654 results about "Reflection spectrum" patented technology

The invention relates to the technical field of filter films, and discloses a filter film thickness detection device and a detection method. The method comprises the following steps: acquiring a first parallel beam, a second parallel beam and a third parallel beam; fixing a to-be-measured filter film sample on a sample table, and measuring the to-be-measured filter film sample to obtain a reflection spectrum and an initial refractive index parameter; irradiating the to-be-measured filter film sample by using the first parallel light beam, the second parallel light beam and the third parallel light beam, dividing the measurement area into a plurality of sub-areas according to the initial refractive index parameter, and fitting by using a least square method to obtain the optimal thickness value and refractive index value of each sub-area; based on the optimal thickness value, the refractive index value and the reflection spectrum, a mapping relation between the spectral reflectivity and the thickness is established, and a target thickness distribution diagram is obtained through iterative algorithm solving and error compensation calculation. According to the invention, the problem of uneven measurement of the thickness of the large-area filter film is solved, and the precision, efficiency and reliability of thickness detection of the filter film are remarkably improved.

The invention relates to the technical field of medicine quality detection, and particularly discloses an optical detection method and system for the content of vitamin tablets. The method comprises the following steps: driving an optical fiber probe array to carry out three-dimensional multi-angle near-infrared scanning through a multi-axis mechanical arm, and collecting reflection spectrum data; a weighted spectrum is generated through derivative spectrum analysis and double evaluation, and auxiliary material noise is corrected and separated in combination with subspace projection and a dynamic kernel function; performing spectral vector projection and regression coefficient iterative optimization through an online PLS model, and synthesizing an error coefficient based on a four-level index retrieval standard library to perform dual-channel feedback; and finally, fusing the credibility weight to output a detection result of the binding confidence. The method realizes nondestructive and high-precision detection of the vitamin tablets, has the beneficial effects of multi-dimensional data fusion, dynamic error compensation and high model adaptability, and remarkably improves the detection accuracy and reliability.

The invention relates to the related technical field of semiconductor wafers, in particular to a full-automatic wafer film thickness detection method and system based on spectral reflection, and the method comprises the steps: obtaining a wafer surface reflection spectral signal, and extracting spectral feature information and wavelength parameters; identifying a polarization characteristic parameter and an interface interference characteristic parameter, introducing the wavelength parameter as an adjusting variable, determining a wavelength dependence term, and generating a global film thickness distribution map, thereby solving the problems that in a detection scene with a multi-layer film or a rough interface, the influence of an incident light polarization state on a reflection signal is not fully considered, the reflection signal characteristic extraction is distorted, and the detection accuracy is poor. According to the method, the technical problem that the film thickness obtained through reflection characteristic backstepping deviates from the actual film thickness is solved, polarization characteristic parameters and interface interference characteristic parameters are recognized, the thickness of each detection point is determined after the film refractive index is corrected, the thickness detection precision is effectively improved, and the influence of spectral signal noise and interface interference is reduced; the technical effect of accurately presenting the global film thickness distribution of the wafer film is achieved.

The invention provides a wavelength deviation compensation method and system for rapid wavelength analysis of a far-end fiber bragg grating, and relates to the technical field of fiber bragg grating sensing, and the method comprises the steps: collecting grating reflection spectrum signals of different transmission distances, carrying out frequency domain transformation to separate phase components, and building a mapping relation between the transmission distance and dispersion cumulant; calculating an initial wavelength offset estimation value; identifying a refractive index section, and establishing a segmentation compensation coefficient; constructing a wavelength-strain-temperature three-dimensional space, and optimizing a compensation coefficient according to the trajectory curvature; and updating the compensation coefficient according to the residual gradient. The wavelength analysis precision of the far-end fiber bragg grating can be improved, and the influence of dispersion on measurement is reduced.

