Remote Gas Leak Detection Using Spectral Filtering and Turbulence Imaging
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Solution Overview
Problem
Existing gas leak detection methods are not selective in source location, unreliable across varying environments, expensive, and require human monitoring, limiting their effectiveness for 24-hour operation.
Innovation Solution
A system comprising a lens, filter, and detector that processes image data to identify turbulence flows indicative of gas leaks, using algorithms to enhance contrast and automate detection, allowing for unmanned remote detection and location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cryogenically cooled infrared systems are used for gas leak detection, then detection sensitivity is improved, but system cost and maintenance complexity increase significantly
Solution Approach 1:
The patent replaces expensive cryogenically cooled systems with uncooled microbolometer cameras that are significantly cheaper and require no complex cooling maintenance. The microbolometer technology provides sufficient detection capability without the high cost and complexity of cryogenic cooling systems, making the system economically viable for widespread deployment.
Solution Approach 2:
The patent substitutes the mechanical cryogenic cooling system with an electronic/image-processing-based solution. Instead of physically cooling the detector to extreme temperatures, the system uses uncooled detectors combined with advanced image processing algorithms to achieve comparable or superior detection performance at lower cost and complexity.
2Measurement precision
If hyperspectral imaging systems are used for gas detection, then gas detection capability is improved, but spatial resolution is sacrificed and system cost increases to hundreds of thousands of dollars
Solution Approach 1:
The patent applies selective spectral filtering using narrow-bandpass filters that target specific gas absorption wavelengths. Instead of capturing the full hyperspectral range, the system focuses detection resources on the specific wavelengths where the target gas absorbs light, maintaining detection sensitivity while preserving spatial resolution and reducing system complexity.
Solution Approach 2:
The patent changes the spectral parameter by using tunable bandpass filters that can be adjusted to match specific gas absorption characteristics. This allows the system to optimize detection for different gases without requiring a full hyperspectral imager, thereby maintaining both detection capability and spatial resolution while reducing cost.
3Measurement precision
If optical gas imaging systems with narrow bandpass filters are used, then gas selectivity is improved, but background contrast is reduced making detection unreliable
Solution Approach 1:
The patent employs alternating filtration between the target gas wavelength and a reference wavelength, capturing multiple images in sequence. By periodically switching between detection of the gas signal and the background signal, the system can subtract the background component and enhance the gas-specific signal, thereby maintaining selectivity while improving contrast.
Solution Approach 2:
The system uses the reference wavelength images as feedback to characterize and remove background signals. By continuously monitoring the background at reference wavelengths and subtracting this information from the target wavelength images, the system maintains high gas selectivity while compensating for background variations and improving overall detection contrast.
4Extent of automation
If automatic image processing algorithms are implemented, then 24-hour unmanned monitoring is enabled, but processing complexity increases
Solution Approach 1:
The patent applies a tiered processing approach where basic gas detection algorithms run continuously on all images, while more complex analysis is applied only when gas signals are detected. This partial application of processing complexity enables 24-hour automated monitoring for basic detection, with enhanced processing reserved for confirming and analyzing detected events, thereby achieving automation without excessive overall complexity.
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 low-cost, accurate, and automated gas leak detection and location within seconds, even under low contrast conditions, providing high-contrast images for quick leak identification and severity assessment.
Implementation Method 1
a filter located after the lens, the filter having one or more passbands that pass wavelengths which match one or more emission or reflectively wavelengths of the gas being monitored
Implementation Method 2
A detector is arranged to receive the image after the image passes through the lens and the filter and the detector is configured to generate image data representing the scene
Data Source
AI summary
A system for monitoring for a gas leak from a gas containing structure. The system includes a lens that directs an image of a scene of interest through an optical filter to a detector. The filter, associated with the lens, has one or more passbands that pass wavelengths which match one or more emission or reflectively wavelengths of the gas being monitored. A detector receives the image after the image passes through the lens and the filter. The detector generates image data representing the scene including the gas containing structure. A processor is configured to process the image data by executing machine executable code stored on a memory. The machine executable code processes the image data to identify turbulence flows in the image data such that a turbulence flow indicates a gas leak. The code generates and sends an alert in response to the identification of a turbulence flow.