26 results about "Spectral fitting" patented technology

The invention discloses a spectrum simulation control method and system for all-weather illumination and a storage medium, and belongs to the technical field of illumination control, and the method comprises the steps: constructing a reference spectrum model with solar terms, time and weather conditions as indexes, the model being established based on multi-band solar spectrum data of a target area and associated environmental parameters; configuring a composite LED light source covering ultraviolet, visible and infrared bands, calling the reference spectrum model in combination with the current solar term, time and environmental parameters, and resolving to generate a multi-channel driving signal to drive the light source to fit a target spectrum; and closed-loop control is formed through real-time feedback and correction of the spectrum sensor. The system for realizing the method comprises a data acquisition and modeling module, a spectrum fitting and control module, a composite LED light source module and other core units. The system can reproduce a natural spectrum in a high-fidelity manner, has dynamic self-adaption, all-weather coverage and personalized adjustment capabilities, is stable and reliable in operation, and can be widely applied to various illumination scenes.

The invention provides a light spot measurement system and method. The system comprises a measurement module, a light source and a spectrograph. The light source is used for projecting a light spot to the standard mark, and the light spot and the standard mark generate relative displacement in a preset direction at a preset speed; the spectrograph is used for measuring spectral information of reflected light of the standard mark; the measuring module is used for determining the corresponding spectrum goodness of fit and the time duration when the spectrum goodness of fit is larger than a preset value in the relative displacement process according to the spectrum information collected by the spectrograph at different moments, and determining the spot size of the spot according to the time duration, the preset speed and the size of the standard mark in the preset direction. The accuracy of light spot measurement can be improved.

The present disclosure relates to a method for predicting the enthalpy of a phase change material, a near-infrared spectrum of a phase change material sample is subjected to a partial least squares regression analysis with a standard enthalpy to establish a first calibration model; then a spectral fitting residual matrix is selected according to the construction process of the first calibration model, the spectral fitting residual matrix and the enthalpy matrix are combined, and are used as input signals and teacher signals of an extreme learning machine respectively to obtain a second calibration model; through the combined application of the first calibration model and the second calibration model, the linear relationship and the nonlinear relationship between the near-infrared spectrum of the phase change material sample and the enthalpy can be comprehensively considered, the enthalpy prediction capability in a wide range is achieved, and the model prediction accuracy is improved.

The invention discloses a multifunctional spectrum lamp. Comprising a driving module, an LED light source, an aluminum substrate, a lens and an embedded software module, the LED light source is formed by four independent light source modules with different primary colors and is shaped like a Chinese character'tian ', and the LED light source is fixed on the aluminum substrate; the lens is mounted on the LED light source; the embedded software module comprises a spectrum simulation display module and a transmission module; the spectrum simulation display module is used for generating spectrum fitting data based on spectrum and photoelectric parameters input and set by each light source module, and transmitting the spectrum fitting data to the driving module through the transmission module; and the driving module is fixed on the aluminum substrate, is electrically connected with the LED light sources through the aluminum substrate, and controls and adjusts the power supply current proportion of each light source module according to the spectrum fitting data.

A method comprises obtaining, via one or more sensors positioned in a wellbore formed in a subsurface formation, a full spectrum of the subsurface formation at a first depth, wherein the full spectrum is decomposed into peak components and continuum background components. The method comprises identifying one or more elements based on the peak components. The method comprises modifying a generalized set of elemental standards to generate a constrained set of elemental standards based on the one or more elements. The method comprises performing a fitting of the full spectrum to the constrained set of elemental standards to determine an elemental composition at the first depth of the subsurface formation.

The invention belongs to the technical field of environment remote sensing and atmospheric science, and particularly relates to a methane column concentration remote sensing inversion system for eliminating an aerosol absorption effect and a method thereof. The core-shell aerosol simulation module is used for constructing a core-shell particle size structure, and SSA and ASY characteristic values under each combination are calculated by adopting a Mie theory; an aerosol lookup table construction module screens out an aerosol lookup table according to the interval constraint of SSA in a specific wave band; the SBDART spectrum simulation module reads the aerosol lookup table and the meteorological parameter file, and calculates the absorption spectrum response of the target area; the SCIATRAN input conversion module is used for processing the spectral data to generate an input data set conforming to an SCIATRAN format; and the methane column concentration inversion module combines SCIATRAN analog output and a remote sensing observation spectrum to carry out spectrum fitting and residual error optimization, and outputs a final methane column concentration estimation value. According to the method, errors caused by aerosol absorption are effectively reduced, and the inversion reliability and regional adaptability of the concentration of the methane column are improved.