The invention discloses a cable defect detection method and system based on double-path coupling frequency domain reflection, and the method comprises the steps: enabling a signal generator to generate two groups of correlated sine frequency sweeping signals, namely a test signal S1 and a reference signal S2; s1 is injected into the head end of the cable, and a reflected signal R1 is collected; respectively extracting the spectrum characteristics of the amplitudes and the phase differences of the R1, the S1 and the S2 by adopting a double-path signal comparison device, carrying out comprehensive judgment, and determining the reflection spectrum characteristic of the R1; the reflection coefficient spectrum is optimized through a window function, and signal features are obtained; converting the optimized frequency spectrum into a time domain reflection waveform, and extracting reflection peak time information; and calculating defect positions by combining electromagnetic wave propagation velocity. According to the cable defect detection method and system based on double-path coupling frequency domain reflection, high-precision detection of a long-distance cable is realized; and two paths of coupling signals are introduced for comparison, so that the accuracy of phase measurement is improved, and an efficient nondestructive detection scheme is provided for power grid operation and maintenance and the like.

The invention relates to the technical field of blueberry production, in particular to a blueberry sorting method, system and device and a storage medium. Real-time images of blueberries on a conveying line are collected through a preset period, and image segmentation is carried out to obtain subsets; analyzing the images in the subsets to obtain appearance features, and performing primary sorting based on the features to obtain a plurality of primary sorting subsets; then reflection spectrum information of the subsets is obtained, secondary sorting is carried out, and a plurality of secondary sorting subsets are obtained; recording transmission coordinates of the images in each secondary sorting subset, and generating a corresponding coordinate set; a plurality of parameters of the blueberries are calculated by utilizing the characteristics of size, color, surface defects and the like, the appearance quality is evaluated, refined grading is realized, grading is provided for deep processing or sales, the product value is improved, the subjectivity and inconsistency of manual sorting are reduced, and the efficiency and the accuracy are improved; the internal quality is detected by combining reflection spectrum information, and the diversified requirements of the market for the blueberry quality are met.

The invention relates to an infectious bacterium detection method and system based on double effects of a reflection spectrum and autofluorescence, and belongs to the field of biomedical detection. The method comprises the following steps: acquiring hyperspectral images of different samples under different light sources; performing data preprocessing on the collected sample hyperspectral image, realizing pixel-level alignment of the dual-effect image based on feature matching and image registration, and constructing a data set; the method comprises the following steps: constructing a wound infection bacterium detection model based on double effects of a reflection spectrum and autofluorescence, and comprising a double-branch feature extraction module which comprises a reflection branch and a fluorescence branch which are respectively used for extracting reflection hyperspectral image features and fluorescence hyperspectral image features; the redundant feature screening module screens the features extracted by the reflection branch and the fluorescence branch through a channel attention mechanism; and the feature fusion module adopts a cross-branch cross attention mechanism to fuse the features of the double branches. According to the method, learning is carried out from two physicochemical characteristics, and the effectiveness and adaptability of the technology are improved.

The invention relates to the technical field of quality detection, in particular to an agricultural product quality detection method and system. The method comprises the following steps: carrying out multi-plane spectrum scanning on an apple through a near-infrared spectrometer to obtain a reflection spectrum and carrying out baseline correction; then, analyzing the mildewing degree of the apple pulp through cellulose spectral band identification and peak intensity attenuation index deduction; thirdly, identifying a preposed abnormal spectrum risk factor based on the mildew degree data, generating a mildew preposed abnormal spectrum risk factor, and constructing a quality detection model through sequential evolution traceability association of the abnormal factor and the mildew degree; finally, the detection model is sent to a terminal to execute agricultural product quality detection. According to the invention, the quality detection technology is optimized, so that the quality detection technology is more accurate.

The invention discloses a multi-modal imaging method and system based on acoustic-thermal coupling, and relates to the field of artificial intelligence, and the method comprises the steps: firstly obtaining thermal radiation data and ultrasonic reflection data of a target equipment region, and obtaining thermal radiation embedded features and ultrasonic embedded features through feature representation learning; performing multi-stage compensation on the thermal radiation embedding characteristic to generate a thermal field compensation reference characteristic of each stage; synchronously carrying out equal-stage multi-stage compensation on the ultrasonic embedded features, coupling the ultrasonic compensation result of the previous stage with the thermal field reference features of the corresponding stage between every two continuous stages of compensation, and combining the ultrasonic embedded features and coupling output in the later stage of compensation; and finally, performing imaging by using the acoustic-thermal coupling characteristics after multi-stage compensation to obtain an acoustic-thermal coupling imaging result fusing the thermal distribution characteristics of the target equipment region and the ultrasonic reflection spectrum characteristics. According to the method, deep fusion of acoustic and thermal information is realized through multi-stage feature compensation and dynamic cross-modal coupling, and the comprehensiveness and accuracy of equipment area detection are improved.

