560 results about "Spectral imaging" patented technology

The invention discloses a dynamic path planning and self-adaptive control method and system for a coating robot, and relates to the technical field of coating automation. The method comprises the following steps: acquiring point cloud data through three-dimensional scanning equipment, constructing a dynamically updated workpiece curved surface model, and extracting curvature, edge and high-curvature mutation region features; a spraying path is generated based on a reinforcement learning algorithm, and path density, speed and coating supply are dynamically adjusted for a high-curvature area; distance, force feedback and environment parameters are fused, and mechanical arm and spray gun parameters are dynamically adjusted; dividing operation sub-areas and distributing tasks based on robot capability characteristics to realize multi-machine cooperation; and fault redundancy control and multispectral imaging are added to optimize the coating quality. The system comprises a sensing module, a decision-making module, an execution module, a redundancy control module and a communication module. According to the invention, the uniformity of the complex curved surface coating, the multi-machine cooperation efficiency and the system anti-interference capability are improved, and the method is suitable for spraying large workpieces such as aircraft fuselages and high-speed rail vehicle bodies.

The invention relates to the technical field of image processing, in particular to an image acquisition and analysis method and system, and provides the following scheme: obtaining a visible light and near-infrared multispectral image, generating a spectral difference image, and performing weighted fusion to obtain a first image; segmenting a target region based on the fused saliency map, and calculating a pixel reflectance ratio; solving a color mapping matrix according to the reflectance ratio, and carrying out color correction on the target region to obtain a standardized feature image; and extracting characteristic parameters such as spectrums, colors and textures, inputting the characteristic parameters to a multi-branch convolutional neural network, fusing the characteristic parameters through an attention mechanism, and outputting a state classification result and a quantitative index. The cross-spectral imaging difference can be adaptively compensated, and the fusion precision and the analysis stability are improved.

The invention provides a multi-source fusion spectrum cross-domain high-precision prediction method and system based on transfer learning. The method comprises the following steps: S1, acquiring spectrograms collected by a spectral imaging device under multiple wavelengths; s2, extracting various types of features from the spectrogram; s3, training a fusion model to obtain a trained fusion model; and S4, inputting a to-be-predicted spectrum into the trained fusion model, and outputting a result. According to the invention, 10 <-4 > nm-level wavelength prediction can be achieved in a common industrial camera system, and the level of a scientific research-level grating spectrometer (0.001-0.002 nm) can be reached / exceeded; on a narrow-band, middle-band and wide-band multi-scene cross-domain data set, the mean absolute error (MAE) can be reduced from the nanoscale to the magnitude of 10 <-4 > nm, and excellent robustness is kept under the conditions of noise, feature deficiency and few samples.

The invention relates to the technical field of multispectral imaging, in particular to a multispectral imaging fused pattern recognition image acquisition method and device, and the method comprises the following steps: obtaining a multiband substrate response value through a multispectral sensor, generating response difference distribution through moving average filtering, inputting cross-correlation analysis, extracting a space offset vector, and compensating displacement; after the signal intensity of the mark points is captured, Gaussian fitting is carried out to generate registration coordinates, triangular mesh division is carried out, offset is calculated, interpolation mapping is carried out, a registration error distribution diagram is generated, bilinear interpolation remapping is carried out to collect time sequence parameters, and a multispectral imaging data set is output. According to the method, noise is eliminated through moving average filtering, offset vectors are extracted in a cross-correlation mode, array displacement is compensated, mark points are positioned through two-dimensional Gaussian fitting, a registration error graph is constructed through triangular meshes, parameters are collected through bilinear interpolation remapping, geometric distortion is corrected, feature consistency and collection synchronism are enhanced, and the imaging resolution ratio and the signal-to-noise ratio are improved.

The invention discloses an intermediate infrared polarization spectrum imaging method and device. The method comprises the following steps: carrying out joint coding on an intermediate infrared light beam carrying to-be-measured target space, spectrum and polarization information by adopting an intermediate infrared polarization spectrum modulator consisting of metasurface units which are arranged in an array and have non-correlation response characteristics; projecting the coding light field to a two-dimensional detector array to generate a two-dimensional coding image under single exposure; and decoding the two-dimensional coding image through a reconstruction unit so as to reconstruct and obtain a space-spectrum-polarization four-dimensional data cube of the target to be measured. The problem that polarization information cannot be rapidly obtained in the prior art is solved, target full information can be obtained under single exposure, and the system has the advantages of being high in imaging speed, simple in structure, easy to miniaturize and the like.

