Agricultural Machine Control for Adaptive Residue Chopping Thresholds
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Solution Overview
Problem
Traditional control systems for agricultural work machines, such as harvesters, struggle with inconsistent operational environments, leading to over-reactions or under-reactions in adjusting operational parameters due to fixed threshold values, which can result in inefficient power consumption and suboptimal residue chopping quality.
Innovation Solution
A system that learns the responsiveness of agricultural work machines by analyzing sensor data to determine a threshold target value for adjusting operational parameters, using a control unit to make real-time adjustments based on the relationship between operational and performance parameters, ensuring efficient power consumption and desired chopping quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If fixed threshold values are used for adjusting operational parameters, then the control system is simple to implement, but the system produces over-reactions or under-reactions leading to inefficient power consumption and suboptimal residue chopping quality
Solution Approach 1:
The patent transforms the static fixed threshold control system into a dynamic adaptive control system. The control unit continuously learns and updates the responsiveness characteristics of the agricultural work machine based on sensor data, enabling the threshold values to adapt automatically to varying field conditions and machine states, thereby resolving the contradiction between implementation simplicity and operational effectiveness
Solution Approach 2:
The control system performs self-learning and self-adjustment by automatically monitoring sensor data, analyzing machine responsiveness, and updating control parameters without external intervention. This self-service capability eliminates the need for manual calibration while optimizing residue chopping quality and power consumption across diverse operating conditions
2Manufacturing precision
If aggressive adjustments to operational parameters are made to improve residue chopping quality, then chopping quality improves, but power consumption increases disproportionately
Solution Approach 1:
The patent implements a feedback mechanism where sensor data continuously monitors both residue chopping quality and power consumption. The control unit analyzes this feedback to determine the actual responsiveness of the machine, enabling it to make precise, minimal adjustments that achieve quality improvements without excessive power consumption by adapting to the machine's true operational characteristics
Solution Approach 2:
The control system dynamically adjusts operational parameters based on learned responsiveness characteristics. By understanding how specific parameter changes affect machine performance, the system can make optimized adjustments that achieve desired chopping quality while minimizing power consumption, avoiding both aggressive over-adjustments and insufficient corrections
3Manufacturing precision
If the control system makes frequent adjustments to operational parameters, then residue chopping quality improves, but the system complexity increases
Solution Approach 1:
The control system automatically performs sensing, analysis, and adjustment operations without external intervention. The control unit continuously monitors sensor data, learns machine responsiveness characteristics, and autonomously determines when and how to adjust operational parameters, maintaining high chopping quality while managing system complexity through automated decision-making
Data Source
AI summary
An agricultural system includes one or more processors and memory storing instructions executable by the one or more processors, that, when executed, cause the agricultural system to: obtain first sensed data representative of one or more performance parameters; generate a command to adjust, by a first adjustment value, an operational parameter of the agricultural work machine; obtain second sensed data representative of the one or more performance parameters, the first sensed data generated prior to the adjustment and the second sensed data generated after the adjustment; compare the one or more performance parameters of the agricultural work machine, represented by the first sensor data, to the one or more performance parameters of the agricultural work machine, represented by the second sensor data; generate a threshold target value for use in adjusting the operational parameter based on the comparison; and control the agricultural work machine based on the threshold target value.