Calibration Drift Tracking for Long-Term Measurement Analysis
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Solution Overview
Problem
Existing calibration methods do not effectively address cumulative drift in measurement devices, making it difficult to determine optimal calibration time intervals and assess device performance over time.
Innovation Solution
A system and method to calculate and store cumulative drift in measurement devices, allowing for the determination of calibration time intervals based on the detected drift, and providing insights into device performance and potential maintenance needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If regular field calibrators are used to perform single calibration actions with measurement devices, then calibration accuracy is improved, but the ability to track cumulative drift over time deteriorates because each calibration is performed independently without considering historical drift patterns
Solution Approach 1:
The system pre-calculates and stores drift values between calibration points by continuously monitoring measurement deviations. This preliminary action captures drift information that would otherwise be lost, enabling future calibrations to be informed by historical drift patterns rather than treating each calibration as an isolated event
Solution Approach 2:
The system implements feedback by storing calculated drift values and using them to inform subsequent calibration decisions. The drift information feeds back into the calibration process, allowing the system to adjust calibration timing and accuracy requirements based on observed drift patterns from previous measurement cycles
2Productivity
If calibration time intervals are extended to improve productivity, then fewer calibration actions are required, but measurement reliability deteriorates due to untracked cumulative drift affecting measurement accuracy
Solution Approach 1:
The system introduces drift values as an intermediary parameter that bridges the gap between extended calibration intervals and measurement reliability. By calculating and storing drift information between calibration points, the system maintains reliability awareness even when calibrations are performed less frequently, allowing productivity to improve without sacrificing measurement trustworthiness
3Reliability
If cumulative drift tracking is implemented to improve measurement reliability, then calibration scheduling accuracy is improved, but device complexity increases due to additional data storage and calculation requirements
Solution Approach 1:
The system extracts the drift calculation and storage functionality from the core calibration process, implementing it as a separate, dedicated mechanism. By isolating the drift tracking function, the system improves reliability through specialized handling of drift data while managing complexity through functional separation rather than embedding complex logic throughout the entire calibration system
Data Source
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AI summary
The present invention keeps track of the cumulative absolute drift of a measurement device, in connection with calibration actions performed by a calibrator. Measurement results are saved (22) in each measurement instant, and if they exceed a threshold value (23), an adjustment step is performed (24). Irrespective of the adjustment steps, the latest drift value (25) during the latest calibration interval is summed (26) with the previous cumulative drift value. The cumulative drift value, i.e. AbsDrift, is saved to a server, from where it can be illustrated visually (27). If there is an uncommon pattern or large cumulative drift present, an indication or alarm (28) can be sent to the user of the calibrator.