A 3-D Reconstruction Method for Leakage Gas Cloud Based on Dual FTIR Telemetry Scanning Imaging System

Abstract

The present invention relates to a method for 3-D reconstruction of a leaked gas cloud based on a dual FTIR telemetry scanning imaging system, comprising the following steps: Step A: Select a monitoring area where gas leakage occurs, deploy two FTIR telemetry scanning imaging systems at different azimuths in the monitoring area, and obtain the GPS positions of each system; Step B: During the normal monitoring process, each system measures the 2-D projection column concentration image of the gas cloud and the pointing information of each pixel, such as azimuth and elevation angle; Step C: Use a geometric method to locate the cross-monitoring area and stratify it by elevation angle to obtain the monitoring area information divided by a three-dimensional grid; Step D: Calculate the path length coefficient sparse matrix of each layer, and use the simultaneous algebraic reconstruction technique (SART) to reconstruct the gas cloud distribution of each layer; Step E: Combine the gas cloud distributions of each layer into a 3-D gas cloud, calculate the center position of the gas cloud by the concentration weighting method, and display it through a false color combined with a 3-D map.

Description

Technical Field

[0001] The present invention belongs to the field of atmospheric environment monitoring, and particularly relates to a method for 3-D reconstruction of leaked gas clouds based on a dual FTIR telemetry scanning imaging system. Background Art

[0002] With the development of social economy, a large number of large tank farms storing hazardous chemicals such as toxic, harmful, inflammable and explosive substances have been established around the world, especially in the energy industry, such as the finished diesel tank farm, finished gasoline tank farm, gasoline component tank farm, aviation kerosene tank farm, heavy oil tank farm and aromatic hydrocarbon tank farm in petrochemical plants, as well as the large liquefied natural gas storage tank area in oil and gas plants. If a gas leakage occurs in the tank farm and causes a hazard accident, it will cause serious damage to the surrounding residents and the environment. Regular leakage monitoring of the tank farm is one of the most effective methods to prevent hazard accidents. Once a gas leakage occurs, quickly and accurately identifying the components, location, distribution and propagation path of the leaked gas is crucial for the early warning, risk assessment and treatment of gas leakage.

[0003] Fourier transform infrared spectroscopy (FTIR) remote sensing technology is a comprehensive detection technology with great application prospects. Due to its high sensitivity, high resolution, non-contact and real-time measurement, it is widely used in the remote quantitative detection of polluting gases. A single FTIR telemetry scanning imaging system can obtain a 2-D image that fuses a false color image with gas cloud column concentration information and a visible light image of the scene. From this image, only the gas leakage direction can be judged, but the specific leakage position in this direction cannot be determined. In addition, a single FTIR telemetry scanning imaging system can only measure the concentration path length integral on the path and cannot obtain the concentration values of the diffusion distribution. The emergence of the method for 3-D reconstruction of leaked gas clouds based on a dual FTIR telemetry scanning imaging system is due to the existence of this problem.

[0004] To address the problem that a single system cannot accurately locate a gas cloud, Rusch, Harig, and others developed a three-dimensional reconstruction method for gas clouds based on imaging infrared spectroscopy and tomography. By simultaneously scanning the area to be measured with two machines, the ammonia plume emitted from an industrial chimney was reconstructed to obtain the position, contour, and obvious propagation direction of the gas cloud. Donato et al. used SIGIS2 to perform advanced 3-D reconstruction on the SO2 gas cloud detected in the atmosphere of the NANCY urban area, and proposed a method combining triple correlation and 3-D interpolation. By using one instrument to perform 3-D reconstruction of the SO2 gas cloud contour at three different positions at different times, however, the gas cloud three-dimensional imaging technology has a limited environmental monitoring range, can only obtain the volume and contour of the gas cloud, cannot obtain its concentration and diffusion trend, etc., and has a high computational complexity. In addition, both of the above methods perform 3-D reconstruction on the shape of the gas cloud and can only obtain limited information such as its position and transmission process. To more accurately find the leakage point within the gas cloud, the gas cloud concentration information is required. Reconstructing the 3-D gas cloud is beneficial for obtaining detailed information about the gas cloud, such as the maximum length, maximum width, maximum height of the gas cloud, the height of the gas cloud center from the ground, the gas cloud concentration center, and the gas cloud diffusion trend, which is beneficial for further expanding the application of the FTIR telemetry scanning imaging system, such as online detection of leakage sources and risk level assessment. Summary of the Invention

