A small spectral detection gas cloud imaging device based on a galvanometer and a cassette telescope

Abstract

The application discloses a small-sized spectral detection gas cloud imaging device based on a galvanometer and a cassette telescope and relates to the technical field of spectral detection devices. The small-sized spectral detection gas cloud imaging device based on the galvanometer and the cassette telescope comprises an identification scanning module, a two-dimensional tracking galvanometer and an imaging module. The identification scanning module comprises a cassette telescope and a two-dimensional scanning galvanometer. The imaging module comprises a Fourier interference module and a high-speed photoelectric point detector. A diaphragm is arranged between the two-dimensional tracking galvanometer and the imaging module. The combination of the cassette telescope and the two-dimensional scanning galvanometer realizes high-precision positioning of a to-be-measured scene and spectral data collection, thereby avoiding the problem that, in the prior art, spectral data is inconsistent or lost due to uncertain target positions, and thus ensuring that spectral data of each target position is effectively collected and transmitted.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of spectral detection devices, in particular to a small spectral detection gas cloud imaging device based on a galvanometer and a cassette telescope. BACKGROUND

[0002] Spectral detection gas cloud imaging technology is a perfect combination of spectral technology and imaging technology, and has both spectral and spatial resolution capabilities. Spectral detection gas cloud imaging is more conducive to the identification, capture and tracking of gas targets, and gas cloud imaging technology is widely used in remote sensing, environmental monitoring and other fields. According to the light splitting method, the gas cloud imaging technology can be divided into two categories: interference type and dispersion type. Traditional dispersion type spectral imaging technology usually uses prisms and gratings as light splitting elements, and the technology is relatively mature, and spectral imaging is realized by scanning. However, the traditional grating spectral imaging uses a grating and a grating of a surface array detector, and the scanning system is relatively large and slow.

[0003] The limitations of the prior art at least include the following problems. First, in the existing gas cloud imaging equipment, a fixed observation method and a traditional scanning method are usually used, which can easily lead to difficulty in accurately tracking the target area in real time and obtaining spectral data. Its limitations are that when the target area changes dynamically, the response capability of the traditional equipment is weak, and it is difficult to accurately capture the spectral data of each moving position point. Secondly, the existing technology has efficiency problems in spectral data transmission and processing. Generally, the gas cloud imaging device needs to rely on multiple components for data collection, transmission and analysis. Such a complex multi-level data flow can easily cause information loss or delay, thereby affecting real-time analysis and imaging quality. Especially in the face of large-scale and complex weather environments, the existing equipment lacks efficient coordination and data synchronization capability, making it difficult to ensure the generation of high-quality spectral images. In addition, the existing spectral gas cloud imaging equipment has low precision and sensitivity when detecting irregular targets or complex background environments, and it is difficult to accurately identify and locate each specific target. This limitation can easily lead to blurred or erroneous gas cloud imaging images, thereby affecting the accurate evaluation of key parameters such as gas cloud composition and concentration. SUMMARY

[0004] In view of the deficiencies of the prior art, the present application provides a small-sized spectral detection gas cloud imaging device based on a galvanometer and a cassette telescope, which solves the problem that in the existing gas cloud imaging equipment, a fixed observation mode and a traditional scanning method are usually adopted, which easily leads to difficulty in accurately tracking a target area in real time and acquiring spectral data, and the limitation is that when the target area changes dynamically, the response capability of the traditional equipment is weak, and it is difficult to accurately capture the spectral data of each moving position point, secondly, the existing technology has efficiency problems in spectral data transmission and processing, generally, the gas cloud imaging device needs to rely on multiple components for data collection, transmission and analysis, and such a complex multi-level data flow is easy to cause information loss or delay, thereby affecting real-time analysis and imaging quality, especially when facing a large range and complex weather environment, the existing equipment lacks efficient cooperation and data synchronization capability, and it is difficult to ensure the generation of high-quality spectral images, in addition, the existing spectral gas cloud imaging equipment has low precision and sensitivity when detecting irregular targets or complex background environments, and it is difficult to accurately identify and locate each specific target, and such limitation is easy to cause the blurring or error of the gas cloud imaging image, thereby affecting the accurate evaluation of the key parameters such as the composition and concentration of the gas cloud.

[0005] To achieve the above object, the present application is implemented by the following technical scheme: a small-sized spectral detection gas cloud imaging device based on a galvanometer and a cassette telescope, comprising: an identification scanning module, a two-dimensional tracking galvanometer and an imaging module, the identification scanning module comprises a cassette telescope and a two-dimensional scanning galvanometer, the imaging module comprises a Fourier interference module and a high-speed photoelectric point detector, and a diaphragm is arranged between the two-dimensional tracking galvanometer and the imaging module; it is assembled as: the identification scanning module performs trajectory identification scanning processing on the to-be-measured scene based on a preset moving trajectory, obtains measured target spectral data of a plurality of moving position points, and simultaneously adjusts the position of the two-dimensional tracking galvanometer, so that the two-dimensional tracking galvanometer receives the measured target spectral data of each moving position point, and transmits the received measured target spectral data of each moving position point to the Fourier interference module through the diaphragm in a perpendicular manner for interference processing, and inputs the interference processing result to the high-speed photoelectric point detector for inversion analysis, to obtain a measured target (leakage gas) concentration curve graph.

[0006] Further, the measured target spectral data comprises a reflection intensity value of the measured target at each wavelength, and the measured target comprehensive spectral image comprises a comprehensive reflection intensity value of the measured target at each wavelength.

[0007] Further, the specific steps of the trajectory recognition scanning module for trajectory recognition scanning of the to-be-measured scene based on the preset moving trajectory are as follows: at each moving position point, the to-be-measured scene image data is acquired by the cassette telescope, and the position information of the measured target is analyzed and determined, wherein the to-be-measured scene image data includes the pixel value and two-dimensional pixel coordinates of each to-be-measured pixel point in the to-be-measured scene image; after the position information of the measured target is determined, the measured target is scanned by the two-dimensional scanning galvanometer to obtain the measured target spectrum data of each moving position point.

[0008] Further, the specific steps of acquiring the to-be-measured scene image data by the cassette telescope and analyzing and determining the position information of the measured target are as follows: the to-be-measured scene image is divided into a plurality of image regions, and each image region data includes a plurality of to-be-measured pixel points; for each image region, the pixel value of each to-be-measured pixel point is analyzed and determined to obtain the pixel mean value and the pixel standard deviation value of each image region; the pixel mean value and the pixel standard deviation value of each image region are analyzed and determined to obtain the pixel threshold value of each image region; the pixel threshold value of each image region and the pixel value of each to-be-measured pixel point are analyzed and determined to obtain a plurality of measured target pixel points in the to-be-measured scene image; the pixel value and two-dimensional pixel coordinates of the plurality of measured target pixel points in the to-be-measured scene image are analyzed and determined to obtain the initial center pixel coordinates of the measured target in the to-be-measured scene image; the initial center pixel coordinates of the measured target in the to-be-measured scene image are subjected to spatial conversion processing to obtain the center three-dimensional space coordinates of the measured target in the to-be-measured scene image, which are marked as the position information of the measured target.

