Concave-Rotor Clearance Control Using Kernel Size Feedback
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Solution Overview
Problem
Existing systems for adjusting operating clearance between concave assemblies and crop processing rotors in combine harvesters are inefficient and fail to adapt to varying crop sizes and conditions, leading to inconsistent spring forces and cumbersome adjustments.
Innovation Solution
A system that utilizes image sensors to capture and analyze kernel dimensions, determines central core sizes, and adjusts operating clearance based on boundary conditions, including a feedback loop and additional factors like debris-to-kernel ratio, to automate the adjustment process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual adjustment of operating clearance is used, then the system can be simple in structure, but the adjustment process becomes cumbersome and inefficient
Solution Approach 1:
The system automatically adjusts operating clearance based on real-time crop condition detection and historical data analysis, eliminating the need for manual intervention. The controller autonomously determines optimal clearance values and actuates the concave assembly position without operator input, making the system self-regulating and highly efficient.
Solution Approach 2:
The patent replaces manual mechanical adjustment with an automated control system that uses sensors, processors, and actuators. The mechanical adjustment mechanism is coupled to a controller that receives input from crop condition sensors and automatically positions the concave assembly, substituting human-operated mechanical systems with automated electromechanical systems.
2Reliability
If fixed spring force is applied to concave assembly, then the structure is simple, but the spring force becomes inconsistent under varying crop conditions
Solution Approach 1:
The system transitions from a static spring force mechanism to a dynamic adjustment system. The controller continuously monitors crop conditions and adjusts the concave assembly position in real-time, allowing the operating clearance to dynamically adapt to varying crop sizes, moisture content, and debris levels, ensuring consistent processing performance.
Solution Approach 2:
The system incorporates feedback loops where sensors detect crop conditions and debris-to-kernel ratios, the controller processes this information along with historical data, and adjusts the concave assembly position accordingly. This closed-loop control ensures consistent spring force application by continuously correcting for variations in crop conditions.
3Adaptability or versatility
If operating clearance is adjusted for different crop sizes, then the system becomes adaptable, but the adjustment process becomes complex and time-consuming
Solution Approach 1:
The system uses historical crop data stored in memory to pre-determine optimal operating clearance settings for different crop types and conditions. When a new crop is detected, the controller retrieves relevant historical data and quickly adjusts the concave assembly position, eliminating the need for time-consuming manual trial-and-error adjustments.
Solution Approach 2:
The automated control system independently monitors crop conditions and self-adjusts the operating clearance without requiring operator intervention. The controller continuously adapts to changing crop conditions by processing sensor data and automatically repositioning the concave assembly, making the system highly adaptable and responsive to varying crop sizes and types.
4Measurement precision
If image sensors are used to detect kernel dimensions, then measurement precision is improved, but the system complexity increases
Solution Approach 1:
The system replaces manual measurement methods with automated image sensors and computer vision technology. The sensor captures images of kernels, and the controller processes these images to automatically determine kernel dimensions, replacing mechanical calipers or manual measurement with optical detection and digital image analysis.
Solution Approach 2:
The system creates digital copies of kernels through image capture and uses these copies for measurement and analysis. The controller processes the image data to extract dimensional information without physically contacting the kernels, using optical copies instead of direct mechanical measurement.
Data Source
AI summary
Technologies for controlling operating clearance between a concave assembly and a crop processing rotor of a combine harvester can be automated. The technologies can include a device configured to estimate respective dimensions of kernels of a crop harvested by a combine harvester as well as determine boundary conditions for the operating clearance based on the estimated respective dimensions of the kernels. Also, the boundary conditions are related to respective central core sizes (such as respective cob sizes) which can be determined based on the estimated respective dimensions of the kernels. The determination can include deriving the boundary conditions from a table including correlations between kernel dimensions and central core sizes, and the table can be enhanced by a feedback loop. The operating clearance can be automatically adjusted according to the determined boundary conditions and some additional factors such as a debris-to-kernel ratio in an output of the harvester.