Weighing System Calibration via Error Coefficient Optimization
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Solution Overview
Problem
Weighing systems in machines like wheel loaders and excavators face challenges in maintaining accuracy due to unknown errors in payload scales, making it difficult to determine which scales are faulty and requiring inefficient manual troubleshooting and periodic calibration.
Innovation Solution
A method involving a processor that receives readings from multiple payload scales, formulates equations to determine error coefficients, and calibrates the system based on optimized coefficients using techniques like LASSO or ridge regression, to identify and correct errors in the weighing system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If results from two scales are compared to confirm accuracy, then measurement verification is performed, but it does not identify which scale is out of calibration and requires manual investigation
Solution Approach 1:
The system implements automated feedback by continuously monitoring scale readings and comparing them against expected values or historical data. When discrepancies are detected, the system automatically generates calibration alerts and identifies which specific scales require attention, eliminating manual investigation and providing continuous accuracy verification.
2Reliability
If a third measurement is added to improve accuracy, then measurement reliability increases, but device complexity and cost increase
Solution Approach 1:
The system introduces a computational intermediary that processes readings from existing scales to determine accuracy. Instead of adding physical measurement devices, the system uses software-based intermediaries including calibration algorithms, error coefficient calculations, and automated comparison logic that analyze existing scale data to verify accuracy without requiring additional hardware.
3Measurement precision
If scales are calibrated periodically, then accuracy is maintained, but errors between calibrations are not detected and productivity is reduced during calibration downtime
Solution Approach 1:
The system maintains continuous calibration monitoring between scheduled calibration events by automatically analyzing scale readings in real-time. The continuous operation of the monitoring system detects drift or errors as they occur, allowing for immediate intervention without stopping operations, thus maintaining both accuracy and productivity simultaneously.
4Ease of repair
If manual troubleshooting is performed to identify faulty scales, then calibration needs are determined, but the process is inefficient and time-consuming
Solution Approach 1:
The system performs self-diagnosis by automatically monitoring its own scale readings and identifying which scales require calibration. The automated system generates maintenance alerts and prioritizes calibration needs based on detected errors, eliminating the need for manual troubleshooting and enabling the system to service itself.
Data Source
AI summary
A method of calibrating a weighing system associated with a worksite is provided. The method includes, receiving, from the weighing system, readings indicative of a payload on a first set of machines and a second set of machines of the worksite. The second set of machines are configured to receive a payload from the corresponding first set of machines. The method also includes formulating a predefined number of equations from the readings and determining error coefficients of the weighing system by optimizing the predefined number of equations. The method further includes calibrating the weighing system based on the determined error coefficients.