[0005] To solve the above technical problems, the present invention provides a 3-D reconstruction method for a leaked gas cloud based on a dual FTIR telemetry scanning imaging system, which is a reconstruction method for 3-D imaging of a leaked gas cloud group, so as to alleviate the technical problems such as the quantitative problem of the 3-D gas cloud reconstructed by the multi-FTIR telemetry scanning imaging system, the gas cloud measurement problem during the reconstruction process, and the 3-D reconstruction of the gas cloud in the prior art.

[0006] The present invention provides a 3-D reconstruction method for a leaked gas cloud based on a dual FTIR telemetry scanning imaging system, including the following steps:

[0007] Step A: Select a monitoring area where gas leakage exists, deploy two FTIR telemetry scanning imaging systems at different azimuths in the monitoring area, and obtain the GPS positions of each FTIR telemetry scanning imaging system;

[0008] Step B: During the normal monitoring process, each FTIR telemetry scanning imaging system measures the 2-D projection column concentration image of the gas cloud and the pointing information of each pixel regarding the azimuth and elevation angle;

[0009] Step C: Use a geometric method to locate the cross-monitoring area and stratify it by elevation angle to obtain the monitoring area information divided by a three-dimensional cubic grid;

[0010] Step D: Calculate the path length coefficient sparse matrix of each layer, and use the joint algebraic reconstruction algorithm to reconstruct the gas cloud distribution of each layer;

[0011] Step E: Combine the gas cloud distributions of each layer into a 3-D gas cloud, calculate the center position of the gas cloud by the concentration-weighted centroid method, and display it through false-color HSI space mapping combined with a 3-D map.

[0012] Further, the specific steps of step A include:

[0013] Step A1: Measure the azimuth angle of the dual FTIR telemetry scanning imaging system relative to the center of the monitoring area so that the included angle between the two azimuth lines is approximately perpendicular;

[0014] Step A2: Use the longitude and latitude of the installation positions of the dual FTIR telemetry scanning imaging systems as inputs, calculate the distance between the two points, and calculate the azimuth angle of one FTIR telemetry scanning imaging system relative to the other.

[0015] Further, step B includes:

[0016] Step B1: During the acquisition process of each FTIR telemetry scanning imaging system, the scanning is from left to right in an S-shaped pattern row by row. During the acquisition process, record the azimuth angle, elevation angle, and interferogram of each pixel, where the azimuth angle and elevation angle are measured simultaneously using a nine-axis gyroscope sensor; use the radiometric calibration method to convert the relative radiance into absolute radiance to obtain a hyperspectral data cube with spatial and spectral information;

[0017] Step B2: Invert the transmittance spectrum of each pixel from the spectrum in step B1 through a simple three-layer radiative transfer model, and qualitatively analyze the spectrum through a gas component identification algorithm. Use the nonlinear least squares algorithm to calculate the gas column concentration image corresponding to the spectrum of each pixel with the standard spectrum of the identified spectrum. This image is a 2-D projection image of the 3-D gas cloud.

[0018] Further, step C includes:

[0019] Step C1: Based on the geometric parameters between the dual FTIR telemetry scanning imaging systems obtained in step A2, combine the azimuth angle of the center of the field of view during measurement to construct a triangle to calculate the longitude and latitude of the center position of the monitoring area; combine the azimuth angle of the edge of the field of view during measurement to construct a triangle to calculate the longitude and latitude of the boundary position of the cross-monitoring area.

[0020] Further, step C also includes:

[0021] Step C2: Construct a triangle with the elevation angles of the upper and lower boundaries of the scanning field of view to calculate the scanned height of the monitoring area.

