Ultrasonic Flow Meter Uncertainty Analysis with Cloud CBM
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Solution Overview
Problem
Industrial ultrasonic flow meters lack near real-time condition-based uncertainty analysis, leading to inadequate preventative maintenance and potential failures, as current diagnostics tools are limited to stranded physical assets and do not provide predictive maintenance insights.
Innovation Solution
A cloud-enabled system performs condition-based monitoring and uncertainty analysis on flow measurement data from ultrasonic flow meters, generating prognostics data and creating a virtual twin for real-time testing, enabling near real-time flow measurement condition-based uncertainty analysis and improving operational performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cloud-based CBM analysis and uncertainty analysis are implemented, then measurement precision and reliability are improved, but device complexity and infrastructure requirements increase
Solution Approach 1:
A cloud-based environment serves as an intermediary between the flow meter and the DCS, performing CBM analysis and uncertainty analysis on flow measurement data. The cloud environment receives raw flow measurement data, processes it through multiple analysis stages, and returns validated flow rates with uncertainty values to the local system, thereby improving measurement precision without adding complexity to the physical flow meter infrastructure
Solution Approach 2:
The patent creates a virtual copy of the flow measurement system in the cloud environment, where virtual instances of the flow meter and analysis algorithms replicate the physical system's functionality. This virtual copying enables comprehensive data analysis and validation without modifying the physical flow meter hardware, resolving the contradiction between improved measurement precision and reduced device complexity
2Productivity
If near real-time analysis is performed, then productivity and response time are improved, but use of energy and computational resources increase
Solution Approach 1:
The system performs CBM analysis and uncertainty analysis at periodic intervals based on predetermined thresholds and schedules, rather than continuously processing all incoming data. The cloud-based environment analyzes flow measurement data at optimized frequencies, balancing near real-time productivity improvements with reduced computational energy consumption by processing data only when significant changes or threshold violations occur
3Reliability
If comprehensive CBM analysis and uncertainty analysis are performed, then reliability is improved, but loss of time for data processing increases
Solution Approach 1:
The cloud-based environment performs preliminary CBM analysis on flow measurement data to identify potential issues and trends before they result in failures. By conducting preliminary assessments continuously in the cloud, the system prepares maintenance recommendations and uncertainty evaluations in advance, reducing the time needed for critical decision-making while maintaining high reliability through comprehensive analysis
Data Source
AI summary
A method includes obtaining flow measurement data from a flow meter in an industrial process control system. The method also includes sending the flow measurement data to a cloud-based environment. The method further includes performing condition based monitoring (CBM) analysis on the flow measurement data in the cloud-based environment to determine CBM data. The method also includes performing uncertainty analysis on the CBM data in the cloud-based environment to determine a validated flow rate with an uncertainty value. The method further includes comparing the validated flow rate to the flow measurement data to determine a technically audited flow rate. The method also includes sending the technically audited flow rate to a distributed control system (DCS) associated with the flow meter.