796 results about "Absorbance spectra" patented technology

The invention discloses a ppb-grade methane gas online detection method, equipment, a medium and a product, and relates to the field of data processing. The method comprises the following steps: acquiring an infrared absorption spectrum signal, and obtaining original spectrum data; performing multi-scale noise separation and baseline correction on the original spectral data to obtain de-noised effective spectral features, and extracting methane specific absorption peaks from the de-noised effective spectral features; comparing the methane specific absorption peak with the interference gas spectral line through a multi-spectral line weight matching algorithm to obtain methane characteristic intensity; carrying out self-adaptive calibration on the methane characteristic intensity according to the drift compensation model to obtain calibrated characteristic intensity; obtaining a ppb-level methane concentration value through a concentration inversion model; and inputting the sorted concentration time sequence data into an anomaly detection model to detect a methane leakage event. By designing signal processing and algorithm analysis, the dependence on equipment hardware performance is reduced, and the use cost of ppb-level methane gas detection is reduced.

The invention relates to the technical field of water pollution detection, in particular to a water quality pollution multi-dimensional analysis system which comprises the following steps: synchronously measuring an ultraviolet-visible absorption spectrum of a water sample to be detected and scattered light intensity in an orthogonal direction, and deducting spectrum baseline interference caused by suspended particulate matters in the water sample through a correction algorithm; the interferents in the water sample are selectively converted and degraded by applying a programmed potential to the inflowing water sample to be detected; the reverse pulse is periodically applied, so that the online regeneration function of the electrode is realized; analyzing the spectral data by adopting a multivariate correction algorithm, and calculating the concentration of the target pollutant; the calculation residual error of the multivariate correction algorithm is analyzed, new interference and system performance drift of current measurement are diagnosed, and a corresponding system state code is generated; and responding to the system state code, automatically starting and carrying out state checking and multi-point calibration on the instrument, and using a calibration result to update the analysis model. Through multi-dimensional perception and closed-loop operation, accuracy and reliability of water quality monitoring are guaranteed.

The invention relates to the technical field of mine safety, and discloses a coal mine underground gas monitoring method and system. The method comprises the following steps: acquiring methane absorption intensity data by adopting a tunable diode laser absorption spectrum, converting the methane absorption intensity data into gas concentration based on a Lambert-Beer law, performing temperature and humidity compensation, calculating a transmission priority according to concentration deviation to form a data packet, and establishing a spatial interpolation model by utilizing multipoint data to predict gas concentration distribution. Calculating a risk assessment index based on the predicted distribution, automatically adjusting the rotating speed of the ventilator, and controlling the electrical equipment to be powered off. According to the method, the technical problems of low detection precision, incomplete monitoring coverage, low data transmission efficiency and lack of prediction and early warning capabilities in the existing underground coal mine gas monitoring method are solved. And the accuracy of gas concentration detection and the intelligent level of gas monitoring are improved.

The invention relates to the field of data management, in particular to a VOCs pollution working condition data treatment method based on artificial intelligence. The method comprises the following steps: firstly, constructing a three-dimensional model of a factory, a pipeline and treatment equipment based on a BIM tool and a GIS technology, and deploying an Internet of Things sensor to collect VOCs pollution data; collecting original infrared absorption spectrum data of VOCs, and performing component identification by using a non-negative matrix factorization algorithm; a machine learning model is trained in combination with historical data, and short-term emission prediction is carried out; cooperative scheduling is carried out on the governance equipment through a multi-agent game optimization algorithm, and an optimal operation scheme is generated; constructing volume cloud modeling, and dynamically displaying an optimization effect; and if the predicted emission exceeds the standard, performing emission abnormity traceability analysis by using a graph neural network, and outputting a fault diagnosis report. According to the method, the VOCs emission prediction precision and the treatment efficiency are effectively improved.

The invention discloses a ship carbon emission on-line monitoring method, device and equipment, and the method comprises the steps: building a comprehensive emission feature library through collecting infrared absorption spectrum, gas flow and other multi-source emission signals in a ship operation process; eliminating gas cross interference by adopting a spectrum separation analysis technology, and establishing a concentration inversion mechanism to generate an independent monitoring domain; high and low emission working condition modes are identified through working condition relevance evaluation, and intelligent allocation of monitoring resources is achieved; marine environment compensation nodes are established, layered temperature and humidity correction control is implemented, and environment-adaptive ship environment parameters are generated; the multi-stage early warning trigger time is determined by adopting an early warning threshold backward deduction analysis technology, a ship emission monitoring time sequence table and a graded monitoring instruction set are constructed, full-working-condition, all-weather and high-precision intelligent monitoring of ship emission is realized, and reliable technical guarantee is provided for ship environmental protection compliance and marine environmental protection.