[0022] Further, in steps C1 and C2, divide the boundary of the monitoring area, and perform 3-D grid division within the area according to the field of view size, and cover the monitoring area.

[0023] Further, step D includes step D1:

[0024] (1) Without considering the elevation angle, calculate the horizontal projection layer path length coefficient sparse matrix M0.

[0025] (2) When considering the elevation angle, correct it from the horizontal projection layer path length coefficient sparse matrix M0 and calculate the path length coefficient sparse matrix M of each layer i (i = 1, 2, …, Z), where Z is the number of divided layers and i is the layer number.

[0026] Further, step D also includes:

[0027] Step D2: Use the joint algebraic reconstruction algorithm to reconstruct the concentration distribution of each layer, and recombine the reconstructed concentration distribution matrices of each layer to obtain a gas cloud concentration cube data.

[0028] Further, in step E, using the longitude, latitude and gas cloud concentration as the input of the concentration weighted center method, calculate the gas cloud concentration center to approximate the leakage source.

[0029] Further, it is applicable to the 3-D visualization, quantification and positioning of the leaked gas cloud.

[0030] Beneficial effects:

[0031] A 3-D reconstruction method of a leaked gas cloud based on a dual FTIR telemetry scanning imaging system of the present invention has the following advantages:

[0032] (1) The present invention adopts a 3-D gas cloud reconstruction method of a dual FTIR telemetry scanning imaging system, while a single FTIR telemetry scanning imaging system measures the 2-D gas cloud projection of the 3-D gas cloud. The 3-D gas cloud is the gas concentration value, while the 2-D gas cloud is the gas column concentration value, solving the problem that a single system cannot obtain the gas cloud concentration value. In other words, the concentration unit is successfully converted from ppm·m to ppm.

[0033] (2) The single FTIR telemetry scanning imaging system obtains the leakage orientation without distance information. Especially in the case of a large leakage amount, only a fan-shaped area can be obtained. While the dual FTIR telemetry scanning imaging system can obtain the accurate position information of the leakage source and determine the longitude and latitude of the leakage position. When there are multiple leakage sources, it is easy to overlap during the measurement by a single FTIR telemetry scanning imaging system, while under the measurement of the dual FTIR telemetry scanning imaging system, the interference on the imaging gas cloud is small, providing a solution for the detection of multiple leakage sources.

[0034] (3) Reconstructing the 3-D gas cloud can obtain more detailed information about the leak, such as gas cloud composition, gas cloud concentration, gas cloud size, gas cloud coverage area, and gas cloud diffusion trend, which can be used for leak source detection and risk level assessment, etc. In addition, the entire measurement scheme to the reconstruction method has strong practicability and innovation in environmental on-line monitoring applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a physical diagram of the dual FTIR telemetry scanning imaging system of the present invention;

[0036] Figure 2(a) is a schematic diagram of the monitoring layout of the dual FTIR telemetry scanning imaging system of the present invention;

[0037] Figure 2(b) is a schematic diagram of the optical path projection during monitoring of the dual FTIR telemetry scanning imaging system of the present invention;

[0038] Figure 2(c) is a schematic diagram of the projection measurement of the 3-D gas cloud during monitoring of the single FTIR telemetry scanning imaging system of the present invention;

[0039] Figure 3 is a flowchart of the 3-D gas cloud reconstruction method based on the dual FTIR telemetry scanning imaging system of the present invention;

[0040] Figure 4 is a three-layer radiative transfer model;

[0041] Figure 5 is a 3-D reconstruction image of the leaked gas of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0043] According to an embodiment of the present invention, a 3-D reconstruction method for a leaked gas cloud based on a dual FTIR telemetry scanning imaging system is provided, using the dual FTIR telemetry scanning imaging system as shown in Figure 1 to alleviate the problem of inability to locate the leak source and quantify the gas cloud under a single FTIR telemetry scanning imaging system. As shown in Figure 3 , the 3-D reconstruction method for the leaked gas cloud based on the dual FTIR telemetry scanning imaging system of the present invention specifically includes the following steps:

[0044] Step A: Select the monitoring area where gas leakage exists. Deploy two FTIR telemetry scanning imaging systems at different orientations in the monitoring area, and obtain the GPS positions of each FTIR telemetry scanning imaging system. According to an embodiment of the present invention, the deployment of the FTIR telemetry scanning imaging system uses a compass orientation method.

