Harvester Crop Flow Monitoring via Zone-Based Camera Detection
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Solution Overview
Problem
Existing self-propelled harvesting machines require continuous manual monitoring of crop flow within the harvesting attachment to prevent uneven crop speed, grain losses, and detection of foreign bodies, which is labor-intensive and prone to operator error, and existing detection systems are limited in their ability to detect issues beyond a small area or foreign bodies.
Innovation Solution
A self-propelled harvesting machine equipped with a sensor unit featuring cameras that monitor the crop flow across the entire harvesting attachment, connected to an evaluation and control unit that automatically adjusts operational parameters and provides warnings or countermeasures for crop flow problems and foreign bodies, using image evaluation methods to detect irregularities and motion blur or image comparison techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an optical sensor is arranged above the feeder conveyor's inlet to detect crop material properties, then the combine harvester can automatically adjust working element settings based on crop color analysis, but the detection is limited to a very small area directly in front of the feeder conveyor and cannot detect crop flow problems or foreign objects in other areas
Solution Approach 1:
The monitoring area is divided into multiple zones (first zone between stem dividers and cutter bar, second zone behind cutter bar to cross-conveyor auger) with different monitoring requirements. The system segments the header into monitored and non-monitored areas based on partial width utilization detection, applying monitoring only to active harvesting zones.
Solution Approach 2:
The system transitions from a single point detection (optical sensor above feeder conveyor) to area-wide monitoring by implementing zone-based monitoring across the entire header width, adding spatial dimensionality to the detection coverage.
2Reliability
If the operator continuously monitors the crop flow within the harvesting attachment to detect uneven flow, foreign objects, and grain losses, then crop flow problems can be detected, but the operator requires considerable concentration throughout the entire harvesting process
Solution Approach 1:
The harvesting system performs self-monitoring through automated sensors and image evaluation that detect crop flow irregularities, foreign objects, and material properties without requiring continuous operator attention. The system monitors itself and can trigger automatic responses or warnings.
Solution Approach 2:
The system continuously captures images of the crop flow, evaluates them in real-time, and provides feedback to the operator through warnings or automatic adjustments. This closed-loop feedback mechanism replaces manual monitoring with automated detection and response.
3Reliability
If the camera monitors the entire crop flow within the harvesting header, then early detection of foreign objects and crop flow problems is achieved, but the system complexity increases
Solution Approach 1:
The monitoring system applies different monitoring strategies to different zones: the first zone (between stem dividers and cutter bar) is monitored for foreign objects and crop flow irregularities, while the second zone (behind cutter bar to cross-conveyor auger) is monitored for crop flow uniformity. Non-active areas are excluded from monitoring when partial width utilization is detected.
4Productivity
If the system monitors only the part of the harvesting header that is being supplied with crop when partial width utilization is detected, then the monitoring efficiency is improved, but the detection coverage is reduced
Solution Approach 1:
The monitoring system dynamically adapts its coverage area based on actual harvesting conditions. When partial width utilization is detected, the system automatically adjusts which zones are monitored, focusing computational resources on active harvesting areas rather than the entire header width.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively relieves the operator of continuous monitoring, enabling early detection of crop flow issues and foreign bodies, reducing grain losses and potential damage to machinery by automatically adjusting settings and providing alerts or corrective actions.
Implementation Method 1
The image evaluation method is advantageously designed as a motion blur technique, in which the exposure time of the individual images can be adjusted so that motion blur from the moving crop flow is captured and irregularities in the crop flow are displayed as sharp images.
Implementation Method 2
The image evaluation method is designed as an image comparison method in which the exposure time of the individual images is adjustable such that a shift in crop characteristics from image to image can be detected.
Data Source
Figure 1
AI summary
The self-propelled harvesting machine (1) is provided with a harvest recovery attachment (3), which has a harvested crop receiving device and a harvested crop conveyer system. A sensor unit (5) is provided, which monitors the harvested crop flow within the harvest recovery attachment.