The invention discloses a spectrum aliasing decoupling and concentration inversion method under the cross influence of multi-source environmental factors, belongs to the field of industrial process control and environment monitoring, and constructs an environment-spectrum collaborative fusion decoupling model for concentration prediction. The method specifically comprises the following steps: respectively collecting absorption spectrum signals of specified mixed gas at different temperatures, pressures and known concentrations, meanwhile, collecting environmental parameter data, constructing a multi-source data set, and carrying out denoising, dimension reduction and preprocessing on the multi-source data set; constructing a self-supervised feature extraction network for adaptive modulation of environmental parameters to realize deep fusion of spectrum and environmental information; the feature expression capability and generalization performance of the self-supervised feature extraction network are improved by using a self-supervised learning mechanism; and constructing a BPBO-GRNN self-adaptive concentration inversion optimization model for realizing inversion of mixed gas concentration and self-adaptive optimization of model parameters. According to the invention, high-precision concentration inversion and stable detection of the aliasing gas can be realized.

The invention belongs to the technical field of flow field optical measurement, and particularly relates to a high-enthalpy plasma gas temperature measurement method, system and device based on an absorption spectrum. Generating a composite modulation signal through a high-frequency sine wave and a low-frequency sawtooth wave, and enabling incident light to pass through a flow field measurement area in parallel through laser modulation and beam shaping; the detector receives the transmission light and converts the transmission light into an electric signal containing harmonic information, the signal acquisition device is used for performing signal acquisition, the phase-locked demodulation algorithm is used for extracting second harmonic, and the temperature is inversely deduced by combining the double-spectral-line temperature measurement method and the Fourier coefficient amplitude ratio of the second harmonic with the HITRAN database. The system comprises a signal driving module, a laser emission module, a detection acquisition module and a temperature measurement module. The device is composed of a signal generator, an in-phase adder and the like, and a laser is matched with a driving power supply to guarantee stable work. According to the scheme, aiming at the problems of weak signal absorption and insufficient signal-to-noise ratio under complex working conditions, the measurement accuracy and reliability are improved by composite modulation, harmonic extraction and a bispectral line algorithm, and an effective means is provided for research on thermal characteristics of the high-enthalpy plasma.

The invention discloses a water sample pollution traceability analysis method fusing absorption-three-dimensional fluorescence spectrum characteristics, and relates to the field of water sample spectrum analysis traceability. According to the method, high-precision prediction of pollutant indexes is realized by utilizing multi-dimensional information of a three-dimensional fluorescence spectrum and an absorption spectrum of a water sample, qualitative and quantitative traceability of main pollution components and potential emission sources in a water body is carried out based on correlation analysis of the prediction indexes, a pollutant feature library and an emission source database, and the method has the advantages of high accuracy and high accuracy. The integration of water quality monitoring and pollution source management is realized, and a systematic and real-time technical means is provided for pollution analysis of a complex water body.

The invention provides a mineralogical substance composition testing method and system based on multispectral data fusion. The method comprises the following steps: separating out a first characteristic interference signal caused by the oxidation state of an iron element and a second characteristic interference signal caused by the oxidation state of a manganese element by adopting wavelet transform in a superposition region of a Raman spectrum signal and a visible light absorption spectrum; performing spatial weighting on the intensity of the first feature interference signal and the intensity of the second feature interference signal to construct a multi-dimensional feature vector, inputting the multi-dimensional feature vector to a pre-trained residual neural network, and combining a radioactivity attenuation parameter measured by a gamma spectrometer to determine the radioactivity attenuation of the first feature interference signal and the second feature interference signal. And generating a mineralogical substance composition test result containing a mineral phase, an isomorphic substitution ratio, color cause analysis data and a radiation safety level. According to the method, the collaborative interpretation of the multispectral data and the radiation parameters can be realized, the mineral component analysis precision is improved, the color formation mechanism is synchronously analyzed, and the radioactive risk level is quantitatively evaluated.