The invention provides a decoupling and Kalman filtering temperature strain demodulation method and system for double fiber gratings, and relates to the technical field of optical fiber sensing. The method comprises the following steps: firstly, designing an FBG sensing module for measuring environment temperature change and strain information; the FBG sensing module comprises a two-channel sensing system composed of an FBG1 sensor and an FBG2 sensor, and is used for measuring environment temperature change and strain information at the same time. Then, aiming at optical signals which are acquired by the two FBG sensors and contain physical quantity information, a wavelength demodulation module is used for acquiring the central wavelength drift distance of reflection spectrums of the two FBG sensors; temperature sensitivity coefficients and strain sensitivity coefficients of the two FBG sensors are obtained, and a linear equation set is constructed for independent variation of temperature and strain to perform matrix decoupling so as to distinguish the influence of the temperature and the strain on the change of the central wavelength; and performing optimization estimation on the decoupled temperature and strain by using the prior information of the temperature and the strain and combining a real-time measurement value by adopting a Kalman filtering method.

The invention discloses a spectral polarization imaging three-dimensional reconstruction method and device based on a pixel array, and a medium, and relates to the technical field of image processing, and the method mainly comprises the steps: collecting original images, which are fixedly obtained by pixels, of corresponding spectral bands and polarization angles; extracting sub-image information under each spectral band and polarization angle according to pixel positions, and stacking to generate a four-dimensional data volume; constructing a polarization geometric model according to the four-dimensional data body, and constructing an actual expression of the linear polarization degree in combination with a Fresnel reflection theory; constructing a redundant dispersion constraint equation and a theoretical expression of the relation between the diffuse reflection spectrum polarization degree and the incident angle and the imaging target refractive index; substituting the redundant dispersion constraint equation into a combined residual function of the theoretical expression and the actual expression, and performing parameter inversion on the combined residual function; and carrying out three-dimensional shape recovery under imaging target surface normal reconstruction based on an inversion result. According to the method, time delay and space registration errors caused by time-sharing acquisition are eliminated.

The invention relates to a data analysis technology, and discloses a spectral feature and artificial intelligence fused grain heavy metal detection method and system.The method comprises the steps that a near-infrared diffuse reflection spectrum, a laser-induced breakdown spectrum and a surface enhanced Raman spectrum of a grain sample are obtained, a matrix accumulation area thermodynamic diagram is constructed according to the near-infrared diffuse reflection spectrum, and the matrix accumulation area thermodynamic diagram is obtained; the method comprises the following steps: optimizing a laser-induced breakdown spectrum based on a thermodynamic diagram of a matrix accumulation area, carrying out dual-channel spatial-temporal feature extraction on a surface enhanced Raman spectrum and the optimized laser-induced breakdown spectrum to obtain a fusion feature vector, carrying out weighted fusion optimization on the fusion feature vector based on a signal-to-noise ratio of multispectral data to obtain an optimized fusion feature vector, and finally obtaining a fusion feature vector. And carrying out migration adaptation on a pre-trained grain detection model by using a pre-marked new grain sample, and carrying out heavy metal content identification on the grain sample by using the adaptive grain detection model according to the optimized fusion feature vector to obtain a heavy metal detection result. The precision of grain heavy metal detection can be improved.

The invention discloses a method for detecting the strain of a key part of a wind turbine generator based on a temperature compensation OFDR demodulation weak fiber bragg grating array, and relates to the technical field of wind turbine generator detection, and the method comprises the steps: installing a weak fiber bragg grating sensor array at the key strain part according to the structural characteristics of the wind turbine generator, a temperature reference grating is arranged in the non-strain area or the constant-temperature area so as to monitor the temperature change in real time; a tunable laser, an optical fiber coupler and a photoelectric detector are utilized to construct an optical frequency domain reflection demodulation system, and system calibration is completed; based on an optical frequency domain reflection demodulation system, reflection spectrum signals are collected, the relation between wind turbine generator strain and temperature change is analyzed through a temperature compensation mechanism, and strain information of key parts of the wind turbine generator is obtained. According to the method, the accuracy and reliability of strain detection are effectively improved, and the problem of measurement errors caused by neglecting the influence of temperature change in a traditional method is solved.