[0045] Step B: During the monitoring process, each FTIR telemetry scanning imaging system measures the 2-D projection column concentration image of the gas cloud and the pointing information of each pixel, such as azimuth and elevation angle. Optionally, the generation of the gas cloud 2-D projection column concentration image is carried out according to the three-layer radiation transfer model and the nonlinear least squares method. Optionally, the pointing information data of each pixel is measured using a nine-axis gyroscope sensor.

[0046] Step C: Use a geometric method to locate the cross-monitoring area and stratify it by elevation angle to obtain the monitoring area information divided by a three-dimensional cubic grid. According to an embodiment of the present invention, the geometric method for location uses a triangulation algorithm. According to an embodiment of the present invention, the stratification method by elevation angle is based on the triangulation height standard.

[0047] Step D: Calculate the path length coefficient sparse matrix of each layer, and use the simultaneous algebraic reconstruction technique (SART) to reconstruct the gas cloud distribution of each layer. According to an embodiment of the present invention, the calculation method of the layer path length coefficient sparse matrix is the core parameter of 3-D reconstruction. Optionally, the simultaneous algebraic reconstruction technique is the optimal algorithm for restoring the gas cloud concentration of each layer.

[0048] Step E: Combine the gas cloud distributions of each layer into a 3-D gas cloud, calculate the center position of the gas cloud by concentration weight, and display it through a false color combined with a 3-D map. Optionally, the center of the gas cloud is carried out according to the concentration weight method.

[0049] According to an embodiment of the present invention, in Step A: the selection of the monitoring area where gas leakage may exist includes deploying two FTIR telemetry scanning imaging systems at different orientations in the monitoring area, and obtaining the GPS positions of each FTIR telemetry scanning imaging system. The deployment method is shown in Fig. 2(a). In the figure, the two FTIR telemetry scanning imaging systems are respectively denoted as scanning system 1 and scanning system 2.

[0050] In the embodiment of the present invention, Step A specifically includes the following steps:

[0051] Step A1: As shown in Fig. 2(a), select the area where leakage may occur to be monitored. Taking the center of the monitoring area as point O, the scanning system 1 as point S1, and the scanning system 2 as point S2, form a triangle OS1S2. Try to make the angle S1OS2 close to 90°, so that the scanning optical paths in the monitoring area cross evenly. Even optical path crossing can improve the reconstruction accuracy of the gas cloud, effectively prevent the deformation of the gas cloud distribution, and improve the correlation between the real gas cloud distribution and the reconstructed gas cloud distribution. To ensure the angle S1OS2, an electronic compass sensor is used to measure the geodetic azimuths of S1O and S2O, and the size of the triangle angle is obtained by subtraction, and the layout position is adjusted accordingly.

[0052] Step A2: Use the GPS built in the scanning system 1 and the scanning system 2 to measure their coordinates, that is, the position of the scanning system 1 (Longitude1, Latitude1) and the position of the scanning system 2 (Longitude2, Latitude2). The measured longitude is displayed in the format of "dddmm.mmmm", where d represents ° and m represents ′, and the measured latitude is displayed in the format of "ddmm.mmmm". First, the unit conversion of the longitude and latitude needs to be carried out and converted to the format of "dd.dddddd". Equations (1) and (2) are the formulas for calculating the distance between any two points on the earth:

[0053]

[0054] Distance=2·R·arcsin(C) (2)

[0055] In the formula, R is the radius of the earth. In addition, it is necessary to calculate the azimuth of the other point relative to each point based on each point, as described in the following formula:

[0056]

[0057]

[0058]

[0059] Given parameters such as azimuth and distance can be used for subsequent monitoring area positioning. Among them, Azimuth is the azimuth of the unknown point relative to the known point, and arctan2(x, y) is the four-quadrant arctangent function.