The invention discloses a mixed gas absorption spectrum analysis method and system based on variational mode decomposition, specific laser is injected into an optical resonant cavity unit, and a detector unit continuously monitors the light intensity change and records a light intensity attenuation signal; pre-processing the recorded light intensity attenuation signal; carrying out VMD decomposition on the preprocessed ring-down signal to obtain a plurality of IMF components, respectively introducing CO2 and CO gases with known concentrations into the optical resonance unit, and recording spectral data of each single gas component; calculating the similarity and contribution degree of each IMF component, and setting a weight combination to form a joint score; the gas with the highest joint score is selected, the score is compared with an adaptive threshold value, and when the score is higher than the adaptive threshold value, the IMF component is marked as the characteristic component of the corresponding gas; and finally, gathering and outputting the marked IMF components according to gas types to obtain characteristic signals of the gases, thereby realizing multi-component gas separation in the mixed gas absorption spectrum.

The invention discloses a detection system of an absorption spectrum water quality multi-parameter analyzer, and relates to the field of water quality detection. Comprising a water sample acquisition and self-adaptive preprocessing module, a full-spectrum dynamic acquisition and waveband optimization module, a multi-dimensional data fusion processing module, a dynamic evolutionary model training and optimization module, an intelligent pollution traceability and parameter inversion module and a real-time decision and early warning response module. According to the detection system of the absorption spectrum water quality multi-parameter analyzer, through multi-dimensional data fusion, a dynamic evolution model and a spectrum fingerprint traceability technology, the pollutant concentration can be accurately inverted, the pollution source can be rapidly positioned, and the diffusion trend is predicted in combination with hydrological-meteorological data; graded early warning and customized disposal suggestions are synchronously generated, and the environmental protection supervision platform and the treatment terminal are linked through the Internet of Things, so that closed-loop response of detection, source tracing, early warning and disposal is realized.

The invention relates to the technical field of water vapor concentration detection, and discloses a water vapor concentration online detection method and system based on a multi-wavelength infrared absorption spectrum, and the method comprises the steps: controlling an infrared light source module to emit pre-modulated light, enabling the pre-modulated light to pass through a gas chamber module, inputting the pre-modulated light into a photoelectric detection module, and converting the pre-modulated light into a sample electric signal; acquiring temperature data and pressure data at a preset position of the air chamber module in real time; calculating to obtain an initial differential absorption signal by using the sample electric signal and combining a Lambert-Beer law; based on the temperature data and the pressure data, performing temperature and pressure dynamic compensation on the initial differential absorption signal by using a pre-stored compensation database to obtain a target differential absorption signal; and determining the water vapor concentration according to the target differential absorption signal. According to the invention, the effects of improving the measurement precision and the measurement stability of the water vapor concentration and measuring the water vapor concentration online in real time can be achieved.

The methods described herein provide improvements in composite infrared absorption imaging. The scanning approach described herein reduces erroneous measurements caused by thermal drift and optical interference that occurs between light scattering from the top surface of the sample and light scattering from the underlying substrate. Embodiments described herein relate to imaging and spectroscopy, and more particularly, to improvements in photo-thermal imaging and spectroscopy systems, and techniques for obtaining spectral information characterizing optical properties and / or materials or chemical compositions of a sample, such as information related to infrared (IR) absorption spectroscopy.

The invention discloses a natural gas calorific value test result correction method, system, equipment and medium, and relates to the technical field of natural gas analys.The method comprises the steps that according to the initial calorific value, the carbon dioxide content and the relative density obtained through testing and pressure data and temperature data of a test point, the first nitrogen content is obtained through calculation based on an S-GERG88 state equation; calculating a first calorific value by using the first nitrogen content and the initial calorific value, and performing iterative calculation according to the first calorific value to obtain a second nitrogen content until the absolute value of the difference between the second nitrogen content and the first nitrogen content is smaller than a preset value; determining the first calorific value corresponding to the obtained second nitrogen content as a target calorific value; through an iterative algorithm, the accuracy of a natural gas calorific value test result and a natural gas working condition compression factor calculation result through the laser absorption spectrometry can be greatly improved, and then the path reliability and applicability of natural gas energy metering through the laser absorption spectrometry are improved.

