Implement Wear Detection Using Pull Vectors and Soil Imaging
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Solution Overview
Problem
Automated farming operations lack effective monitoring of implement wear and states, leading to potential damage to implements and other vehicles due to insufficient real-time feedback to operators.
Innovation Solution
An implement management system that uses sensors and machine learning models to detect implement wear by measuring orientation vectors and monitor implement states through image analysis, allowing for real-time adjustments to the vehicle's operating mode to prevent damage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated farming operations are used to increase productivity, then the operator can perform other tasks in parallel, but the operator becomes unavailable to monitor implement conditions during operation
Solution Approach 1:
The implement management system enables the implement to monitor itself through integrated sensors that automatically detect wear conditions and state parameters without requiring operator intervention. The system self-diagnoses implement health by continuously collecting data from force sensors, angle sensors, and cameras, then processes this information to determine wear levels and alert operators only when necessary.
Solution Approach 2:
The patent replaces manual visual inspection with automated sensing systems. Force sensors substitute for operator tactile assessment, angle sensors replace visual angle measurement, and camera systems with machine learning models substitute for operator visual judgment of implement condition. This mechanical-to-automated substitution maintains monitoring reliability while enabling operator availability for other tasks.
2Ease of operation
If the operator periodically checks the implement from the cabin, then monitoring is possible, but the operator cannot continuously monitor during automated operations
Solution Approach 1:
The sensor system operates continuously throughout implement operation, constantly collecting data on force, angle, and visual conditions. This continuous monitoring replaces periodic manual checks, ensuring no wear events are missed while requiring minimal operator attention. The system maintains uninterrupted surveillance of implement health parameters without burdening the operator.
Solution Approach 2:
The patent introduces an intermediary automated monitoring system between the operator and the implement. Sensors and processing electronics act as intermediaries that continuously observe implement conditions and only engage the operator when wear thresholds are exceeded. This intermediary layer provides reliable continuous monitoring while keeping the operator out of the monitoring loop during normal operation.
3Productivity
If the implement is not monitored properly, then the operator can focus on other tasks, but the implement may break or a component may fall off causing damage
Solution Approach 1:
The system performs preliminary detection of wear conditions before they progress to failure. By continuously monitoring force and angle deviations and comparing them against wear models, the system identifies early signs of component degradation. Alerts are generated proactively when wear reaches predetermined thresholds, allowing operators to address issues before components break or detach and cause damage.
Solution Approach 2:
The implement management system establishes a closed-loop feedback mechanism where sensor data continuously feeds into wear analysis algorithms, which then provide feedback to the operator through alerts. This feedback loop maintains operational efficiency by allowing uninterrupted work while simultaneously preventing damage through timely warnings about deteriorating implement conditions. The system balances productivity and safety through automated feedback rather than continuous operator attention.
Data Source
AI summary
An implement management system detects implement wear and monitors implement states to modify operating modes of a vehicle. The system can determine implement wear using the pull of the implement on the vehicle, the force and angle of which is represented by an orientation vector. The system may measure a current orientation vector and determine an expected orientation vector using sensors and a model (e.g., a machine learned model). Additionally, the implement management system can determine an implement state based on images of the soil and the implement captured by a camera onboard the vehicle during operation. The system may apply different models to the images to determine a likely state of the implement. The difference between the expected and current orientation vectors or the determined implement state may be used to determine whether and how the vehicle's operating mode should be modified.