IP Library › Granted Patent US 12,433,190
Granted Patent B2
US 12,433,190 · App. 17/904,271 · Granted Oct 7, 2025

Method for operating a machine for harvesting and/or separating root crops, associated machine and associated computer program product

Inventor: Wolfram Strothmann (Osnabrück, DE)
Assignee: Grimme Landmaschinenfabrik GmbH & Co. KG
A01D33/04A01D33/08G06V20/68
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Quick Facts
Patent No.
US 12,433,190
App. No.
17/904,271
Granted
Oct 7, 2025
Kind
B2
Abstract

A method is provided for operating a machine for harvesting root crops and/or for separating root crops from further additionally conveyed material that includes at least soil in the form of loose earth and/or soil aggregates, and also, if applicable, leaves and/or stones. By means of at least one electromagnetic, in particular optical, or acoustic image capturing unit, at least one inspection image is captured of at least one portion of the material, moved relative to a machine frame of the machine by at least one transport element, in particular a screen belt. On the basis of at least one inspection data set generated using the inspection image and/or formed by this image, an evaluation device generates an adjustment signal for adjusting at least one operating parameter of the transport element and/or a further transport element of the machine. At least one feature for describing the ability to be screened of the additionally conveyed soil is determined by the evaluation device and is used for adjusting the operating parameter. The invention also relates to a machine for harvesting root crops and a computer program product.

Claims (27)

1. A method for operating a machine for harvesting root crops and/or for separating root crops from further additionally conveyed material that includes at least soil in the form of loose earth and/or soil aggregates, the method comprising the steps of:

capturing, by means of at least one electromagnetic or acoustic image acquisition unit, an inspection image of at least one portion of the material moved relative to a machine frame of the machine by a transport element,

generating, on the basis of at least one inspection data set generated using the inspection image and/or formed by the inspection image, via an evaluation device, an adjustment signal for adjusting at least one operating parameter of the transport element and/or a further transport element of the machine,

determining at least one feature for describing a capability of the additionally conveyed soil to be screened by the evaluation device and

using the at least one feature for adjusting the at least one operating parameter.

2. The method as claimed in claim 1 , wherein the at least one feature comprises one or more values which describe the size, shape, strength, or color of one or more soil aggregates and/or one or more distributions of the size, shape, strength or color of a plurality of soil aggregates.

3. The method as claimed in claim 1 wherein the at least one feature is determined by the evaluation device on the basis of an input data set, generated by or formed by the inspection data set, by a neural-network-based, histogram-based and/or structure-from-motion analysis.

4. The method as claimed in claim 3 , wherein the neural network is a convolutional neural network, which classifies each input data set into one of a number of classes which represent values of different screening capability features.

5. The method as claimed in claim 3 , wherein for the determination of the at least one feature by the evaluation device, a region of the inspection image or of the inspection data set is selected that contains at least 75 soil aggregates.

6. The method as claimed in claim 5 , wherein a part of the inspection data set representing the region is provided directly or in processed form as an input data set into the neural-network-based, histogram-based and/or structure-from-motion analysis, in which the region is assigned the at least one feature which is used for adjusting the at least one operating parameter.

7. The method as claimed in claim 1 , wherein by means of a classification method, constituents of the material present in the inspection image are determined.

8. The method as claimed in claim 1 , wherein the evaluation device at least partly evaluates the at least one inspection data set locally on the machine or on a directly connected towing vehicle.

9. The method as claimed in claim 1 , wherein the evaluation device evaluates the at least one inspection data set on a wirelessly connected server.

10. The method as claimed in claim 1 , wherein the at least one operating parameter of the transport element, formed as a screening band, is a screening band speed, a collection screening band speed, an adjustable height of at least one triangular roller, an adjustable height of a drop stage, a frequency of a knocker, an amplitude of a knocker, the position of a knocker, and/or the inner width of the screening band.

11. The method as claimed in claim 1 , wherein a moisture content of the soil aggregates is determined by a moisture sensor and used in the evaluation device for adjusting the at least one operating parameter.

12. The method as claimed in claim 1 , wherein the determination of the at least one operating parameter is part of a control loop of the machine.

13. The method as claimed in claim 12 , wherein a rooting depth and/or a driving speed are additionally controlled with the control loop.

14. The method as claimed in claim 1 , wherein the at least one operating parameter is adjusted by a database in which features and operating parameters are stored such that they are linked to each other.

