Tailings Elevator Plug Prevention via Sensor Metrics
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Solution Overview
Problem
Agricultural equipment, such as combines, face downtime and reduced efficiency due to tailings elevator plugging, which is difficult to anticipate and can be caused by increased tailings volume from changes in machine settings or field conditions, leading to potential damage to machine components.
Innovation Solution
A sensor system that generates a metric indicating the likelihood of tailings elevator plugging, allowing a controller to automatically adjust controllable mechanisms, such as sieve clearance, chaffer settings, and fan speed, to prevent plugging and maintain optimal tailings volume.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the operator manually monitors and responds to tailings elevator plugging conditions, then the machine can operate with simple equipment, but the machine downtime increases and harvesting efficiency decreases
Solution Approach 1:
The system performs preliminary action by detecting tailings volume changes and predicting plugging conditions before they occur. The controller continuously monitors tailings volume metrics and makes proactive adjustments to controllable mechanisms (sieve clearance, chaffer settings, fan speed) to prevent plugging, rather than waiting for manual detection and response.
Solution Approach 2:
The system implements feedback by continuously monitoring tailings volume through sensors and using this information to automatically adjust machine settings. The controller receives sensor signals, generates tailings volume metrics, and uses this feedback loop to maintain optimal operating conditions and prevent plugging events.
2Reliability
If the operator manually adjusts machine settings to prevent plugging, then the equipment complexity remains low, but the operator cannot react quickly enough to rapid changes in field conditions
Solution Approach 1:
The system enables self-service by automatically monitoring tailings volume and adjusting controllable mechanisms without operator intervention. The controller independently processes sensor data, determines when adjustments are needed, and executes the adjustments to controllable mechanisms, freeing the operator from continuous manual monitoring and adjustment tasks.
Solution Approach 2:
The system replaces manual mechanical operation with an automated control system. Instead of the operator manually adjusting settings based on visual inspection or experience, the controller uses sensor data and automated logic to adjust sieve clearance, chaffer settings, and fan speed, providing faster and more consistent responses to changing conditions.
3Productivity
If the tailings elevator operates at high capacity to maintain productivity, then the harvesting efficiency is maximized, but the risk of plugging increases
Solution Approach 1:
The system applies dynamics by continuously adapting machine settings based on real-time tailings volume conditions. Rather than operating at a fixed high capacity setting, the controller dynamically adjusts controllable mechanisms (increasing sieve clearance, modifying chaffer settings, changing fan speed) in response to detected tailings volume changes, allowing the system to maintain high productivity while adapting to conditions that reduce plugging risk.
Data Source
AI summary
A sensor signal is received, and is indicative of a sensed parameter. A metric is generated that indicates a likelihood of a tailings elevator plug, based upon the sensed parameter. A controller determines whether adjustments to controllable mechanisms are to be made, based upon the metric, in order to avoid a tailings elevator plug and, if so, automatically makes the adjustments.