501 results about "Short wave infrared" patented technology

The invention discloses an artificial intelligence machine vision image acquisition system, and the system comprises a multi-mode perception layer which integrates a self-adaptive optical module, inhibits metal reflection, captures a visible light to short wave infrared image, and captures a motion edge; the dynamic adaptive layer adopts an illumination compensation and motion compensation module to dynamically adjust camera parameters and micro displacement compensation, feeds back an illumination trend, outputs a motion vector to the cognitive layer, generates a confrontation sample through a GAN, simulates virtual defects in combination with a physical engine, and expands training data; the cognitive reasoning layer is used for deploying a dynamic routing network, distributing computing resources according to image complexity and optimizing feature extraction efficiency; reducing data deviation through anti-fact analysis, and generating a thermodynamic diagram to explain a detection basis; and the collaborative decision-making layer is used for rapidly screening samples by edge nodes, training a global model by cloud aggregated data, automatically triggering manual rechecking when the confidence coefficient of the model is insufficient, synchronously optimizing a training set and a causal reasoning module by a rechecking result, and improving the labeling efficiency through AR assistance.

The invention relates to the technical field of machine learning, in particular to a grain classification and recognition method and system based on image analysis, and the method comprises the following steps: obtaining grain particle image data, calculating a gray histogram and a gradient change rate, calling a gray co-occurrence matrix to extract grain particle texture density, and scanning a sliding window to obtain local feature parameters of grain particles. According to the method, through combined analysis of a gray level histogram and a gradient change rate, dynamic extraction of particle textures through a sliding window, enhancement of complex surface feature capture, normalization of contrast and direction consistency parameters, construction of weighted feature vectors, dynamic correction of variance contribution degree and suppression of environmental interference, and fusion of near-infrared and short-wave infrared reflectivity changes, the near-infrared and short-wave infrared reflectance change is improved. And quantifying the mean value and peak-to-valley ratio of spectrum difference values, matching visible light characteristics to verify multi-dimensional constraints, constructing a spectrum-texture matrix by local reflectivity rate and gradient change rate, and synchronously evaluating global similarity and spatial distribution difference by adopting Euclidean distance and local offset double-layer matching.

The invention discloses a display screen dead pixel fault prediction detection method and system. The method comprises the following steps: collecting a visible light image, a short wave infrared image, an ultraviolet fluorescence image, a driving current time sequence signal and surface temperature distribution data of a display screen; performing dynamic noise injection and cross-modal alignment on the data to generate a preprocessed multi-modal data set; inputting the preprocessed multi-modal data set into a space-time fusion network, extracting space-time correlation characteristics in a dead pixel diffusion process through the space-time fusion network, and generating a pixel-level dead pixel mask of a current frame and a diffusion probability thermodynamic diagram of a future time period based on the space-time correlation characteristics; and according to the dead pixel mask and the diffusion probability thermodynamic diagram, dynamically adjusting detection parameters to adapt to target equipment, and outputting a probabilistic diagnosis result of dead pixel causes in combination with physical relevance of multi-modal data.

The invention relates to the technical field of regulating valve monitoring, in particular to a regulating valve opening degree monitoring method and system based on image recognition, and the method comprises the following steps: S1, constructing a composite optical mark: machining annular grooves and longitudinal convex ridges which are distributed in a staggered manner on the surface of a valve rod to form a composite mark belt; s2, anti-interference stereo imaging: collecting visible light and short wave infrared images to generate a fusion point cloud set; s3, dynamic shielding compensation: generating a three-dimensional point cloud model of a complete composite marking band; s4, thermal expansion decoupling calculation: visual displacement errors caused by thermal expansion are eliminated; and S5, time-space domain closed-loop calibration: reversely reckoning the opening value by using the structured light three-dimensional coordinate to carry out cross validation. According to the invention, high-precision, high-robustness and verifiability monitoring of the opening degree of the regulating valve is realized, and the measurement stability and engineering applicability under complex working conditions are effectively improved.

