Disk Gang Load Monitoring for Accurate Plugging Detection
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Solution Overview
Problem
Existing systems struggle to accurately detect disk gang plugging during tillage operations, making it difficult for operators to determine when corrective actions are necessary to remove accumulated field materials.
Innovation Solution
A tillage implement equipped with load sensors and a computing system that determines total and average loads per disk gang, using correction factors and penetration depth to calculate a plug status value, initiating control actions such as notifications or adjustments to prevent plugging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If load sensors are installed on each disk gang to detect plugging, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The system divides the tillage implement into multiple disk gangs, each equipped with its own load sensors. This segmentation allows independent monitoring of each disk gang's load conditions, enabling precise detection of plugging events on specific gangs while maintaining overall system manageability through modular architecture.
Solution Approach 2:
The load sensors serve multiple functions: they detect plugging conditions, monitor soil resistance variations, and provide data for optimizing tillage depth and speed. This multi-functionality improves detection accuracy while justifying the added system complexity through versatile operational benefits.
2Reliability
If average load per disk is calculated to normalize detection, then detection reliability is improved, but computational requirements increase
Solution Approach 1:
The system transforms raw load sensor data into normalized parameters by calculating average load per disk. This parameter transformation accounts for variations in disk size, number of disks per gang, and soil conditions, significantly improving detection reliability while using computationally efficient averaging algorithms.
Solution Approach 2:
The system applies different normalization factors to different disk gangs based on their specific characteristics (number of disks, size variations). This localized approach ensures each gang is evaluated against its own baseline, improving reliability without requiring complex global models.
3Productivity
If real-time load monitoring is implemented, then productivity is improved through timely corrective actions, but energy consumption increases
Solution Approach 1:
The system continuously monitors load on each disk gang and provides real-time feedback to the operator through alerts or automated controls. This feedback mechanism enables immediate corrective actions when plugging is detected, maintaining high productivity by preventing efficiency losses from undetected plugging events.
Solution Approach 2:
Instead of continuous high-power processing, the system uses periodic sampling of load sensor data and threshold-based detection. This approach maintains productivity through timely detection while reducing energy consumption by processing data only when changes exceed predetermined thresholds.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides accurate detection of disk gang plugging by normalizing loads based on disk size and number, enabling timely corrective actions to maintain efficient tillage operations.
Implementation Method 1
a plurality of load sensors configured to generate data indicative of loads being applied to the plurality of disk gangs
Data Source
AI summary
A tillage implement includes a plurality of disk gangs, with each disk gang including a shaft and a plurality of disks spaced apart from each other along the shaft. Furthermore, the tillage implement includes a plurality of load sensors configured to generate data indicative of loads being applied to the plurality of disk gangs and a computing system communicatively coupled to the plurality of sensors. In this respect, the computing system is configured to determine a total load being applied to each disk gang based on the data generated by the plurality of load sensors. Additionally, the computing system is configured to determine an average load per disk being applied to each disk gang based on the determined total loads. Moreover, the computing system is configured to determine a plug status value for each disk gang based on the determined average loads per disk.