[0009] Further, the specific formulas for calculating the pixel mean value, the pixel standard deviation value, the pixel threshold value of each image region, and the initial center pixel coordinates of the measured target in the to-be-measured scene image are as follows: wherein, XsJ u XsJ ut XsJ u XsJ u XsJ u XsJ i XsJ ix' is the initial center two-dimensional pixel horizontal coordinate of the measured target in the to-be-tested scene image, y' is the initial center two-dimensional pixel vertical coordinate of the measured target in the to-be-tested scene image, y" is the center three-dimensional space vertical coordinate of the measured target in the to-be-tested scene image, y'" is the center two-dimensional vertical coordinate of the to-be-tested scene image, f is the horizontal focal length value of the to-be-tested scene image, f is the vertical focal length value of the to-be-tested scene image, and JLz is the distance value of the measured target in the to-be-tested scene image from the card type telescope. i x' is the initial center two-dimensional pixel horizontal coordinate of the measured target in the to-be-tested scene image, y' is the initial center two-dimensional pixel vertical coordinate of the measured target in the to-be-tested scene image, y" is the center three-dimensional space vertical coordinate of the measured target in the to-be-tested scene image, y'" is the center two-dimensional vertical coordinate of the to-be-tested scene image, f is the horizontal focal length value of the to-be-tested scene image, f is the vertical focal length value of the to-be-tested scene image, and JLz is the distance value of the measured target in the to-be-tested scene image from the card type telescope.

[0010] Further, the specific steps of obtaining the center three-dimensional space coordinate of the measured target in the to-be-tested scene image are as follows: obtaining the center coordinate of the to-be-tested scene image, the horizontal focal length value of the to-be-tested scene image, the vertical focal length value, and the distance value of the measured target in the to-be-tested scene image from the card type telescope, and comprehensively analyzing the initial center pixel coordinate of the measured target in the to-be-tested scene image to obtain the center three-dimensional space coordinate of the measured target in the to-be-tested scene image; wherein the specific formula for calculating the center three-dimensional space coordinate of the measured target in the to-be-tested scene image is as follows: x' is the initial center two-dimensional pixel horizontal coordinate of the measured target in the to-be-tested scene image, y' is the initial center two-dimensional pixel vertical coordinate of the measured target in the to-be-tested scene image, y" is the center three-dimensional space vertical coordinate of the measured target in the to-be-tested scene image, y'" is the center two-dimensional vertical coordinate of the to-be-tested scene image, f is the horizontal focal length value of the to-be-tested scene image, f is the vertical focal length value of the to-be-tested scene image, and JLz is the distance value of the measured target in the to-be-tested scene image from the card type telescope. x x' is the initial center two-dimensional pixel horizontal coordinate of the measured target in the to-be-tested scene image, y' is the initial center two-dimensional pixel vertical coordinate of the measured target in the to-be-tested scene image, y" is the center three-dimensional space vertical coordinate of the measured target in the to-be-tested scene image, y'" is the center two-dimensional vertical coordinate of the to-be-tested scene image, f is the horizontal focal length value of the to-be-tested scene image, f is the vertical focal length value of the to-be-tested scene image, and JLz is the distance value of the measured target in the to-be-tested scene image from the card type telescope. y x' is the initial center two-dimensional pixel horizontal coordinate of the measured target in the to-be-tested scene image, y' is the initial center two-dimensional pixel vertical coordinate of the measured target in the to-be-tested scene image, y" is the center three-dimensional space vertical coordinate of the measured target in the to-be-tested scene image, y'" is the center two-dimensional vertical coordinate of the to-be-tested scene image, f is the horizontal focal length value of the to-be-tested scene image, f is the vertical focal length value of the to-be-tested scene image, and JLz is the distance value of the measured target in the to-be-tested scene image from the card type telescope.

[0011] Further, the specific steps of obtaining the center three-dimensional space coordinate of the measured target in the to-be-tested scene image are as follows: obtaining the center coordinate of the to-be-tested scene image, the horizontal focal length value of the to-be-tested scene image, the vertical focal length value, and the distance value of the measured target in the to-be-tested scene image from the card type telescope, and comprehensively analyzing the initial center pixel coordinate of the measured target in the to-be-tested scene image to obtain the center three-dimensional space coordinate of the measured target in the to-be-tested scene image; wherein the specific formula for calculating the center three-dimensional space coordinate of the measured target in the to-be-tested scene image is as follows:

[0012] Further, the specific steps of calculating the three-dimensional position adjustment value and the adjusted three-dimensional position coordinate of the two-dimensional tracking galvanometer are as follows: Wherein, the Δx is horizontal direction adjustment value of two-dimensional tracking galvanometer, X is three-dimensional position horizontal coordinate of two-dimensional scanning galvanometer, X' is initial three-dimensional position horizontal coordinate of two-dimensional tracking galvanometer, ξ1 is horizontal adjustment coefficient stored in database, the Δy is vertical direction adjustment value of two-dimensional tracking galvanometer, Y is three-dimensional position vertical coordinate of two-dimensional scanning galvanometer, Y' is initial three-dimensional position vertical coordinate of two-dimensional tracking galvanometer, ξ2 is vertical adjustment coefficient stored in database, the Δz is depth direction adjustment value of two-dimensional tracking galvanometer, Z is three-dimensional position depth coordinate of two-dimensional scanning galvanometer, Z' is initial three-dimensional position depth coordinate of two-dimensional tracking galvanometer, ξ3 is depth adjustment coefficient stored in database, X'' is adjusted three-dimensional position horizontal coordinate of two-dimensional tracking galvanometer, Y'' is adjusted three-dimensional position vertical coordinate of two-dimensional tracking galvanometer, Z'' is adjusted three-dimensional position depth coordinate of two-dimensional tracking galvanometer.

[0013] Further, the specific steps of obtaining the concentration curve of the measured target are as follows: in the Fourier interference module, for each moving position point, based on the reflection intensity value of the measured target at each wavelength, the weighted coefficient of each wavelength of each moving position point is analyzed; the reflection intensity value of the measured target at each wavelength of each moving position point is comprehensively analyzed by combining the weighted coefficient of each wavelength of each moving position point respectively, to obtain a comprehensive spectral image of the measured target, that is, the comprehensive reflection intensity value of the measured target at each wavelength; the comprehensive reflection intensity value of the measured target at each wavelength is input into the Fourier interference module for interference processing to obtain interference fringe information of the measured target, and Fourier transform analysis processing is performed to obtain the frequency spectrum information of the measured target; the frequency spectrum information of the measured target is input into the high-speed photoelectric point detector for inversion analysis processing to obtain the concentration curve of the measured target (leakage gas).

[0014] Further, the specific formula for calculating the comprehensive reflection intensity value of the measured target at each wavelength is as follows: Wherein, ZfS (λ) is the comprehensive reflection intensity value of the measured target at wavelength λ, Fs (λ) is the reflection intensity value of the measured target at wavelength λ of the rth moving position point, ω (λ) is the weighted coefficient of wavelength λ of the rth moving position point, r=1, 2, 3, …, r0, r0 is the number of moving position points. r (λ) for the reflection intensity value of the measured target at wavelength λ of the rth moving position point, ω r (λ) for the reflection intensity value of the measured target at wavelength λ of the rth moving position point, ω

[0015] The present application has the following beneficial effects:

[0016] (1), the small spectral detection gas cloud imaging device based on galvanometer and cassette telescope, through the combination of cassette telescope and two-dimensional scanning galvanometer, high-precision positioning and spectral data acquisition of the scene to be measured are realized, specifically, first, the image data of the scene to be measured is obtained through the cassette telescope, and the target position in each image area is determined by using the mean value, standard deviation and other analysis of pixel value, then, the two-dimensional scanning galvanometer is used to scan the measured target accurately, and the spectral data of each moving position point is obtained, thereby avoiding the problem of inconsistent or missing spectral data caused by uncertain target position in the traditional technology, and further ensuring that the spectral data of each target position is effectively collected and transmitted.

[0017] (2), the small spectral detection gas cloud imaging device based on galvanometer and cassette telescope, after target positioning, the target is tracked in real time by the two-dimensional tracking galvanometer, so that the device can accurately adjust the position of the target even if the target is moving, and the spectral information of the target can be continuously monitored, by synchronously adjusting the three-dimensional position coordinates of the two-dimensional tracking galvanometer, the accuracy of spectral data transmission can be ensured all the time, this real-time adjustment and accurate control solves the information deviation problem caused by spectral data transmission error in the traditional spectral detection device, and effectively improves the stability of the system and the reliability of data collection.

