Ultrasonic Flow Meter Prognostics Using Cloud-Based Virtual Twins
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Solution Overview
Problem
Current industrial process control and automation systems lack near real-time condition-based uncertainty analysis for ultrasonic flow meters, which hinders predictive maintenance and increases the risk of meter failure.
Innovation Solution
A cloud-enabled system that performs near real-time condition-based uncertainty analysis for ultrasonic flow meters, utilizing a combination of local and cloud-based processing devices to generate prognostics data and create a virtual twin of the flow meter for real-time testing and modeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional ultrasonic flow meter monitoring is used, then the system structure remains simple, but the ability to perform near real-time condition-based uncertainty analysis and predictive maintenance is insufficient
Solution Approach 1:
The patent introduces a cloud-based processing system as an intermediary between the ultrasonic flow meter and the user. The flow meter transmits measurement data to the cloud platform, which performs condition-based uncertainty analysis and generates prognostics reports. This intermediary approach enables advanced analytics without adding complexity to the flow meter hardware itself.
Solution Approach 2:
The patent creates a virtual twin of the flow meter in the cloud-based system. This virtual replica receives and processes measurement data, allowing for simulated testing and modeling without affecting the physical flow meter operation. The virtual twin enables comprehensive prognostics analysis while keeping the physical system simple.
2Reliability
If no condition-based uncertainty analysis is performed, then the system operation remains simple, but the risk of meter failure increases
Solution Approach 1:
The patent performs condition-based uncertainty analysis and prognostics evaluation in advance before actual meter failure occurs. The cloud-based system continuously analyzes measurement data, assesses uncertainty levels, and predicts potential failures, allowing maintenance to be scheduled proactively rather than reactively.
Solution Approach 2:
The patent implements a feedback mechanism where measurement data from the flow meter is continuously transmitted to the cloud-based system, which analyzes the data and generates prognostics reports. These reports provide feedback on the meter's health status and uncertainty levels, enabling continuous monitoring and predictive maintenance decisions.
3Measurement precision
If virtual twin instance is created for prognostics analysis, then the measurement accuracy and testing capability improve, but the computational resources and processing time increase
Solution Approach 1:
The patent performs prognostics analysis and uncertainty evaluation at periodic intervals rather than continuously. The cloud-based system processes measurement data in batches, generating prognostics reports at scheduled times. This periodic approach maintains measurement precision while reducing computational resource requirements and processing time compared to continuous real-time analysis.
Data Source
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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.