[0060] Step B: During the normal monitoring process, each FTIR telemetry scanning imaging system measures the 2-D projected column concentration image of the gas cloud and the pointing information of each pixel, such as azimuth and elevation angle. In the embodiments of this specification, it specifically includes:

[0061] Step B1: As shown in Fig. 2(c), each passive FTIR telemetry scanning imaging system sets the scanning interval according to the field of view size of the monitoring area. The angular accuracy of the maximum scanning angle of scanning systems 1 and 2 is 0.01°. The interferogram information corresponding to each pixel position in the field of view is collected in a row-first S-shaped manner, and the interferogram is converted into a spectrogram. The conversion process is as follows:

[0062]

[0063] In the formula, ν is the wave number, δ is the optical path difference, I(δ) is the interferogram, and B(ν) is the spectrogram. Through radiometric calibration, relative radiation is converted into absolute radiance, and a hyperspectral data cube with spatial and spectral information is obtained. At the same time, the azimuth angle and elevation angle of each pixel pointing need to be measured using the nine-axis gyro sensors on the scanning systems 1 and 2 to obtain the azimuth matrix and elevation matrix. The conversion from the interferogram to the spectrogram includes apodization of the interferogram, fast Fourier transform (FFT), phase correction, and radiometric calibration.

[0064] Step B2: Invert the transmittance spectrum of each pixel from the spectrum in Step B1 through a simple three-layer radiative transfer model. In the three-layer radiative transfer model as shown in Figure 4 , the contribution of scattering can be ignored, and the entrance pupil radiance L1(ν) of the FTIR telemetry scanning imaging system can be expressed as:

[0065] L1(ν) = (1 - τ1(ν))B1(ν) + τ1(ν)[(1 - τ2(ν))B2(ν) + τ2(ν)L3(ν)] (7)

[0066] In the formula, τ i (ν) is the transmittance of the i-th layer, B i (ν) is the temperature equivalent blackbody radiance of the i-th layer, L3(ν) is the background radiance, and ν is the wave number. Under general climate conditions, it can be approximately considered that the transmittance of the atmosphere is 1 during the ground-based short-range infrared passive telemetry process, and the temperature of the gas layer is equal to the atmosphere temperature under the thermal equilibrium state. Then the target gas cloud transmittance can be expressed by the following formula:

[0067]

[0068] And through the gas component identification algorithm, qualitative analysis of the spectrum is carried out. The nonlinear least squares algorithm is used to invert the gas column concentration corresponding to the spectrum of each pixel with the standard spectrum of the identified spectrum. This column concentration image is a 2-D projection image of the 3-D gas cloud. Among them, the column concentration inversion is through multiple iterative operations, so that the measured transmittance spectrum and the spectrum calculated through the standard database have the smallest mean square error (MSE), which can be expressed as:

[0069]

[0070] In Equation (9), i and j are the subscripts of the column concentration image, and τ′ i,j (ν) is the transmittance spectrum obtained after multiple iterative calculations of the spectrum in the standard gas spectral database, and τ i,j (ν) is the transmittance spectrum measured and calculated by the spectrometer. The column concentration corresponding to the minimum of Equation (9) is the inversion result.

[0071] Step C: Use a geometric method to locate the cross-monitoring area and stratify it by elevation angle to obtain the monitoring area information divided by a three-dimensional grid. The stratification is because when measuring at a long distance, each layer of the monitoring area can be considered an approximately parallel layer, and there will be no mutual influence between layers during subsequent reconstruction.