[0018] (3), the small spectral detection gas cloud imaging device based on galvanometer and cassette telescope, by combining the Fourier interference module with the high-speed photoelectric point detector, the sensitivity and accuracy of gas cloud imaging are significantly improved by using the technical advantages of interference processing and inversion analysis, the Fourier interference module combines two infrared beams with different optical path differences by the principle of light interference, produces interference phenomenon, and converts the time domain signal represented by infrared spectrum to frequency domain by Fourier transform, obtains the frequency distribution of spectrum, and analyzes and inverts the gas concentration curve information, the introduction of the diaphragm effectively adjusts and controls the passing path of light, ensures the transmission quality and stability of spectral data, the setting of the diaphragm not only optimizes the data collection process, but also reduces the interference of background light, so that the Fourier interference module can focus on the spectral characteristics of the target object, thereby improving the signal-to-noise ratio of the whole system and ensuring the accuracy of the imaging result.

[0019] Of course, implementing any product of the present application does not necessarily need to achieve all the advantages described above at the same time. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 The structure diagram of the small spectral detection gas cloud imaging device based on galvanometer and cassette telescope.

[0021] Figure 2A specific step flow chart for obtaining spectral data of a measured target at a plurality of moving position points in a small spectral detection gas cloud imaging device based on a galvanometer and a cassette telescope.

[0022] In the figure: 1, two-dimensional scanning galvanometer; 2, two-dimensional tracking galvanometer; 3, cassette telescope; 4, diaphragm; 5, photoelectric point detector. DETAILED DESCRIPTION

[0023] The embodiment of the present application solves the problem that in the existing gas cloud imaging equipment, a fixed observation mode and a traditional scanning method are usually used, which can easily lead to difficulty in accurately tracking and acquiring spectral data of a target area in real time, and the limitation is that when the target area changes dynamically, the response capability of the traditional equipment is weak, and it is difficult to accurately capture the spectral data of each moving position point. Secondly, the existing technology has efficiency problems in spectral data transmission and processing. Generally, the gas cloud imaging device needs to rely on multiple components for data collection, transmission and analysis. Such complex multi-level data flow can easily cause information loss or delay, thereby affecting real-time analysis and imaging quality. Especially in the face of large-scale and complex weather environment, the existing equipment lacks efficient cooperation and data synchronization capability, and it is difficult to ensure the generation of high-quality spectral images. In addition, the existing spectral gas cloud imaging equipment has low precision and sensitivity when detecting irregular targets or complex background environments, and it is difficult to accurately identify and locate each specific target. Such limitations can easily lead to blurred or erroneous gas cloud imaging images, thereby affecting the accurate evaluation of key parameters such as gas cloud composition and concentration.

[0024] The general idea of the problem in the embodiment of the present application is as follows:

[0025] Firstly, the image data of the scene to be measured is obtained by the cassette telescope, and the specific position of the measured target is determined by analyzing the values and standard deviations of each pixel point in the image. Then, the target is scanned by the two-dimensional scanning galvanometer to obtain the spectral data of each moving position point. After obtaining the target position data, the position is dynamically adjusted by the two-dimensional tracking galvanometer to ensure accurate tracking of each target point and real-time transmission of data. At this time, the spectral data transmission is controlled by the diaphragm to ensure that the data is not disturbed by the outside world and accurately transmitted to the high-speed photoelectric point detector. Finally, in the imaging module, the spectral data of each moving position point is analyzed and interfered and inverted according to the reflection intensity value under different wavelengths and combined with the weighting coefficient, and the concentration curve of the measured target (leakage gas) is generated to provide accurate data for subsequent analysis.

[0026] Please refer to Figure 1The embodiment of the present application provides a technical scheme: a small-sized spectral detection gas cloud imaging device based on a galvanometer and a cassette telescope, comprising: an identification scanning module, a two-dimensional tracking galvanometer 2 and a high-speed photoelectric point detector 5, wherein the identification scanning module comprises a cassette telescope 3 and a two-dimensional scanning galvanometer 1, and a diaphragm 4 is arranged between the two-dimensional tracking galvanometer 2 and the high-speed photoelectric point detector 5; and the identification scanning module is assembled as follows: based on a preset movement track, the identification scanning module performs track identification scanning processing on a to-be-detected scene to obtain measured target spectral data of a plurality of movement position points, and simultaneously performs position adjustment on the two-dimensional tracking galvanometer 2, so that the two-dimensional tracking galvanometer 2 receives the measured target spectral data of each movement position point, and the received measured target spectral data of each movement position point is transmitted to the high-speed photoelectric point detector 5 through the diaphragm 4 in a vertical manner for comprehensive analysis, so as to obtain a measured target comprehensive spectral image.

[0027] The embodiment of the present application provides a technical scheme: a small-sized spectral detection gas cloud imaging device based on a galvanometer and a cassette telescope, comprising: an identification scanning module, a two-dimensional tracking galvanometer 2 and a high-speed photoelectric point detector 5, wherein the identification scanning module comprises a cassette telescope 3 and a two-dimensional scanning galvanometer 1, and a diaphragm 4 is arranged between the two-dimensional tracking galvanometer 2 and the high-speed photoelectric point detector 5; and the identification scanning module is assembled as follows: based on a preset movement track, the identification scanning module performs track identification scanning processing on a to-be-detected scene to obtain measured target spectral data of a plurality of movement position points, and simultaneously performs position adjustment on the two-dimensional tracking galvanometer 2, so that the two-dimensional tracking galvanometer 2 receives the measured target spectral data of each movement position point, and the received measured target spectral data of each movement position point is transmitted to the high-speed photoelectric point detector 5 through the diaphragm 4 in a vertical manner for comprehensive analysis, so as to obtain a measured target comprehensive spectral image.

[0028] In the embodiment, the preset movement track is a spherical movement track, the focal length of the cassette telescope is equal to the radius of the sphere, the focal point and the center of the sphere coincide, and the two-dimensional tracking galvanometer 2 is located at the center of the sphere.

[0029] The measured target spectral data comprises a reflection intensity value of the measured target at each wavelength.

[0030] The center of the two-dimensional tracking galvanometer 2 coincides with the secondary focal point of the cassette telescope 3; target light is detected by the high-speed photoelectric point detector 5 after sequentially passing through the primary and secondary focal points of the cassette telescope 3 and the two-dimensional scanning galvanometer 1, is two-dimensionally scanned by the two-dimensional scanning galvanometer 1, is deflected by the two-dimensional tracking galvanometer 2, and is combined with the high-speed photoelectric point detector 5 to realize spectral gas cloud imaging.

[0031] The two-dimensional scanning galvanometer 1 can realize rotation of the X and Y axes (achieved by a rotating motor); the two-dimensional tracking galvanometer 2 can realize compensation of the rotation angle of the two-dimensional scanning galvanometer 2 (achieved by a rotating motor), so that the light paths of different fields of view are reflected along the same angle to the inside of the high-speed photoelectric point detector 5 through rotation of the X and Y axes of the two-dimensional tracking galvanometer 2.

[0032] The diaphragm 4 is used to prevent the influence of non-required diffraction wavelengths on spectral scanning, and to enhance spectral resolution and spectral measurement accuracy.

