680 results about "Spectral response" patented technology

The invention discloses a visual detection system and method for tiny flaws of industrial products, and belongs to the technical field of product detection, multi-source image data of a target industrial product under multiple detection angles and illumination conditions are acquired, and an image information matrix is established; performing region segmentation and texture enhancement on the image, and extracting local texture direction inconsistency parameters; carrying out normalization analysis on the pixel ratio under different spectrum channels, and calculating a multispectral reflectance ratio abnormal index; constructing a deep convolution recognition model; reasoning the image by using the model, and outputting a defect judgment result and a confidence score; judging whether the area is a flaw area based on a dynamic threshold mechanism, and outputting a detection report containing flaw position information and a visual heat map; according to the method, multi-dimensional fusion identification of texture structure disturbance and spectral response abnormity is realized, the micro defect identification precision is effectively improved, and the method has high robustness, automation and engineering practicability and is suitable for high-precision quality control requirements of various industrial scenes.

The invention relates to an optical film detection method, device and equipment based on image processing. The method comprises the following steps: collecting multiple frames of images of a multilayer optical film under different illumination conditions, and carrying out preprocessing and characteristic value calculation on the multiple frames of images to obtain a characteristic value response matrix; calculating an optimal weight coefficient of each frame of image according to the feature value response matrix, and performing multi-frame image feature fusion to obtain integrated feature representation; performing multi-scale defect feature extraction on the integrated feature representation to obtain a defect candidate region; spectral response characteristics are extracted based on the defect candidate area, matching degree calculation is carried out on the spectral response characteristics and a preset wavelength-film thickness mapping relation matrix, and a multilayer film defect distribution diagram is obtained; and performing autoregression prediction and processing control parameter optimization on the multilayer film defect distribution diagram to obtain a closed-loop control scheme. According to the invention, accurate identification and classification of different film layer defects are realized, and closed-loop control of defect detection results and manufacturing parameter optimization is further realized.

The invention belongs to the technical field of intelligent lighting, and discloses an intelligent adjustment method and system for the spectrum of a quantum dot light-emitting lamp. The objective of the invention is to solve the problem that an existing lighting system cannot meet personalized healthy lighting requirements. The method comprises the following steps: firstly, acquiring user biological rhythm, environment spectrum, use scene, user preference and physiological health data through multi-dimensional data acquisition, and constructing a feature data set; then human factor optical feature extraction and cross-situation demand analysis are carried out, and a spectral response model is established; carrying out quantum dot material photoelectric characteristic mapping and spectrum synthesis modeling based on the model, and determining a luminescence parameter space; constructing a spectrum optimization model, performing multi-objective optimization by comprehensively considering visual comfort, energy efficiency and health influence, and generating a dynamic spectrum regulation and control strategy; closed-loop verification and adaptive optimization are carried out based on real-time physiological feedback, and an intelligent spectrum adjustment scheme is formed. According to the invention, the advantage of spectrum adjustability of the quantum dot material is fully exerted, and real personalized intelligent illumination is realized.

A method for quality inspection of an etching paste material based on a spectral response difference, including: identifying a position of density mutation boundary through spectral collection and density gradient analysis. Applying a specific frequency beam to obtain the resonance response parameter, generating stress field reconstruction data. Performing a reverse optical tracking to obtain a defect formation path, generating degradation prediction data. Establishing a self-organizing optical monitoring grid, to form a hierarchical spectral fingerprint library. Constructing a multi-point linked defect blocking network, to form an interconnected optical energy field. Monitoring a cooperative response to obtain network stability data, Identifying abnormal position coordinates based on a material quality grade and the network stability data, obtaining the abnormal position coordinates. Performing a phase adjustment to obtain a phase difference spectral set, conducting a phase comparison marking on the abnormal position coordinates, completing the quality inspection of the etching paste material.

The invention belongs to the technical field of all-dielectric metamaterial optical devices and machine learning, and discloses an all-dielectric metasurface target spectral response reverse design method based on deep learning. And realizing efficient prediction of the transmission spectrum by using a convolutional neural network-recurrent neural network-residual network architecture. A fitness function is designed, and a machinable structure is generated by aiming at single-peak and multi-peak target wavelength optimization and combining a linear and shape optimization strategy. The method breaks through the limitation of spectrum dependence and fixed structure type of the traditional reverse design, realizes on-demand design, and remarkably improves the design efficiency and processing compatibility of the integrated photonic device.