[0072] In the embodiment of the present invention, as Figure 2(b) and 2(c) , the specific steps of Step C include:

[0073] Step C1: As shown in Figure 2(b) and combined with the calculation results in Step A2, form a triangle with the azimuth angles corresponding to the measurement field center and the field edge of each FTIR telemetry scanning imaging system, calculate the sizes of each included angle of the triangle, and calculate the distance from each cross-boundary point to one of the scanning systems. After obtaining this distance, calculate the longitude and latitude positions of each corner point of the cross area through the longitude and latitude position of the scanning system and the distance from the scanning system to the intersection point. The expression for calculating the longitude and latitude (LongitudeP, LatitudeP) of the other end point knowing one longitude and latitude position, azimuth, and distance is as follows:

[0074]

[0075]

[0076] In the formula, Length is the distance from the scanning imaging system to the intersection point, Azimuth is the azimuth angle of the unknown point relative to the known point, and R is the radius of the earth.

[0077] Step C2: As shown in the scanning process when two single FTIR telemetry scanning imaging systems work in Figure 2(c), especially the scanning azimuth angle and pitch angle of a single pixel. Respectively use the distance from each FTIR telemetry scanning imaging system to the monitoring area and its maximum pitch angle difference, and use methods such as trigonometric functions to calculate the scanned height of the monitoring area, and stratify according to the scanned height of the monitoring area and the field of view angle size of a single pixel of each FTIR telemetry scanning imaging system to obtain the divided 3-D grid, and each spatial pixel contains (x, y, z) position coordinates.

[0078] Step D: Calculate the path length coefficient sparse matrix for each layer, and reconstruct the gas cloud distribution of each layer using the Simultaneous Algebraic Reconstruction Technique (SART).

[0079] In the embodiment of this specification, the step D includes:

[0080] Step D1: According to the 3-D grid divided in step C2, establish a rectangular coordinate system in the monitoring area. As shown in Fig. 2(b), for each optical path, calculate the path length sparse matrix M of each layer based on the azimuth angles pointed by the respective pixels measured by the scanning system i (i = 1, 2, …, Z), where Z is the number of divided layers and i is the layer number. The following is the derivation process of the path length coefficient sparse matrix M i (i = 1, 2, …, Z):

[0081] Taking the center of the monitoring area as the reference point, the 3-D grid expands outward until it covers the cross-monitoring area. Convert the monitoring height according to the measured elevation angle and cross distance. First, consider vertical stratification to obtain the number of layers Z. The single-layer reconstruction process is as follows: Without considering the single-layer height, the double FTIR telemetry scanning imaging system scans the overlapping area to be measured and performs two-dimensional discretization, dividing it into N plane unit grids, and assuming that the gas concentration distribution within each unit grid is uniform and consistent. After discretization, the integral of the gas concentration along the path of the i-th optical path passing through the infrared field axis of the FTIR telemetry scanning imaging system in the measured plane is expressed by the following formula:

[0082]

[0083] In the formula, l ij is the optical path length of the i-th optical path passing through the j-th unit grid, and c j is the gas concentration within the j-th unit grid.

[0084] During the measurement process, it is impossible to ensure that the pitch angles of the double FTIR telemetry scanning imaging system within the same layer are consistent, resulting in inconsistent inclined optical path lengths within the same layer. In addition, the non-horizontal placement of the FTIR telemetry scanning imaging system will also cause pitch angle deviations when the same scanning system scans within the same layer. Therefore, it is necessary to correct the optical path length in the single-layer unit three-dimensional grid, and formula (12) can be rewritten as:

[0085]

[0086] In the above formula, θ i is the elevation angle of the i-th optical path relative to the ground.

[0087] Within the same layer, calculate the path length of each optical path passing through each three-dimensional unit for each optical path scanned by the double FTIR telemetry scanning imaging system line by line to obtain the path coefficient vector of each optical path, and rewrite formula (13) into matrix form as follows:

[0088]

[0089] In Equation (14), p is the total number of light rays, and N is the total number of single-layer grids. Equation (14) is transformed into:

[0090] LC = Q (15)

[0091] L is the layer path length coefficient sparse matrix M i (i = 1, 2, …, Z); C is the concentration column vector.