The invention provides a method and system for detecting metal abrasive particle defects in lubricating oil, and the method comprises the following steps: scanning a lubricating oil sample collected by a machine by using a multispectral imaging system to obtain a two-channel image of a visible light wave band and a near-infrared wave band; the dual-channel image comprises a visible light image and a near-infrared image; respectively enhancing the visible light image and the near-infrared image, and carrying out fusion analysis on the enhanced images to obtain a dual-channel fusion image; performing window sliding on the dual-channel fusion image, and constructing a direction constraint factor; performing threshold segmentation on the dual-channel fusion image through a direction constraint factor to obtain an abrasive particle region; and an actual metal abrasive particle defect image is collected to analyze the abrasive particle area, and an identification result is obtained. By performing enhanced fusion identification on the visible light image and the near-infrared image and performing dual identification on the contour and the texture, the accuracy is improved, and the misjudgment rate is reduced.

The invention discloses an ultra-high-speed imaging device based on acousto-optic filtering modulation. The ultra-high-speed imaging device comprises a spectrum modulation system, a spectrum imaging system and a data processing system. The spectrum modulation system utilizes an acousto-optic tunable filter (AOTF) to dynamically modulate broadband continuous spectrum light, narrow-band illumination light which rapidly changes along with time is generated, and time information of a dynamic scene is effectively mapped to a spectrum dimension. And the spectral imaging system images the spectral coded dynamic scene to the hyperspectral camera to realize acquisition of spectral space-time information. The data processing system performs spectral crosstalk correction, channel separation and demosaicing reconstruction on the acquired original mosaic image, and recovers a time sequence image according to a spectrum-time mapping relation, thereby realizing single-shot superspeed imaging in a dynamic process. The device has the advantages of being simple and compact in structure, flexible in time window, high in imaging fidelity and the like, and has wide application prospects in the fields of rapid dynamics such as microfluidics, laser processing and ultrafast physics.

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 discloses a reconstruction spectral imaging system based on an electromagnetic drive Fabry-Perot resonant cavity, and belongs to the field of spectral imaging. The system comprises an optical lens group, an electromagnetic driving device, a Fabry-Perot resonant cavity, a photoelectric detection array and a calculation unit, the cavity length of the Fabry-Perot resonant cavity can be adjusted through the electromagnetic driving device. The optical lens group receives light reflected or emitted by an external to-be-measured target scene and carries out collimation processing, and then the light enters the Fabry-Perot resonant cavity. The Fabry-Perot resonant cavity screens the incident light based on the resonance condition of the cavity length of the Fabry-Perot resonant cavity, and the screened light is emitted to the photoelectric detection array; the photoelectric detection array converts the incident light intensity into an electric signal and outputs the electric signal to the calculation unit; and a spectrum reconstruction model is built in the calculation unit, and a hyperspectral image of the to-be-measured target scene is obtained by using the spectrum reconstruction model based on the electric signal. The working range and the spectral imaging precision of the spectral imaging system based on the Fabry-Perot resonator are improved, the technological requirements are reduced, and the engineering applicability of the spectral imaging system based on the Fabry-Perot resonator is improved.

The invention belongs to the technical field of component prefabrication, particularly relates to a digital twinning-based fabricated building prefabricated component production process, solves the problems of insufficient quality and low construction efficiency in the prior art, and constructs virtual mapping of a design-production-construction whole process through a digital twinning technology. The method realizes data-driven intelligent decision making and flexible production, and specifically comprises the following steps: an intelligent design cooperation stage: a complete quality guarantee system is constructed through arrangement of structures such as an AI visual detection system and a block chain traceability system, the AI visual detection system adopts a multispectral imaging and deep learning technology, and the AI visual detection system adopts a multi-spectral imaging and deep learning technology; various defects on the surface of the component can be accurately identified, a visual thermodynamic diagram is generated, and a quality closed loop is realized by matching with an automatic repairing function of a mechanical arm; the block chain traceability system links the whole process quality data in real time through an encryption technology, and when a detection value does not reach the standard, the intelligent contract automatically triggers a rectification process and locks a problem component to form a complete quality prevention and control chain.