The invention relates to the technical field of spectral analysis, and discloses a method and a system for detecting the concentration of trace metal ions. The method comprises the following steps: acquiring original spectral response data of an electronic smoke sample; carrying out signal separation by utilizing a frequency domain feature extraction technology to obtain an initial spectrum data set; performing background noise filtering and baseline drift correction on the initial data to obtain a refined spectrum data set; constructing a concentration-wavelength mapping relation through absorption peak positioning and characteristic wave band screening on the basis of the refined spectrum data set; carrying out continuous time sequence sampling on the samples based on the mapping relation to generate a concentration dynamic change data set; analyzing a concentration fluctuation rule and an abnormal point in the dynamic data, and generating concentration risk assessment data; and finally outputting a time sequence detection file. According to the method, high-precision dynamic monitoring and intelligent risk assessment of trace metal ion concentration are realized, interference is effectively inhibited, and sensitivity and early warning capability are improved.

The invention discloses a liquid medicine foreign matter detection method and system based on machine vision, and the method comprises the steps: obtaining multiband spectral data of a liquid medicine sample, and carrying out the normalization processing to generate a liquid medicine background standard spectral feature template; comparing the refractive index spectral characteristics of the template and the foreign matter-containing liquid medicine, and recording the surface roughness scattering mode and polarized light reflection angle change data of a foreign matter area; calculating a spectrum peak displacement quantized value according to the polarized light data, and extracting foreign matter edge spectrum gradient information in combination with a threshold value; calculating a transparency spectral attenuation coefficient based on the edge gradient information, and obtaining spectral contrast enhancement factors of different foreign matters in combination with the spectral response characteristic data; and if the enhancement factor does not reach the standard, adjusting the spectrum correction parameter and recalculating, fusing the scattering mode and the multi-angle incident spectrum response result to carry out consistency verification, and obtaining a final identification result containing the foreign matter material type and the danger level. The method can improve the drug detection accuracy and guarantee the drug quality safety.

The invention belongs to the technical field of image recognition, and discloses a multi-modal road change detection method based on reinforcement learning optimization, and the method specifically comprises the steps: S1, designing normative natural language Prompt input and semantic analysis; s2, carrying out text semantic vectorization; s3, inputting and preprocessing road scene multi-modal data; s4, road image feature embedding and multi-modal association are carried out; s5, performing multi-modal feature alignment and dynamic fusion; s6, carrying out parameter optimization and online simulation verification on the detection model; and S7, performing multi-target reinforcement learning optimization and scene verification. According to the method, three-dimensional space structure characteristics, spectral response characteristics and long-time-sequence observation data can be cooperatively processed, adaptive optimization of detection model parameters can be achieved through reinforcement learning, the problems that a traditional method is poor in characteristic coupling and poor in dynamic adaptive capacity in a complex scene are effectively solved, and the method is suitable for large-scale popularization and application. And a novel road change detection normal form with innovativeness and practical application value is provided for the fields of urban governance and intelligent transportation.

The invention relates to the technical field of image recognition, and discloses a surface dirty image recognition method applied to a window-cleaning robot and a related device, and the method comprises the steps: carrying out the preprocessing of a multispectral image collected by the window-cleaning robot, and obtaining a preprocessed image, meanwhile, integrating a side wheel collision signal and a falling detection signal of the window cleaning robot to obtain a window boundary safety map; performing dynamic weighted mixed attention processing and convolution multi-scale stripe pooling processing under edge constraint to obtain an enhanced feature map; edge security perception smudginess segmentation is carried out on the enhanced feature map to obtain a smudginess segmentation result and an edge security region identifier, and a cleaning strategy mapping table for smudginess at different positions is established; according to the method, a dirt density thermodynamic diagram is generated, a path planning algorithm is executed, and a safe cleaning track is generated, so that stable spectral response can be obtained under various illumination conditions, and the stability and reliability of dirt recognition in different environments are ensured.

