Gas Leak Imaging Using Luminance Change Frequency Analysis
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Solution Overview
Problem
Existing gas leak detection methods struggle to accurately identify gas leaks in wide fields due to temperature variations and background interference, particularly when using infrared cameras, as the temperature difference between the background and the gas is small, making it difficult to distinguish the gas from the background.
Innovation Solution
A gas leak detection device and method that utilizes a series of image data acquisition, luminance change evaluation, and luminance change frequency distribution calculation to identify gas leaks by comparing luminance changes over time, integrating these changes to enhance detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single captured image is used for gas leak detection, then the detection process is simple and fast, but the detection accuracy deteriorates when temperature difference between background and gas is small
Solution Approach 1:
The system performs preliminary actions by capturing multiple images before making a detection decision. Instead of relying on a single image, the system accumulates multiple image data in chronological order, evaluating luminance changes across these preliminary captures to improve detection accuracy while maintaining efficiency through automated processing.
2Measurement precision
If multiple image data are captured and analyzed, then the gas detection accuracy is improved, but the processing time and complexity increase
Solution Approach 1:
The system applies partial action by selectively processing only the necessary image data. It captures multiple images but processes them through efficient algorithms that evaluate luminance changes at pixel levels, integrating only the essential information needed for detection. This approach achieves high accuracy without requiring excessive processing of all possible image parameters.
3Measurement precision
If multiple image data are captured and analyzed, then the gas detection accuracy is improved, but the processing time increases
Solution Approach 1:
The system maintains continuity of useful action by continuously capturing image data in chronological order and processing it through an integrated evaluation framework. The luminance change evaluation unit continuously compares images, and the integration process accumulates useful information over time, enabling accurate detection without excessive delays. The continuous processing approach ensures that detection accuracy improves with more data while minimizing idle time.
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
The method accurately detects gas leaks regardless of temperature variations and background interference by emphasizing luminance changes over time, providing clear visualization of gas presence.
Implementation Method 1
The infrared camera includes a detection element for detecting infrared rays. In the detection element, the intensity of the infrared rays incident on the infrared camera is detected, and the sensing result is converted into an electrical signal.
Implementation Method 2
an electromagnetic wave emitted from the background (for example, the ground, a wall of a building, or the like) of a field and an electromagnetic wave that has passed through a detection target gas (CO2 gas) present between the background of the field and the infrared camera to absorb some energy are detected
Data Source
AI summary
This gas leak detection device acquires a plurality of pieces of image data obtained by imaging a field in chronological order, and compares the luminance of each pixel in two pieces of image data to evaluate a luminance change for each pixel included in the image data. By integrating the luminance change for each pixel, a luminance change frequency distribution in the image data is calculated. Gas leaking in the field is detected on the basis of the luminance change frequency distribution calculated in this way.