The invention discloses a lithium battery laser welding detection method, and belongs to the technical field of nondestructive testing. The method comprises the following steps: acquiring a three-dimensional path point sequence of a to-be-detected welding seam; controlling the transient thermal excitation unit to apply transient thermal excitation along the path; a high-speed multispectral imaging unit is used for synchronously collecting the thermal radiation attenuation process of the weld joint under at least two different spectral bands, and a space-time spectrum data cube is formed; and finally, inputting the data cube into an artificial intelligence model for defect identification. The system correspondingly comprises a three-dimensional visual sensor, a transient thermal excitation unit, a high-speed multispectral imaging unit and a synchronous control and data processing unit. According to the method, different types of welding defects such as air holes and incomplete fusion can be effectively distinguished by analyzing the heat diffusion characteristic difference under different spectral bands, the interference of uneven surface emissivity is inhibited, and the online detection accuracy and reliability of the three-dimensional complex welding seam are improved.

The invention belongs to the technical field of spectrum separation identification and spatial information analysis, and discloses a flame environment-oriented multi-depth spatial spectrum light ray measurement system, which comprises a light ray collection module used for converging dynamic flame radiation light rays; the spectrum separation module is used for spatially separating a plurality of different wavelengths of the flame radiation light converged by the light collection module to form multi-wavelength radiation light with spatially separated wavelengths; the space light splitting module is used for uniformly splitting the multi-wavelength radiation light subjected to wavelength space separation into a plurality of light beams and transmitting the light beams to the multi-spectral imaging unit; the multispectral imaging unit comprises a plurality of imaging modules, and each imaging module is used for receiving radiation information of one light beam and performing imaging; and the light analysis module is used for calculating and obtaining multi-wavelength original radiation information of different depth positions of the flame. According to the invention, multi-wavelength radiation information of different depths in a flame three-dimensional space can be obtained, and a basis is provided for establishing a flame environment temperature field model.

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 relates to a spectral confocal three-dimensional shape reduction method and system based on a super-surface spectral imaging chip. The method comprises the following steps: a continuous spectrum light source device emits a continuous spectrum light beam to a dispersion objective lens, the continuous spectrum light beam is subjected to spatial separation along an optical axis direction through the dispersion objective lens and then is irradiated to the surface of a to-be-measured three-dimensional topography object, and the continuous spectrum light beam is reflected on the surface of the object; a part of the reflected light beam penetrates through a light hole of the shading plate, then irradiates a focusing lens, is focused by the focusing lens and then enters a super-surface spectral imaging chip, and the super-surface spectral imaging chip collects wavelength information; wavelength information collected by the super-surface spectral imaging chip is converted into height information, and the three-dimensional shape of the surface of the object is fitted according to the height information and the pixel position corresponding to the height information. According to the invention, the reduction of the three-dimensional morphology can be realized through one-time photographing of the simple optical system, the morphology reduction efficiency is high, and the cost is low.

The invention relates to the technical field of forestry intelligent monitoring, and particularly discloses an intelligent monitoring system for the growth condition of afforestation and greening nursery stocks based on deep learning, which is characterized in that multi-modal growth data of the nursery stocks are acquired through a multi-spectral imaging sensor, a three-dimensional laser scanning sensor and an environment monitoring sensor, and a standardized data set is formed through space-time alignment processing; extracting morphological structure and spectral response features through spatial domain and frequency domain parallel analysis, and generating multi-dimensional feature representation through cross-modal fusion; converting the parameters into growth state parameters by utilizing a feature recombination and space mapping technology; identifying an abnormal growth mode through time sequence dynamic analysis; and finally, adaptively adjusting the working parameters of the sensor according to the abnormal type to form closed-loop monitoring. The problem that an existing monitoring system cannot autonomously optimize a monitoring strategy according to the abnormal state is solved, and accurate monitoring and intelligent regulation and control of the nursery stock growth condition are achieved.

The invention discloses a multispectral imaging technology-based maintenance method, device and equipment, and the method is applied to the maintenance equipment, and comprises the steps: determining a light supplement strategy according to the environment data of a target region, and carrying out the light supplement of the target region based on the light supplement strategy; acquiring a first spectral image, a second spectral image, a third spectral image and a fourth spectral image for the target area; performing fusion processing on the first spectral image, the second spectral image, the third spectral image and the fourth spectral image to determine a spectral feature map; performing feature analysis on the spectral feature map to determine fault information in the target area; according to the method, the multi-spectral imaging technology is used for detecting the hidden defects on the surface of the equipment facility, the fault can be accurately recognized, the position and the specific type of the fault can be determined, and the recognition accuracy and efficiency are remarkably improved.

