Optical Trailer Status Prediction for Crop Transfer Control
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Solution Overview
Problem
Simultaneously controlling the harvesting and crop transfer process between an agricultural harvester and a trailer is difficult, leading to potential crop spillage, especially in conditions that cause temporary signal drop-outs in camera-based systems.
Innovation Solution
A method using an optical sensor to obtain and process image data for determining and estimating status parameters of a trailer, allowing proactive adjustments to the crop transfer process, including predicting future positions and conditions to minimize spillage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If camera-based automatic crop transfer control systems are used to assist the driver, then the operator's task is alleviated, but the system is vulnerable to temporary signal drop-outs and cannot provide full automation
Solution Approach 1:
The system performs preliminary actions by continuously estimating trailer status parameters (position, orientation, filling level) based on historical image data and movement patterns before actual crop transfer occurs. This allows the control system to proactively adjust the crop transfer process to prevent misalignment and spillage, rather than merely reacting to current conditions. The estimation mechanism prepares the system in advance for potential changes in trailer status, ensuring continuous reliable control even during temporary signal drop-outs.
2Measurement precision
If the crop transfer control system reacts to current image data, then it can respond to actual conditions, but it cannot prevent misalignment before it occurs
Solution Approach 1:
The system performs preliminary actions by continuously estimating trailer status parameters (position, orientation, filling level) based on historical image data and movement patterns before actual crop transfer occurs. This allows the control system to proactively adjust the crop transfer process to prevent misalignment and spillage, rather than merely reacting to current conditions. The estimation mechanism prepares the system in advance for potential changes in trailer status, ensuring continuous reliable control even during temporary signal drop-outs.
Solution Approach 2:
The system dynamically adapts the crop transfer process by continuously updating trailer status estimates and adjusting transfer parameters in real-time. The control system modifies crop transfer rate, spout positioning, and other parameters based on predicted trailer conditions, enabling proactive prevention of misalignment rather than static or reactive control.
3Measurement precision
If the optical sensor continuously monitors the trailer, then accurate status parameters are obtained, but the system complexity increases
Solution Approach 1:
The system creates a virtual model (copy) of the trailer's status by estimating position, orientation, and filling level parameters based on processed image data and movement patterns. This virtual representation allows the control system to work with simplified parameter estimates rather than requiring direct continuous sensing of all trailer conditions, reducing system complexity while maintaining measurement precision.
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 provides robust crop transfer control with minimal spillage risk, even in conditions causing signal drop-outs, by preemptively adjusting the process to avoid misalignment and optimize crop delivery.
Implementation Method 1
using an optical sensor of the agricultural harvester to obtain image data relating to the nearby trailer
Data Source
Figure 1
Figure 2
AI summary
A method of controlling a crop transfer process for transferring crop (40) between an agricultural harvester (10) and a nearby trailer (30). The method comprises, at different points in time, using an optical sensor (16) of the agricultural harvester (10) to obtain image data relating to the nearby trailer (30). The obtained image data is processed to determine a status parameter of the nearby trailer (30) at those different points in time. Based on the determined status parameter at the different points in time, the status parameter of the nearby trailer (30) at a further and later point in time is estimated. The crop transfer process is then adjusted in dependence of the estimated status parameter.