The present application relates to camouflage recognition imaging system and camouflage recognition method, specifically relates to a kind of multispectral camouflage recognition imaging system and camouflage recognition method, solve the technical problems that existing camouflage recognition imaging system range of matter is small, application scene is limited, or camouflage recognition method cannot real-time imaging, real-time identification, or spectral database construction efficiency is low.The multispectral camouflage recognition system of the present application includes image acquisition unit, data processing unit and display storage unit, image acquisition unit uses snapshot type spectral imaging chip, can real-time exposure, real-time data processing;Data processing unit can obtain continuous spectral information by means of spectral fitting degree identification technology, according to the characteristic spectrum of different kinds of identification target selects feature database, changes identification target, greatly increases the identifiable spectral range.In the multispectral camouflage recognition method of the present application, spectral correction is included, can remove the interference of environmental light factor, work under different daylight color temperature.

The invention provides a spectrum fitting method, which comprises the following steps of: firstly, acquiring a target spectrum chart containing a corresponding relationship between wavelength and radiation power, identifying a target maximum peak wavelength in the target spectrum chart, and selecting a matched chip model from a preset chip data table; identifying a target secondary peak wavelength, and selecting one-to-one corresponding fluorescent powder models from the fluorescent powder data table; then, synthesizing a current spectrogram according to spectrogram data of the chip and the fluorescent powder model, and comparing optical parameters of the current spectrogram with optical parameters of a target spectrogram; if yes, trial matching succeeds; and if not, adjusting the weight of the fluorescent powder model according to a preset rule, and re-synthesizing and comparing. Compared with a traditional mode of relying on artificial experience judgment and repeated physical matching tests, the method has the advantages that the lengthy adaptation period is avoided, the material consumption is reduced, the adaptation cost is reduced, and the product research and development iteration efficiency is improved.

This invention discloses a hyperspectral image stitching method and system based on spectral fitting. The method includes extracting feature points from each hyperspectral image, matching feature points from multiple hyperspectral images, transforming feature points obtained from the feature points, constructing a spectral fitting function for the overlapping region based on the set of feature point pairs, obtaining the corresponding spectral coefficients by minimizing the spectral fitting function, calculating the new spectral values ​​of pixels in the overlapping region, keeping the non-overlapping region unchanged, and then fusing them to obtain the final panoramic image, achieving a better stitching effect.

This invention discloses a method for fitting infrared spectra of greenhouse gases based on iterative inversion of instrument line function, relating to the field of atmospheric greenhouse gas infrared spectroscopy measurement technology. This method, based on iterative inversion of instrument line function, obtains greenhouse gas concentrations and fits calibrated spectra by iteratively calibrating infrared spectral parameters and instrument line function. By acquiring dynamic conditions such as current ambient temperature and gas pressure, and combining them with absorption cross-section reference values ​​in a database, this invention can calculate the absorption cross-section value under real conditions for each wavenumber point, eliminating errors caused by fixed parameter assumptions. Furthermore, by iteratively optimizing the instrument's center wavenumber and resolution width, the matching degree between the calibrated spectrum and the actual measured spectrum is significantly improved, especially under high noise and complex multi-component interference conditions, enhancing the overall accuracy of spectral fitting and thus ensuring the accuracy and reliability of greenhouse gas concentration inversion data.

The application discloses a broadband cavity enhanced absorption spectrum system detection optimization method, medium and equipment, the method first calibrates the broadband cavity enhanced absorption spectrum detection system, obtains the effective optical path curve and the absorption cross section of the to-be-detected gas of the system, and then constructs a plurality of spectral fitting band parameters according to the intensity of the absorption peak in the effective optical path curve and the absorption cross section of the to-be-detected gas. Actual observation is carried out, and an atmospheric actual measurement spectrum diagram is obtained. The actual measurement spectrum diagram is first subjected to spectral fitting by using low-range spectral fitting parameters, and the fitting result is judged. If the fitting result is within the measurement range of the spectral fitting parameters, the result is output. If the range of the fitting result exceeds the measurement range, higher-range spectral fitting parameters are replaced, spectral fitting is carried out again, and until the spectral fitting result meets the measurement range, the result is output.