The invention relates to the technical field of aerial target identification, and discloses an aerial dynamic target accurate identification method and system. The method comprises the following steps: acquiring multi-dimensional spectral data of a target through a multi-spectral imaging device, extracting spatial distribution characteristics, establishing a three-dimensional motion track model according to the spatial distribution characteristics, and calculating an instantaneous velocity vector; a motion deviation index set is generated in combination with preset reference motion parameters, abnormal behavior categories are divided through clustering analysis, and a key frame sequence is marked; reconstructing a local motion characteristic spectrum based on the key frame sequence, extracting morphological change parameters, and inputting the morphological change parameters into a pre-trained target recognition network to obtain a type recognition result and a confidence score; when the confidence coefficient is lower than a threshold value, activating a supplementary recognition process, acquiring high-resolution texture data, and fusing the high-resolution texture data with the initial recognition result to generate a final recognition tag; and updating the feature database and adjusting the network weight according to the final identification tag.

The invention provides a polarization hyperspectral water quality monitoring system and method, and the system comprises a tower footing polarization hyperspectral imaging module which is disposed on a building beside a to-be-detected water area, and carries out the area array staring scanning of the to-be-detected water area through a polarization hyperspectral imager, so as to obtain a water body polarization hyperspectral image signal of the to-be-detected water area; the image spectral data processing module is used for deducting dark current and spurious signals from the water body polarization hyperspectral image signals, and calculating the water body spectral reflectivity of the water area to be measured according to the water body polarization hyperspectral image signals by combining a gray value and reflectivity relation model constructed by using the hyperspectral image signals of the gray scale calibration plate; and the water quality parameter spatial distribution inversion module is used for performing inversion on the to-be-detected water quality parameters of the to-be-detected water area according to a pre-constructed water quality parameter inversion model and the water body spectral reflectivity. According to the technical scheme, the integration level is high, the automation degree is high, rapid deployment can be achieved, and all-day continuous unattended monitoring can be achieved.

A method of imaging an internal surface of a conduit, the method including deploying an inspection assembly within an internal volume of a conduit, the inspection assembly having a camera and a lighting array including a plurality of light emitters; illuminating a region of interest on said internal surface using the lighting array; and capturing image data of the region of interest using the camera, the image data including spatial data and intensity data at a plurality of different narrowband wavelength ranges of light.

The invention relates to the technical field of gas monitoring, and provides a spectrum analysis-based gas leakage monitoring system, which comprises a tunable laser source, an optical curtain forming device, a scanning optical sensor, a spectrum analysis module, a three-dimensional spectrum model construction module, a leakage traceability and diffusion prediction module, an intelligent early warning module and a snapshot type multispectral imaging unit, and an open optical path and a distributed multi-node layout are adopted. According to the invention, through the steps of optical screen scanning, spectral data acquisition and processing, three-dimensional dynamic model construction, intelligent analysis leakage determination, leakage traceability visualization and adaptive learning, precise monitoring, identification, traceability and early warning of gas leakage are realized; gas identification, leakage traceability and diffusion prediction are realized based on a three-dimensional dynamic model, deep learning and fluid mechanics, the monitoring effect is optimized by adopting distributed layout and self-adaptive learning, rapid disposal is assisted by graded early warning, and the accuracy, real-time performance and safety of gas leakage monitoring are greatly improved.

The invention provides a narrow-band stacked cellulose liquid crystal quantum dot spectrum modulation system, a spectrum imaging system and a spectrum imaging method, which are used for solving the problems of narrow spectrum regulation and control wave band, wide absorption peak, low absorption efficiency, low energy utilization rate and easy generation of phase change during high-concentration doping of quantum dots in the existing liquid crystal spectrum modulation system. And high-energy-efficiency spectrum information sensing is difficult to realize. The narrow-band stacked cellulose liquid crystal quantum dot spectrum modulation system comprises N narrow-band cellulose liquid crystal quantum dot spectrum modulators which are sequentially stacked, and a plurality of quantum dot-nanocellulose liquid crystal spectrum elements are arranged on each narrow-band cellulose liquid crystal quantum dot spectrum modulator in an area array type mosaic array mode. The narrow-band cellulose liquid crystal quantum dot spectrum modulator is used for directly modulating narrow-band spectrums in the X direction and the Y direction, narrow-band spectrum regulation and control in the Z direction are achieved in combination with stacking combination of N narrow-band cellulose liquid crystal quantum dot spectrum modulators, and finally convenient modulation of multi-spectrum-band information in the X direction, the Y direction and the Z direction in the whole space is achieved.