The invention discloses a photovoltaic module surface defect online detection method based on multi-modal image fusion, and relates to the technical field of photovoltaic module detection.The method comprises the steps that a visible light line-scan digital camera, a short-wave infrared camera, an EL line-scan digital camera and a laser speckle imaging module are installed to collect real-time data, an optical image is subjected to dynamic window median filtering, and the surface defect of the photovoltaic module is obtained; the method comprises the following steps: carrying out time moving average combined dynamic threshold segmentation on an infrared image and an EL image, carrying out image-guided outlier filtering on 3D point cloud data, judging a pixel defect type based on gray-temperature correlation and calculating a fusion weight, respectively inputting the optical image, the infrared image, the EL image and 3D point cloud into GhostNet, lightweight ViT, CNN and PointNet-Lite to extract features, and carrying out image fusion on the 3D point cloud data. And after global average pooling and splicing, inputting into a channel attention module to generate a modal weight, and after weighted fusion, obtaining a defect type through a full connection layer. According to the invention, the accuracy of defect detection is effectively improved.

The invention relates to a visible light / short-wave infrared dual-band common-caliber optical system, which comprises a common-caliber part, a plane beam splitter, a visible light channel subsystem and a short-wave infrared channel subsystem, and is characterized in that the common-caliber part is positioned at the foremost end of the optical system and consists of a primary reflector and a secondary reflector which are coaxially arranged; the plane beam splitter is located on a light path behind the secondary reflector, full-wave-band light from an object side is reflected by the primary reflector and the secondary reflector in sequence, then reaches the plane beam splitter to be split, and then enters the visible light channel subsystem and the short-wave infrared channel subsystem to be imaged in different wave bands, and the optical system achieves dual-wave-band common caliber. According to the invention, the design of long focal length and large aperture of the dual-band system is realized, the target detection / identification capability of the system is improved, the system has the advantages of high spatial resolution, long operating distance and high identification probability, meanwhile, the system structure is effectively simplified, the system volume is reduced, the installation and adjustment difficulty is reduced, and a relatively low obscuration ratio and relatively high imaging quality are realized.

A short-wave infrared photothermal (SWIP) microscopy system and method for vibrational imaging of a sample generates shortwave infrared excitation light probe light. The excitation light and the probe light are combined to generate a combined beam, which is focused to generate a focused combined beam, which is directed onto the sample to obtain a SWIP signal generated by absorption-induced thermo-optic selective heating of the sample. The SWIP signal is collected through an aperture in a condenser and detected.

The invention provides an imperfect soybean hyperspectral imaging classification method based on deep learning. Efficient and accurate classification is realized by fusing spectrum and image features. Acquiring spectrum and image data by using a hyperspectral imaging system; the data quality is improved through a preprocessing method; and constructing a dual-channel feature fusion model, and reinforcing key feature extraction in combination with an attention mechanism. According to the method, the classification precision of 95.13% and 94.00% in the visible light-near infrared band and the short wave infrared band is achieved, and compared with a traditional support vector machine and a convolutional neural network method, the classification precision is remarkably improved. The model deeply digs spectral image features through a deep learning network, analyzes the association between the spectral image features and soybean quality, and enhances the robustness and generalization ability of the model. The method has the advantages of being high in precision, rapid in detection, high in adaptability and the like, is suitable for different varieties and large-scale detection scenes, and provides an efficient solution for agricultural product quality monitoring, automatic sorting and agricultural scientific research.

The invention discloses a visible light and short wave infrared common-aperture optical system which is used for solving the technical problem that an existing multi-band common-aperture optical system cannot meet the detection requirements of large view field, high resolution and high sensitivity at the same time. The optical system comprises a visible light optical system and a short-wave infrared optical system, and a primary reflector, a secondary reflector, a beam splitter prism, a visible light relay lens group and a first imaging unit jointly form the visible light optical system; and the primary reflector, the secondary reflector, the beam splitter prism, the short-wave infrared image space telecentric relay lens group, the view field divider and the N second imaging units jointly form a short-wave infrared optical system. The optical system disclosed by the invention shares the primary reflector and the secondary reflector, so that the focal length of the optical system is increased, and the requirement of high resolution is met; and meanwhile, the short-wave infrared optical system adopts the view field divider and N second imaging units, and the large-view-field and high-sensitivity infrared detection requirements of the optical system on a dark and weak target are met through splicing of N paths of view fields.

