Online Sensor Validation Using Remote Reference Calibration
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Solution Overview
Problem
Conventional methods for validating measurements from online sensors in industrial processes are prone to human error and environmental disruptions, leading to inaccurate data and the need for skilled technicians, who may not always perform tests accurately.
Innovation Solution
Implement automated calibration and intervention prompts by collecting samples from online sensors and comparing them to offsite measurements in a controlled environment, using software to adjust and validate data accuracy, and sending notifications for maintenance or replacement as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If field technicians perform manual calibration and validation of online sensors, then local real-time adjustment can be made, but human error and subjective analysis reduce measurement accuracy
Solution Approach 1:
The patent introduces an intermediary validation system where field technician measurements are cross-checked against reference measurements from controlled environment labs. This intermediary layer (automated comparison system) mediates between the technician's local calibration and the true measurement accuracy, eliminating the need for technicians to independently judge accuracy while preserving their ability to perform local adjustments.
Solution Approach 2:
The system implements automated feedback by comparing field measurements with reference measurements and providing objective validation results to technicians. This feedback loop allows technicians to perform local calibrations with confidence, knowing their measurements will be validated or corrected by the automated system, thereby improving measurement precision without reducing operational ease.
2Reliability
If skilled technicians are deployed for sensor validation, then accurate measurements can be obtained, but human error and environmental disruptions still affect reliability
Solution Approach 1:
The system enables self-service validation where the automated system performs its own validation by comparing measurements against reference standards without requiring continuous technician oversight. The system autonomously identifies when calibration is needed and performs corrections, eliminating human error while maintaining high reliability. The technician's role is reduced to initiating and monitoring the automated process rather than performing manual validation.
3Loss of time
If manual calibration by technicians is performed, then local adjustment can be made quickly, but the veracity of measurements may be in doubt due to human error
Solution Approach 1:
The system performs preliminary automated validation of technician measurements before they are finalized. By pre-comparing field measurements with reference measurements and identifying discrepancies early in the process, the system allows technicians to quickly correct issues while maintaining measurement veracity. This preliminary check prevents time-consuming re-calibration later while ensuring accurate results.
4Speed
If field conditions are used for sensor testing, then real-time validation is possible, but environmental disruptions cause measurement inaccuracies
Solution Approach 1:
The validation process is segmented into two distinct phases: (1) rapid field validation using portable equipment for quick screening, and (2) precise controlled environment validation for final accuracy confirmation. This segmentation allows the system to capture the speed advantage of field testing while eliminating its accuracy disadvantages by transferring critical samples to controlled labs for definitive measurement.
Data Source
AI summary
A system and method is provided for correction of sensors in an industrial process. A first sensor provides first data corresponding to measured variables for at least one respective process component, which are further aggregated in data storage with corresponding contextual tags comprising time series identifiers. For a given sample from the industrial process, at least the first data having a corresponding time series identifier are obtained for comparison with second data collected via a second sensor and which comprises measured variables corresponding to the at least one respective process component from the given sample. A feedback signal is selectively generated based on a determined error between the collected first data and the collected second data corresponding to the given sample, and may in an embodiment be used for automatically calibrating the first sensor. The feedback signal may further or alternatively be used to prompt interventions in the first sensor.

