Predictive Row Cleaner Control for Consistent Seedbed Depth
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing seeding implements face challenges in creating a clean, consistent seedbed due to residue from previous harvests, which can prevent opener discs from reaching the desired trench depth and affect planting efficiency.
Innovation Solution
A system comprising a row cleaner, a work vehicle, sensors, and a controller that dynamically adjusts the pressure applied by the row cleaner and the speed of the work vehicle based on real-time sensor data and pre-planting data, such as satellite and historical harvest data, to optimize seedbed preparation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the row cleaner applies high pressure to break up residue, then the seedbed cleanliness is improved, but the energy consumption increases
Solution Approach 1:
The row cleaner system dynamically adjusts the downforce pressure applied to the soil surface based on real-time sensor data about residue conditions. The controller modulates the hydraulic system to vary pressure levels, applying higher pressure only when and where residue requires intensive breaking, rather than maintaining constant high pressure across all terrain, thus reducing overall energy consumption while maintaining seedbed cleanliness standards.
Solution Approach 2:
The system changes operating parameters (downforce pressure, vehicle speed) based on detected field conditions. Sensors detect residue type and quantity, and the controller adjusts pressure parameters accordingly - applying higher pressure for heavy residue patches and lower pressure for clean areas, optimizing the balance between seedbed preparation quality and energy usage.
2Manufacturing precision
If the work vehicle reduces speed to allow the row cleaner to break up residue effectively, then the seedbed preparation quality is improved, but the productivity decreases
Solution Approach 1:
The work vehicle speed is dynamically adjusted based on real-time residue detection. The system maintains higher speeds on clean terrain to preserve productivity, and automatically reduces speed only when sensors detect areas requiring intensive residue breaking, thus minimizing the impact on overall planting efficiency while ensuring seedbed preparation quality in problem areas.
Solution Approach 2:
The system applies different speed regimes to different field zones based on local residue conditions. Rather than reducing speed uniformly across the entire field, the controller identifies specific areas with excessive residue and reduces speed only in those localized zones, maintaining optimal speed in clean areas to preserve overall productivity.
3Ease of operation
If the row cleaner applies consistent pressure across all field conditions, then the operating simplicity is maintained, but the seedbed consistency deteriorates
Solution Approach 1:
The row cleaner system operates autonomously by detecting field conditions and self-adjusting its downforce pressure without operator intervention. Sensors continuously monitor residue conditions, and the controller automatically modulates hydraulic pressure to maintain optimal seedbed consistency across varying terrain, eliminating the need for manual pressure adjustments while ensuring consistent results.
Solution Approach 2:
The system incorporates sensor feedback loops that continuously monitor field conditions and adjust row cleaner pressure in real-time. The sensors detect variations in residue and soil conditions, and the controller uses this feedback to automatically pressure-modulate the row cleaner, maintaining seedbed consistency without requiring operator awareness or intervention.
4Productivity
If the system uses multiple sensors and real-time data processing to optimize row cleaner operation, then the planting efficiency is improved, but the device complexity increases
Solution Approach 1:
The sensor system and controller are designed to perform multiple functions: detecting residue type, measuring residue quantity, determining optimal pressure settings, and coordinating vehicle speed adjustments. This multi-functionality consolidates what could be separate complex subsystems into an integrated control architecture, improving planting efficiency while limiting the growth of overall system complexity.
Data Source
AI summary
A system may include a row cleaner configured to apply a pressure to a field and a work vehicle coupled to the row cleaner and configured to traverse through the field, where the work vehicle comprising an engine configured to adjust a speed of the work vehicle. The system may also include a sensor configured to provide sensor data indicative of the field and a controller comprising a memory and a processor, where the controller is communicatively coupled to the row cleaner, the engine, and the sensor. The controller may provide an instruction to adjust the pressure applied by the row cleaner, the speed of the engine, or both based on the sensor data.