parameter that was determined in the harvesting process, and based on the at least one set criterium, a prognosis regarding the attainability of an actual harvesting goal is formulated, the prognosis being taken into account in the adjustment of the operating parameters.

Abstract: A combine harvester has at least one cleaning device which includes at least one sieve and one cleaning fan, at least one conveyor device for conveying at least a portion of the crop material that exits the cleaning device into a higher region of the combine harvester and including at least one elevator having a lower intake region and an upper transfer region, the crop material being conveyed in the elevator via conveyor plates which are situated on a circulating chain, and the elevator includes, in its lower region, at least two interspaced deflection axles for the circulating chain, which are oriented transversely to the longitudinal extension of the combine harvester.

Abstract: An agricultural harvesting machine includes different working units, an input and display unit, a memory and evaluation unit, and a control device for influencing adjustable operating parameters of the working units, at least one set criterium being stored in the memory and evaluation unit, and, based on at least one crop material parameter and/or operating parameter that was determined in the harvesting process, and based on the at least one set criterium, a prognosis regarding the attainability of an actual harvesting goal is formulated, the prognosis being taken into account in the adjustment of the operating parameters.