Harvesting Machine Crop Processing Control via Sensor Feedback
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Solution Overview
Problem
Existing agricultural harvesting machines lack real-time monitoring capabilities to optimize crop processing based on crop content and size, leading to suboptimal performance and inefficiencies.
Innovation Solution
A control system for agricultural harvesting machines that utilizes first and second sensors to receive crop content and size measures, computes a crop processing metric, and generates control signals to adjust the machine's operational parameters in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time sensor monitoring and control adjustment is implemented, then crop processing optimization is improved, but device complexity increases
Solution Approach 1:
The system continuously monitors crop content and size using sensors, computes processing metrics, and adjusts machine operation in real-time based on this feedback. This closed-loop control enables dynamic optimization of crop processing while maintaining manageable system complexity through automated decision-making.
Solution Approach 2:
The harvesting machine autonomously adjusts its own operation based on real-time crop conditions. The control system automatically computes processing metrics from sensor data and generates control signals to optimize processing parameters without requiring external intervention, thereby improving productivity while the system manages its own complexity.
2Use of energy by moving object
If real-time control adjustment is implemented, then fuel efficiency is improved, but device complexity increases
Solution Approach 1:
The system dynamically adjusts machine operation parameters in real-time based on current crop conditions. By continuously adapting processing levels to match actual crop content and size, the system optimizes fuel consumption while the control system manages complexity through automated dynamic adjustment rather than static settings.
Solution Approach 2:
The control system changes operational parameters such as processing level and speed based on real-time crop measurements. This parameter adjustment enables the machine to operate at optimal fuel efficiency points while the automated system handles the complexity of continuous parameter optimization.
3Productivity
If real-time control adjustment is implemented, then throughput is improved, but device complexity increases
Solution Approach 1:
The system uses real-time sensor feedback on crop content and size to dynamically adjust processing parameters, thereby optimizing throughput. The closed-loop control ensures that the machine operates at optimal speeds and processing levels, improving productivity while the automated feedback mechanism manages system complexity.
4Reliability
If real-time control adjustment is implemented, then wear and tear reduction is improved, but device complexity increases
Solution Approach 1:
The system performs preliminary assessment of crop conditions using sensors before finalizing processing parameters. By evaluating crop content and size in advance, the control system can pre-adjust settings to optimal levels, reducing mechanical stress and wear on components while the automated preliminary action manages system complexity.
Solution Approach 2:
The control system dynamically adjusts processing parameters based on real-time crop conditions, preventing operation under suboptimal conditions that would cause excessive wear. This dynamic adaptation protects machine components while the automated system manages the complexity of continuous optimization.
Data Source
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AI summary
Systems and methods are provided for monitoring operation of an agricultural harvesting machine, such as a forage harvester. A first sensor, operably coupled, in use, to the harvesting machine, obtains first sensor data which is indicative of a crop content measure. A second sensor, operably coupled, in use, to the harvesting machine, obtains second sensor data which is indicative of a crop size measure. A crop processing metric is calculated in dependence on the first and second sensor data and used to control operation of one or more operable components of or otherwise associated with the agricultural harvesting machine, e.g. to adjust a level of processing applied by the harvesting machine.