The invention relates to the technical field of photovoltaic power generation, in particular to a photovoltaic effective solar irradiance measurement method, which comprises the following steps of: converting optical power into irradiance and tracing the irradiance to an SI unit system by taking trap detection transmitted by a low-temperature radiation meter as an optical power standard device and combining a precise diaphragm; respectively collecting the output voltage of the total radiometer, the output voltage of the monitoring radiometer, the zenith angle of the total radiometer in the non-shielding state and the solar irradiance output by the absolute radiometer when the total radiometer is in the shielding state and the non-shielding state, and calibrating the total radiometer; angle response, temperature response, sensitivity linear response and spectral response data of the total radiometer and the photovoltaic module under different influence parameters are obtained, a correction coefficient set is obtained through fitting and used for conducting temperature, angle, irradiance linearity and spectral mismatch correction on the irradiance measured by the total radiometer, photovoltaic effective solar irradiance data are obtained, and the photovoltaic effective solar irradiance data are obtained. Accurate measurement of the solar irradiance for photovoltaic power generation is realized.

The invention discloses an automatic pixel calibration method for a Micro LED display screen, and the method comprises the steps: carrying out the multi-dimensional detection of the real-time brightness, color and temperature of each pixel through a high-precision multispectral sensor, obtaining the actual optical characteristics of each pixel, including but not limited to the parameters of brightness, color temperature, color difference, spectral response and the like, and carrying out the detection of the pixels; and deviation analysis: analyzing the detection data of each pixel through a deep learning algorithm, identifying brightness, color and current deviation, determining the correction demand of each pixel, and performing quantitative analysis on the deviation of each pixel. A high-precision multispectral sensor and a deep learning algorithm are introduced, so that the detection and calibration process of each pixel is more accurate. By dynamically adjusting the current output, the problems of pixel aging, uneven brightness, chromatic aberration and the like can be solved, so that the stability and consistency of the display effect are remarkably improved, and the service life of the Micro LED display screen is prolonged.

The invention belongs to the field of astronomical telescopes, and particularly relates to a large-aperture spliced telescope adjusting device and method, and the method comprises the steps: starting a light source module, providing a far-field illumination light beam for a spliced primary mirror, and carrying out the confocal adjustment of each sub-mirror through an adjusting mechanism according to the far-field illumination light beam; the light source switching module is used for providing a near-field illumination light beam for the spliced primary mirror, and the near-field illumination light beam is split into two separated sub light beams by the pyramid mirror after penetrating through a splicing seam of the spliced primary mirror; performing dispersion on all the sub-beams through a dispersion prism, and converging the dispersed sub-beams through an achromatic lens to form dispersion stripes; the phase difference of the dispersion fringes is extracted through the camera, and co-phase adjustment is carried out on the sub-mirrors through the adjusting mechanism according to the phase difference of the dispersion fringes. According to the invention, high-precision and high-flux spectral response calibration and co-phase detection of the large-aperture spliced telescope can be realized, so that reliable technical support is provided for construction and operation of a next-generation giant astronomical telescope.

The invention discloses a visible light communication data transmission method based on dynamic modulation, and particularly relates to the field of visible light technology communication. The method comprises the following steps: performing nonlinear dynamic feature extraction on an actual light intensity signal emitted by a light emitting diode to generate a spectral response feature set; performing segmented analysis on the frequency domain distortion evolution trend based on the frequency spectrum response feature set to obtain a plurality of frequency spectrum distortion subintervals; performing local modulation parameter optimization on each spectrum distortion subinterval to obtain a dynamic local modulation parameter set; mapping the dynamic local modulation parameter set into a modulation driving strategy sequence, and generating a dynamic modulation waveform signal sequence; performing detection and time-frequency feature extraction on the dynamic modulation waveform signal sequence to obtain a target signal sequence after noise suppression; and the target signal sequence is demodulated, complete data is recovered, visible light communication data transmission is completed, and the optical communication signal quality and the data recovery capability in a complex modulation environment are effectively improved.

The invention provides a consistency correction method and device based on a multi-source satellite inversion water color index, and the method comprises the steps: converting the surface reflectance of a multi-source satellite sensor of a target water area into remote sensing reflectance, and carrying out the water body range extraction of the multi-source satellite sensor, so as to determine the water body range, carrying out multi-class interference pixel removal on the image of the surface reflectance in the water body range to obtain effective remote sensing reflectance; calculating a chromaticity angle inverted by the multi-source satellite sensor based on the effective remote sensing reflectivity and a CIE chromaticity system; performing spectral response correction on the chromaticity angle inverted by the multi-source satellite sensor based on a polynomial spectral correction model constructed by the water optical simulation data set; performing system deviation correction on the chromaticity angle of the multi-source satellite sensor after spectral response correction by a cross calibration correction model established based on the synchronous observation data of the multi-source satellite sensor; and determining the water color index of the target water area based on the chromaticity angle after system deviation correction.