The invention discloses a tire surface microcrack detection method and system based on multispectral imaging, and the method comprises the steps: receiving a multispectral polarization image sequence of a tire surface, and generating an initial stress feature tensor based on Mueller matrix decomposition; performing topological data analysis on the initial stress characteristic tensor, constructing a crack characteristic bar code, and decomposing the bar code structure into a plurality of persistent coherence groups; performing feature enhancement on the persistent coherent group by using a generative adversarial network, and generating a labeled training sample set; performing model training on the labeled training sample set on the basis of a visual Transform architecture to generate a micro-crack detection model; deploying the microcrack detection model, performing online reasoning on a multispectral image acquired in real time, performing crack shape parameterization in combination with a Hough forest algorithm, and generating a microcrack detection report including position, length and width. According to the embodiment of the invention, the accuracy and adaptability of microcrack detection can be improved.

The invention discloses a one-dimensional ultra-wide field-of-view ultra-high spectral resolution dispersion coherent imaging spectrometer, which belongs to the technical field of spectral imaging, and comprises a first microlens array used for obtaining incident light of a one-dimensional ultra-wide field-of-view in a horizontal plane; the plurality of optical fibers are used for transmitting incident light of a one-dimensional ultra-wide field of view; the second micro lens array is used for collimating incident light from each optical fiber into broadband parallel light beams; the grating beam splitter interferometer is used for dispersing the broadband parallel light beams into a plurality of narrow-band parallel light beams with different propagation directions; the cylindrical lens is used for converging the two paths of coherent light of each narrow-band parallel light beam to a target block of the detector, and converging the narrow-band parallel light beams with different propagation directions to different target blocks respectively; and the detector is used for obtaining a continuous broadband ultra-high resolution spectrum according to the two paths of coherent light received by each target block. According to the invention, a one-dimensional ultra-wide field of view is obtained in a horizontal plane, and ultra-high spectral resolution can be obtained.

The invention relates to the technical field of coal conveying safety monitoring, and discloses a method for detecting foreign matters on a coal conveying belt in a coal conveying system. The method comprises the steps that laser scanning point clouds and spectral imaging information are collected from multiple azimuth angles, a multi-dimensional light field model representing belt surface geometric topology and material reflection characteristics is established, and a driving motor power spectrum and a bearing vibration spectrum are synchronously obtained. And associating the multi-source information, carrying out three-dimensional dynamic reconstruction and material marking on the conveying load, and further separating out the non-coal geometry mixed in the coal flow. And performing spectral feature inversion and mechanical response simulation based on material physical attributes on the separated foreign matter geometry, and performing adaptive mode matching on the result and a non-coal substance standard feature library, thereby accurately identifying the foreign matter type and evaluating the confidence coefficient. And the mechanical arm at the designated position is triggered to execute end effector path planning according to the recognition result. According to the invention, accurate and robust detection and positioning of the foreign matters on the coal conveying belt are realized.

The invention belongs to the technical field of agricultural machinery and intelligent control, and particularly relates to an intelligent precise weeding robot based on multispectral recognition. The robot aims at solving the problems that in the prior art, due to visible light morphological recognition, the forms of crops and weeds are similar, and the recognition precision is low and the robustness is poor in the complex field environment. The robot comprises an autonomous mobile platform and a sensing operation assembly, the sensing operation assembly integrates a multi-mode sensing unit, a data fusion and decision core and a high-energy thermal ablation module, and the multi-mode sensing unit provides eight narrow-band pulse light with specific wavelengths through an active light source illumination module. Realizing synchronous acquisition of spectrum and space information by combining multispectral imaging and three-dimensional profile measurement; the data fusion and decision core performs registration, segmentation and classification on multi-source data to generate weed target coordinates; and the high-energy thermal ablation module implements 1470-nanometer laser accurate ablation based on the coordinates, and verifies the operation effect in real time through coaxial infrared thermal imaging. By means of the technical scheme, high-confidence-coefficient distinguishing and millimeter-level lossless precise weeding of crops and weeds in the complex farmland environment can be achieved.

The invention relates to the technical field of coal mining, in particular to a coal-rock interface detection device based on image recognition. According to the technical scheme, the coal rock interface detection device based on image recognition comprises a detection device body, an image recognition probe, a signal receiving module, an image analysis module, a positioning module and a mounting mechanism, the image recognition probe is arranged at one end of the detection device body, and the signal receiving module is arranged on the top face of the image recognition probe; according to the invention, the multi-modal image acquisition module, the integrated adaptive light source control unit, the multi-spectral imaging unit and the mechanical anti-shake unit are designed, and the adaptive light source can dynamically adjust the brightness according to the ambient light, so that the imaging stability is ensured; according to multispectral imaging, visible light and infrared data are synchronously collected, wave bands are switched in combination with an optical filter wheel disc, the coal rock interface spectral feature recognition capacity is remarkably enhanced, the device can still obtain high-definition and multi-dimensional images in the complex underground environment, and a reliable data basis is provided for subsequent analysis.

