Centralized Fluid Meter Profiling via Distributed Test Benches
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Solution Overview
Problem
There is a lack of organized information regarding laboratory and field data for water meters, which hinders the evaluation of their accuracy in different environments, leading to potential undercharging or overcharging due to measurement errors, necessitating a centralized data collection system that incorporates both types of data from trusted sources.
Innovation Solution
A centralized data collection platform is established using certified fluid meter test benches to gather both laboratory and field data, creating an A Posteriori Database (APD) that generates environment-specific meter profiles and tracks individual meter components' performance and durability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a centralized data collection platform is established to aggregate laboratory and field data from multiple locations, then measurement precision and reliability of meter performance evaluation are improved, but device complexity and data management requirements increase
Solution Approach 1:
The system divides data collection into multiple distributed test benches located in different environments (laboratory and field settings), each independently collecting data locally before transmitting to the central database. This segmentation allows the complex centralized system to be managed through modular distributed units, reducing overall system complexity while maintaining comprehensive data aggregation capabilities.
Solution Approach 2:
The system merges laboratory data (controlled conditions) and field data (real-world conditions) into a single centralized database structure. By combining these different data types from multiple sources into one unified platform, the system achieves comprehensive meter performance evaluation without requiring separate management systems, thus improving measurement precision while managing complexity through integration.
2Reliability
If data is collected from multiple locations and environments to provide comprehensive meter performance data, then reliability of meter selection decisions is improved, but loss of time and resources for data collection increases
Solution Approach 1:
The centralized data collection platform is designed to accommodate multiple data types (laboratory and field data) from various environments and meter types within a single unified system. This multi-functional platform can collect, store, and analyze different kinds of data simultaneously, reducing the time and resources required compared to maintaining separate collection systems for different data types and locations.
Solution Approach 2:
The system implements feedback mechanisms where collected data from multiple locations is analyzed and used to generate performance predictions and recommendations that feed back into meter selection decisions. This feedback loop allows the system to continuously improve its data collection efficiency by learning from previous data patterns and optimizing future collection processes, thereby reducing time loss while maintaining high reliability.
3Ease of operation
If laboratory data is used to predict meter performance, then ease of operation and initial selection is improved, but measurement precision in real-world conditions deteriorates
Solution Approach 1:
The system collects and stores laboratory data under controlled conditions as a preliminary foundation for meter performance evaluation. This preliminary data provides easy-to-access baseline information that simplifies initial meter selection processes. The system then builds upon this foundation by incorporating field data, creating a progressive evaluation approach where ease of operation is maintained in early stages while measurement precision is enhanced through subsequent real-world data integration.
Solution Approach 2:
The system recognizes and preserves the specific qualities of different data sources: laboratory data provides controlled, repeatable measurements ideal for initial screening, while field data provides real-world contextual information for final validation. By maintaining the distinct characteristics of each data type and applying them appropriately in the evaluation process, the system achieves both ease of operation through laboratory data and measurement precision through field data without requiring uniform treatment of all data.
Data Source
AI summary
A platform configured for evaluating metering technologies and generating meter profiles using information derived from a plurality of meters retrieved from a plurality of environments. The platform may include a centralized data storage system in communication with a fluid meter test bench system. A computing device automatically controls fluid meter test bench system to measure the accuracy of fluid meters and transfers meter data to at least one of the centralized data storage system or a local data silo in communication with the centralized data storage system. Exemplary meter data includes meter type data, meter test data and meter environmental data. Meter environmental data may comprise meter install location and at least one of fluid quality data or fluid meter mounting position. The platform is configured to provide a meter profile for each meter tested based at least in part on the meter data and the test system data.