[0033] Specifically, as shown in Figure 2 The specific steps of the identification scanning module performing trajectory identification scanning processing on the to-be-measured scene based on a preset moving trajectory to obtain measured target spectrum data of a plurality of moving position points are as follows: at each moving position point, the to-be-measured scene image data is acquired by the spotting scope 3, and the position information of the measured target is determined by analysis, the to-be-measured scene image data including the pixel value and two-dimensional pixel coordinates of each to-be-measured pixel point in the to-be-measured scene image; after the position information of the measured target is determined, the measured target is scanned by the two-dimensional scanning galvanometer 1 to obtain measured target spectrum data of each moving position point.

[0034] In this embodiment, the image data of the scene to be measured is obtained by the camera telescope, and the pixel value and two-dimensional pixel coordinates of each pixel to be measured are analyzed, which can realize accurate positioning of the measured target. In traditional spectral imaging, the accurate positioning of the target is usually affected by factors such as target motion and light source change. However, through this comprehensive analysis method based on pixel value and coordinates, the target position can be determined more stably and accurately, especially in dynamic scenes, which can ensure the correct collection of spectral data at different moving positions of the target, laying a solid foundation for subsequent spectral image analysis. Traditional spectral detection devices may miss some effective data due to inaccurate scanning accuracy or target position judgment. By combining the image data processing of the camera telescope and the accurate control of the two-dimensional scanning galvanometer, the spectral data of each moving position point can be stably and continuously collected. Especially in the case of target displacement, the camera telescope can quickly analyze and determine the position of the target, so that the scanning galvanometer can adjust the scanning angle at any time to ensure that the spectral data of each position point can be accurately collected. This continuity ensures the integrity of data collection and avoids data loss or repeated collection. Using the image data and pixel coordinate analysis provided by the camera telescope can more efficiently guide the scanning process of the two-dimensional scanning galvanometer, reduce unnecessary scanning areas, and improve the accuracy and efficiency of scanning. The target position of each scan is analyzed accurately to ensure that the scanning process will not waste time or resources in irrelevant areas, which greatly improves the efficiency of the overall data collection. This is particularly important for gas cloud imaging or dynamic target detection that requires fast real-time response, avoiding the low-efficiency scanning and error accumulation problems that may occur in traditional methods. After the target position is determined, the two-dimensional scanning galvanometer is used to accurately scan the target, so that the spectral data of each moving position point can be completely obtained. This combination of accurate positioning and scanning ensures the consistency and accuracy of the spectral data of the target at different positions. In traditional methods, if the target position changes greatly or the scanning process fails to accurately align the target, it may cause errors in the spectral data. However, through this method, the target position and scanning action can be accurately controlled, greatly reducing such errors and ensuring the high quality of the spectral data.

[0035] Specifically, the specific steps of acquiring the image data of the scene to be measured by the card telescope 3 and analyzing and determining the position information of the measured target are as follows: the image to be measured is divided into a plurality of image regions, and each image region data includes a plurality of to-be-measured pixel points; for each image region, the pixel values of each to-be-measured pixel point are analyzed respectively to obtain the pixel mean value and the pixel standard deviation value of each image region; the pixel mean value and the pixel standard deviation value of each image region are analyzed to obtain the pixel threshold value of each image region; the pixel threshold value of each image region and the pixel value of each to-be-measured pixel point are analyzed respectively to obtain a plurality of measured target pixel points in the image to be measured, and the specific steps are as follows: the pixel value of each to-be-measured pixel point in each image region is compared with the corresponding pixel threshold value, and the to-be-measured pixel point with a pixel value greater than or equal to the pixel threshold value is marked as a measured target pixel point; the pixel values and two-dimensional pixel coordinates of the plurality of measured target pixel points in the image to be measured are analyzed to obtain the initial center pixel coordinates of the measured target in the image to be measured; the initial center pixel coordinates of the measured target in the image to be measured are processed by spatial conversion to obtain the center three-dimensional space coordinates of the measured target in the image to be measured, and the center three-dimensional space coordinates are marked as the position information of the measured target.

[0036] The specific formulas for calculating the pixel mean value, the pixel standard deviation value, the pixel threshold value, and the initial center pixel coordinates of the measured target in the image to be measured of each image region are as follows: wherein, XsJ u is the pixel mean value of the u-th image region, XsZ ut is the pixel value of the t-th to-be-measured pixel point of the u-th image region, XsB u is the pixel standard deviation value of the u-th image region, XyZ u is the pixel threshold value of the u-th image region, δ u is the threshold adjustment coefficient of the u-th image region, u = 1, 2, 3, …, u0, u0 is the number of image regions, t = 1, 2, 3, …, t0, t0 is the number of to-be-measured pixel points, x' is the initial center two-dimensional pixel horizontal coordinate of the measured target in the image to be measured, DxS i is the pixel value of the i-th measured target pixel point in the image to be measured, x i is the two-dimensional pixel horizontal coordinate of the i-th measured target pixel point in the image to be measured, y' is the initial center two-dimensional pixel vertical coordinate of the measured target in the image to be measured, y i is the two-dimensional pixel vertical coordinate of the i-th measured target pixel point in the image to be measured, i = 1, 2, 3, …, i0, i0 is the number of measured target pixel points.

[0037] It should be explained that the specific calculation formula of the threshold adjustment coefficient of each image region is as follows: wherein, δ u is the threshold adjustment coefficient of the u-th image region, XsB u is the pixel standard deviation value of the u-th image region, XsJ u is the pixel mean value of the u-th image region, ε is a correction constant stored in the database to prevent division by zero or to avoid problems when the brightness mean value is zero, for example, set to 0.01, u = 1, 2, 3, …, u0, u0 is the number of image regions.

[0038] In this embodiment, the image data of the scene to be measured is obtained by the card telescope, and the pixel value and two-dimensional pixel coordinates of each pixel point to be measured are analyzed, so that the accurate positioning of the measured target can be realized. In traditional spectral imaging, the accurate positioning of the target is usually affected by factors such as the movement of the target itself and the change of the light source. However, through the comprehensive analysis method based on pixel value and coordinates, the target position can be determined more stably and accurately, especially in a dynamic scene, which can ensure the correct collection of spectral data at different moving positions of the target, laying a solid foundation for subsequent spectral image analysis. The traditional spectral detection device may miss some effective data due to inaccurate scanning accuracy or target position judgment. By combining the image data processing of the card telescope and the accurate control of the two-dimensional scanning galvanometer, the spectral data of each moving position point can be stably and continuously collected, especially in the case of target displacement. The card telescope can quickly analyze and determine the position of the target, so that the scanning galvanometer can adjust the scanning angle at any time to ensure that the spectral data of each position point can be accurately collected. This continuity ensures the integrity of data collection and avoids data loss or repeated collection. The image data and pixel coordinate analysis provided by the card telescope can more efficiently guide the scanning process of the two-dimensional scanning galvanometer, reduce unnecessary scanning areas, and improve the accuracy and efficiency of scanning. The target position of each scan is analyzed accurately to ensure that the scanning process does not waste time or resources in irrelevant areas, which greatly improves the efficiency of the overall data collection. This is particularly important for gas cloud imaging or dynamic target detection that requires fast real-time response, avoiding the low-efficiency scanning and error accumulation problems that may occur in traditional methods. After the target position is determined, the two-dimensional scanning galvanometer is used to accurately scan the target, so that the spectral data of each moving position point can be completely obtained. This combination of accurate positioning and scanning ensures the consistency and accuracy of the spectral data of the target at different positions. In traditional methods, if the target position changes greatly or the scanning process fails to accurately align the target, it may lead to errors in spectral data. However, through this method, the target position and scanning action can be accurately controlled, greatly reducing such errors and ensuring the high quality of spectral data.

