Field Device Calibration Modeling for Environmental Measurement Drift
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Solution Overview
Problem
Field devices in automation technology face significant challenges in maintaining measurement accuracy due to varying environmental stress parameters, requiring frequent and time-consuming recalibrations to address the impact of temperature, pressure, vibrations, and chemical conditions.
Innovation Solution
A method where field devices form groups based on shared measurement tasks and environmental conditions, with calibration data and environmental information collected and analyzed to create a mathematical model, allowing for adaptation of measurement algorithms across the group, reducing the need for individual recalibrations and improving measurement performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If repeated calibrations are performed to address environmental stress parameters, then measurement accuracy is improved, but calibration time and effort increase significantly
Solution Approach 1:
The system performs preliminary calibration in the factory under controlled conditions and stores this calibration data. The field device then uses this pre-established calibration data to compensate for environmental variations during operation, eliminating the need for repeated field calibrations.
Solution Approach 2:
The system continuously monitors environmental parameters (temperature, humidity, pressure) and uses this feedback to dynamically adjust measurements based on the stored calibration data and characterization information, maintaining accuracy without recalibration.
2Measurement precision
If individual field devices are calibrated separately to account for environmental influences, then measurement accuracy is maintained, but service costs and operational complexity increase
Solution Approach 1:
The system combines calibration data, environmental characterization information, and measurement algorithms into a unified framework. Multiple field devices with similar environmental exposures are grouped together, allowing centralized management and reducing operational complexity.
Solution Approach 2:
The system creates universal compensation models that can be applied across multiple field devices of the same type exposed to similar environmental conditions. A single characterization model serves multiple devices, reducing the need for device-specific calibration management.
3Ease of manufacture
If factory calibration is performed without considering specific environmental conditions, then calibration process is simplified, but measurement performance deteriorates under varying environmental stress
Solution Approach 1:
The system performs preliminary characterization of environmental influences during factory calibration, identifying which environmental parameters affect each device type. This preliminary action enables the device to compensate for specific environmental stresses during operation while maintaining simple factory calibration procedures.
Solution Approach 2:
The system changes the parameters used in factory calibration from simple reference measurements to include environmental characterization data. By incorporating environmental parameter ranges and stress conditions into the calibration process, the system maintains simplicity while improving reliability under varying conditions.
Data Source
Figure 1
AI summary
Method for improving the measuring performance of automation field devices (1), wherein each of the field devices (1) determines or monitors at least one physical or chemical process variable of a medium (2) using a measuring algorithm, is calibrated using specific calibration data and is exposed to measurable environmental influences at the particular measuring position thereof, wherein the method has the following method steps of: • capturing the calibration data of the field devices (1) and/or capturing in each case an item of environmental information from the environment of the field devices (1) at defined intervals of time, • storing the environmental information and calibration data provided with a time stamp in a database (3), • selecting at least one group (A) of field devices (1) which determine a physical or chemical process variable using the substantially identical measuring algorithm and which correspond with respect to the captured environmental information within predefined tolerance limits, • correlating the environmental information and calibration data captured over time, • creating a mathematical model which represents the functional relationship between the calibration data and the environmental information, • adapting the measuring algorithm on the basis of the model, • transmitting the adapted measuring algorithm to all field devices (1) in the group (A).