The invention provides a photovoltaic module damage intelligent detection method and system based on an unmanned aerial vehicle image, and relates to the technical field of unmanned aerial vehicle image.An unmanned aerial vehicle collects a multi-angle high-altitude image of a photovoltaic module array according to a predetermined path and records geographic position information; image splicing and overlap region correction are carried out by using the information to form a high-resolution panoramic image; in combination with a pre-constructed three-dimensional topological structure model, identifying and marking photovoltaic modules in the panorama, and generating a module distribution diagram; by analyzing the actual spectral response characteristics of each component, comparing standard data in a material science database, and screening suspected damage areas; applying an adaptive threshold algorithm and morphological operation to the areas to generate a feature map; and integrating real-time environmental factors and historical performance changes, extracting target features influencing the performance reduction of the photovoltaic module, predicting a damage state, and finally generating a detection report. According to the invention, the detection efficiency of the photovoltaic module is improved.

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 discloses a liquid crystal display brightness adjusting system and method based on ambient light perception, and the system comprises a high-precision ambient light sensor which obtains the ambient light illuminance and color temperature data in real time; the analog-to-digital converter is used for converting the analog optical signal into a digital signal; an embedded microcontroller; the temperature sensor is tightly attached to the liquid crystal panel backlight unit; and the control input end of the liquid crystal driving chip is connected with the driving signal output end of the embedded microcontroller through a serial peripheral interface bus. The technical normal form of a liquid crystal display dimming system is fundamentally reconstructed: in a physical layer, photoelectric signals and human eye spectral response offset are corrected through a spectral separation mechanism, a carrier recombination effect is inhibited based on a thermodynamic equation, and the physical authenticity of brightness output is ensured; in a control layer, a motion state compensation model and a spatial topology perception algorithm are constructed, and brightness space-time consistency control in a dynamic scene is realized.

The invention relates to the technical field of image recognition, in particular to an unmanned aerial vehicle tracking system and method based on image recognition, and the system comprises a spectrum optimization module, a trajectory analysis module, a form adjustment module, a flight anomaly detection module and a tracking optimization module. According to the method, the brightness information of the ambient light and the reflected light of the unmanned aerial vehicle is finely analyzed and the spectral response of the image is adjusted, so that the image definition is greatly improved, the unmanned aerial vehicle can be accurately identified under various illumination conditions, and the flight path of the unmanned aerial vehicle is calculated in real time by accurately analyzing the image bounding box and timestamp information of the unmanned aerial vehicle. According to the method and the system, the tracking process is ensured to be continuous and accurate, any form change is effectively captured by continuously monitoring the form of the unmanned aerial vehicle in continuous image frames, the behavior mode change of the unmanned aerial vehicle is responded in time, and in the aspect of flight abnormity monitoring, behaviors inconsistent with a conventional flight mode can be accurately analyzed, and potential security threats can be identified in time.

The invention discloses a depth and color fused true color three-dimensional point cloud acquisition method and system, and the method comprises the steps: setting a plurality of lasers to emit specific spectrum laser, enabling the specific spectrum laser to be reflected by the surface of an object, and filtering the specific spectrum laser through a narrow-band optical filter of a corresponding wave band, thereby enabling a corresponding sensor to only receive a single-spectrum laser line emitted by a corresponding laser emitter. A laser center point position and an intensity response value are extracted through a sub-pixel-level laser line refinement technology; calibrating the unified measurement coordinate system through sensor pose calibration; according to the light transmittance of an optical filter, spectral response characteristics of an image sensor and the like, correcting and compensating the intensity response value, calculating a compensation factor to obtain a color value of a measurement point, fusing a three-dimensional coordinate with corrected color information, outputting true color point cloud data, and presenting depth and color information of an object at the same time. The three-dimensional information and the color information of the object are synchronously obtained, so that the measurement data contain rich spectral characteristics.