The application discloses a kind of soil organic carbon and spectral coupling generation model method and system, belong to soil remote sensing monitoring technical field.The method includes five core steps of data preprocessing, dry soil spectrum fitting, SOC mapping model construction, morphological parameter generation, spectral reconstruction and bidirectional verification.Brightness-shape-humidity (BSM) theoretical framework separates spectral brightness and shape effect, fuses random forest algorithm and double-stage hybrid optimization model, and constructs the bidirectional reversible mapping system between spectral morphological parameter and SOC content.The application breaks through the limitation of traditional technology one-way inversion, can be based on soil spectrum high-precision inversion SOC content, and can also generate high-fidelity soil spectrum according to target SOC content, has physical explainability and data-driven flexibility, solves the technical problems of cross-regional spectral deviation and lack of explainability, and provides reliable tool for soil carbon cycle remote sensing monitoring.

This invention relates to the field of spectral analysis technology, and particularly to a spectral fitting method and system for a spectrally tunable light source. The system includes a host computer and a slave computer. The slave computer includes a light source unit, a spectral sensing unit, an optical path guiding unit, a standard reference unit, a measurement platform unit, and a radiation dose monitoring unit. The host computer includes a communication control module, a data storage module, a spectral modeling module, and a fitting decision module. In this scheme, by employing staged, physically isolated spectral fitting control, the time-consuming drive search and iterative optimization process is entirely completed on the standard reference unit, with only a very small number of verification irradiations performed on the photosensitive object under test, thereby technically minimizing the light radiation interference on the object under test.

The invention discloses an advanced fitting analysis method and system for an SFG spectrum. The method comprises the following steps: after preprocessing original SFG spectral data, automatically generating an initial amplitude and a central position of a Gaussian peak in combination with data local maximum intensity within a specified search tolerance range according to a predefined peak group and a nominal center of a target peak; fitting the spectral data by using a multi-Gaussian function model and a nonlinear least square optimization algorithm to obtain fitting parameters of each Gaussian peak; refining and combining Gaussian peak parameters after successful fitting; automatically identifying and calculating the intensity of a specific key characteristic peak; and generating a detailed SFG spectrum fitting graph and a fitting parameter report. According to the method, accurate, stable and automatic deconvolution and quantitative analysis of the SFG spectrum are realized, and objective and repeatable data with deep physical and chemical significance is provided for the fields of material science, surface chemistry and the like.

The invention discloses an AI adaptive healthy lighting cooperative control system and method based on multi-modal physiological perception. The system comprises a multi-modal sensor module, an AI decision control module, a multi-channel LED driving module and a full-spectrum LED light source module. The method comprises the following steps: acquiring environment illumination intensity, color temperature, full spectrum distribution and human body existence and movement track data, and inputting the data into a pre-trained deep light color adaptation model; a pupil fluctuation response model, a spectrum fitting compensation algorithm and a crowd visual transient characteristic library are built in the model, environment parameters, human body states, time and crowd types are used as input, and cooperative control parameters of brightness, color temperature and ultrahigh frequency strobe frequency are dynamically decoupled and output. The integrated design of physiological perception, AI decision making, spectrum fitting and dynamic prediction is achieved, the visual comfort is improved, eyesight health is protected, and meanwhile energy consumption is reduced.

The invention relates to the technical field of spectral data processing, in particular to an NBI Doppler frequency shift spectrum fitting method and system for optimizing high-value region stability. According to the technical scheme, the method comprises the following steps: data loading and preprocessing: obtaining wavelength and intensity data of an NBI Doppler frequency shift spectrum, after preprocessing, identifying characteristic peaks in the spectrum, and extracting peak height, peak position and peak width parameters of the characteristic peaks; and background fitting: a final background curve is obtained by combining quadratic polynomial fitting with pure background region screening, and a pure background region is defined according to a residual error of initial background fitting. By introducing a mixed peak shape model, two-step background fitting and a differential parameter constraint and weighted optimization strategy aiming at a high-value peak, the technical bottlenecks of poor model suitability, inaccurate background estimation, high-value region easy oscillation and the like in traditional NBI Doppler frequency shift spectrum fitting are systematically solved; and the overall precision of spectrum fitting, the stability of a high-value region and the processing efficiency are remarkably improved.

