Gas Network Obstruction Detection Using Dynamic Baseline Models
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Solution Overview
Problem
Current methods for monitoring gas networks under pressure are inadequate for detecting obstructions in complex networks, as they are designed for long, straight pipelines and only detect leaks, failing to account for obstructions in pipelines between sources and consumers.
Innovation Solution
A method involving sensors to determine physical parameters at various times and locations, using estimation algorithms to establish a physical or mathematical model, which is updated regularly to detect and quantify obstructions by comparing baseline and operational phase measurements, generating alarms and obstruction costs when deviations are detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional monitoring methods designed for long straight pipelines are used, then leak detection capability is maintained, but obstruction detection capability is lost in complex gas networks
Solution Approach 1:
The system dynamically adapts the physical model to complex network configurations by continuously updating it during operational phases and recalibrating during baseline phases. The model evolves to accommodate changing network conditions, consumer patterns, and pipeline states, enabling reliable obstruction detection in previously unsuitable complex network topologies.
Solution Approach 2:
The invention changes the operational parameters of the monitoring system by introducing multiple operational phases (baseline and monitoring phases) with different measurement and evaluation strategies. This allows the system to adapt to varying network conditions and maintain detection accuracy across different operational states in complex networks.
2Measurement precision
If a physical model is continuously updated to detect obstructions, then detection accuracy is improved, but computational complexity and data processing requirements increase
Solution Approach 1:
The system employs periodic baseline phases interspersed between operational monitoring phases to recalibrate and simplify the physical model. This periodic resetting prevents cumulative computational complexity from growing indefinitely while maintaining high detection accuracy during operational phases through the use of established baseline comparisons.
Solution Approach 2:
Baseline phases are performed in advance to establish reference models before entering operational monitoring phases. This preliminary action prepares the system with pre-computed reference data and simplified models, reducing the computational burden during real-time obstruction detection while maintaining high accuracy through comparison against pre-established baselines.
3Measurement precision
If baseline phases are frequently interrupted to update the model, then model accuracy is maintained, but operational monitoring time is reduced
Solution Approach 1:
The system performs partial baseline updates rather than complete recalibrations during baseline phases. By updating only the necessary portions of the physical model that have drifted from baseline conditions, the system maintains model accuracy while minimizing the time spent out of operational monitoring mode, thus reducing loss of monitoring time.
Data Source
AI summary
A method is provided for detecting and quantifying obstructions in a gas network under pressure or vacuum. The gas network may be provided with a sensor(s) capable of recording the status of a source(s), consumers, or consumer areas. The method includes: a possible start-up phase; a baseline or zero phase; and an operational phase. The operational phase includes: reading out the first group and second group of sensors; re-estimating, determining or calculating the physical model or mathematical relationship on the basis of the read measurements from the sensors; determining or calculating of the existence of an obstruction in the system based on the difference and/or its derivatives between the parameters of the physical model or mathematical relationship as determined during the baseline or zero phase and the operational phase; generating an alarm and/or generating a degree of obstruction and/or generating the corresponding obstruction if an obstruction is detected.