Tillage Element Damage Detection via Reference Comparison
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Solution Overview
Problem
Monitoring the health and function of agricultural tillage machines is challenging due to visibility issues caused by soil and crop residue, which limits the effectiveness of sensors in autonomous operations.
Innovation Solution
A method and system that generate and compare representations of tillage elements when engaged with the soil and when raised above ground using computing devices to detect damage, employing sensors and lift elements to assess position and condition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are used to monitor tillage elements while engaged with soil, then damage detection capability is improved, but visibility is obscured by soil and crop residue making monitoring ineffective
Solution Approach 1:
The system captures images of tillage elements before they engage with the soil (when visibility is clear) and stores them as reference images. This preliminary action allows subsequent damage detection to occur by comparing current images against these pre-captured references, eliminating the need to monitor during obscured engagement conditions.
Solution Approach 2:
The system creates visual copies (images) of the tillage elements in their known good state and uses these copies for comparison. By capturing and storing reference images before soil engagement, the system can detect damage by comparing current visual copies against the stored reference copies, bypassing the visibility problem during actual engagement.
2Loss of time
If continuous monitoring of tillage elements is performed during field traversal, then damage detection timeliness is improved, but system complexity increases due to challenging environmental conditions
Solution Approach 1:
Instead of continuous monitoring during engagement, the system performs periodic image capture at specific moments when tillage elements are raised above ground and visibility is clear. This periodic approach maintains damage detection capability while significantly reducing system complexity compared to continuous monitoring through obscured conditions.
Solution Approach 2:
The system performs the complex image capture and reference storage operation in advance (when conditions are favorable), enabling simple comparison operations later. This shifts the computational and sensing complexity to a preliminary phase when visibility is good, allowing timely detection without maintaining complex monitoring during engagement.
3Measurement precision
If images are captured both before and after soil engagement, then damage detection accuracy is improved, but image processing time and computational resources increase
Solution Approach 1:
The system captures and processes reference images in advance (before soil engagement or when elements are raised), storing them for later comparison. By performing the image capture and initial processing preliminarily, the actual damage detection requires only comparison operations, reducing real-time processing time while maintaining high accuracy through pre-established references.
Data Source
AI summary
An agricultural machine includes a body configured to traverse a field, the body carrying tillage elements configured to engage soil. At least one lift element is configured to raise the tillage elements above ground. A sensor is configured to detect a position of tillage elements above the ground. A computing device is configured to compare the detected position to a reference to detect damage to the agricultural machine. A method includes generating a first representation of tillage elements, traversing a field with the tillage elements engaging soil of the field, raising the tillage elements above ground to disengage the soil of the field, generating a second representation of the tillage elements while the tillage elements are above the ground, and comparing the second representation to the first representation to detect damage to the agricultural implement. Generating and comparing the representations are performed by at least one computing device.