The invention belongs to the technical field of oil stain detection, and particularly relates to a water surface oil stain detection method, system and equipment, the water surface oil stain detection system comprises a flexible circuit board FPC, an InGaAs infrared sensor, an infrared narrow-band filter and an optical lens, light enters a visible light camera and the optical lens through an external lens, the visible light camera collects visible light images, and the visible light images are transmitted to the InGaAs infrared sensor; the optical lens focuses a light beam, then light with a specific wavelength is screened out through the near-infrared narrow-band filter, the screened light is received by the InGaAs infrared sensor, and the InGaAs infrared sensor is connected with the FPC; the method has the advantages that visible light imaging and short wave infrared spectrum analysis technologies are ingeniously fused, so that the accuracy and the reliability of oil stain detection are remarkably improved. Under the current background that environmental protection and water resource management are increasingly severe, powerful technical support is undoubtedly provided for water surface pollution monitoring.

The invention relates to the technical field of zirconia ceramic sintering, and discloses a zirconia ceramic microwave single-die-cavity rapid sintering system and an intelligent temperature control method.The system comprises a high-temperature-resistant metal cavity, a microwave generation unit, a temperature detection and control unit, a coil base assembly and an auxiliary structure, and centralized control is achieved through an intelligent touch control computer. A microwave single-mode resonance mode is adopted, a silicon carbide wave absorbing layer is used for enhancing microwave absorption, materials are evenly heated from inside to outside, an intelligent temperature control method is used for monitoring the temperature in real time based on a short-wave infrared thermometer, a PI D control algorithm is combined, the power of a magnetron is dynamically adjusted through an adjustable power source, the temperature control precision reaches + / -2 DEG C, and the temperature control precision reaches + / -2 DEG C; the problems of non-uniform temperature, high energy consumption, high rejection rate, long sintering time and the like in a traditional zirconia ceramic sintering process are effectively solved, the production efficiency can be greatly improved, the cost is reduced, the product quality is improved, the equipment also supports multiple process modes, and diversified production requirements are met.

The invention discloses a farmland soil moisture content real-time surveying system and method based on unmanned aerial vehicle multispectral imaging. The method comprises the steps that multispectral sensor parameters are configured, and an unmanned aerial vehicle flight scanning path is planned; a space coordinate system and time synchronization mechanism is established, and high-precision positioning and time synchronization are achieved; collecting and calibrating visible light, near-infrared and short-wave infrared original image data to form a spectral signal set; calculating an image signal-to-noise ratio, screening a low-quality image, and executing noise suppression; extracting timestamp information from the suppressed image, performing spatial positioning, and establishing a spatial corresponding relation database; calculating time synchronization precision and performing image correction; evaluating the spatial resolution according to the distortion coefficient; calculating a comprehensive quality parameter, comparing the comprehensive quality parameter with a threshold value, and obtaining a soil moisture content distribution parameter when a condition is met; a farmland moisture state map is generated, partition marking is carried out according to a multi-level standard, a monitoring result is output, and high-precision and real-time monitoring of the farmland soil moisture content is achieved.

The invention relates to a microscope system, in particular to a confocal microscope system of a short-wave infrared band. The system comprises a bright / dark field microscopy subsystem, a photon emission microscopy subsystem, a short wave infrared laser scanning confocal microscopy subsystem, a fluorescence confocal microscopy subsystem and a control module. According to the system provided by the invention, the short-wave infrared fluorescence lifetime curve can be obtained through the electro-luminescence emission and / or photoluminescence emission of the semiconductor device in the integrated circuit, so that the defect type of the semiconductor can be judged. Besides, the system adopts a multi-subsystem optical path multiplexing structure in structural design, short-wave infrared fluorescence generated by exciting a defect or a failure point is collected while observation is facilitated, high integration level is achieved, and observation, positioning and failure analysis of the defect or the failure point can be achieved only by using a single system provided by the invention.