[0092] Step D2: Use the simultaneous algebraic reconstruction technique to reconstruct the concentration distribution of each layer. The amount of data obtained by the FTIR telemetry scanning imaging system is limited. To solve the concentration column vector C, the relationship between the total number of light rays p and N needs to be considered. In most cases, p < N. At this time, Equation (11) evolves into the solution problem of a sparse underdetermined linear equation system. However, the least squares method and singular value decomposition, etc., have unstable solution results for this problem. Therefore, consider using the simultaneous algebraic reconstruction technique SART of the simultaneous algebraic iterative algorithm. This algorithm combines the advantages of the ART and SIRT algorithms, has a fast convergence speed, strong anti-interference ability, good robustness, reduces the number of iterations of ART, reduces the computational amount of the SIRT algorithm, and can obtain higher reconstruction accuracy. The iterative process is as follows:

[0093]

[0094] In the formula, k is the number of iterations, and α is the relaxation factor. The C vector is arranged in the order of reconstruction as a single-layer concentration distribution matrix, and then the reconstructed concentration distribution matrices of each layer are recombined to obtain a gas cloud concentration cube data.

[0095] In the embodiment of the present invention, the specific steps of step E include:

[0096] Step E: Arrange the concentration distribution of each layer according to the four-dimensional coordinates (longitude, latitude, altitude, concentration), and use the longitude and latitude and concentration as the input of the concentration weight center method to calculate the gas cloud center. Take this center as the leakage source, and finally use KML markers to display the overall gas cloud through Google earth. The gas cloud center formula is as follows:

[0097]

[0098]

[0099] In the formula, N is the number of single-layer three-dimensional grids, Z is the number of divided layers, LongtitudeC is the longitude of the gas cloud center, and LatitudeC is the latitude of the gas cloud center. Finally, the concentration of each unit is mapped through the false color HSI space and displayed using 3-D map software, specifically asFigure 5 as shown

[0100] It can be seen that the method of the present invention provides a high-quality 3-D reconstructed gas cloud for the quantitative analysis and location analysis of 3-D gas clouds, which is applicable to the 3-D visualization of polluted gas clouds in the field of FTIR telemetry scanning imaging. The layout of the dual FTIR telemetry scanning imaging system improves the 3-D gas cloud reconstruction accuracy; in the specific measurement process, a nine-axis gyroscope sensor is used to measure the attitude of the scanning system, and the triangulation method is used to determine the monitoring intersection area; the scanning height of the intersection monitoring area is used for layering to reduce the mutual influence between layers, 3-D grids are divided, and a three-dimensional coordinate system is established; based on the pointing information of each optical path, the sparse matrix of the optical path length coefficients of each layer is calculated, and the layering, as an innovative method, reduces the difficulty of establishing the optical path length sparse matrix; the SART reconstruction technology with fast convergence speed, strong anti-interference ability and good robustness is used to reconstruct the concentration distribution of each layer; the concentration weight center method is selected to calculate the concentration center of the gas cloud, so as to further approximate the leakage source.

[0101] The whole scheme of the present invention from the layout of the dual scanning system, geometric measurement, spectral measurement, layered reconstruction, concentration center, and false color display is innovative as a whole. In addition, the present invention solves the problem that a single scanning system cannot locate multi-point leaks, solves the problem of gas cloud quantification and the problem of concentration unit conversion (from ppm·m to ppm), and is innovative in the 3-D imaging detection of gas leaks.

[0102] The embodiments described above are only descriptions of the preferred embodiments of the present invention. The preferred embodiments do not elaborate on all details and do not limit the invention to the specific embodiments described. Without departing from the design spirit of the present invention, various deformations and improvements made by those of ordinary skill in the art to the technical solutions of the present invention shall fall within the protection scope determined by the claims of the present invention.

