Ultrasonic Flow Meter Health Monitoring With Multi-Variable Histograms
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Solution Overview
Problem
Existing ultrasonic flow meters lack the ability to reliably determine their operational condition, including installation situation, and provide a historical view of their operational history, often leading to inaccurate diagnoses and insufficient maintenance planning.
Innovation Solution
The method involves creating and analyzing histograms of at least two different operational variables, such as absolute transit time and signal strength, to assess consistency and reliability of the flow meter's condition, using existing data without additional hardware, and employing a health monitoring module for autonomous diagnostics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If only small control samples of flow meters are inspected due to high inspection costs, then inspection costs are reduced, but the reliability of operational condition determination deteriorates
Solution Approach 1:
The flow meter performs self-diagnosis by autonomously monitoring its own operational variables (transit time, signal strength) and generating histograms to assess its condition. This eliminates the need for external inspection equipment and reduces dependency on manual servicing, thereby improving reliability without proportionally increasing system complexity.
Solution Approach 2:
The system continuously monitors operational variables, compares histogram distributions against reference data, and provides feedback about the flow meter's condition. This closed-loop feedback mechanism enables reliable detection of degradation trends without requiring complex external inspection systems.
2Reliability
If only snap-shot view of current operational condition is provided, then monitoring complexity is reduced, but the ability to detect historical patterns and predict failures deteriorates
Solution Approach 1:
The system pre-processes operational data by continuously aggregating values into histograms during normal operation. This preliminary organization of data into bin structures enables rapid historical pattern recognition when needed, as the data is already structured for analysis rather than requiring real-time complex processing.
Solution Approach 2:
The monitoring approach segments operational data into separate histograms for different variables (transit time, signal strength) and compares them against reference distributions. This segmentation enables efficient historical pattern detection by analyzing each variable's distribution characteristics independently, reducing overall processing time.
3Reliability
If single histogram of one operational variable is used for diagnosis, then device complexity is reduced, but the risk of false diagnoses increases
Solution Approach 1:
The system combines multiple histograms representing different operational variables (transit time, signal strength) and compares their joint distribution patterns against reference data. This merging of multiple data sources improves diagnostic accuracy by cross-validating findings across multiple parameters, reducing false diagnoses without requiring excessive complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides more detailed and reliable information about the flow meter's condition, differentiating between installation issues and meter faults, enabling predictive maintenance and reducing the risk of false diagnoses.
Implementation Method 1
an ultrasonic flow meter (5) for measuring a flow rate of a fluid flowing through a pipe (9) by use of an exchange of ultrasonic signals between a pair of ultrasonic transducers (27)
Implementation Method 2
the absolute transit time t abs of an ultrasonic signal measured in microseconds
Data Source
Figure 1
Figure 2a~2b
Figure 3
AI summary
The present disclosure is directed to a method for determining an operational condition of an ultrasonic flow meter (5, 6), the method comprising: - continuously, regularly, and/or on demand determining values of at least two different pre-determined operational variables (q, tabs, Vpp, Tinternal, Tfluid, Δφ) of the ultrasonic flow meter (5, 6); - for each of the at least two different pre-determined operational variables (q, tabs, Vpp, Tinternal, Tfluid, Δφ), filling a variable-specific histogram by aggregating the occurrences of the determined values of said operational variable (q, tabs, Vpp, Tinternal, Tfluid, Δφ) in bins of said histogram; and - determining an operational condition of the ultrasonic flow meter (5, 6) based on a statistical distribution in one of the histograms if a statistical distribution in another one of the histograms is consistent with said operational condition of the ultrasonic flow meter (5, 6).