The invention discloses an ultra-wide-spectrum endoscopic imaging device capable of being used for short-wave infrared fluorescence imaging, which is used for in-vivo minimally invasive imaging and comprises an illumination module, a wide-spectrum image transmission module, an imaging module and an image processing module. The illumination module consists of a light source and a light guide optical fiber, and is used for generating illumination light from ultraviolet to short wave infrared band and transmitting the illumination light to the wide-spectrum image transmission module; the wide-spectrum image transmission module consists of a few-interface optical imaging channel and a light guide illumination channel, and is used for illuminating an imaging target, exciting target fluorescence and collecting image signals from ultraviolet to short-wave infrared bands; the imaging module is composed of an optical filter and an imaging camera, and the imaging camera can be a wide spectral response image sensor or can be formed by combining cameras working in different wavebands and is used for converting optical images in different wavebands into image data; and the image processing module is used for registering and fusing image data of different wavebands in real time and displaying the image data.

The invention provides a visible light and short wave infrared fluorescent endoscopic imaging system and method, and belongs to the technical field of fluorescent endoscopic imaging, and the system comprises an endoscope which is used for guiding a light signal into a position needing to be checked and collecting a light signal reflected or transmitted from a target tissue; a light source; the light source adopts a multimode light source and is connected with the endoscope through an optical fiber; a camera module; the camera module is connected with the endoscope through the optical bayonet, and the camera module can receive optical signals output by the endoscope and convert the optical signals into image information; and the controller is in control connection with the light source, the camera module and the display, the camera module transmits the image information into the controller for processing, and the display displays the image information processed by the controller. By fusing the visible light imaging mode and the short wave infrared fluorescence imaging mode, surface details and deep structure information of the tissue can be captured at the same time, and the high-resolution and high-definition imaging effect is achieved.

The invention provides a short-wave infrared detector digital alloy material and a preparation process thereof. The preparation process comprises the following steps: growing a GaSb buffer layer on the surface of an n-type GaSb substrate; starting a first In furnace, and growing an InAs layer on the surface of the GaSb buffer layer in cooperation with an As beam; starting a second In furnace, and growing a quaternary solid solution layer matched with a GaSb buffer layer lattice on the surface of the InAs layer in cooperation with the Ga furnace and the AsSb beam; and alternately growing an InAs layer and a quaternary solid solution layer on the surface of the quaternary solid solution layer to generate a superlattice structure until the total thickness of the superlattice structure reaches a set target thickness, thereby obtaining the digital alloy material. According to the digital alloy material for the short-wave infrared detector and the preparation technology of the digital alloy material, the short-wave infrared detector can be expanded to the wave band ranging from 2.4 micrometers to 2.8 micrometers at the 50% cut-off wavelength.

The invention relates to the technical field of vegetation root system nondestructive testing, in particular to a multispectral vegetation root system identification system and method based on a differentiable physical engine, and the system comprises a multispectral LiDAR module which is used for transmitting near-infrared laser and short-wave infrared laser, scanning a target area, obtaining dual-wavelength reflectivity data, and determining the vegetation root system according to the dual-wavelength reflectivity data; generating a reflectivity ratio matrix by adopting a reflectivity ratio classification model; the differentiable physical engine is used for quantizing the dynamic relationship between the vegetation root growth rate and the soil resistance by adopting a coupling model according to the reflectivity ratio matrix, generating a physical model and updating the physical model at a preset time interval; and the data processing and three-dimensional modeling module is used for generating a three-dimensional root system model and a health assessment result according to the reflectivity ratio matrix and the physical model, and outputting the three-dimensional root system model and the health assessment result. According to the scheme, soil penetration and root system and foreign matter distinguishing can be carried out, the vegetation native environment is not damaged, dynamic monitoring analysis is carried out, and the accuracy of recognition analysis is improved.