The invention relates to the technical field of photoelectric detectors, and discloses an infrared photoelectric detector which comprises a bottom layer, a heterojunction and a top layer which are sequentially stacked from bottom to top, the bottom layer is used for being electrically connected with a first electrode, the top layer is used for being electrically connected with a second electrode, the heterojunction at least partially covers the bottom layer, and the top layer is used for being electrically connected with a second electrode. The top layer at least partially covers the heterojunction, the top layer at least partially has light transmittance, and the heterojunction comprises a narrow band gap material layer. By means of the mode, the infrared photoelectric detector can achieve infrared detection which does not need complex refrigeration equipment and is high in response speed, wide in polarization response and spectral response range and high in stability.

The invention provides a parameter correction method and system for tunnel dynamic lighting environment simulation, and relates to the technical field of tunnel lighting detection. The method comprises the following steps: collecting tunnel pavement optical data, lamp operation state data, external daytime brightness data, traffic parameter data and environmental parameter data; estimating an initial parameter set based on the data and a preset scattering / reflection model; obtaining and normalizing an actual measurement illumination field according to the measurement geometry and spectral response; constructing a tunnel three-dimensional illumination simulation model, and generating a simulated illumination field; and comparing the corrected illumination field with the simulated illumination field, calculating a difference index and iteratively optimizing parameters until the difference converges, and obtaining a final corrected parameter set. According to the invention, the accuracy, adaptability and energy efficiency level of tunnel lighting simulation and regulation are improved.

The invention discloses a method and a system for identifying an anti-counterfeit label. The method comprises the following steps: acquiring spectral response characteristics of the anti-counterfeit label to be identified through a multiband optical sensor; extracting a dynamic coding area and a base material characteristic area in the spectral response characteristics, wherein the dynamic coding area comprises topological distribution information of a programmable encryption particle array; processing the topological distribution information of the dynamic coding region through a feature compression algorithm to generate a first verification factor, and extracting a spatial frequency feature of the base material feature region as a second verification factor; and uploading the first verification factor and the second verification factor to a cloud verification platform through a secure communication protocol, wherein the cloud verification platform is internally provided with a dynamic spectral feature library and a physical feature association model. According to the invention, through a double-engine architecture of programmable dynamic target and environment adaptive verification, the problems of static replicability and environment vulnerability of physical anti-counterfeiting are solved, and collaborative rise of anti-counterfeiting strength and use reliability is realized.

The invention relates to the technical field of industrial vision multispectral imaging detection, in particular to a defect detection method and system based on multispectral fusion imaging, and the method comprises the steps: synchronously collecting a multi-channel spectral image of the surface of an object to be detected, and generating an enhanced feature map fusing multispectral information; identifying and preliminarily marking a suspected defect region by applying a region segmentation algorithm based on anomaly detection; extracting a multi-dimensional spectral response curve of each region in each original spectral channel, and constructing a spectral feature vector; matching the vector with a standard template of a pre-established defect spectral feature database, and classifying and confirming defect types; and carrying out contour refined analysis, calculating the geometric dimension and position of the defect, and generating a structured detection report. According to the method, the sensitivity of defect detection and the classification accuracy are improved through accurate matching of multispectral fusion and spectral features, and automatic and high-precision defect identification is realized.

The invention provides a light source control method and system based on data analysis, and the method comprises the steps: carrying out the multi-channel spectral characteristic collection of an LED light source through a spectrum analyzer array and an optical fiber probe, obtaining a spectral response curve and an interference image, carrying out the multi-scale analysis processing, and generating a multi-dimensional data tensor; performing interference mode and defect signal decoupling analysis on the multi-dimensional data tensor to obtain an interference mode feature and an interference-defect discrimination result; performing spatial distribution analysis on the interference sensitivity of the wafer surface by adopting preset kernel density estimation and a graph neural network according to the interference mode characteristics and the interference-defect judgment result, and generating an interference sensitivity distribution matrix; according to the interference sensitivity distribution matrix, the current waveform and light beam phase distribution of the LED light source are accurately modulated, intelligent control over the LED light source is achieved, the influence of multi-mode interference on semiconductor detection is effectively eliminated, and the accuracy of nanoscale defect detection is improved.