15. A machine for harvesting root crops and/or for separating root crops, the machine comprising:

at least one electromagnetic or acoustic image acquisition unit,

a transport element, selectively moveable relative to a machine frame of the machine, and

an evaluation device as well as means for adjusting the transport element or an additional transport element, wherein the machine carries out the steps of the method as claimed in claim 1 .

16. A non-transitory computer-readable recording medium with instructions stored thereon, that when executed by a processor, cause a machine for harvesting root crops and/or for separating root crops to execute the following steps:

capturing, by means of at least one electromagnetic or acoustic image acquisition unit, an inspection image of at least one portion of material moved relative to a frame of the machine by a transport element,

generating, on the basis of at least one inspection data set generated using the inspection image and/or formed by this image, via an evaluation device, an adjustment signal for adjusting at least one operating parameter of the transport element and/or a further transport element of the machine,

determining at least one feature for describing a capability of additionally conveyed soil to be screened by the evaluation device, and

using the at least one feature for adjusting the at least one operating parameter.

Assignments (2)
CHANGE OF NAME Recorded Apr 9, 2026
From: GRIMME LANDMASCHINENFABRIK GMBH & CO. KG
To: GRIMME LANDMASCHINENFABRIK SE & CO. KG
Reel/Frame 075373/0665 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 6, 2022
From: STROTHMANN, WOLFRAM
To: GRIMME LANDMASCHINENFABRIK GMBH & CO. KG
Reel/Frame 061621/0746 →
Priority Claims (1)
DE 102020103941.7 · Feb 14, 2020 · national
Continuity (1)
Related Publication 20230080863A1 · Mar 16, 2023
References Cited (39)
US 3435950A · Lew · 1969 [cited by applicant]
US 4324336A · Sandbank · 1982 [cited by applicant]
US 5653633A · Kalverkamp et al. · 1997 [cited by applicant]
US 6119442A · Hale · 2000 [cited by applicant]
US 20070056258A1 · Behnke · 2007 [cited by applicant]
US 20080027888A1 · Azzam et al. · 2008 [cited by applicant]
US 20110112684A1 · Pellenc · 2011 [cited by applicant]
US 20130159671A1 · Brown et al. · 2013 [cited by applicant]
US 20140050364A1 · Brueckner et al. · 2014 [cited by applicant]
US 20170013773A1 · Kirk et al. · 2017 [cited by applicant]
US 20170235471A1 · Scholer et al. · 2017 [cited by applicant]
US 20180042176A1 · Obropta et al. · 2018 [cited by applicant]
US 20180047177A1 · Obropta et al. · 2018 [cited by applicant]
BE 1003540A3 · 1992 [cited by applicant]
CN 104011736A · 2014 [cited by applicant]
CN 104062298A · 2014 [cited by applicant]
CN 105684627A · 2016 [cited by applicant]
CN 110602943A · 2019 [cited by applicant]
CN 112970032A · 2021 [cited by applicant]
CN 112970033A · 2021 [cited by applicant]
DE 213115A1 · 1984 [cited by applicant]
DE 19804147A1 · 1998 [cited by applicant]
DE 102015224175B3 · 2017 [cited by applicant]
EA 202292299A1 · 2022 [cited by applicant]
EP 699379A2 · 1996 [cited by applicant]
EP 1763988A1 · 2007 [cited by applicant]
JP S60122083A · 1985 [cited by applicant]
JP 2011240257A · 2011 [cited by applicant]
JP 2015529154A · 2015 [cited by applicant]
JP 2018001115A · 2018 [cited by applicant]
SU 950227A1 · 1982 [cited by applicant]
WO 2018008041A2 · 2018 [cited by applicant]
WO 2020094654A1 · 2020 [cited by applicant]
WO 2020094655A1 · 2020 [cited by applicant]
Hofsstee, J.W. et al., “Aardappelopbrengst meten met beeldverwerking kan”, Landbouwmechanisatie, Apr. 2003 (Apr. 2003), Issue No. 2003. [cited by applicant]
Third Party Observation issued Jun. 2, 2022. [cited by applicant]
Morquin, D. et al., “An integrated neural network-based vision system for automated separation of clods from agricultural produce”, Engineering Applications of Artificial Intelligence 16, pp. 45-55, Feb. 15, 2003 [Feb. … [cited by applicant]
Rady, Rapid and/or nondestructive quality evaluation methods for potatoes: A review, Computers and Electronics in Agriculture, 2015, pp. 31-48, vol. 117. [cited by applicant]
Office Action and Search Report issued in corresponding CN Application No. 202180014742.8 on Mar. 22, 2024. [cited by applicant]