The embodiment of the invention provides a switch cabinet partial discharge quantum sensing monitoring device. The device is applied to the technical field of power equipment monitoring, and comprises a light path regulation and excitation module which is used for generating and beam-splitting detection laser of a quantum sensor coupled to each Rydberg atom; the quantum electromagnetic induction module acts on Rydberg atoms and a partial discharge electromagnetic field, and fluorescence or absorption spectrum characteristics of atomic energy level transition are changed; extracting a weak discharge signal, and converting the weak discharge signal into an analyzable electric signal; the signal processing and diagnosis module is combined with spatial information acquired by a quantum sensor of doydberg atoms in a distributed manner, and a time-frequency analysis and pattern recognition algorithm is adopted to extract discharge characteristic quantity; partial discharge positioning, type identification and insulation state evaluation are realized based on the parameters, and a real-time monitoring result and early warning information are output. In this way, through deep fusion of quantum sensing and advanced signal processing, a high-precision and high-reliability technical solution is provided for power equipment state monitoring.

The invention relates to the technical field of chemical or physical testing, in particular to a differential absorption spectrum-based respiratory inflammation marker detection system, which comprises the following steps of: determining an effective spectrum interval of an original spectrum curve by using a marker wave band of a marker to be detected; splitting the effective spectral interval by using a wavelet basis to obtain a plurality of spectral decomposition hierarchies; determining the separation effectiveness of the spectral decomposition hierarchy waveform by using the difference of adjacent data points in the spectral decomposition hierarchy waveform and the difference of frequency peak values of adjacent spectral decomposition hierarchies; determining an effective hierarchy in the spectral decomposition hierarchy by using a differential value of the separation effectiveness sequence; and determining a target filtering frequency threshold value by utilizing respective separation effectiveness of the effective hierarchy and the current spectral decomposition hierarchy corresponding to the effective hierarchy, and further filtering the spectral decomposition hierarchy to obtain the content of the to-be-detected marker. According to the technical scheme, the accuracy of detecting multiple gas markers caused by inflammation of the respiratory tract is improved.

The present invention relates in one aspect to an absorption spectroscopy apparatus for measuring one or more gases in an atmosphere, wherein the apparatus comprises a wavelength-tunable laser source, a control circuit configured to provide an electrical drive current to the wavelength-tunable laser source; wherein the control circuit is configured to create the electrical drive current as a modulated drive current, wherein the modulated drive current alternates between at least a first and a second drive current, the first drive current configured to cause the wavelength-tunable laser source to emit laser radiation at a first wavelength and the second drive current configured to cause the wavelength-tunable laser source to emit laser radiation at a second wavelength, different from the first wavelength, and wherein the modulated drive current defines a sequence of pulses, each pulse having a non-rectangular pulse shape.

The present invention discloses a multi-component gas concentration detection system, which relates to the field of gas concentration detection, and comprises: a light source, which is used for emitting detection light covering the absorption wave band of a target gas; the light splitting assembly is used for dispersing the detection light and at least splitting the detection light into a first light beam and a second light beam; the air chamber is provided with an optical signal detection module and an acoustic signal detection module; the first light modulator is used for carrying out wavelength selection and modulation on the second light beam; wherein the first light beam is received by the light signal detection module to form an absorption spectrum detection light path; the second light beam is absorbed by the gas to be detected and then excites a sound wave signal through a photoacoustic effect, and the sound wave signal is received by the sound signal detection module to form a photoacoustic spectrum detection light path. By adopting the scheme, synchronous detection of multi-component gas, compactness of a detection structure and high-sensitivity detection of low-concentration gas can be considered.

The invention discloses a water quality monitoring method based on turbidity compensation, which comprises the following steps: establishing a standard absorption spectrum curve of a plurality of turbidity substances, establishing a multivariate standard turbidity compensation database based on a polynomial fitting model, the data dimension of each multivariate standard turbidity compensation database being turbidity-wavelength-absorbance; acquiring the absorption spectrum and turbidity of the to-be-detected liquid; taking the wavelength of the visible light region as the reference wavelength of multi-element turbidity compensation, and carrying out regression analysis on the absorbance of the to-be-measured liquid with the current turbidity at the reference wavelength and the absorbance of the plurality of turbidity substances at the reference wavelength to obtain the contribution proportion of each turbidity substance; and calculating a total interference spectrum according to the contribution proportion of each turbidity substance, and subtracting the total interference spectrum from the absorption spectrum of the liquid to be detected to obtain a corrected spectrum. According to the method, spectral information of complex suspended matters in water is simulated through spectral information of various turbidity substances, the universality of a compensation model is improved, and the accuracy of water quality detection is improved.

