Meter Event Detection for Process Data Apportioning
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Solution Overview
Problem
Existing meters face challenges in efficiently storing and managing process data due to high storage costs and labor-intensive data analysis, necessitating a need for event notification and data apportioning to reduce unnecessary data storage and improve accessibility.
Innovation Solution
A meter electronics system that continuously stores process data, detects events, and generates notifications while apportioning relevant data into event-related and context data for efficient data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If process data is continuously stored for a long duration with high write frequency, then data availability for post-event analysis is improved, but storage cost increases prohibitively
Solution Approach 1:
The patent segments the continuous process data into discrete event-related data sets. Instead of treating all data uniformly, the system identifies specific events (such as alarms, high/low process limits, operator interventions) and extracts only the data portions associated with these events. This segmentation allows the system to maintain data availability for relevant analysis while dramatically reducing the total volume of stored data, thereby resolving the contradiction between data availability and storage cost.
2Loss of information
If all process data is stored and retained for analysis, then comprehensive post-event analysis capability is improved, but labor required for data access and monitoring increases
Solution Approach 1:
The patent applies preliminary action by pre-processing and organizing process data into event-related data sets before they are needed for analysis. The system continuously monitors process data, automatically identifies events, and pre-sorts the associated data into structured formats. When users need to perform post-event analysis, the relevant data is already prepared and organized, eliminating the need for manual data retrieval and filtering operations. This preliminary organization significantly reduces the labor and time required for data access while maintaining comprehensive analysis capability.
3Measurement precision
If high write frequency is used for storing process data, then data resolution and detail are improved, but storage resource consumption increases
Solution Approach 1:
The patent applies local quality by varying the data storage resolution based on the local context of process events. During normal operation, data may be stored at a standard resolution. However, when events are detected (such as process upsets, alarms, or operator actions), the system automatically increases the write frequency and data resolution specifically for those time periods and parameter sets. This localized high-resolution storage ensures measurement precision is maintained where it matters most (during events) while using lower resolution during stable periods, thereby optimizing the balance between data quality and storage resource consumption.
Data Source
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AI summary
A meter electronics (20) configured to notify of an event and apportion process data is provided. The meter electronics (20) comprises a memory (230) configured to continuously store the process data (410) for a duration (412), a processor (210) communicatively coupled to the memory (230). The processor (210) is configured to detect one or more events (430) in the process data (410) and at least one of generate a notification (460) and apportion the process data (410) based on the detected one or more events (430).