The invention discloses a high and cold slope disaster body segmentation method fusing optical and SAR images, and the method comprises the following steps: 1, carrying out the snow coverage normalization processing based on the visible light green light wave band and the short wave infrared wave band of an optical image, and generating an ice and snow mask through an expectation maximization algorithm and a Gaussian mixture model; 2, preprocessing the optical image and the SAR image; step 3, constructing a high and cold slope disaster body segmentation model based on a Transform network; 4, training the segmentation model by using Dice loss and cross entropy loss in a combined manner, and freezing parameters of an image encoder in the training process; and step 5, inputting the high and cold slope remote sensing image into the trained segmentation model, and outputting a segmentation result of the slope disaster body by the segmentation model. According to the method, the problems of large ice and snow interference and poor multi-source data collaboration in high and cold slope disaster body segmentation are solved, and the segmentation precision and the engineering applicability are improved.

The invention discloses a compact coaxial turn-back type three-waveband multifunctional common-aperture optical system. Belongs to the technical field of photoelectricity, and particularly relates to the technical field of compact coaxial turn-back type three-waveband common-caliber photoelectricity. The problem that an existing aperture-dividing type optical system is difficult to miniaturize and light and has chromatic aberration is solved. The device comprises a coaxial turn-back type afocal objective lens, a laser emission light path, a short-wave imaging light path and a medium-wave imaging light path, a laser beam emitted by a laser emission light path is emitted to a target through a coaxial turn-back type afocal objective lens, the target reflects the laser beam and a short-wave infrared beam to the coaxial turn-back type afocal objective lens, and meanwhile, the target radiates a medium-wave infrared beam to the coaxial turn-back type afocal objective lens; the coaxial turn-back type afocal objective reflects the laser beam and the short-wave infrared beam to the short-wave imaging light path for imaging, and the coaxial turn-back type afocal objective reflects the medium-wave infrared beam to the medium-wave imaging light path for imaging.

The invention discloses a compact off-axis reflection type three-waveband multifunctional common-caliber optical system. Belongs to the technical field of photoelectricity, and particularly relates to the technical field of compact off-axis reflection type three-waveband common-caliber photoelectricity. The laser, short-wave infrared and medium-wave infrared common aperture and laser emission and receiving integrated optical design are realized, and the target detection, positioning aiming and laser guiding performance of the system is improved. The system comprises an off-axis reflection type afocal objective lens, a laser emission light path, a short-wave imaging light path and a medium-wave imaging light path, a laser beam emitted by a laser emission light path is emitted to a target through an off-axis reflection type afocal objective lens, the target reflects the laser beam and a short-wave infrared beam to the off-axis reflection type afocal objective lens, and meanwhile, the target radiates a medium-wave infrared beam to the off-axis reflection type afocal objective lens; the off-axis reflection type afocal objective reflects the laser beam and the short-wave infrared beam to the short-wave imaging light path for imaging, and the off-axis reflection type afocal objective reflects the medium-wave infrared beam to the medium-wave imaging light path for imaging.

The invention discloses a vehicle blind area dynamic enhancement and warning system for a low-light environment, and relates to the technical field of automobile active safety, and the system comprises a short wave infrared imaging module which is used for capturing a passive thermal feature image of a scene behind the side of a vehicle; the multi-source signal acquisition module is used for acquiring a vehicle bus signal representing a vehicle motion state and an operation intention of a driver in real time; the data processing and risk assessment module is connected with the short wave infrared imaging module and the multi-source signal acquisition module, and is used for performing fusion processing on the thermal feature image and the vehicle bus signal, identifying a blind area target and calculating a dynamic risk level of the blind area target; the grading warning and intervention module is connected with the data processing and risk assessment module; the short-wave infrared imaging technology which is sensitive to night light and high in anti-interference capacity is adopted, the imaging problem under extremely low illumination is fundamentally solved, and stable detection of vehicles and pedestrians in a long distance in a completely light-source-free environment is achieved.