The invention, which belongs to the technical field of spectral imaging, discloses an ultra-wide-band ultra-wide-field-of-view high-spectral-resolution real-time imaging spectrometer comprising a first micro-lens array, a plurality of optical fibers, a plurality of second micro-lens arrays and a plurality of assemblies. First micro lenses in each column of the first micro lens array are arranged on a vertical plane arc, and micro lenses in each row are arranged on a horizontal plane straight line, so that incident light of a one-dimensional ultra-wide view field is obtained in real time; through optical fiber coupling, incident light is transmitted to the second micro lens array to be collimated into parallel light beams; according to the components, light of different wavebands is processed through the optical filter, the plane transmission grating and the detector, first-order diffraction light beams of different wavelengths in the different wavebands are received by the detector after diffraction, and space information and spectral information are obtained in real time according to an irradiated target block. The imaging spectrometer provided by the invention has the advantages of ultra-wide wave band, ultra-wide field of view, high spectral resolution, real-time measurement, compact structure and high stability, and is suitable for a remote sensing photoelectric reconnaissance detection system.

The invention discloses a spectral imaging device and a spectral image recombination method. The spectral imaging device comprises a relay lens group, a light filtering module and an imaging module which are sequentially arranged along a light path, the relay lens group is used for transmitting an optical signal emitted by the to-be-tested sample to an imaging plane of the relay lens group to form an image of the to-be-tested sample; the light filtering module is arranged on an imaging plane of the relay lens group and is provided with a linear gradual change filtering area, and the light filtering module and the to-be-detected sample image can relatively move along the working wave band change direction of the linear gradual change filtering area, so that the complete wave band range of the linear gradual change filtering area covers each spatial position of the to-be-detected sample; and the imaging module is used for acquiring the optical signal filtered by the optical filtering module and realizing spatial and spectral imaging of the to-be-detected sample. According to the spectral imaging device, efficient and continuous spectral data acquisition is realized through relative movement between the to-be-detected sample image and the light filtering module.

The invention discloses a spectral imaging calculation system based on spectral response enhancement of a color detector, and belongs to the technical field of spectral imaging, the spectral imaging calculation system comprises a birefringence light splitting module and a color detector, the birefringence light splitting module comprises a polarizer, a birefringence crystal and a polarization analyzer, the polarizer, the birefringent crystal, the polarization analyzer and the color detector are sequentially and coaxially arranged along an optical axis; the color detector is also electrically connected with a signal processing module; incident light is converted into linearly polarized light through the polarizer, the linearly polarized light is decomposed into o light and e light through the birefringent crystal, and the o light and the e light are combined into emergent light through the polarization analyzer. The emergent light passes through a color detector to obtain a measurement signal; and the signal processing module receives the measurement signal and reconstructs a spectral image in combination with the spectral response matrix of the birefringence light splitting module and the spectral response function of the color detector. The spectral response characteristics of multiple color channels of the color image sensor are combined with the birefringence color development polarization principle, the rank of a spectral response matrix is expanded, and the spectral resolution and the imaging precision are improved, so that the spectral information of a substance is more accurately acquired and analyzed.

The invention provides an electrical equipment overheating hidden danger early warning method and system based on unmanned aerial vehicle multi-spectral imaging, and belongs to the technical field of power equipment state monitoring, and the method comprises the steps: firstly obtaining ultraviolet photons and spatial point cloud data collected by an unmanned aerial vehicle; a three-dimensional model is constructed based on the point cloud, and electric field distribution information is obtained through finite element analysis. And the photon data and the electric field information are combined, and the discharge charge quantity and distribution are obtained through space inversion correction. And calculating the discharge current density by using an energy dissipation model, and determining the discharge thermal power loss density in combination with the local electric field. And finally, a steady-state heat conduction equation is solved based on the heat conduction and dissipation parameters, temperature field distribution under heat balance is calculated, and early warning information is generated when the steady-state temperature exceeds a heat-resistant threshold value. According to the invention, early-stage accurate prediction and positioning of the hidden overheating fault of the electrical equipment caused by insulation degradation are realized.