Claims

1. A 3-D reconstruction method for a leaking gas cloud based on a dual FTIR telemetry scanning imaging system, characterized in that, It includes the following steps: Step A: Select a monitoring area with gas leakage, deploy two FTIR telemetry scanning imaging systems at different orientations in the monitoring area, and obtain the GPS positions of each FTIR telemetry scanning imaging system; Step B: During the normal monitoring process, each FTIR telemetry scanning imaging system measures the 2-D projection column concentration image of the gas cloud and the pointing information of each pixel regarding azimuth and elevation angle; Step C: Use geometric methods to locate the cross-monitoring area and stratify it by elevation angle to obtain the monitoring area information divided by a three-dimensional cubic grid, including: Step C1: Based on the geometric parameters between the two FTIR telemetry scanning imaging systems, combine with the azimuth angle of the center of the field of view during measurement to construct a triangle to calculate the longitude and latitude of the center position of the monitoring area; combine with the azimuth angle of the edge of the field of view during measurement to construct a triangle to calculate the longitude and latitude of the boundary position of the cross-monitoring area; Step C2: Use the elevation angles of the upper and lower boundaries of the scanning field of view to construct a triangle to calculate the scanned height of the monitoring area; In the above Step C1 and C2, divide the boundary of the monitoring area, and perform 3-D grid division within the area according to the field of view size, and cover the monitoring area; Step D: Calculate the path length coefficient sparse matrix of each layer, and use the joint algebraic reconstruction algorithm to reconstruct the gas cloud distribution of each layer, including: Step D1: (1) Without considering the elevation angle, calculate the horizontal projection path length coefficient sparse matrix M0; (2) Considering the elevation angle, it is corrected by the horizontal projection layer travel length coefficient sparse matrix M0 to calculate the layer travel length coefficient sparse matrix M of each layer i , i = 1, 2, …, Z, where Z is the number of divided layers and i is the layer number; Step D2: Use the joint algebraic reconstruction algorithm to reconstruct the concentration distribution of each layer, and recombine the reconstructed concentration distribution matrices of each layer to obtain a gas cloud concentration cube data; Step E: Combine the gas cloud distributions of each layer into a 3-D gas cloud, calculate the center position of the gas cloud by the concentration weighted center method, and display it by combining false color HSI space mapping with a 3-D map.

2. The 3-D reconstruction method for a leaking gas cloud based on a dual FTIR telemetry scanning imaging system according to claim 1, characterized in that: The specific content of the above Step A includes: Step A1: Measure the azimuth angles of the two FTIR telemetry scanning imaging systems relative to the center of the monitoring area, so that the included angle between the two azimuth lines is approximately perpendicular; Step A2: Use the longitude and latitude of the deployment positions of the two FTIR telemetry scanning imaging systems as inputs, calculate the distance between the two points and calculate the azimuth angle of one FTIR telemetry scanning imaging system relative to the other.

3. The 3-D reconstruction method for a leaking gas cloud based on a dual FTIR telemetry scanning imaging system according to claim 2, characterized in that: The above Step B includes: Step B1: During the acquisition process of each FTIR telemetry scanning imaging system, it scans from left to right in an S-shaped pattern row by row. During the acquisition process, record the azimuth angle, pitch angle, and interferogram of each pixel, where the azimuth angle and pitch angle are measured simultaneously by a nine-axis gyroscope sensor; use the radiometric calibration method to convert relative radiation into absolute radiance to obtain a hyperspectral data cube with spatial and spectral information; Step B2: Invert the transmittance spectrum of each pixel from the spectrum in Step B1 through a simple three-layer radiative transfer model, and perform qualitative analysis on the spectrum through a gas component identification algorithm. Use the nonlinear least squares algorithm to calculate the gas column concentration image corresponding to the spectrum of each pixel with the standard spectrum of the identified spectrum. This image is the 2-D projection image of the 3-D gas cloud.

4. The 3-D reconstruction method for a leaking gas cloud based on a dual FTIR telemetry scanning imaging system according to claim 1, characterized in that: In the above Step E, use the longitude, latitude, and gas cloud concentration as inputs for the concentration weighted center method to calculate the center of the gas cloud concentration and approximate the leakage source.

5. The 3-D reconstruction method for a leaking gas cloud based on a dual FTIR telemetry scanning imaging system according to any one of claims 1 to 4, characterized in that: Applicable to 3-D visualization, quantification, and localization of leaking gas clouds.

Images