Method and system for remote imaging explosive gases
Inventors
WANG, Naixiang • Wu, Mengting • Wang, Yuelin • Yu, Zhinan • TSE, Ming Leung Vincent
Assignees
Hong Kong Applied Science and Technology Research Institute ASTRI
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Publication Number
US-12117391-B1
Publication Date
2024-10-15
Expiration Date
Abstract
The present invention provides a method and a system for remote imaging of explosive gases in an area. The method comprises: illuminating the area with a light source having a uniform light intensity distribution over an infrared wavelength range; acquiring images of the illuminated area with an image sensor through gas detection filters having bandpass central wavelength corresponding to absorption curves of target gases respectively; determining existence of the target gases based on the acquired images; predicting distribution of gas concertation for existing target gases respectively by using a non-linear prediction model; and constructing gas distribution images of the area based on the predicted distribution of gas concertation. The present invention can recognize different gases with overlapping absorption curves and provide more accurate prediction of gas concentrations.
Core Innovation
The disclosed subject matter provides a method for remote imaging of explosive gases in an area. The method illuminates the area with a light source having a uniform light intensity distribution over an infrared wavelength range and acquires one or more images of the illuminated area with an image sensor through one or more gas detection filters. Each gas detection filter has a bandpass central wavelength corresponding to absorption curves of one or more target gases respectively.
The method determines existence of the one or more target gases based on the one or more acquired images. For existence determination, corrected pixel intensity is compared to a threshold, and calibrated background intensity corresponding to the one or more detection filters is used to obtain the corrected pixel intensity. The description further includes a dynamic threshold to eliminate dark background contribution and enhance sensitivity.
For existing target gases, the method predicts one or more distribution of gas concentration using a non-linear prediction model. The non-linear prediction model uses corrected pixel intensity, calibrated background intensity, and nonlinearity factors, where the nonlinearity factors represent contributions from wavelength dependence of the absorption coefficient of the target gas, wavelength dependence of the absorption spectrum shape of the target gas, and a non-absorbing wavelength region between an absorption band and the band-width of the detection filter. One or more gas distribution images are constructed based on the predicted gas concentration distributions.
Claims Coverage
The independent claim covers four core inventive actions: uniform-intensity infrared illumination, acquisition through gas-specific bandpass filters matched to target-gas absorption curves, gas existence determination, and non-linear concentration prediction to construct gas distribution images. Dependent claims further refine the existence determination using calibrated background correction and thresholding with dynamic thresholds, and refine the concentration prediction using nonlinearity factors tied to absorption coefficient wavelength dependence, absorption spectrum shape, and a non-absorbing region between an absorption band and filter bandwidth. One dependent claim further specifies a system architecture including a processor-controlled filter wheel with detection filters whose central wavelengths and full width at half maximum match the absorption curves.
Uniform infrared illumination with gas-matched detection filters
Illuminating the area with a light source having a uniform light intensity distribution over an infrared wavelength range; acquiring one or more images of the illuminated area with an image sensor through one or more gas detection filters having bandpass central wavelength corresponding to absorption curves of one or more target gases respectively.
Existence determination using corrected pixel intensity and calibrated background
Determining existence of the one or more target gases based on the one or more acquired images by calculating a corrected pixel intensity using a calibrated background intensity corresponding to the detection filter and comparing the corrected pixel intensity to a threshold to conclude gas existence.
Dynamic threshold to eliminate dark background contribution
Using a dynamic threshold value to eliminate dark background contribution to enhance sensitivity when determining gas existence based on corrected pixel intensity.
Non-linear concentration prediction model with absorption-parameterized nonlinearity factors
Predicting one or more distribution of gas concentration for one or more existing target gases respectively by using a non-linear prediction model with nonlinearity factors representing contribution from wavelength dependence of the absorption coefficient of the target gas, contribution from wavelength dependence of the absorption spectrum shape of the target gas, and contribution from a non-absorbing area between the absorption band of the target gas and band-width of the detection filter.
Gas distribution imaging based on non-linear predicted concentration
Constructing one or more gas distribution images of the area based on the one or more predicted distribution of gas concentration.
Processor-controlled filter wheel with absorption-matched filter parameters
A remote imaging system illuminates an area with a uniform-intensity mid-wave infrared light beam, captures an infrared image using an image sensor, and uses a processor-controlled filter wheel with multiple detection filters whose central wavelengths and full width at half maximum match the absorption curves of a target explosive gas.
Overall, the claim set centers on remote multispectral infrared imaging using uniform-intensity illumination and detection filters matched to target-gas absorption curves, determining gas existence using calibrated background correction and thresholding, including a dynamic threshold, and predicting concentration distributions using a non-linear prediction model parameterized by nonlinearity factors tied to absorption coefficient wavelength dependence, absorption spectrum shape, and a non-absorbing region; gas distribution images are then constructed from the predicted concentrations.
Stated Advantages
Enhance sensitivity by eliminating dark background contribution using a dynamic threshold.
Documented Applications
Remote imaging of explosive gases in an area, including detection of target gases having absorption curves matched to detection filter bandpass central wavelength.
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