Meter Sizing Analysis System Identifies Quantization Effects
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Solution Overview
Problem
Utility meters are often incorrectly sized for properties, leading to inefficient measurement and premature wear, as existing auditing methods are labor-intensive and lack precision, resulting in utilities replacing meters with the same incorrect size due to lack of correctly sized inventory.
Innovation Solution
A system and method that identifies incorrectly sized utility meters by detecting quantization effects in meter data, using a computer-implemented method and meter sizing analysis system to select and order replacement meters with correct sizing, improving monitoring accuracy and reducing labor and capital needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual auditing methods are used to identify incorrectly sized meters, then comprehensive inspection coverage can be achieved, but labor intensity and time consumption increase significantly
Solution Approach 1:
The patent replaces manual mechanical auditing processes with automated data analysis systems that process meter readings and consumption patterns electronically. The system automatically identifies quantization effects in meter data to determine incorrect sizing, eliminating the need for manual field audits while maintaining or improving detection accuracy.
Solution Approach 2:
The system enables meters to effectively self-identify their sizing issues through the analysis of their own operational data. By monitoring quantization effects in the meter's own readings and consumption patterns, the system allows meters to flag their own sizing problems without external intervention, reducing the need for manual inspection.
2Measurement precision
If comprehensive manual meter auditing is conducted, then all incorrectly sized meters can be identified, but labor costs and operational complexity increase
Solution Approach 1:
The patent extracts the key diagnostic information (quantization effects) directly from existing meter data streams without requiring additional complex auditing equipment. By focusing analysis on specific data patterns already present in normal meter operations, the system simplifies the auditing process while maintaining high identification accuracy.
Solution Approach 2:
The system uses a unified data analysis approach that can identify incorrect meter sizing across different meter types and installation locations using the same quantization effect detection methodology. This universal approach eliminates the need for location-specific or meter-type-specific auditing procedures, reducing overall system complexity.
3Ease of manufacture
If meters are replaced based on scheduled replacement programs, then inventory management is simplified, but incorrectly sized meters are replaced with the same incorrect size
Solution Approach 1:
The system incorporates feedback from historical meter performance data and consumption patterns to inform replacement decisions. By analyzing quantization effects in existing meter data, the system provides feedback about correct sizing requirements, ensuring that replacement meters are properly sized rather than simply replacing with identical units.
Solution Approach 2:
The system performs preliminary identification of incorrectly sized meters before replacement occurs. By detecting quantization effects and determining correct sizing requirements in advance, the system ensures that when meters are replaced, the correct sized meters are ordered and installed, preventing the propagation of sizing errors to replacement units.
Data Source
AI summary
A computer implemented method for selecting an appropriately sized meter for use in a selected application implemented by a computer processor implementing instructions stored in a non-transient memory is described. The instructions include receiving utility meter data transmitted from a plurality of utility meters, each utility meter being installed at a unique utility monitoring location, identifying incorrectly sized utility meters based on utility meter data for particular utility meters that displays quantization effects, and selecting an appropriate meter based on the identification of the utility meters displaying quantization effects.