Transient Pressure Event Source Detection in Pipelines
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Solution Overview
Problem
Current systems are unable to quickly and automatically detect the source of transient pressure events in complex pipeline networks, which complicates proactive maintenance and pipeline management due to the complexity of wave propagation through mixed materials and constrained pipeline routes.
Innovation Solution
A transient pressure event detection system that uses a data repository, sensor data receivers, and an event detecting unit to determine potential source locations by analyzing timestamp differences and simulating transient events, with a scoring system to identify the most likely source based on arrival times and amplitude decay, and employs pre-computation of arrival-time/attenuation values for scalable computing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual expert analysis is used to detect transient source locations, then measurement precision can be maintained, but productivity and response time deteriorate significantly
Solution Approach 1:
The patent replaces manual expert analysis with an automated computational system that uses numerical methods to simulate pressure wave propagation and automatically determine source locations based on sensor data, eliminating the need for human intervention while maintaining accuracy
Solution Approach 2:
The system creates a virtual copy of the pipeline network through a digital model that replicates the physical network's structure and properties, allowing simulated pressure wave propagation to be performed on the copy rather than physically analyzing each scenario
2Productivity
If automated detection systems are implemented, then productivity improves, but device complexity increases due to the need for multiple sensors and computational resources
Solution Approach 1:
The system uses a single integrated software platform that performs multiple functions including pressure wave simulation, source location determination, and network modeling, eliminating the need for separate specialized devices for each function
Solution Approach 2:
The patent introduces a computational model as an intermediary between the physical sensor network and the analysis process, where the model mediates by simulating pressure wave propagation and translating sensor data into source location information
3Reliability
If comprehensive network monitoring is implemented, then reliability improves, but loss of energy increases due to continuous data processing and simulation
Solution Approach 1:
The system performs preliminary computations by pre-calculating pressure wave propagation characteristics for different scenarios and storing them in the digital model, allowing rapid source location determination without performing full simulations for every event
Solution Approach 2:
The patent applies partial action by selectively simulating pressure wave propagation only for the specific network segments and time periods relevant to detected events, rather than continuously processing the entire network, thereby reducing computational energy consumption
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
Enables rapid and automatic detection of transient pressure event sources, improving pipeline management and maintenance by accurately locating events even in complex networks with mixed materials, and scaling with increasing network size using cloud-based computing.
Implementation Method 1
Pressure transients have been known about for about 200 years and the mathematics which describes the physics of the phenomena for about 100 years
Data Source
AI summary
A transient pressure event detection system and method for a pipeline network are disclosed. The system includes a data repository encoding route data on the pipeline network, a data receiver configured to receive timestamped pipeline sensor data from each of a plurality of sensors that are spaced apart in the pipeline network, use the sensor data received to identify a transient pressure event occurrence and the timestamp for the event occurrence's arrival time, determine routes in the pipeline network between the sensors, for each route determine a potential source location in the pipeline network for the transient pressure event, perform a simulated transient event for each potential source location and determine a modelled arrival time of a transient corresponding to the event, compare the timestamp of the event occurrence with the modelled arrival time and select the potential source location corresponding to the closest modelled arrival time.