Online System Identification for Bad Pipeline Data Replacement
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Data acquisition and control systems in complex engineered systems face challenges in ensuring timely, accurate, and reliable data monitoring due to issues like broken communication links, faulty data packets, and missing data, which can disrupt the operation of systems such as pipelines and power grids.
Innovation Solution
A method and system that analyze process readings from remote terminal units along a pipeline to identify influencing and target process readings, assess for bad data, and generate estimated readings or update system models, switching between learning and estimation modes as needed, to ensure continuous data integrity and control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data acquisition systems monitor processes in real-time using remote terminal units, then timely and accurate data monitoring is achieved, but broken communication links and faulty data packets can cause data loss and reliability issues
Solution Approach 1:
The patent introduces an online system identifier that acts as an intermediary between remote terminal units and the data acquisition system. This intermediary continuously monitors data quality, detects bad data packets, and replaces them with estimated values derived from system models and correlated readings, thereby preventing data loss and maintaining reliability without requiring changes to the existing RTU infrastructure
Solution Approach 2:
The system performs preliminary actions by continuously updating system models and identifying correlated readings before bad data occurs. When communication issues arise, the pre-established models and correlated data relationships enable immediate estimation and replacement of bad data, preventing information loss rather than reacting after data corruption is detected
2Reliability
If the system uses estimated readings to replace bad data, then data continuity is maintained, but the complexity of analyzing correlations and updating models increases
Solution Approach 1:
The patent segments the data processing function into distinct modules: an online system identifier that analyzes correlations between readings, a model updater that maintains system models, and a data estimator that generates replacement values. This segmentation allows each component to perform its specific function efficiently without requiring the entire system to handle all complexity simultaneously, making the overall system more manageable despite the increased functionality
3Measurement precision
If the system continuously updates system models and correlates readings, then measurement precision is improved, but computational resources and processing time are consumed
Solution Approach 1:
The system implements periodic action by updating system models at scheduled intervals rather than continuously, while maintaining continuous monitoring of data quality. The online system identifier periodically re-evaluates correlations and refreshes models based on accumulated data, balancing the need for measurement precision with computational efficiency and processing time constraints
Data Source
AI summary
A system, a method, and a computer program for monitoring or controlling a field instrument in a pipeline, including receiving a plurality of process readings which originated from a plurality of remote terminal units that are distributed along a portion of the pipeline, analyzing the received plurality of process readings to determine a plurality of influencing process readings and a target process reading, assessing whether the target process reading includes bad data, and generating an estimated process reading or updating a parameter of a system model based on the plurality of influencing process readings and based on whether the target process reading includes bad data.