[0039] Specifically, the specific steps of obtaining the three-dimensional space coordinates of the center of the measured target in the to-be-measured scene image are as follows: obtaining the center coordinate of the to-be-measured scene image, the horizontal focal length value of the to-be-measured scene image, the vertical focal length value of the to-be-measured scene image, and the distance value of the measured target in the to-be-measured scene image from the card-type telescope 3, and comprehensively analyzing the initial center pixel coordinates of the measured target in the to-be-measured scene image to obtain the three-dimensional space coordinates of the center of the measured target in the to-be-measured scene image.

[0040] The specific formula for calculating the three-dimensional space coordinates of the center of the measured target in the to-be-measured scene image is as follows: Wherein, x" is the three-dimensional space horizontal coordinate of the center of the measured target in the to-be-measured scene image, x' is the initial center two-dimensional pixel horizontal coordinate of the measured target in the to-be-measured scene image, x" is the two-dimensional horizontal coordinate of the center of the to-be-measured scene image, f x is the horizontal focal length value of the to-be-measured scene image, JLz is the distance value of the measured target in the to-be-measured scene image from the card-type telescope 3, y" is the three-dimensional space vertical coordinate of the center of the measured target in the to-be-measured scene image, y' is the initial center two-dimensional pixel vertical coordinate of the measured target in the to-be-measured scene image, y" is the two-dimensional vertical coordinate of the center of the to-be-measured scene image, f y is the vertical focal length value of the to-be-measured scene image, and z" is the three-dimensional depth coordinate of the center of the measured target in the to-be-measured scene image, i.e.

[0041] In this embodiment, the three-dimensional spatial coordinates of the target are calculated by combining the initial center pixel coordinates of the target in the scene image to be measured, the focal length value, and the distance between the target and the telescope. This method converts two-dimensional image data into actual three-dimensional spatial data, which helps to accurately determine the specific position of the target. Especially in complex scenes, the target may have changes in the depth direction, and two-dimensional images cannot provide sufficient spatial information. However, through the calculation of three-dimensional coordinates, the spatial position of the target can be fully restored, greatly improving the accuracy of target positioning, especially in dynamic tracking and high-precision measurement. In this embodiment, when calculating the three-dimensional spatial coordinates of the target to be measured, the image center coordinates, horizontal and vertical focal length values, target distance from the telescope, and other parameters are considered. The combination of these parameters can effectively eliminate errors introduced by image distortion, focal length errors, or distance changes, ensuring high accuracy in target position calculation. By considering the comprehensive influence of these parameters, the reliability of the measurement results can be significantly improved, avoiding position deviations caused by environmental factors or equipment errors. This accurate three-dimensional positioning method is particularly suitable for precision measurement and real-time monitoring systems. By calculating three-dimensional spatial coordinates, the system can more accurately determine the depth position of the target (such as the front and back positions of the target), which is crucial for target scanning and tracking in complex scenes. For example, in a scene with multiple objects or target depth overlaps, relying solely on two-dimensional coordinates may result in errors, while three-dimensional coordinates can clearly determine the actual position of the target in space, helping the tracking system accurately adjust the scanning trajectory. Especially in dynamic cloud detection or fast-moving target monitoring, three-dimensional spatial coordinate calculation can update the spatial position of the target in real time, ensuring efficient scanning and tracking. Through three-dimensional spatial coordinate calculation, the system can not only handle two-dimensional changes in the plane but also handle changes in the depth direction of the target. This three-dimensional spatial positioning capability makes the system more flexible when facing different types of measurement requirements. For example, if the target distance changes or is at different physical levels (such as the difference between the foreground and background), three-dimensional spatial coordinates can reflect the relative position changes of the target in real time. In this way, the system can adaptively adjust and is not limited by environmental complexity, thereby improving measurement performance in irregular or dynamic scenes. Accurate three-dimensional spatial coordinate calculation provides reliable spatial positioning information for subsequent spectral data acquisition. The system can accurately control the movement of the scanning device (such as a galvanometer) based on the three-dimensional coordinates of the target, ensuring more accurate spectral data acquisition. Especially in tasks that require fine adjustment of direction and angle, three-dimensional coordinate calculation can provide precise target position reference for spectral data acquisition, further improving data acquisition quality and efficiency.

[0042] Specifically, the specific steps of adjusting the position of the two-dimensional tracking galvanometer 2 synchronously and in parallel to make the two-dimensional tracking galvanometer 2 receive the measured target spectrum data of each moving position point through the diaphragm 4 are as follows: for each moving position point, the three-dimensional position coordinates of the two-dimensional scanning galvanometer 1, the initial three-dimensional position coordinates of the two-dimensional tracking galvanometer 2, i.e. the three-dimensional coordinates at the last time point, are acquired in real time respectively, if it is the first moving position point, then it is the initial three-dimensional position coordinates, i.e. the three-dimensional position coordinates when not moving, and the three-dimensional position adjustment value of the two-dimensional tracking galvanometer 2 is analyzed, the three-dimensional position adjustment value including the horizontal direction adjustment value, the vertical direction adjustment value and the depth direction adjustment value; the initial three-dimensional position coordinates of the two-dimensional tracking galvanometer 2 are adjusted based on the three-dimensional position adjustment value to obtain the adjusted three-dimensional position coordinates of the two-dimensional tracking galvanometer 2.

[0043] The specific steps of calculating the three-dimensional position adjustment value and the adjusted three-dimensional position coordinates of the two-dimensional tracking galvanometer 2 are as follows: wherein Δx is the horizontal direction adjustment value of the two-dimensional tracking galvanometer 2, X is the three-dimensional position horizontal coordinate of the two-dimensional scanning galvanometer 1, X' is the initial three-dimensional position horizontal coordinate of the two-dimensional tracking galvanometer 2, ξ1 is the horizontal adjustment coefficient stored in the database, Δy is the vertical direction adjustment value of the two-dimensional tracking galvanometer 2, Y is the three-dimensional position vertical coordinate of the two-dimensional scanning galvanometer 1, Y' is the initial three-dimensional position vertical coordinate of the two-dimensional tracking galvanometer 2, ξ2 is the vertical adjustment coefficient stored in the database, Δz is the depth direction adjustment value of the two-dimensional tracking galvanometer 2, Z is the three-dimensional position depth coordinate of the two-dimensional scanning galvanometer 1, Z' is the initial three-dimensional position depth coordinate of the two-dimensional tracking galvanometer 2, ξ3 is the depth adjustment coefficient stored in the database, X" is the adjusted three-dimensional position horizontal coordinate of the two-dimensional tracking galvanometer 2, Y" is the adjusted three-dimensional position vertical coordinate of the two-dimensional tracking galvanometer 2, and Z" is the adjusted three-dimensional position depth coordinate of the two-dimensional tracking galvanometer 2.

