Pipeline Geometry Calibration Using Controlled Pressure Waves
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current diagnostics for long distance pipelines fail to accurately account for significant geometry changes such as tees and wyes, and cannot distinguish between pipeline features like bends and elbows from deposition features, leading to issues like build-ups and blockages.
Innovation Solution
The method involves inducing pressure waves into the pipeline and analyzing the corresponding pressure responses to identify geometric features like tees, wyes, and curves, using a combination of statistical process control and machine learning to differentiate these features from depositions or leaks by comparing signal variations and establishing confidence bounds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional diagnostic methods are used for long distance pipelines, then the diagnostic system is simple and easy to operate, but it cannot accurately identify geometric features like tees and wyes, leading to misidentification of deposition features
Solution Approach 1:
The patent uses pressure waves (a form of mechanical vibration) propagating through the pipeline to interact with geometric features. When pressure waves encounter features like tees, wyes, or bends, they reflect back with characteristic patterns that can be analyzed to identify the feature type and location, enabling accurate differentiation from deposition features without requiring complex physical inspection equipment
Solution Approach 2:
The patent replaces traditional mechanical or visual inspection methods with acoustic/pressure wave-based detection. By substituting physical probing with pressure wave propagation and analysis, the system achieves remote, automated identification of geometric features while maintaining operational simplicity and improving measurement precision
2Reliability
If traditional diagnostics are used, then the system is easy to operate, but it cannot distinguish between pipeline features like bends and deposition features, resulting in false diagnoses
Solution Approach 1:
The system analyzes reflected pressure waves and uses the feedback information to identify characteristic patterns associated with different geometric features. By comparing the reflected wave patterns against known signatures of tees, wyes, bends, and deposition features, the system achieves reliable differentiation and reduces false diagnoses
Solution Approach 2:
The patent changes the parameter being measured from simple pressure readings to detailed pressure wave reflection patterns. By analyzing the temporal and amplitude characteristics of reflected pressure waves, the system can distinguish between geometric features and deposition features based on their unique acoustic signatures, improving reliability without requiring complex additional hardware
3Measurement precision
If automated pressure wave analysis with machine learning is implemented, then feature identification accuracy is improved, but the device complexity and computational requirements increase
Solution Approach 1:
The patent replaces manual analysis of pressure wave data with automated machine learning algorithms. The system collects pressure wave reflection data and uses trained machine learning models to automatically identify geometric features, reducing the need for complex manual interpretation while improving identification accuracy and consistency
Solution Approach 2:
The system uses machine learning models that have been pre-trained on pressure wave data to perform self-service identification of geometric features. Once trained, the system can autonomously analyze new pressure wave patterns and identify features without requiring external expert intervention, improving precision while managing complexity through automation
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for real-time, accurate identification of geometric features in pipelines, enabling effective characterization and preventing issues like build-ups and blockages by distinguishing between geometric features and deposition-related issues.
Implementation Method 1
controlling a flow into or out of a conduit to induce pressure waves in the conduit; measuring, with a pressure transducer, pressure responses in the conduit due to contact of the pressure waves with a geometric feature
Implementation Method 2
at least two pressure waves are induced to elicit or cause at least two corresponding pressure responses that may reflect off of a geometric feature, and travel as pressure responses back to the source
Data Source
AI summary
Systems and methods of the present disclosure relate to identifying geometric features of a conduit. A method includes controlling a flow into or out of a conduit to induce pressure waves in the conduit; measuring, with a pressure transducer, pressure responses in the conduit due to contact of the pressure waves with a geometric feature of the conduit; and identifying the geometric feature, based on the pressure responses.