UAV Methane Source Localization Using Back-Trajectory Mapping
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Solution Overview
Problem
Existing methods are inadequate for efficiently identifying and localizing methane emissions sources in natural gas production and distribution systems, leading to undue product loss, environmental impact, and safety hazards.
Innovation Solution
A system and method utilizing an unmanned aerial vehicle (UAV) equipped with gas concentration sensors and a weather station to measure methane concentrations, combine data with meteorological data, and apply stochastic particle trajectory models to determine the location of methane sources, generating a spatial map of emissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional ground-based monitoring methods are used to detect methane emissions, then the system complexity is low, but the detection precision and source localization accuracy are insufficient
Solution Approach 1:
The patent transitions from ground-based two-dimensional monitoring to three-dimensional aerial monitoring using UAVs. The gas concentration sensor is mounted on a UAV that operates in three-dimensional space, enabling detection from multiple angles and heights, which significantly improves source localization accuracy while the integrated onboard computer maintains system manageability
Solution Approach 2:
The UAV platform serves multiple functions: it carries the gas concentration sensor for detection, the onboard computer for data processing and source localization calculation, and the positioning system for spatial tracking. This multi-functional integration improves measurement precision without proportionally increasing overall system complexity
2Measurement precision
If comprehensive meteorological data collection and stochastic particle trajectory modeling are implemented, then the source localization accuracy is improved, but the loss of time for data processing increases
Solution Approach 1:
The system collects meteorological data (wind speed, wind direction, temperature, pressure) in real-time and uses it immediately in the stochastic particle trajectory model. The onboard computer processes the trajectory calculations continuously as new gas concentration data becomes available, rather than waiting for complete data sets, thus improving localization accuracy without excessive time loss
Solution Approach 2:
The patent replaces complex mechanical sampling and laboratory analysis methods with computational modeling. The stochastic particle trajectory model uses mathematical algorithms to simulate gas dispersion and reverse-calculate source locations, which is computationally faster than traditional mechanical measurement and analysis approaches
3Productivity
If real-time gas concentration monitoring along flight paths is performed, then the productivity of emission detection is improved, but the use of energy by the moving object increases
Solution Approach 1:
The UAV performs continuous gas concentration monitoring along its flight path without interruption. The gas concentration sensor operates continuously, and the onboard computer continuously processes data and updates source localization estimates. This continuous operation maximizes detection efficiency and productivity while the UAV maintains steady flight to optimize energy consumption
Solution Approach 2:
The system uses the UAV's own motion and onboard resources to perform detection and analysis. The UAV's flight path itself becomes the measurement trajectory, and the onboard computer uses the UAV's positioning data and sensor readings to self-determine source locations, eliminating the need for separate ground-based measurement systems and reducing overall energy requirements
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 efficient identification and quantification of methane emissions, reducing product loss, environmental footprint, and safety risks by accurately locating and mapping methane sources.
Implementation Method 1
a gas concentration sensor configured to measure a gas concentration
Implementation Method 2
apply a stochastic particle trajectory model to the measured gas concentration, the UAV data, and the weather data
Data Source
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AI summary
Systems, devices, and methods for receiving, by a ground control station (GCS) (106) having a processor (1702) with addressable memory (1706), a plurality of point source gas concentration measurements; receiving, by the GCS, a meteorological data corresponding to each point source concentration gas measurement; determining, by the GCS, if each point source gas concentration measurement is an elevated ambient gas concentration; generating, by the GCS, a back trajectory (904) for each elevated ambient gas concentration; storing, by the GCS, the position of each generated back trajectory in a grid; determining, by the GCS, a probability of a gas source location corresponding to the stored positions in the grid; and generating, by the GCS, an overlay (1302) showing the probability of the gas source location.