The invention relates to the technical field of textile detection, in particular to a computer-aided textile color fastness prediction method, which comprises the following steps: acquiring multi-source data before and after a textile color fastness test through computer control equipment, including digital images, reflection spectrum data, process parameters and dye characteristic component data, carrying out pretreatment; extracting color difference features and spectrum similarity features, and screening by adopting a dimension reduction algorithm to form a core feature vector; a machine learning algorithm is adopted to construct a color fastness prediction model, parameters are optimized in combination with cross validation and an early stop mechanism, model fine tuning is executed, and a final optimization model is obtained; and outputting a color fastness grade prediction result, and carrying out spectrum similarity secondary verification. According to the method, objective, efficient and high-precision prediction of the color fastness grade of the textile is realized, and the problems of high subjectivity and low efficiency of traditional manual evaluation are solved.

The invention discloses a hyperspectral satellite target rock and mineral identification method and system based on spectral characteristic parameters. The method comprises the following steps: S1, collecting and preprocessing a standard rock and mineral reflection spectrum curve; s2, collecting a regional hyperspectral satellite image and carrying out image preprocessing; s3, identifying diagnostic spectral reflection and absorption characteristics of the target rock mine based on the standard curve; s4, screening and extracting a diagnostic spectral range of the hyperspectral satellite image; s5, calculating diagnostic spectral characteristic parameters of the hyperspectral image target rock mine; and S6, on the basis of the S5, processing the spectral characteristic parameters obtained by calculation, and realizing target rock and mine identification based on multi-dimensional diagnosis spectral characteristics. According to the method, the application potential of the hyperspectral satellite image in the field of remote sensing geology is effectively improved and the scientificity and the accuracy of the hyperspectral satellite image in large-range rock and ore recognition drawing application are improved through the target rock and ore standard spectral curve characteristic analysis, hyperspectral satellite image processing and spectral characteristic parameter estimation methods.

The invention relates to the technical field of exhibition lamps, in particular to an exhibition lamp and an exhibition method, and the method comprises the following steps: inputting preset exhibit database information, extracting exhibit numbers, material types, dominant tone ranges and size information, carrying out point-by-point scanning on exhibit surfaces, collecting reflection spectrum data, converting the reflection spectrum data into CIELAB values, and integrating the extracted information and the collected data. And establishing an exhibit basic information set. The comprehensive exhibit basic information set is established by combining the preset database information and the real-time scanning and acquisition of the surface reflection spectrum or the CIELAB value of the exhibit, so that the subsequent illumination design can be carried out based on the unique optical characteristics of each exhibit, the accuracy and pertinence of personalized illumination are improved, and the material details and color levels can be deeply revealed. Secondly, processing the optical data of the exhibit by using a preset weight set associated with a specific display target, and generating an ideal display illumination parameter including spectral distribution and a brightness value;

The invention discloses a degraded cultivated land soil organic matter three-dimensional mapping method fusing remote sensing, near-earth sensing and historical data, and relates to the technical field of digital soil mapping, the method is based on an INLA-SPDE three-dimensional model framework, remote sensing, near-earth sensing and historical data are fused, and high-precision three-dimensional mapping is achieved. The method comprises the following steps: collecting organic matter data and near-sensing visible near-infrared reflection spectrum data of different depths of a soil profile at each sampling point in a research area, then screening visible near-infrared reflection spectrum characteristic wavebands significantly related to organic matters, collecting and integrating historical data, and completing standardization processing on remote sensing and near-earth sensing data; dividing a modeling set and a verification set, calculating a range value based on a semi-variable function, determining triangular mesh parameters, and constructing an SPDE model; the near sensing data and the remote sensing data serve as covariables and are fused into the INLA-SPDE three-dimensional model, and a soil organic matter three-dimensional space distribution diagram is generated after model fitting and uncertainty is quantified. According to the method, the problem that the vertical change of the soil attribute cannot be accurately simulated by a traditional method is solved, and high-precision and high-efficiency three-dimensional mapping of the regional scale soil organic matter in the horizontal and vertical dimensions is realized.