The invention discloses a saturated spectrum processing method for wide-range detection of an absorption spectrum of a tunable diode, and relates to the technical field of spectrum gas detection. According to the saturated spectrum processing method for wide-range detection of the absorption spectrum of the tunable diode, an effective spectrum signal is obtained by performing denoising and baseline correction on an original absorption spectrum signal, a plurality of spectrum characteristic parameters are extracted to calculate a saturated quantized value, and a complete absorption spectrum line contour is reconstructed by adopting a spectrum reconstruction algorithm according to the quantized value, so that the wide-range detection of the absorption spectrum of the tunable diode is realized. The method comprises the following steps of: constructing a saturation quantitative evaluation system, a layered self-adaptive spectrum reconstruction strategy, a dual-mode detection fusion mechanism and a working condition compensation model, calculating weights of an absorption spectrum and a wavelength modulation spectrum through an S-type function, correcting a preliminary concentration value by combining environment temperature, pressure and a compensation model, and outputting an accurate final gas concentration. Without additional hardware, wide-range high-precision gas detection is realized, and environmental interference and saturation influence are eliminated.

The invention relates to the technical field of microbe traceability analysis, in particular to a microbe traceability analysis method based on an infrared absorption spectrum and a database, and the method comprises the following steps: acquiring absorbance spectral data: acquiring background spectral data for multiple times, performing background correction, acquiring spectral data of a sample containing a strain, and finally calculating the absorbance spectral data; preprocessing the absorbance spectrum data: smoothing the absorbance spectrum data by adopting an SG smoothing algorithm, and calculating a first-order derivative or a second-order derivative of the smoothed absorbance spectrum data to obtain an absorbance spectrum data set; spectral range selection: presetting different spectral ranges, and selecting different spectral ranges for analysis according to requirements; analyzing the similarity of the strains: analyzing the similarity of the absorbance spectral data set of the strains by adopting an improved hierarchical clustering algorithm; bacterial strain traceability analysis: determining a classification threshold by adopting a threshold determination algorithm, and judging microorganism traceability information; the traceability analysis precision is high, and the reliability, the stability and the practicability are high.

The invention provides a method for analyzing femtosecond laser-induced damage behaviors on the surface of a Zn-doped KDP crystal, and belongs to the technical field of engineering optics based on computer data processing. The method comprises the following steps: firstly, respectively analyzing the influence of the Zn doping amount on the band gap and electroacoustic coupling of the KDP crystal through an ultraviolet-visible absorption spectrum and a Brillouin light scattering spectrum; then constructing a one-dimensional model, respectively simulating the electron density, lattice temperature and time evolution of electron temperature on the surface of the Zn-doped KDP crystal under femtosecond laser irradiation through an electron density accumulation rate equation and a double-temperature model, and theoretically analyzing the influence of the Zn doping amount on the damage behavior of the surface of the KDP crystal. And a theoretical model for calculating the femtosecond laser induced damage threshold is established, so that the optimal doping amount of Zn is determined in a lossless manner. A real sample is not contacted, so that the sample utilization rate is improved; the simulation process is more stable and controllable, and the data repeatability is high; and the research period can be shortened, and optimal doping amount screening is accelerated.

The invention discloses an intelligent monitoring method for casing gas recovery, and relates to the technical field of casing gas detection and analys.The method comprises the steps that casing gas parameters including gas pressure, instantaneous gas volume and gas temperature are collected in real time, and spectrum data are collected through ultraviolet and infrared spectrum sensors; a scattering feature calculation module and a shielding feature calculation module are introduced into a Transformer network, oil mist scattering interference features and shielding interference features are extracted, weight fusion is performed on ultraviolet and infrared spectrum data, interference spectrum hazard values are eliminated, a net absorption spectrum is generated, and concentration is calculated in combination with the Lambert-Beer law to perform safety early warning. Coupling between casing gas parameters is considered, and a long-short-term memory network is adopted to construct a pressure coupling model to correct a pressure threshold value; and the electric control adjustable pipeline is controlled through a PID algorithm to dynamically adjust the drift diameter, so that precise monitoring, safe early warning and stable recovery of the sleeve gas are realized.