The invention discloses an optical metasurface structure parameter design model training and application method and a related device, and relates to the technical field of nanometer photonics nanometer structure design, the method comprises the following steps: obtaining a data set, the data set comprises multiple groups of sample data of each optical metasurface in a plurality of optical metasurfaces, the sample data comprises a sample structure name, a sample structure parameter and a sample spectral response, word embedding and position code embedding are respectively carried out on the sample structure name and the sample structure parameter to obtain an embedded sample structure name and an embedded sample structure parameter, a feature extractor is further utilized to extract and obtain a fusion feature, and the fusion feature is extracted to obtain a fusion result; and taking the fusion features as input, generating an embedded sample structure parameter predicted value by using a structure parameter generator, subsequently calculating total loss, and performing iterative updating based on the total loss until training is completed. The method can be suitable for design of structure parameters of optical metasurface of different structure types and different spectral targets, and generalization ability is improved.

The invention discloses a PVC film coating uniformity detection method based on spectral analysis, and relates to the technical field of optical detection, and the method comprises the following steps: S001, adopting a controllable incident illumination system with a multi-angle rotation function to carry out continuous angle scanning on the surface of a PVC film, collecting reflection spectrum intensity data in a corresponding wave band range according to different incident angles, and generating a spectrum data matrix containing interference characteristics; and S002, carrying out continuous wavelet transform processing on the spectral data matrix, carrying out multi-scale local decomposition on a spectral response signal, extracting and separating a periodic interference characteristic signal, and obtaining a purified spectral matrix after interference reduction. According to the method, through multi-angle spectrum collection and interference feature stripping, accurate identification of a coating thickness abnormal area and combination of strength indexes, spraying parameters are regulated and controlled, a detection-compensation-reinspection closed-loop mechanism is constructed, interference misjudgment is effectively avoided, and the accuracy and regulation and control efficiency of uniformity detection of the PVC film coating are improved.

The invention relates to the technical field of display screen defect visual inspection, in particular to an LED display screen defect visual inspection method and system, and the method comprises the following steps: collecting an image of an LED display screen; performing gamma correction and noise suppression on the image of the LED display screen to obtain a preprocessed image; local contrast enhancement and adaptive threshold segmentation are applied to the preprocessed image, and candidate abnormal areas are identified; for the candidate abnormal region, extracting at least one dimension feature which comprises at least one of brightness, color, texture, edge gradient and spectral response; processing the at least one dimension feature based on a preset discrimination rule so as to distinguish real microdefects, optical artifacts and digital artifacts of the LED display screen; and outputting the type, the position and the confidence of the defect obtained by distinguishing. The detection accuracy and reliability are improved.

The invention discloses an indicator light multi-state cascade identification method based on a deep learning shared network, and belongs to the field of intelligent inspection of power equipment. According to the method, low-order textures and spatial features of an image are extracted through a unified convolutional neural network, and a shared feature map is formed; a channel separation mechanism is adopted, the shared feature map is distributed to color recognition and state detection parallel branches according to dimension weights, the form discrimination branch on the uppermost layer analyzes geometric contour features through a full-connection layer, and circular / strip-shaped classification is achieved; the color identification branch adopts a dual-channel convolution kernel to respectively strengthen red / green spectral response, and color judgment is completed through feature map comparison; state detection branches fuse space pooling and brightness statistical analysis, and a decision boundary of an on-off state is established. According to the method, parameter redundancy can be reduced, the identification precision of each sub-task is improved, and the requirement of the inspection equipment for real-time judgment of a multi-dimensional state is met.

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 laser broken line rapid identification method for a spinning process, relates to the field of spinning detection, and is used for solving the problem of high identification error rate in a multi-material blending and frequent line changing environment. A multi-channel optical behavior characteristic matrix is formed by constructing a broken line recognition mechanism based on material perception and light intensity behavior characteristic collaborative modeling, collecting light intensity response data of yarn channels, constructing a dynamic detection sequence and extracting characteristics such as shielding amplitude gradient and recovery time delay. A yarn material identifier is introduced, a spectral response template is matched, a broken yarn judgment threshold group is generated, whether shielding sudden change and delay recovery characteristics are met or not is judged in combination with a detection sequence, a broken yarn event is accurately recognized, and recognition parameters are corrected in real time according to the shielding edge change rate and fluctuation stability in light intensity changes before and after yarn breakage. The dynamic optimization of the broken line judgment condition is realized, and the recognition precision and the response speed are improved.