The invention relates to the technical field of coating thickness measurement, in particular to an anti-reflection coating thickness measurement method and system based on a dual-light-path infrared reflection method, and the method comprises the steps: obtaining a reflection signal of a light beam of a measurement light path incident to the surface of a to-be-measured sample coating and a reflection signal of a light beam of a reference light path incident to the surface of a standard sample coating at each moment; performing inversion at each moment to obtain a thickness measurement value of the coating of the to-be-measured sample; collecting reflection spectrum data of the exposed substrate in real time; acquiring a spectral characteristic value and a change degree at each moment; acquiring a predicted thickness measurement error at the next moment of each moment, acquiring a base compensation factor at each moment, and evaluating whether a thickness measurement value at each moment needs to be inversely calculated again or not; if so, constructing a target function at each moment, and optimizing parameters of a Fresnel model of an inversion thickness measurement value at each moment; and carrying out inversion calculation on the thickness measurement value of the coating of the sample to be measured at each moment. The invention aims to improve the stability and precision of the thickness measurement of the anti-reflection coating.

The invention provides a semiconductor epitaxial growth control method and system, a control device and a related product, and relates to the technical field of semiconductor detection.The semiconductor epitaxial growth control method comprises the steps that reflection spectrum data is obtained in real time and analyzed to obtain an optical feature set, then the optical feature set is input into an optical transmission model for iterative optimization, and a predicted growth rate is obtained; and comparing the predicted growth rate with the target growth rate, generating deviation information, and outputting a process adjustment control instruction, so that the main control system performs closed-loop correction on the process parameters in the next process period. According to the invention, the optical feature set can dynamically represent the influence of the interface transition layer on the reflection spectrum, so that the inversion precision and robustness of the real epitaxial structure state are improved; closed-loop correction is performed on the process parameters based on the predicted growth rate, so that the growth rate drift can be inhibited in time, the process disturbance can be adaptively compensated, the manual calibration and intervention requirements are reduced, and the production stability, repeatability and batch-to-batch consistency are improved.

The invention discloses a chicken manure crude protein content detection model construction method, a chicken manure crude protein content detection system and a detection method, relates to the technical field of bioinformatics, solves the problems of high cost, serious pollution and low efficiency of an existing chicken manure crude protein content detection technology, and improves the accuracy of chicken manure resource application. The obtained sample set comprises visible-near infrared reflection spectrum and crude protein content of the chicken manure; carrying out pretreatment on the visible-near infrared reflection spectrum by adopting a plurality of pretreatment methods; screening out an optimal preprocessing method and a corresponding preprocessing spectrum by using a partial least square regression model; obtaining a characteristic wave band by using a plurality of characteristic selection methods; and based on the crude protein content and the characteristic wave band, constructing and screening an optimal chicken manure crude protein content detection model. The method provided by the invention is suitable for detecting the content of crude proteins in chicken manure by using manure resources.

The invention provides a recycled object processing method and device applied to a dustbin and electronic equipment, and relates to the field of data processing. The method comprises the following steps: acquiring reflection spectrum data, weight data and laser scanning data aiming at a target recycled object; performing feature recognition on the reflection spectrum data, the weight data and the laser scanning data to determine multi-modal features; inputting the multi-modal features into a multi-modal fusion model to obtain a classification result and a confidence score corresponding to the classification result; and a recycling instruction is generated according to the classification result and the confidence score, and the dustbin is controlled to recycle the target recycled object according to the recycling instruction. By implementing the technical scheme provided by the invention, the accuracy of treating the recycled materials is improved.

The invention discloses a chicken manure crude protein content detection model construction method, a chicken manure crude protein content detection system and a detection method, relates to the technical field of bioinformatics, and solves the problems that an existing chicken manure crude protein content detection technology is serious in pollution in the detection process, and a spectral analysis technology is serious in information redundancy during detection, high in cost and poor in model stability. The sample set comprises visible-near infrared reflection spectrum and crude protein content of chicken manure; obtaining three spectral indexes corresponding to the visible-near infrared reflection spectrum, the MSC pretreatment spectrum and the SNV pretreatment spectrum, and screening out the optimal wavelength position and the corresponding three spectral indexes; constructing a data set by using the three spectral indexes and the crude protein content, and performing fitting through multiple fitting modes; evaluating the plurality of fitting equations, and screening out an optimal fitting equation and a corresponding pretreatment method and wavelength position as a chicken manure crude protein content detection model. The method provided by the invention is suitable for detecting the content of crude proteins in chicken manure by using manure resources.

