Field Measurement Rate Control Using Correlation Patterns
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Solution Overview
Problem
Battery-operated field devices in process automation require frequent maintenance due to limited battery life, necessitating process downtime for battery replacement, which affects operational efficiency.
Innovation Solution
A method that optimizes the measurement rate of a first field device by determining correlation patterns with a second field device using machine learning, allowing reduced power consumption and extended battery life through adaptive measurement rate adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the measurement rate is increased to ensure sufficient process monitoring, then the reliability of process monitoring is improved, but the battery consumption increases and battery life decreases
Solution Approach 1:
The measurement rate is made dynamically adjustable rather than fixed. The system automatically adapts the measurement rate of the first field device based on the correlation strength between measurement variables, switching between high measurement rate (when correlation is weak) and low measurement rate (when correlation is strong), thereby optimizing both monitoring reliability and battery life
Solution Approach 2:
The measurement rate parameter is changed based on the determined correlation pattern. When a strong correlation pattern is identified between the first and second measurement variables, the measurement rate is reduced; when correlation is weak or absent, the measurement rate is maintained at higher levels, thus extending battery life while preserving monitoring reliability
2Duration of action of moving object
If the measurement rate is reduced to extend battery life, then the battery life is improved, but the process monitoring capability deteriorates
Solution Approach 1:
The system uses feedback from the correlation analysis of multiple field devices to dynamically adjust the measurement rate. By continuously evaluating the correlation between measurement variables from different field devices, the system determines whether reduced measurement rates will compromise monitoring reliability, and adjusts accordingly
Solution Approach 2:
The system performs preliminary correlation analysis during a learning phase before normal operation. This preliminary action establishes the correlation patterns between measurement variables, enabling the system to proactively adjust measurement rates to extend battery life while maintaining monitoring capability based on pre-established correlation knowledge
3Ease of repair
If field devices are taken out of operation for battery replacement, then the battery can be replaced, but the process installation must be stopped causing downtime
Solution Approach 1:
The system performs preliminary correlation analysis and learns the correlation patterns between field devices during normal operation. This preliminary action enables the system to predict when reduced measurement rates can be safely applied, allowing battery replacement to be performed during operation without stopping the process installation
Solution Approach 2:
The system enables self-service operation by automatically adjusting measurement rates based on correlation patterns, allowing the field device to continue operating with reduced power consumption during battery replacement. The correlation-based control system maintains process monitoring reliability even when one device operates in battery replacement mode
Data Source
AI summary
The present disclosure relates to a method for optimizing a measurement rate of a field device in a measurement system. The measurement system includes at least one second field device in which a measurement variable of the field device is correlated with the measurement variable of the second field device. The method determines a respective specific correlation pattern between the first measurement variable and the second measurement variable based on a learning phase. This makes it possible to check the measured values from the second field device for the correlation pattern during normal measurement operation and to change the measurement rate of the field device during the corresponding time window. This makes it possible to increase the service life and/or availability in the process installation.