The invention provides a spectral imaging type defect detection method and system for a coating of an isolating switch, and relates to the technical field of electrical equipment maintenance, and the method comprises the following steps: S1, collecting a multiband reflection image of the coating on the surface of the isolating switch through a multispectral imaging device, the multiband at least comprising a visible light band, a near-infrared band and a short-wave infrared band; and S2, carrying out registration and fusion processing on the multi-band reflection image. According to the method and system, visible light, near-infrared and short-wave infrared bands are fused through multispectral imaging, high-precision defect recognition and thickness inversion are achieved, physical damage of traditional contact type detection to a plating layer is avoided, reflection interference is restrained through polarization filtering, the illumination fluctuation influence is eliminated through an ambient light dynamic compensation algorithm, and the detection accuracy is improved. And finally, in combination with structured light three-dimensional reconstruction and a multispectral inversion model, a coating thickness distribution diagram and a service life prediction curve are generated, data support is provided for preventive maintenance, and the service life of equipment is prolonged.

The invention provides a precise and small broadband hyperspectral imager, which is used for solving the technical problem that the existing broadband spectral imager from visible near-infrared to short-wave infrared for sceneries cannot meet the increasingly harsh imaging requirements. According to the small broadband hyperspectral imager, the front optical assembly of an off-axis two-reflection structure and the spectrometer assembly in a free-form surface reflector, optical path multiplexing and axis folding mode are adopted, the number of used lenses is greatly reduced, meanwhile, the length of a spectrometer is effectively reduced, and the imaging precision is improved. The volume and the weight of the spectral imager are greatly reduced; besides, front surfaces and rear surfaces of a first lens and a second lens in the spectrometer assembly are plated with broadband antireflection films from visible near-infrared to short-wave infrared according to light angles, and broadband detection from visible near-infrared to short-wave infrared can be realized in combination with a broadband refrigeration type detector. And the complexity and the installation and adjustment difficulty of the detector assembly and the circuit assembly are greatly reduced.

The invention discloses a high-resolution semiconductor surface and interior flaw detection method and device based on a multi-photon nonlinear fluorescence effect, and relates to nonlinear optics and optical imaging semiconductor detection. The short-wave infrared light penetrates through a semiconductor to be detected, a surface or an internal defect to trigger scattering, the transmittance / reflectivity and the power are changed, the thin film containing the high-order nonlinear fluorescent nanoparticles is excited, the luminance generates magnitude order change, and the defect detection contrast ratio and the imaging resolution ratio are improved. Full-automatic control is achieved through an FPGA and LabVIEW, sub-images are automatically collected and spliced, and gray scale abnormal areas are analyzed to judge defect types and distribution. The optical imaging device comprises an exciting light generation module, a sample scanning module, a nonlinear fluorescent film imaging module and an intelligent control analysis module, realizes short-wave infrared light excitation and visible light-near infrared detection, and has the advantages of intelligence, high resolution, low cost and large-area full-automatic flaw detection. The method is suitable for large-scale semiconductor efficient flaw detection, gets rid of dependence on an infrared imaging camera, and reduces system cost.

A sensor includes an array of optically active pixels disposed on a semiconductor die. The array of optically active pixels includes at least one pixel (P1) configured to detect short wavelength infrared radiation (SWIR), and at least one pixel (P2) configured to detect visible light incident on the sensor.

The invention discloses an intelligent optical sensing system based on multispectral fusion, and relates to the technical field of optical sensing, and the system comprises a multispectral image collection module which is used for synchronously collecting original image data of a target scene under three spectral channels of visible light, near-infrared and short-wave infrared; the space-time registration and preprocessing module is used for carrying out high-precision space-time registration and radiation correction on the images of different spectrum channels; the self-adaptive feature extraction and fusion module is used for extracting multi-scale spectral features from the registered multi-spectral image and dynamically selecting and weighting a fusion strategy according to scene content; and the lightweight decision network module outputs a final target identification and state discrimination result. According to the technical scheme, the time-space consistency of multispectral data acquisition can be realized, the cross-band registration precision is improved, the robustness under the conditions of low contrast, shielding and severe weather is enhanced, meanwhile, the calculation complexity and memory occupation are greatly reduced, and the method is suitable for edge calculation equipment with limited resources.

