Pipeline Obstruction Detection via Genetic Algorithm Optimization
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Solution Overview
Problem
Existing methods for identifying obstructions in pipeline networks are invasive, require extensive flow-rate and pressure measurements, and are not suitable for complex networks, especially when intermediate flow-rates and pressures are unknown.
Innovation Solution
A method using genetic algorithms to minimize the discrepancy between simulated and measured pressure and flow-rate values, calculating an equivalent diameter to detect obstructions by optimizing the internal diameter of pipeline sections, which is non-invasive and requires a reduced number of measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If indirect pressure drop measurement method is used to detect obstructions, then the method is non-invasive and can be applied continuously under single-phase and multiphase conditions, but it requires knowledge of flow-rates in each section of the pipeline which is normally impossible to obtain
Solution Approach 1:
The patent introduces an intermediary computational model (hydraulic simulation model) that acts as a bridge between the limited available measurements (inlet/outlet flow-rates and boundary pressures) and the unknown intermediate parameters. The model uses genetic algorithms to optimize and infer the missing flow-rate and pressure data in intermediate pipeline sections, enabling the pressure drop method to be applied without direct measurement of intermediate flow-rates.
2Reliability
If passive noise measurement method is used, then the method is non-invasive and can be applied in continuity, but it is limited to single-phase fluid conditions and requires transducers positioned within a few hundreds of meters from obstructions
Solution Approach 1:
The patent changes the detection parameter from acoustic noise (which is limited to single-phase fluids and short distances) to pressure drop measurements (which can be applied to both single-phase and multiphase fluids over long distances). By using the hydraulic model to infer intermediate flow parameters, the system maintains detection capability while expanding adaptability to different fluid conditions and pipeline configurations.
3Length of stationary object
If pressure wave method is used, then obstructions in very long pipelines can be detected and localized, but it requires specific pressure-wave generation equipment and can only be applied to single-phase fluid conditions
Solution Approach 1:
The patent creates a universal detection method that works for both single-phase and multiphase fluids by using standard pressure and flow-rate measurements combined with a hydraulic simulation model. The model can handle different fluid phases and pipeline configurations, making the system multi-functional and adaptable to various operating conditions without requiring specialized equipment for each fluid type.
4Duration of action of stationary object
If existing indirect measurement methods are used, then continuous monitoring is possible, but extensive flow-rate and pressure measurements are required throughout the pipeline network
Solution Approach 1:
The patent extracts only the essential measurements needed for obstruction detection by using a hydraulic simulation model to infer the missing intermediate parameters. Instead of requiring extensive flow-rate and pressure measurements at every pipeline section, the system uses a reduced set of measurements at boundary conditions (inlet/outlet flow-rates and boundary pressures) combined with genetic algorithm optimization to achieve continuous monitoring with minimal instrumentation.
Data Source
AI summary
It is described a method for detecting and identifying obstructions in a pipeline network for transporting fluids, wherein the network is composed of a plurality of pipeline sections (P) and a plurality of junctions (N). The method comprising the following phases: acquiring the geometrical data of a predefined number of pipeline sections (P) for which the presence of obstructions has to be evaluated; measuring the actual flow-rate values (Q1) of the fluid in one or more pipeline sections (P) and of the actual pressure values (h1) of the fluid at one or more junctions (N) of the network; comparison between the values of the nominal diameters (D1) of said pipeline sections (P) and the corresponding equivalent diameters (Dieq) of said pipeline sections (P); calculating, by means of a specific numerical model, the theoretic flow-rate values (QiT) and pressure values (hiT) of the fluid for said equivalent diameters (Dieq). With =(Dieq)α×Di method provides a calculation phase of the value of the variables vector αi which minimize a function based on the discrepancy between the actual flow-rate (Qi) and pressure (hi) values effectively measured and the corresponding theoretical flow-rate (QiT) and pressure (hiT) values, wherein said calculation phase is performed by applying a certain own fitness function J(α) of the genetic algorithms (GAs).