[0044] In this embodiment, by obtaining the three-dimensional position coordinates of the two-dimensional scanning galvanometer 1 and the initial position coordinates of the two-dimensional tracking galvanometer 2, and calculating the position adjustment amount, the position of the galvanometer can be adjusted in real time, and the accurate position change of each moving position point can be dynamically adjusted to a new target position. This real-time adjustment function ensures that the galvanometer can always be aligned with the target to be measured when the target position changes, avoiding errors in spectral data acquisition caused by inaccurate device position. Especially for fast-moving or position-uncertain targets, real-time adjustment greatly improves measurement accuracy and stability. By subdividing the horizontal, vertical, and depth directions for adjustment, the system can accurately control the galvanometer in each direction in three-dimensional space. This multi-dimensional adjustment ensures that the two-dimensional tracking galvanometer 2 can accurately align with each scanning position point, avoiding data loss or deviation caused by incomplete scanning or misalignment. In spectral detection applications, accurate alignment of the target is crucial because deviation can affect the quality of spectral acquisition, thereby affecting the final analysis results. The three-dimensional position adjustment of the two-dimensional tracking galvanometer 2 ensures that it can accurately receive spectral data from each moving position point through the diaphragm. Spectral data acquisition is crucial for subsequent analysis. If the spectral acquisition position is inaccurate, it may cause inconsistency in the data, affecting the final spectral image analysis effect. By accurately adjusting the galvanometer position, the system can ensure that each target position is accurately captured, thereby improving the accuracy and consistency of the collected spectral data. In complex dynamic scenarios, targets may frequently change or be at different depth levels. Through three-dimensional position adjustment, the system can accurately track these targets, ensuring effective monitoring and data acquisition in complex environments. Whether the target is far away or close to the device, three-dimensional position adjustment can ensure that the galvanometer always adjusts to the correct position to capture the spectral information of the target. The system automatically adjusts the galvanometer position without human intervention, greatly improving the efficiency and accuracy of operation. This automated process can reduce human error and avoid errors caused by human intervention, while also speeding up the data acquisition process. In high-frequency data acquisition or multi-target scanning scenarios, automatic position adjustment ensures that the system can quickly respond and complete target scanning in a timely manner. By adjusting the position based on the adjustment coefficients stored in the database, the system can adapt to the characteristics of different devices and various measurement scenarios. The application of adjustment coefficients ensures that the system maintains stable performance under different experimental conditions, whether the scanning environment changes or the light source is different. The system can maintain optimal spectral acquisition status through reasonable adjustment, enhancing the adaptability and stability of the system. Precise three-dimensional position adjustment makes the conversion of each target position during the scanning process smoother and more efficient. By optimizing the adjustment process of the galvanometer, the time for invalid or repeated scanning is reduced, improving the efficiency of the scanning process. In dynamic detection, the scanning path and direction can be quickly adjusted to avoid delays in the scanning process.Thus, the data acquisition speed and the overall performance of the system are improved.

[0045] Specifically, the specific steps of obtaining the concentration curve of the measured target are as follows: in the Fourier interference module, for each moving position point, the weighted coefficient of each wavelength of each moving position point is analyzed based on the reflection intensity value of the measured target at each wavelength; the reflection intensity value of the measured target at each wavelength of each moving position point is comprehensively analyzed by combining the weighted coefficient of each wavelength of each moving position point, respectively, to obtain a comprehensive spectral image of the measured target, i.e. the comprehensive reflection intensity value of the measured target at each wavelength; the comprehensive reflection intensity value of the measured target at each wavelength is input into the Fourier interference module for interference processing to obtain interference fringe information of the measured target, and Fourier transform analysis processing is performed to obtain the spectral information of the measured target; the spectral information of the measured target is input into the high-speed photoelectric point detector 5 for inversion analysis processing to obtain the concentration curve of the measured target (leakage gas).

[0046] The specific formula for calculating the comprehensive reflection intensity value of the measured target at each wavelength is as follows: Wherein, ZfS(λ) is the comprehensive reflection intensity value of the measured target at wavelength λ, FS(λ) is the reflection intensity value of the measured target at wavelength λ of the rth moving position point, ωr(λ) is the weighted coefficient of wavelength λ of the rth moving position point, r = 1, 2, 3, …, r0, r0 is the number of moving position points. r (λ) is the reflection intensity value of the measured target at wavelength λ of the rth moving position point, ω r (λ) is the weighted coefficient of wavelength λ of the rth moving position point, r = 1, 2, 3, …, r0, r0 is the number of moving position points.

[0047] It should be explained that the interference principle of the Fourier interference module is that two infrared beams with different optical path differences are combined through the interference principle of light to produce interference, and the time domain signal represented by the infrared spectrum is converted to the frequency domain through Fourier transform to obtain the frequency distribution of the spectrum.

[0048] The interference fringe information of the measured target refers to the interference pattern of the reflection intensity value of the measured target at different wavelengths in space obtained through the Fourier interference module, specifically:

[0049] When light is reflected back from the surface of the measured target, light waves will meet light waves through different paths to produce interference. If the reflecting surface is flat and the reflected light is coherent, the interference of these light waves will form a striped pattern, and the change in reflection intensity reflects certain physical properties of the target surface or interior, such as the interaction of gas molecules with light waves.

[0050] The interference fringes usually show periodic changes, and the interval, shape and contrast of the interference pattern contain information about the frequency, phase difference, propagation path of the reflected light and the surface or volume characteristics of the target.

[0051] By analyzing the interference fringes in detail, the physical properties of the target surface or gas leakage can be derived, especially for gas detection, the analysis of interference fringes helps to identify the presence of different gas molecules and their concentrations.

[0052] The spectral information of the measured target refers to the conversion of the measured target's reflection intensity data into a frequency domain representation through Fourier transform, which generally reflects the frequency distribution of light waves. Specifically:

[0053] The signal in the time domain (spatial domain) is converted into a frequency domain signal, and the reflection intensity value is usually measured in different wavelength ranges, while the Fourier transform converts this information into frequency components, each of which represents the change of the reflection signal at different time or space points.

[0054] The spectral information contains the frequency, amplitude, phase and other components of the light wave, and the spectrum can reveal the interference pattern of the reflected wave, the non-uniformity of the target surface, the surface characteristics, and the characteristics of the gas leakage or gas composition. For example, a specific gas will have specific absorption or scattering characteristics on the spectrum, and these spectral characteristics can be used to distinguish different types of gas.

[0055] Different gases have specific absorption characteristics at different wavelengths, which are reflected as specific frequency response peaks or changes in the spectral graph. These information is very important for gas concentration measurement.

[0056] Inversion analysis is the process of calculating the concentration of the measured target (especially gas) from the obtained spectral information. Specifically:

[0057] Inversion is to use known models or empirical formulas to deduce the concentration of the target gas from the measured spectral data. There is a known mathematical relationship between the absorption or scattering intensity change of each wavelength in the spectrum and the concentration of a specific gas. Through inversion analysis, the concentration information of the gas can be extracted from these spectral characteristics.

[0058] Standard spectral inversion models can be used, such as the Beer-Lambert Law, which shows the relationship between absorbance and gas concentration, path length, and absorption coefficient. The spectral information obtained through Fourier transform can be used to further calculate the absorption intensity of each gas at a specific wavelength, thereby calculating the concentration of the gas.

[0059] And the inversion process needs to combine the known data of the spectral characteristics, absorption intensity, etc. of the gas in the database, and combine the actual measured spectral data for fitting to obtain the concentration of the target gas.

[0060] The concentration curve of the target (leaked gas) is a graph that shows the change of gas concentration over time, usually generated by real-time data processing, and includes the following details:

[0061] Y-axis (concentration value): represents the concentration of the leaked gas, usually expressed in units such as ppm (parts per million) or ppb (parts per billion), which is obtained from the inversion analysis process by analyzing the absorption characteristics of the gas on the spectrum.

[0062] X-axis (time): represents the concentration data at different time points, as the concentration of the leaked gas usually changes over time, the concentration curve can reflect the change of the gas leakage intensity and time.

[0063] Trend of change: the concentration curve shows the fluctuation of gas concentration over time, if the gas leakage is relatively stable, the curve is relatively smooth; if the leakage intensity changes greatly, the curve may appear dramatic fluctuations, through this curve, the behavior of the leaked gas can be analyzed, such as the time of leakage, the speed of leakage, the peak value of gas concentration, etc.

