Unload Conveyor Alignment Using Vision-Based Vehicle Synchronization
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Solution Overview
Problem
The synchronization of agricultural machine operations, particularly during the transfer of crop material from combine harvesters and forage harvesters to receiving vehicles, is laborious and challenging due to limited visibility, environmental conditions, and the need for precise alignment, which existing technologies fail to address effectively.
Innovation Solution
A system equipped with a camera for image capture and processing, machine learning models for vehicle identification, and electromagnetic detecting and ranging modules to generate automated navigation data, enabling the alignment of unloading conveyors with receiving vehicles and monitoring fill levels and distribution, thus assisting or automating the synchronization of machine movements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual alignment of receiving vehicle with unloading conveyor is performed, then operator control flexibility is maintained, but operator workload and difficulty of operation increase significantly
Solution Approach 1:
The patent introduces an automated alignment system that acts as an intermediary between the operator and the vehicles. The system includes sensors mounted on the unloading conveyor that detect the position of the receiving vehicle, and a control system that automatically adjusts the conveyor's position and orientation to achieve alignment. This intermediary system handles the complex alignment task, reducing the operator's workload while maintaining overall system control.
Solution Approach 2:
The patent replaces manual mechanical alignment operations with an automated electromechanical system. Instead of relying on the operator to visually assess and manually adjust the alignment, the system uses sensors to detect vehicle position and automated controls to adjust the conveyor's hydraulic cylinders and positioning mechanisms. This substitution reduces physical workload and improves precision.
2Extent of automation
If automated alignment system is implemented, then operator workload is reduced, but system complexity and initial cost increase
Solution Approach 1:
The automated alignment system serves as an intermediary layer between the existing mechanical unloading infrastructure and the operator. Rather than completely redesigning the unloading system, the patent adds sensors and control logic that work with the existing hydraulic and mechanical components. This approach achieves automation while leveraging existing infrastructure, thereby limiting the increase in overall system complexity.
Solution Approach 2:
The system enables the unloading conveyor to self-align with the receiving vehicle automatically. The sensors continuously monitor the relative position, and the control system autonomously adjusts the conveyor's position without requiring constant operator intervention. This self-service capability reduces the need for complex manual control systems while achieving high levels of automation.
3Productivity
If receiving vehicle has large grain bin capacity, then unloading efficiency is improved, but alignment precision and visibility challenges increase
Solution Approach 1:
The patent replaces visual alignment methods with an automated sensor-based detection and control system. Sensors mounted on the unloading conveyor detect the position, orientation, and dimensions of the receiving vehicle's grain bin. This substitution eliminates the need for the operator to visually estimate alignment, providing precise measurement and control even for large grain bins that are difficult to see or align manually.
Solution Approach 2:
The automated alignment system acts as an intermediary that bridges the gap between the large receiving vehicle and the unloading conveyor. The system's sensors and control algorithms calculate the optimal alignment parameters and automatically adjust the conveyor's position, ensuring precise alignment regardless of the grain bin's size. This intermediary system handles the complexity of aligning with large vehicles, maintaining productivity while ensuring 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
This system improves the efficiency and accuracy of crop transfer operations by providing real-time position data and automated guidance, reducing operator workload and ensuring proper alignment and filling of receiving vehicles, even in challenging environmental conditions.
Implementation Method 1
a camera for capturing images of an area proximate the agricultural harvester and generating image data
Implementation Method 2
an electromagnetic detecting and ranging module for detecting at least one of a fill level and a distribution of grain in the receiving vehicle
Data Source
AI summary
An agricultural harvester includes an unload conveyor for transferring a stream of processed crop out of the agricultural harvester and a camera for capturing images of an area proximate the agricultural harvester and generating image data. A computing device is configured to receive the image data from the camera during a harvest operation; apply a machine learning model to identify, using only image data from the camera, a receiving vehicle from among a plurality of possible different receiving vehicles; determine dimensions associated with the identified receiving vehicle; determine, using the dimensions and the image data, a location of the receiving vehicle relative to the agricultural harvester; and generate automated navigation data based on the location of the receiving vehicle, the automated navigation data to automatically control operation of at least one of the agricultural harvester and the receiving vehicle to align an unloading conveyor with the receiving vehicle.