Pipeline Leak Detection via Time-Varying Pressure Signals
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Solution Overview
Problem
Pipeline networks, such as those transporting natural gas or water, face challenges in detecting leaks due to the impracticality of monitoring every inch, leading to resource loss and undetected issues despite sensors being located along the network.
Innovation Solution
A method and system that measure pressure as a time-varying signal using sensors and a processor-based model tuned on the gas mass conservation law, allowing for leak detection by monitoring these signals based on a model that differentiates between normal and leak conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If sensors are located at regular or irregular intervals along the pipeline network, then monitoring coverage is provided, but leak detection precision deteriorates because every inch of the pipeline cannot be monitored
Solution Approach 1:
The patent introduces a data processing system that acts as an intermediary between the distributed sensors and leak detection. This system collects pressure data from multiple sensors spaced at intervals and uses data fusion algorithms to infer leak conditions, effectively bridging the gap between limited sensor coverage and the need for precise leak detection without requiring continuous monitoring of every pipeline segment
Solution Approach 2:
The patent transitions from spatial dimension analysis to temporal dimension analysis by examining pressure variations over time at discrete sensor locations. By analyzing the time-varying pressure signals and their patterns across multiple time points, the system can detect leaks with higher precision than static spatial monitoring would allow, effectively adding a temporal dimension to the detection process
2Reliability
If extensive sensor coverage is deployed along the pipeline network, then leak detection capability is improved, but system complexity and cost increase
Solution Approach 1:
The patent implements partial monitoring by strategically placing sensors at key locations such as compression stations and along the pipeline at intervals, rather than providing excessive coverage throughout. The data processing system compensates for the limited sensor density by using advanced algorithms that can infer leak conditions from partial data, achieving reliable leak detection without the complexity and cost of extensive sensor deployment
Solution Approach 2:
The patent makes the existing sensors and data processing system multi-functional by enabling them to perform both routine monitoring and leak detection functions. The same pressure sensors used for general pipeline monitoring are also utilized for leak detection through sophisticated data analysis, eliminating the need for separate dedicated leak detection sensor networks and reducing overall system complexity
3Measurement precision
If pressure is monitored continuously at multiple sensors, then leak detection accuracy is improved, but data processing requirements and energy consumption increase
Solution Approach 1:
The patent implements periodic sampling of pressure data at the sensors rather than truly continuous monitoring. The system collects pressure readings at regular time intervals and processes these discrete data points using the data processing system. This periodic approach maintains sufficient leak detection accuracy while significantly reducing the data processing load and energy consumption compared to continuous data acquisition and processing
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
Effectively identifies leaks in pipeline networks by analyzing pressure patterns and flow rates, reducing resource loss and improving monitoring efficiency without requiring extensive sensor coverage.
Implementation Method 1
measuring pressure at each of a plurality of sensors distributed along the pipeline network as a time-varying pressure signal
Implementation Method 2
tuning, using a processor, a model based on gas mass conservation law in the absence of the leak
Data Source
AI summary
A method and system method to detect a leak within a pipeline network include measuring pressure at each of a plurality of sensors distributed along the pipeline network as a time-varying pressure signal. Tuning a model is based on gas mass conservation law in the absence of the leak, the tuning including obtaining the time-varying pressure signal from each of the plurality of sensors, and monitoring the time-varying pressure signals is done to detect the leak based on the model.