[0064] In this embodiment, the gas concentration can be accurately measured by combining Fourier interference and spectral analysis with inversion processing. The Fourier interference module and spectral information can reveal the spectral characteristics of the gas, and the inversion analysis can calculate the gas concentration by using spectral data, providing a more accurate detection method. Compared with traditional gas detection methods, this method can detect a wider range of gas types and has higher sensitivity to low-concentration gases. By analyzing the spectral data of each moving position point, high spatial resolution gas concentration measurement can be achieved. With the adjustment of the two-dimensional scanning mirror and the cooperation of the Fourier interference module, the target area can be gradually scanned, and the gas concentration at each position can be accurately captured. This high spatial resolution capability enables the device to accurately track gas leaks in a wide area and identify the location of the leak source in real time. The real-time generation of concentration curves provides dynamic monitoring functions, tracking the concentration changes of gas leaks over time. The acquisition of real-time data streams can help the system respond quickly to leakage events, provide early warnings, or adjust the equipment in a timely manner. For example, when the concentration rises sharply, the emergency response system can be activated immediately to protect the equipment and prevent catastrophic accidents. Compared with traditional gas analysis methods such as chemical sampling or gas sensor arrays, this method directly calculates the gas concentration from the reflected intensity data of light waves through spectral inversion, avoiding the need for physical sampling and subsequent chemical analysis. The entire process is completed through non-contact optical detection, which not only improves work efficiency but also reduces the risks caused by human error and operational complexity. This method is not only suitable for standard gas concentration monitoring but also can be used in some extreme or unsuitable environments for direct contact detection, such as high-temperature, high-pressure environments, and dangerous gas leaks. Due to the good adaptability of spectral inversion methods to different types of gases, a database can be constructed to measure multiple gases, thereby providing multiple gas detection functions. In the inversion analysis of spectral information, mathematical models (such as the Beer-Lambert law) and database matching techniques can effectively extract valuable information from complex reflection data, which not only improves data processing efficiency but also ensures data analysis reliability. Especially for the detection of complex gas mixtures or small changes, the system can provide trend analysis of gas leaks through concentration curves. By observing the amplitude and time of concentration changes, the leakage period, speed, and possible leak source location can be determined. For example, if the concentration increases significantly at a certain time and lasts for a long time, the leakage time and intensity can be inferred, and the specific location of the leak source can be calculated. The interference fringe information reveals the optical characteristics of the target surface, enabling the method to not only detect gas leaks but also analyze the subtle characteristics of the target surface, such as surface non-uniformity, temperature changes, or target surface damage. These information is of great significance for the maintenance and long-term monitoring of the target.The method can continuously monitor the gas concentration in real time and timely adjust the position of the spectral detection equipment, ensuring the accuracy and stability of the equipment, reducing the probability of false positives and false negatives, and reducing the monitoring blind area caused by equipment failure. In a flammable and explosive gas environment, timely concentration feedback can greatly improve the safety of equipment and personnel. The concentration curve graph not only provides real-time data for gas leakage detection, but also integrates with other sensor data (such as temperature, pressure, etc.) to form a comprehensive analysis platform. This data integration can provide multi-dimensional support for gas leakage prediction, accident analysis, and environmental assessment, and has wide application potential in industrial production, environmental monitoring, and dangerous substance transportation.

[0065] In summary, the present application has at least the following effects:

[0066] By combining the card telescope with the two-dimensional scanning galvanometer, high-precision positioning and spectral data acquisition of the scene to be measured are realized. Specifically, first, the image data of the scene to be measured is obtained through the card telescope, and the target position in each image region is determined by analyzing the mean value and standard deviation of the pixel value. Then, the two-dimensional scanning galvanometer is used to accurately scan the target to be measured, and the spectral data of each moving position point is obtained, thereby avoiding the problem of inconsistent or missing spectral data caused by uncertain target position in traditional technology, and ensuring that the spectral data of each target position is effectively collected and transmitted.

[0067] After the target is located, the two-dimensional tracking galvanometer is used to track the target in real time, ensuring that even if the target is moving, the device can accurately adjust its position and continuously monitor the spectral information of the target. By synchronously adjusting the three-dimensional position coordinates of the two-dimensional tracking galvanometer, the accuracy of spectral data transmission can be ensured at all times. This real-time adjustment and precise control solves the problem of information deviation caused by spectral data transmission errors in traditional spectral detection devices, effectively improving the stability of the system and the reliability of data acquisition.

[0068] By combining the Fourier interference module with the high-speed photoelectric point detector, the sensitivity and accuracy of gas cloud imaging are significantly improved by taking advantage of the technical advantages of interference processing and inversion analysis. The Fourier interference module combines two infrared beams with different optical path differences through the principle of light interference, produces interference phenomena, and converts the time domain signal represented by the infrared spectrum to the frequency domain through Fourier transform to obtain the frequency distribution of the spectrum, thereby analyzing and inverting the gas concentration curve information. The introduction of the stop effectively adjusts and controls the passing path of the light, ensuring the transmission quality and stability of the spectral data. The setting of the stop not only optimizes the data acquisition process, but also reduces the interference of background light, enabling the Fourier interference module to focus on the spectral characteristics of the target object, thereby improving the signal-to-noise ratio of the entire system and ensuring the accuracy of the imaging result.

[0069] While the preferred embodiments of the application have been described, additional variations and modifications can be made to these embodiments by those skilled in the art once they have the benefit of the present disclosure without departing from the spirit and scope of the application. Accordingly, it is intended that the appended claims include all such modifications and variations as fall within the scope of the present application.

[0070] It is apparent that those skilled in the art can make various changes and modifications to the application without departing from the spirit and scope of the application. It is therefore intended that the present application cover all such changes and modifications that are within its scope.

Claims

1. A small-sized spectral detection gas cloud imaging device based on a galvanometer and a cassette telescope, characterized in that, The application relates to a spectral scanning device for detecting a target, which comprises: an identification scanning module, a two-dimensional tracking galvanometer (2), an imaging module, the identification scanning module comprises a cassette telescope (3) and a two-dimensional scanning galvanometer (1), the imaging module comprises a Fourier interference module and a high-speed photoelectric point detector (5), and a diaphragm (4) is arranged between the two-dimensional tracking galvanometer (2) and the imaging module. The identification scanning module is arranged to perform trajectory identification scanning on a to-be-detected scene based on a preset moving track, to obtain measured target spectral data of a plurality of moving position points, and to simultaneously adjust the position of the two-dimensional tracking galvanometer (2) so that the two-dimensional tracking galvanometer (2) receives the measured target spectral data of each moving position point, and vertically transmits the received measured target spectral data of each moving position point to the Fourier interference module through the diaphragm (4) for interference processing, and inputs the interference processing result into the high-speed photoelectric point detector (5) for inversion analysis, to obtain a concentration curve of the target (leakage gas). The measured target spectral data comprises a reflection intensity value of the target at each wavelength.

2. The small-sized gas cloud imaging device based on a galvanometer and a catadioptric telescope for spectral detection according to claim 1, characterized in that, The specific steps of obtaining the measured target spectral data of the plurality of moving position points by performing trajectory identification scanning on the to-be-detected scene based on the preset moving track are as follows: 3.The small-sized gas cloud imaging device based on a galvanometer and a catadioptric telescope according to claim 1, wherein, At each moving position point, the cassette telescope (3) is used to acquire to-be-detected scene image data, and the position information of the target is determined by analysis, wherein the to-be-detected scene image data comprises a pixel value and a two-dimensional pixel coordinate of each to-be-detected pixel point in the to-be-detected scene image. After the position information of the target is determined, the two-dimensional scanning galvanometer (1) is used to scan the target, to obtain the measured target spectral data of each moving position point. The specific steps of acquiring the to-be-detected scene image data by the cassette telescope (3) and determining the position information of the target are as follows:

