Adaptive Gas Imaging Plume Tracking
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Solution Overview
Problem
Existing gas imaging systems are prone to false positives and negatives, and struggle to accurately quantify fugitive gas leaks due to limitations in scanning patterns and environmental factors, leading to inaccurate attribution of emission sources and reduced leak rate quantification accuracy.
Innovation Solution
An adaptive gas imaging system that dynamically adjusts its field of view and bearing using a computing device to center fugitive gas plumes, stitch multiple images together, and calculate emission rates by integrating wind measurements and laser absorption spectroscopy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a gas imager scans a finite field of view continuously and cyclically through predefined frames, then the scanning coverage is systematic and complete, but false positives from noise increase and large plumes spread across multiple frames reduce detection accuracy
Solution Approach 1:
The system dynamically adjusts the camera's field of view, zoom level, and scanning pattern in real-time based on detected plume characteristics. Instead of fixed predefined frames, the camera adapts its observation window to track and center on plumes, optimizing the balance between detection coverage and origin attribution precision.
Solution Approach 2:
The system uses feedback from plume detection results to continuously refine scanning behavior. When plumes are detected, the system adjusts subsequent scanning parameters (zoom level, frame timing, recentering) based on plume size, concentration, and spatial distribution, thereby reducing false positives and improving origin identification accuracy.
2Measurement precision
If the imager recenter on an estimated plume origin and acquire additional frames at predefined zoom, then plume origin identification is enhanced, but the scan cycle is prone to false positives and false negatives
Solution Approach 1:
The system changes scanning parameters (zoom level, frame acquisition timing, recentering offset) based on detected plume characteristics such as size, concentration, and spatial extent. This adaptive parameter adjustment allows the system to optimize detection reliability for different plume scenarios rather than using fixed predefined parameters.
Solution Approach 2:
The system performs preliminary analysis of plume characteristics before final origin attribution. By pre-processing detected plumes to estimate their origin and characteristics, the system can prepare optimized scanning parameters in advance, reducing the risk of false positives and negatives in subsequent confirmatory frames.
3Productivity
If optimally selected frames are used for plume detection, then detection efficiency is improved, but attribution to sources within predetermined frames is restricted and accuracy is reduced
Solution Approach 1:
The system transitions from static predetermined frames to dynamic adaptive framing. The camera's field of view and scanning pattern are continuously adjusted based on real-time plume detection, allowing efficient detection while maintaining accurate source attribution through adaptive recentering and zooming rather than being restricted to fixed frames.
4Quantity of substance
If the imager sees a portion of the plume but does not see an identifiable plume origin, then some plume detection is achieved, but false negatives increase and leak rate quantification accuracy is limited
Solution Approach 1:
The system uses feedback from partial plume observations to guide subsequent scanning actions. When only a portion of a plume is detected without clear origin identification, the system adjusts scanning parameters (recentering, zoom level, frame timing) to actively search for and capture the plume origin, thereby reducing false negatives and improving leak rate quantification accuracy.
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
Enhances the accuracy of fugitive gas leak detection by minimizing false positives and negatives, and provides precise quantification of leak sources, duration, and emission rates through continuous real-time adjustments.
Implementation Method 1
laser absorption spectroscopy with LiDAR
Implementation Method 2
laser absorption spectroscopy with LiDAR
Implementation Method 3
connect to an anemometer
Data Source
AI summary
Systems and methods are described for identifying and validating a fugitive gas leak. The system identifies the onset of a leak, tracks its persistence, and subsequently, notes its gradual disappearance after repairs are initiated. The method comprises initiating an observation period which serves to characterize the behavior of the anticipated leak if it exists. Extracting the underlying distributions of the parameter space for the anticipated leak over an observation period. Data is collected over incremental steps and compared to the current reference distributions. When the test period is complete, the observation window is moved forward to include the data over the validation span. The procedure thus repeats, with an updated reference distribution and re-initialized validation period.