Harvester Vision System for Crop Transfer Alignment
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Solution Overview
Problem
Operators of receiving vehicles face challenges in aligning the grain bin with the spout of a combine or forage harvester during unloading, especially in conditions like excessive dust or nighttime, due to limited visibility, and must estimate the fill pattern to evenly fill large grain bins, which can lead to inefficiencies and grain spillage.
Innovation Solution
A harvester equipped with a vision system featuring two cameras with overlapping fields of view, allowing the formation of a single two-dimensional image and stereo image to determine the location of the receiving vehicle relative to the harvester, enabling precise alignment of the crop transfer arm with the receiving vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the operator manually aligns the grain bin with the spout during unloading, then the receiving vehicle can be positioned correctly, but the operator cannot see into the bin to monitor fill pattern, leading to uneven filling and grain spillage
Solution Approach 1:
A vision system with cameras acts as an intermediary between the operator and the grain bin fill pattern. The cameras capture images of the grain flow and bin filling process, transmitting this visual information to the operator who cannot directly observe it from the cabin. This mediator enables the operator to see and respond to fill patterns without leaving the protected operator position.
Solution Approach 2:
The patent replaces manual visual estimation and mechanical alignment with an automated vision-based system. Instead of relying on the operator's ability to estimate fill patterns through limited visibility, the system uses cameras and image processing to automatically detect and communicate fill status, enabling more precise control without manual intervention.
2Quantity of substance
If the receiving vehicle has a large grain bin to increase capacity, then more grain can be transported, but it becomes harder to evenly fill the bin and avoid spillage due to limited operator visibility
Solution Approach 1:
The vision system provides real-time feedback on the grain fill pattern within the bin. Cameras capture the distribution of grain as it enters the bin, and this information is processed to show the operator whether the fill is even or concentrated in specific areas. This feedback loop enables the operator to adjust the receiving vehicle's position or the unloading rate to achieve even filling, regardless of bin size.
Solution Approach 2:
For large bins that are difficult to monitor, the vision system serves as a critical intermediary that extends the operator's observational capability. The camera system acts as eyes within the bin, providing visual information about fill patterns that would otherwise be completely invisible to the operator, enabling effective management of large-capacity bins.
3Ease of operation
If the operator tries to estimate fill pattern from the cabin to fill the bin evenly, then some control is possible, but estimation errors lead to grain spillage and reduced efficiency
Solution Approach 1:
The patent substitutes the operator's human estimation capability with an automated vision-based detection system. Cameras and image processing algorithms objectively measure the fill pattern, replacing subjective visual estimation with precise, quantifiable data. This substitution eliminates estimation errors while maintaining operator control through informed decision-making based on accurate visual feedback.
Solution Approach 2:
The system provides accurate visual feedback on the actual fill pattern, enabling the operator to make precise adjustments. Rather than relying on estimation, the operator receives real-time information about grain distribution, allowing for accurate control of the filling process and prevention of spillage.
Data Source
AI summary
A harvester includes a crop processor, a crop transfer arm and a vision system with a first camera with a field of view of at least one hundred and forty degrees and a second camera with a field of view of at least one hundred and forty degrees. A control system is configured to combine image data from the first camera and the second camera to form a single two-dimensional image, use the single two-dimensional image to identify the receiving vehicle, combine image data from the first camera and the second camera to form a stereo image, and use the stereo image to determine a location of the receiving vehicle relative to the harvester.