The invention discloses an equipment on-line temperature measurement monitoring method based on thermal imaging, and relates to the technical field of on-line temperature measurement. The method comprises the following steps: synchronously acquiring reflection spectrum data and infrared thermal radiation data of a target surface through an integrated spectrum sensing module and a thermal imaging module; inverting the initial emissivity of the target area according to the reflection spectrum data based on Kirchhoff's law and a pre-stored material feature library; dynamically correcting the initial emissivity to generate a pixel-by-pixel corrected emissivity matrix; and carrying out pixel-by-pixel temperature calculation on the thermal imaging original data, constructing an equipment surface temperature distribution model, and carrying out abnormity early warning according to a preset threshold value. According to the method, through deep fusion of spectrum sensing and thermal imaging data, pixel-by-pixel emissivity calibration of complex surface equipment is realized, and the temperature measurement precision and reliability are remarkably improved.

The invention provides a temperature, strain and acoustic emission measurement method and device based on a tilted fiber bragg grating. The method comprises the following steps: carrying out cladding mode and Ghost mode demodulation on a transmission spectrum of a tilted fiber grating to obtain cladding mode wavelength shift and Ghost mode wavelength shift; wherein the tilted fiber bragg grating is mounted on a target structure; the cladding mode wavelength shift and the Ghost mode wavelength shift are substituted into the two-parameter matrix and solved, and the temperature variation and the strain variation of the target structure are obtained; wherein the two-parameter matrix comprises cladding mode-temperature sensitivity, Ghost mode-temperature sensitivity, cladding mode-strain sensitivity and Ghost mode-strain sensitivity of the tilted fiber bragg grating; and the Bragg reflection spectrum of the tilted fiber grating is demodulated and analyzed to obtain an acoustic emission signal of the target structure. According to the invention, simultaneous measurement of temperature, strain and acoustic emission signals can be realized only by using a single fiber bragg grating.

The invention provides a multi-sensor fusion crop harvesting and pile-dividing cooperative control method and a multi-sensor fusion crop harvesting and pile-dividing cooperative control system. The method comprises the following steps: extracting morphological characteristics of crops from crop image data, and generating a crop maturity identification result according to a difference value between reflection spectrum data of two groups of wavebands; determining a crop quality identification result according to the morphological characteristics and the crop maturity identification result; an opening and closing control instruction is sent to a pneumatic flow guide plate at a pile separation opening corresponding to the crop quality recognition result in a multi-stage pile separation opening in the tail end of the conveying belt, so that the crops on the conveying belt are conveyed to a corresponding pile separation area; and when the pressure value of the pile dividing area is larger than a preset pressure threshold value, the harvesting speed of the crop harvesting and pile dividing all-in-one machine is adjusted according to the pressure value. According to the technical scheme provided by the invention, the shape and maturity of the crops are analyzed through the image and spectral data, piling and harvesting can be intelligently controlled, and accurate and efficient crop quality grading and harvesting management are realized.

The invention relates to a red light therapeutic instrument real-time calibration method based on multi-modal data fusion, which comprises the following steps: firstly, collecting data such as optical power, target surface temperature, internal temperature, reflection spectrum and light source-target surface distance in a time window, and unifying time base alignment; performing anomaly elimination, de-noising and normalization on each modal data, and constructing a standardized data matrix; extracting multi-modal features through power spectral density, wavelet packet decomposition, exponential moving average and Kalman filtering, inputting the multi-modal features into a fusion network containing a modal special encoder and a cross-modal attention unit, and generating a red light treatment state vector; the driving current, the pulse width, the duty ratio, the emission angle and the aging compensation factor are solved in real time through constrained least square optimization and are issued to the driving control module, and the red light source is smoothly adjusted in a soft start mode; the system monitors the output power, calibration is completed if the output power meets a threshold value, and otherwise, the next iteration is started. According to the method, power closed-loop correction can be realized, and dose consistency and thermal safety are improved.