This invention discloses an image fusion method for improving the spatial resolution of shortwave infrared remote sensing images, comprising: step 1, inputting remote sensing images; step 2, adjusting the spatial resolution of remote sensing image B; step 3, principal component analysis of image A; step 4, overlaying and recombining images A, C, and D; step 5, setting a virtual moving window; step 6, determining dominant ground feature pixels; step 7, calculating the spectral composition of dominant ground feature pixels; step 8, spectral fitting; step 9, spectral reconstruction; and step 10, generating a high-resolution shortwave infrared image. This image fusion method for improving the spatial resolution of shortwave infrared remote sensing images has the advantages of high fidelity, simplicity, stability, reliability, and high computational efficiency. It utilizes principal component transformation to extract high-resolution spatial information from spectral images and spectral fitting to fully leverage the spectral information of multispectral and shortwave infrared images, thus improving the spatial resolution of shortwave infrared images while maintaining spectral characteristics.

The invention relates to the technical field of optical sensing imaging, in particular to a wavelength modulation SPR (Surface Plasmon Resonance) imaging sensing system and method, and the system comprises an image collection unit which comprises an incident light path assembly, a sensing assembly and a reflected light path assembly; the temperature control unit comprises a heating element positioned on one side, deviating from the coupling prism, of the sensing chip; and the data processing unit is used for fitting the sensing surface image acquired by the surface array detector and outputting the refractive index of the liquid to be detected. By adopting the low-cost monochromatic LED array, the system cost is greatly reduced, the stability is improved, and high-precision measurement in a wide dynamic range is realized through a self-adaptive spectrum fitting algorithm of the data processing unit; the temperature control unit is used for accurately controlling the temperature field of the liquid drops and manipulating the internal flowing mode of the liquid drops, so that directional enrichment of target molecules in a preset area is realized, substrate modification or exogenous additives are not needed, and the problem of probe saturation of the traditional coffee ring effect is effectively solved.

The invention provides an H2O phase change detection method based on a pumping-sum frequency detection technology, and relates to the field of spectral analysis and precise temperature control. According to the method, a set of pumping-sum frequency detection system construction process comprising a laser emission module, a light beam modulation module, a main temperature control system, a signal acquisition system and a synchronous controller is designed, and excitation and sum frequency detection of interface water molecule vibration energy level transition are realized by using three beams of laser with specific wave bands and polarization characteristics. By accurately controlling the laser pulse time delay and condensation temperature control process, sum frequency spectrum signals of different time nodes are collected, and real-time monitoring and reconstruction of vibration spectrum dynamic evolution in the H2O phase change process are achieved by combining spectrum fitting and time sequence integration. The device has the advantages of being high in time resolution, high in spectral sensitivity, capable of obtaining molecular scale phase change information in real time and the like, and is suitable for H2O phase change condensation kinetic research, high-precision dew point measurement, humidity calibration and other scenes.

Systems, devices, and methods for scanning a laser into wings of an absorption feature; fitting a polynomial to the edges of the scan; dividing a transmitted signal by a fit-derived baseline to compute a transmission of the light; fitting a spectral model with the transmitted signal; and solving for a mole fraction.

One aspect of this disclosure relates to a computer-implemented method for assisting rendering of an image comprising at least one object on a display screen using a computer system. The method may be performed for each pixel individually. One method step involves obtaining at least three monochromatic pre-rendered pixels of the object for at least three intrinsic reflectance levels (R1, R2, R3) of each pixel from a pre-rendering algorithm. Each of the at least three intrinsic reflectance levels (R1, R2, R3) corresponds to a radiance level (L1, L2, L3) generated in the pre-rendering algorithm to constitute at least three respective control points (R1, L1; R2, L2; R3, L3) in a radiance vs. intrinsic reflectance plane, L-Rint. Some rendering algorithms indeed predict radiance levels L for a pixel. The method may further comprise the step of calculating, for a plurality of wavelengths  for a selected spectral colour for the object, a set of spectral fitting weights S derived from a reflectance level R' associated with the selected spectral colour and monochromatic fitting weights W. These monochromatic fitting weights W result from inversely fitting a curve through the at least three control points (R1, L1; R2, L2; R3, L3) in an intrinsic reflectance vs. radiance plane Rint-L. The method further comprises the step of applying the spectral fitting weights S to assist in rendering the image.