4. The small-sized gas cloud imaging apparatus based on a galvanometer and a catadioptric telescope for spectral detection according to claim 3, characterized in that, The to-be-detected scene image is divided into a plurality of image regions, and each image region data comprises a plurality of to-be-detected pixel points. For each image region, the pixel value of each to-be-detected pixel point is analyzed to obtain a pixel mean value and a pixel standard deviation value of each image region. The pixel mean value and the pixel standard deviation value of each image region are analyzed to obtain a pixel threshold value of each image region. The pixel threshold value of each image region and the pixel value of each to-be-detected pixel point are analyzed to obtain a plurality of target pixel points in the to-be-detected scene image. The pixel value and the two-dimensional pixel coordinate of the plurality of target pixel points in the to-be-detected scene image are analyzed to obtain an initial center pixel coordinate of the target in the to-be-detected scene image. The initial center pixel coordinate of the target in the to-be-detected scene image is subjected to space conversion processing to obtain a center three-dimensional space coordinate of the target in the to-be-detected scene image, which is marked as the position information of the target. The specific formulae for calculating the pixel mean value, the pixel standard deviation value, the pixel threshold value of each image region and the initial center pixel coordinate of the target in the to-be-detected scene image are as follows:

5. The small-sized gas cloud imaging apparatus based on a galvanometer and a catadioptric telescope for spectral detection according to claim 4, characterized in that, The specific steps of obtaining the center three-dimensional space coordinate of the target in the to-be-detected scene image are as follows: XsJ u is the pixel mean value of the u-th image region, XsZ ut is the pixel value of the t-th pixel to be measured in the u-th image region, XsB u is the pixel standard deviation value of the u-th image region, XyZ u is the pixel threshold value of the u-th image region, δ u is the threshold adjustment coefficient of the u-th image region, u = 1, 2, 3, …, u0, u0 is the number of image regions, t = 1, 2, 3, …, t0, t0 is the number of pixels to be measured, x' is the initial two-dimensional pixel horizontal coordinate of the measured target in the scene image to be measured, DxS i is the pixel value of the i-th measured target pixel in the scene image to be measured, x i is the two-dimensional pixel horizontal coordinate of the i-th measured target pixel in the scene image to be measured, y' is the initial two-dimensional pixel vertical coordinate of the measured target in the scene image to be measured, y i is the two-dimensional pixel vertical coordinate of the i-th measured target pixel in the scene image to be measured, i = 1, 2, 3, …, i0, i0 is the number of measured target pixels.

6. The small-sized gas cloud imaging apparatus based on a galvanometer and a catadioptric telescope for spectral detection according to claim 4, characterized in that, ​ Obtaining the center coordinate of the to-be-tested scene image, the horizontal focal length value and the vertical focal length value of the to-be-tested scene image, and the distance value of the measured target in the to-be-tested scene image from the cassette telescope (3), and comprehensively analyzing the measured target initial center pixel coordinate in the to-be-tested scene image to obtain the measured target center three-dimensional space coordinate in the to-be-tested scene image; The specific formula for calculating the measured target center three-dimensional space coordinate in the to-be-tested scene image is as follows: wherein X" is the three-dimensional space horizontal coordinate of the center of the measured target in the scene image to be measured, X' is the initial two-dimensional pixel horizontal coordinate of the center of the measured target in the scene image to be measured, X'" is the two-dimensional horizontal coordinate of the center of the scene image to be measured, f x is the horizontal focal length value of the scene image to be measured, JLz is the distance value of the measured target in the scene image to be measured from the camera lens, y" is the three-dimensional space vertical coordinate of the center of the measured target in the scene image to be measured, y' is the initial two-dimensional pixel vertical coordinate of the center of the measured target in the scene image to be measured, y" is the two-dimensional vertical coordinate of the center of the scene image to be measured, f y is the vertical focal length value of the scene image to be measured, and z" is the three-dimensional depth coordinate of the center of the measured target in the scene image to be measured.

7. The small-sized gas cloud imaging apparatus based on a galvanometer and a catadioptric telescope for spectral detection according to claim 1, characterized in that, The specific steps of synchronously adjusting the position of the two-dimensional tracking galvanometer (2) to enable the two-dimensional tracking galvanometer (2) to receive the measured target spectral data of each moving position point through the diaphragm (4) are as follows: For each moving position point, the three-dimensional position coordinate of the two-dimensional scanning galvanometer (1) and the initial three-dimensional position coordinate of the two-dimensional tracking galvanometer (2) are respectively obtained in real time, and the three-dimensional position adjustment value of the two-dimensional tracking galvanometer (2) is analyzed, wherein the three-dimensional position adjustment value includes the horizontal direction adjustment value, the vertical direction adjustment value, and the depth direction adjustment value. Based on the three-dimensional position adjustment value, the initial three-dimensional position coordinate of the two-dimensional tracking galvanometer (2) is adjusted to obtain the adjusted three-dimensional position coordinate of the two-dimensional tracking galvanometer (2). 8.The small-sized gas cloud imaging device based on a galvanometer and a catadioptric telescope according to claim 7, wherein, The specific steps of calculating the three-dimensional position adjustment value and the adjusted three-dimensional position coordinate of the two-dimensional tracking galvanometer (2) are as follows: Wherein, Δx is the horizontal direction adjustment value of the two-dimensional tracking galvanometer (2), X is the three-dimensional position horizontal coordinate of the two-dimensional scanning galvanometer (1), X' is the initial three-dimensional position horizontal coordinate of the two-dimensional tracking galvanometer (2), ξ1 is the horizontal adjustment coefficient stored in the database, Δy is the vertical direction adjustment value of the two-dimensional tracking galvanometer (2), Y is the three-dimensional position vertical coordinate of the two-dimensional scanning galvanometer (1), Y' is the initial three-dimensional position vertical coordinate of the two-dimensional tracking galvanometer (2), ξ2 is the vertical adjustment coefficient stored in the database, Δz is the depth direction adjustment value of the two-dimensional tracking galvanometer (2), Z is the three-dimensional position depth coordinate of the two-dimensional scanning galvanometer (1), Z' is the initial three-dimensional position depth coordinate of the two-dimensional tracking galvanometer (2), ξ3 is the depth adjustment coefficient stored in the database, X" is the adjusted three-dimensional position horizontal coordinate of the two-dimensional tracking galvanometer (2), Y" is the adjusted three-dimensional position vertical coordinate of the two-dimensional tracking galvanometer (2), and Z" is the adjusted three-dimensional position depth coordinate of the two-dimensional tracking galvanometer (2).

9. The small-sized gas cloud imaging apparatus based on a galvanometer and a catadioptric telescope for spectral detection according to claim 2, characterized in that, The specific steps of obtaining the measured target concentration curve are as follows: In the Fourier interference module, for each moving position point, based on the reflection intensity value of the measured target at each wavelength, the weighting coefficient of each wavelength of each moving position point is analyzed; The reflection intensity value of the measured target at each wavelength of each moving position point is comprehensively analyzed by combining the weighting coefficient of each wavelength of each moving position point to obtain the comprehensive spectral image of the measured target, that is, the comprehensive reflection intensity value of the measured target at each wavelength; The comprehensive reflection intensity value of the measured target at each wavelength is input into the Fourier interference module for interference processing to obtain the interference fringe information of the measured target, and Fourier transform analysis processing is performed to obtain the frequency spectrum information of the measured target; The spectrum information of the measured target is input into a high-speed photoelectric point detector (5) for inversion analysis and processing to obtain a concentration curve graph of the measured target (leakage gas).

10. The small-sized gas cloud imaging device based on a galvanometer and a catadioptric telescope for spectral detection according to claim 9, characterized in that, The specific formula for calculating the comprehensive reflection intensity value of the measured target at each wavelength is as follows: wherein ZfS(λ) is the comprehensive reflection intensity value of the measured target at wavelength λ, FsQ r (λ) is the reflection intensity value of the measured target at wavelength λ of the rth moving position point, ω r (λ) is the weighting coefficient of wavelength λ of the rth moving position point, r = 1, 2, 3, …, r0, r0 is the number of moving position points.

Images