The utility model relates to the technical field of heating devices, in particular to a short-wave infrared ray heating curing lamp box which comprises a heat insulation box body, a short-wave infrared ray lamp, an air blowing device, a lampshade fixing plate and a reflection lampshade, and the reflection lampshade comprises an outer shell, an arc-shaped reflection plate, a profiling pressing plate, a locking piece, an insulation base and at least two conductive chucks. The profiling pressing plate and the arc-shaped reflecting plate are arranged in the outer shell from top to bottom in an overlapped mode, and a heating curing groove and an exhaust groove are formed in the bottom face of the heat insulation box body. Short-wave infrared light emitted by the short-wave infrared lamp can be focused on a workpiece to the maximum extent through the arc-shaped reflecting plate, so that the utilization rate of heat energy and the heating efficiency are improved, modular assembly of the reflecting lampshade is achieved, disassembly, assembly and maintenance are convenient, and the practicability is high. The arc-shaped reflecting plates with different reflectivity can be replaced according to the heating requirements of different workpieces, the airflow generated by the blowing device dissipates heat of the short-wave infrared lamp, the heated airflow is blown to the workpieces, and the workpieces can also be heated.

The invention discloses a photovoltaic cell panel invisible defect detection device based on multispectral imaging. The photovoltaic cell panel invisible defect detection device comprises a photovoltaic cell panel to be detected; the excitation module is configured to enable the photovoltaic cell panel to be detected to generate a short-wave infrared band under the irradiation of an excitation light source; the excitation light source comprises a near-infrared light-induced excitation light source and / or an electroluminescent driving power supply; the spectrum acquisition module comprises a multispectral imaging system composed of a variable optical filter and an area-array camera, the variable optical filter adopts a wavelength programmable narrow-band filtering assembly, and the transmission wavelength of the variable optical filter covers a 1050-1250 nm characteristic spectrum band; and the image acquisition and processing system is configured to control switching of spectrum channels of the variable optical filter, control the area-array camera to shoot multispectral images in sequence and process the images. The device overcomes the adverse effect of the sunlight environment on photoluminescence imaging or electroluminescence imaging of the photovoltaic cell panel, so that the imaging level of invisible defects of the photovoltaic cell panel is improved.

The invention discloses a high-precision short-wave infrared hyperspectral imaging soil plastic in-situ detection method and a high-precision short-wave infrared hyperspectral imaging soil plastic in-situ detection device. The device is carried on an unmanned aerial vehicle or an indoor detection platform, large-range short-wave infrared hyperspectral imaging is carried out on soil, data are input into a multi-scale three-dimensional convolution instance segmentation network, space-spectrum dual-mode feature extraction is fused in the network, pixel-level classification of a plastic target under the complex soil background can be achieved, and the detection accuracy is improved. Even if the plastic is partially blocked or fragmented, the plastic can be effectively identified. And performing statistics on types, densities, spatial distribution and material traceability information of plastics in the soil area, and generating a plastic distribution space diagram for environmental plastic recovery path planning. Through the recognition technology, the efficient sorting capacity of the plastic packaging waste is improved, and the defect that in-situ classification recognition precision of mixed, colored or polluted plastic is poor in a traditional recycling method is overcome.

The invention discloses an inversion method for obtaining an N2O gas volume mixing ratio profile based on a short-wave infrared laser occultation detection technology. The inversion method comprises the following steps: calculating a short-wave infrared atmospheric refractive index profile at the center position of an N2O gas absorption spectral line; calculating a collision parameter profile according to the short-wave infrared atmospheric refractive index profile, respectively calculating atmospheric transmittance profiles of an N2O gas absorption spectral line and a reference spectral line based on normalized energy data of infrared laser occultation detection, and executing Abel integral inverse transformation on a difference value between the atmospheric transmittance profiles to obtain an N2O gas absorption coefficient profile; converting the N2O gas absorption coefficient profile into an N2O gas initial volume mixing ratio profile; and by taking the N2O gas initial volume mixing ratio profile as an initial value, carrying out analog calculation on an atmospheric transmittance profile after N2O gas absorption, constructing a cost function, carrying out iterative optimization, outputting an N2O gas volume mixing ratio profile, and obtaining a final inversion result. According to the method, the inversion precision is improved.