The present invention relates to a method and an apparatus for measuring the thickness d of a transparent layer (10), and in particular to a method and an apparatus for measuring the thickness d of glass plates during wet-chemical glass thinning in the manufacturing process.The method for measuring the thickness d of a transparent layer (10) includes: determining an approximate thickness dFFT based on a precisely known dispersion n(1) of the material of the layer (10) by performing Fast Fourier Transformation, FFT, analysis on Fabry-Pérot oscillation, FPO, from the layer (10) in a spectral reflectance measurement (900); and performing a FPO full-spectral fitting procedure (910-0) with the approximated thickness dFFT as starting value d0,0 to determine an initial local best fitting thickness dFPO,0. After the initial local best fitting thickness dFPO,0 has been found, the FPO full-spectral fitting procedure (910-i) may be repeated with specific alternative starting values d0,i to determine a global best fitting thickness dFPO.

The present invention discloses an X-ray measurement system and an X-ray measurement method. A light receiver (2) acquires multiple measurement signals generated by the reflection of several X-ray beams of different energies from an inspection target. Based on a target architecture of the inspection target, several fitting models are created. A spectral fitting analysis of the measurement signals is performed using these fitting models to generate several fitting results for optimization. The fitting results for optimization are then counted to generate several parameter fitting ranges.Based on the parameter fitting ranges, a set of parameters to be checked is generated, which is entered into the fitting models to check its accuracy and is adjusted based on the accuracy and the parameter fitting ranges until an optimization condition is met, where the set of parameters to be checked that meets the optimization condition is then used as an optimized fitting result.

A method comprises obtaining, via one or more sensors positioned in a wellbore formed in a subsurface formation, a full spectrum of the subsurface formation at a first depth, wherein the full spectrum is decomposed into peak components and continuum background components. The method comprises identifying one or more elements based on the peak components. The method comprises modifying a generalized set of elemental standards to generate a constrained set of elemental standards based on the one or more elements. The method comprises performing a fitting of the full spectrum to the constrained set of elemental standards to determine an elemental composition at the first depth of the subsurface formation.

The application provides a temperature measurement method and device based on single-cavity double optical comb, and belongs to the technical field of laser absorption spectrum. A single-cavity double optical comb generation module generates a probe optical comb and a local oscillator optical comb with slightly different repetition frequencies; a temperature control module makes the single-cavity double optical comb generation module work in a constant temperature environment; the probe optical comb and the local oscillator optical comb are respectively amplified and spectrally broadened; the two optical combs are combined through a 2*1 optical fiber coupler, then enter an optical band-pass filter for filtering; the filtered double optical combs pass through a gas medium to be measured, and an interference signal of asynchronous sampling between the double optical combs is obtained through a photodetector; a signal acquisition and processing module is used to acquire the interference signal filtered through an electrical low-pass filter, so that a gas absorption spectrum is obtained; finally, through frequency domain difference and time domain separation, a multi-spectrum fitting method is used to solve the gas temperature. The application combines the advantages of the single-cavity double optical comb, such as high spectral resolution, high coherence and wide spectrum, and the advantages of the multi-spectrum fitting algorithm, such as high robustness, strong anti-noise ability and strong immunity to baseline, so that the gas absorption spectrum measurement and temperature measurement are realized, and the application has a wide application prospect.

This disclosure relates to a method for predicting the octane number of gasoline. A first calibration model is established by performing partial least squares multiple regression analysis on the first near-infrared spectrum of a blended gasoline sample and its standard octane number. Then, based on the construction process of the first calibration model, the spectral fitting residual matrix and the octane number fitting residual matrix are selected and used as the input signal and teacher signal of an extreme learning machine, respectively, to obtain a second calibration model. The combined application of the first and second calibration models comprehensively considers both the linear and nonlinear relationships between the first near-infrared spectrum and the octane number of the blended gasoline sample, providing a wider range of octane number prediction capabilities and improving the model's prediction accuracy. Furthermore, selecting the absorbance in the characteristic spectral region and the standard octane number for regression analysis during the first model construction process can further improve the accuracy of the octane number prediction results.