Agricultural Harvester Control System for Crop Parameter Validation
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Solution Overview
Problem
Agricultural harvesting machines, such as forage harvesters, face issues with determining accurate crop parameters when crop throughput is low or changing, leading to extreme values that result in suboptimal machine settings and potential economic losses due to incomplete coverage of the optical measuring system's viewing area.
Innovation Solution
The implementation of a control arrangement with a second image recognition algorithm to determine the degree of coverage within the viewing area and compare it to a threshold value, allowing for the classification of potentially faulty crop parameters and exclusion from automated settings, utilizing artificial intelligence and semantic segmentation for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If the optical measuring system captures images continuously regardless of crop throughput, then the automated control system can continuously adjust process parameters, but the determined crop parameters become extreme values that do not accurately reflect reality when crop throughput is low or changing
Solution Approach 1:
The system introduces a feedback mechanism where the control unit receives information about crop throughput conditions and uses this feedback to determine whether to trust the determined crop parameters for automated adjustment. When feedback indicates low or changing throughput, the system suspends automated adjustments, preventing erroneous parameter changes while maintaining automation during normal conditions.
Solution Approach 2:
The system changes the operational parameters of the automated control system based on crop throughput conditions. By dynamically adjusting whether automated parameter adjustment is active or suspended based on real-time throughput assessment, the system adapts its measurement and control behavior to current operating conditions, ensuring accuracy is maintained when parameters are used for control.
2Productivity
If the optical measuring system is used to determine crop parameters during operation, then direct adjustment of working units can be achieved, but incomplete coverage of the field of view leads to determination of extreme values and inaccurate crop parameters
Solution Approach 1:
The control unit performs a preliminary assessment of crop throughput conditions before using determined crop parameters for automated adjustment of working units. This preliminary check ensures that parameters are only used when measurement conditions are adequate, preventing unreliable parameters from causing incorrect adjustments during harvesting operations.
Solution Approach 2:
The system implements feedback control where the control unit continuously monitors whether determined crop parameters are reliable based on field of view coverage assessment. This feedback mechanism ensures that automated adjustments of working units are only performed when parameters meet reliability thresholds, maintaining both productivity and reliability during harvesting.
3Productivity
If crop parameters are used for automated setting of process parameters, then harvesting efficiency is improved, but high crop losses occur when parameters represent extreme values due to low or changing crop throughput
Solution Approach 1:
The control unit uses feedback about crop throughput conditions to determine when to trust determined crop parameters for automated process parameter setting. When feedback indicates low or changing throughput that could produce extreme values, the system suspends automated adjustments, preventing crop losses that would result from erroneous parameter-driven decisions while maintaining harvesting efficiency during normal operations.
Solution Approach 2:
The system dynamically changes the operational state of automated parameter adjustment based on crop throughput conditions. By switching between active and suspended states of automated control based on real-time throughput assessment, the system maintains harvesting efficiency when conditions are favorable while preventing crop losses when measurement reliability is compromised.
Data Source
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AI summary
The present invention relates to an agricultural harvesting machine (1) with at least one working unit (6) for harvesting a field crop (4) and/or for processing the harvested crop (5) from the field crop (4). The harvesting machine (1) has a control arrangement (14) which includes an optical measuring system (15) for acquiring image data of the harvested crop (5) of a crop stream (E) located within a field of view (17) of the optical measuring system (15). The optical measuring system (15) is configured to determine at least one crop parameter of the harvested crop (5) from the image data using a first image recognition algorithm in an image recognition routine.The harvesting machine (1) is characterized in that the control arrangement (14) is configured to determine, in addition to the at least one crop parameter, a degree of coverage of the viewing area (17) with crop (5) in the image recognition routine using a second image recognition algorithm based on the image data, to compare the degree of coverage with a predefinable threshold value for the degree of coverage and, if the threshold value is undershot, to classify the determined crop parameter as unsuitable.