The invention provides an all-dielectric film system structure with visible near-infrared low transmission vegetation simulation, intermediate infrared high reflection and microwave high transmission. The device sequentially comprises, from top to bottom, a visible near-infrared simulated vegetation layer which is composed of first to fourth dielectric layers and is configured to simulate vegetation reflection spectrum characteristics in a wave band of 380-2500 nm and has a low transmission characteristic; the intermediate infrared high-reflection layer is formed by alternately stacking a first dielectric layer and a third dielectric layer, and is configured to form high reflection in a wave band of 3-14 microns; and a substrate layer; the thickness of the whole film layer is far smaller than the microwave wavelength, so that the film system keeps high transmission in the microwave band. According to the invention, the amorphous InSb material with high loss characteristic in visible near-infrared light is introduced, so that the average transmissivity of 1500-2500 nm is reduced to 0.095 while high-precision simulation of the vegetation reflectivity spectrum is realized, thereby realizing simulation of low transmissivity of the wave band vegetation.

The invention provides a display control method and system for a liquid crystal display screen, and the method comprises the steps: carrying out the nonlinear spectrum mapping processing of an input RGB drive value, and obtaining a theoretical emission spectrum through combining with the response characteristics of liquid crystal molecules; calculating a reflection spectrum component in the multilayer structure according to the ambient light spectrum, and superposing the reflection spectrum component with the theoretical emission spectrum to obtain an actual observation spectrum; calculating a difference value between the actual observation spectrum and the target spectrum, and converting the difference value into an RGB correction value through a constraint optimization algorithm to obtain an RGB driving value after ambient light compensation; and calculating actual white point color coordinates, and adjusting the actual white point color coordinates to a standard white point position through a progressive white point migration algorithm. Display parameters can be dynamically adjusted according to real-time ambient light conditions, the influence of ambient light reflection on colors is effectively compensated, meanwhile, color temperature consistency and color accuracy are ensured through white point correction, the display quality under different ambient lights is remarkably improved, and the visual experience of a user is improved.

The invention discloses a comprehensive evaluation method for drought resistance of corn varieties, which relates to the technical field of corn variety evaluation, and comprises the following steps: obtaining multi-temporal multi-band reflection spectrum data under the condition of continuous drought of corn, and performing structure coupling modeling on the spectrum data in combination with the structural characteristics of corn leaf epidermis wax, so as to obtain the drought resistance of the corn varieties; constructing a time sequence curve capable of representing the dynamic change of leaf wax distribution as a dynamic spectrum monitoring baseline; differential analysis between continuous time points is carried out based on the dynamic spectrum monitoring base line, spectrum abrupt change points caused by leaf wax migration are identified, and space consistency inspection is combined. According to the method, a dynamic spectrum monitoring baseline and an energy migration fingerprint are constructed, wax migration interference is accurately identified, a spectrum stability hypothesis is broken through, high precision, self-adaption and consistency of evapotranspiration rate inversion under a drought condition are realized through multi-level correction and a closed-loop updating strategy, and scientificity and comparability of drought resistance evaluation are improved.

The invention relates to the technical field of material detection, in particular to a cross-linked polyethylene insulation material impurity full-detection device and system for a high-voltage cable and application, the detection device carries out detection based on single-row continuous flowing insulation material particles, and the detection device comprises a near infrared spectrum imaging unit, a visible light imaging unit and an image processor, and identifying black spot impurities and heterochromatic particles. The full-detection system provides a detection channel for installing full-detection equipment and comprises a current limiting pipe body and a camera obscura structure, and reflection spectrum and surface color information are collected in the camera obscura structure; the full-inspection system further comprises a buffer stock bin, a finished product stock bin, a pneumatic sorting module, a cyclone separator, a cooling fluidized bed and a metal separator. Impurity identification reliability is guaranteed through double optical detection, full-process online detection of insulation material impurities can be achieved, limitation of traditional sampling detection is broken through, full-detection coverage of insulation material particles is achieved, the impurity missing detection risk is eliminated, and the strict requirement of an ultrahigh-voltage cable for insulation material cleanliness is fundamentally met.