Reclaimer Control System Using Historical Data for Overflow Prevention
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current control systems for reclaimers face challenges in anticipating and responding to sudden changes in material bench stability, leading to potential overflows and reduced productivity due to delayed response times caused by acceleration and deceleration ramps, and the high cost of robust 2D sensors.
Innovation Solution
A semi-automatic control system that memorizes and utilizes past operating parameters, such as boom turning speed and mass flow rate, to calculate ideal boom turning speeds, integrating this information into a PID controller to anticipate and adjust control actions in real-time, avoiding overflows and maintaining high productivity without the need for robust 2D sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a scale is mounted at a distance from the bucket wheel to avoid interference, then measurement reliability is improved, but response time deteriorates due to 10-15 second delay
Solution Approach 1:
The system performs preliminary actions by memorizing operating parameters (boom angular position, bucket wheel speed, mass flow rate) during each boom turning movement and using this historical data to predict and adjust speeds in subsequent movements. This anticipatory approach compensates for the inherent delay in scale measurements by preparing control adjustments in advance based on past performance patterns.
Solution Approach 2:
The system implements feedback by continuously measuring mass flow rate with the scale, comparing it against desired values, and using PID controllers to adjust boom turning speed and bucket wheel speed. The feedback loop is enhanced by incorporating historical data from previous boom movements to improve the responsiveness and accuracy of speed adjustments.
2Productivity
If PID controller adjusts speeds rapidly to respond to bench changes, then productivity is improved, but overflow risk increases due to acceleration and deceleration delays of 6-10 seconds
Solution Approach 1:
The system performs preliminary actions by analyzing past operating parameters from previous boom movements and pre-calculating optimal speed adjustments before they are needed. This allows the controller to anticipate required speed changes and initiate adjustments earlier, reducing the impact of acceleration and deceleration delays while maintaining productivity and preventing overflows.
Solution Approach 2:
The system applies dynamic control by using PID controllers that continuously adjust boom turning speed and bucket wheel speed based on real-time mass flow rate measurements and historical data. The control parameters are dynamically modified to optimize both productivity and overflow prevention, adapting to changing bench conditions while accounting for system inertia and delay characteristics.
3Reliability
If manual operation is used to preview and anticipate bench changes, then overflow prevention is improved, but automation level deteriorates
Solution Approach 1:
The system applies self-service by automatically memorizing and analyzing its own operating parameters (boom angular position, bucket wheel speed, mass flow rate) from previous movements, and using this self-generated historical data to autonomously predict and adjust speeds in subsequent movements. This eliminates the need for manual intervention while maintaining the anticipatory capability that prevents overflows, achieving both high automation and reliable overflow prevention.
4Loss of time
If robust 2D sensors are used to detect bench irregularities in advance, then response time is improved, but system cost deteriorates
Solution Approach 1:
The system applies copying by creating a digital replica of the operating conditions through memorization of past performance data (boom angular position, bucket wheel speed, mass flow rate at various angles). Instead of using expensive physical sensors to detect bench irregularities, the system copies and analyzes historical operational patterns to predict future conditions and adjust speeds accordingly, achieving rapid response without expensive hardware.
Solution Approach 2:
The system replaces expensive robust 2D sensors with a cost-effective solution based on processing and analyzing existing operational data that is already being collected by standard sensors (encoders, flow meters). By memorizing and reusing this readily available historical information, the system achieves anticipatory control capabilities without the high cost of specialized sensing equipment.
Data Source
AI summary
A system and method for automated control of reclaimers includes a boom, a bucket wheel, and a translation system. This system comprises memorizing operating parameters used during a turning movement of the boom, allowing identification of positions where there was an overflow or an unsatisfactory reclaiming flow. With this memorized information, the flow controller makes changes to the boom turning speed (Vg), increasing it in positions where the reclaiming flow was low and decreasing it in positions where there was overflow.