The invention relates to the technical field of gas leakage detection and optical remote sensing, particularly discloses a laser natural gas leakage point positioning and imaging processing method based on an unmanned aerial vehicle, and aims to solve the problems of multiple coverage blind areas, low positioning precision and easiness in environmental interference in the prior art. The method comprises the following steps: acquiring a methane concentration integral value through a tunable diode laser absorption spectrum system carried by an unmanned aerial vehicle; constructing an initial concentration point cloud in combination with the high-precision pose and scanning angle data; performing space-time filtering and interpolation enhancement by adopting Kalman filtering and a Gaussian plume model to generate a high-confidence three-dimensional concentration field; and accurately positioning a leakage source by using a gradient rising tracking algorithm in combination with curvature and continuity constraints, and matching pipe network geographic information to perform verification alarm. According to the technical scheme, large-range, high-precision and full-automatic natural gas leakage detection and visual positioning are realized, and the signal-to-noise ratio, the anti-interference capability and the response efficiency are remarkably improved.

The embodiment of the invention provides a method for determining initial parameters of a transient absorption spectrum kinetics curve, and the method comprises the steps: obtaining an initial absorption point and an absorption attenuation termination point of the transient absorption spectrum kinetics curve, and determining a curve segment between the initial absorption point and the absorption attenuation termination point as a total absorption attenuation interval; carrying out weighting processing on a first-order derivative and a second-order derivative of the transient absorption spectrum dynamic curve to obtain a weighted curvature value sequence; the first N-1 weighted curvature values are selected from the weighted curvature value sequence from large to small, and the total absorption attenuation interval is divided into N absorption attenuation intervals corresponding to curve fitting orders according to sampling points corresponding to the first N-1 weighted curvature values; and determining an initial parameter based on a quantitative relationship of 1 / e of the absorption intensity attenuated to the corresponding interval starting point in each absorption attenuation interval in the exponential fitting model, wherein the quantitative relationship is that the absorption intensity at the interval starting point in each absorption attenuation interval is attenuated to the absorption intensity at the corresponding interval starting point. And the fitting efficiency and accuracy of the dynamic curve are improved.

The invention discloses a planetary atmospheric trace gas spectrum telemetering and in-situ fusion detection system and method, and belongs to the technical field of deep space exploration. The detection system has a telemetering mode and an in-situ detection mode, and comprises a telescope module, a laser light source module, a heterodyne spectrum telemetering module, an in-situ absorption spectrum module, a gas sampling and enriching module and a signal acquisition, processing and control module. In the on-orbit stage, a heterodyne spectrum telemetering module is adopted, and a laser light source and sunlight signals are subjected to frequency mixing for atmospheric component telemetering; and after the detector enters an atmospheric descending section, the in-situ absorption spectrum module performs in-situ absorption spectrum measurement by utilizing the detection light of the same laser light source. By performing space-time fusion and joint inversion on the data acquired in the two modes, coherent detection from large-range general survey to fixed-point detailed survey is realized, the problems of load separation of telemetering and in-situ detection and difficulty in data fusion are solved, and the detection efficiency, the data consistency and the integration level of the system are greatly improved.

The invention belongs to the field of optical sensing technology and food component analysis, and discloses a tea polyphenol detection method and a tea polyphenol detection device based on an infrared evanescent wave absorption spectrum. Comprising the following steps that a conical infrared optical fiber sensor is provided, the conical infrared optical fiber sensor is obtained by drawing an optical fiber with the diameter of 150-1000 microns to obtain a conical infrared optical fiber, and then the end faces of the two ends of the conical infrared optical fiber sensor are polished till the end faces of the optical fiber are free of scratches, so that the two end faces of the optical fiber are flat, smooth and bright and form mirror faces; the conical infrared optical fiber sensor is packaged in the sample pool, the upper end of the sample pool is open, and a to-be-detected sample solution is injected and fully coats the optical fiber; an 850-4000 cm <-1 > infrared light source is provided, focused infrared light enters the optical fiber and is fully coupled with the optical fiber, an infrared evanescent wave absorption spectrum is collected, and qualitative and quantitative analysis is carried out on the tea polyphenol content based on the tea polyphenol characteristic peak intensity. The method for detecting the tea polyphenol has the characteristics of rapidness, high sensitivity and low detection limit.

The invention relates to a terahertz spectrum detection technology, in particular to a pericarpium citri reticulatae producing area identification method based on graph regularization sparse principal component analysis and a support vector machine algorithm, and belongs to the field of pericarpium citri reticulatae producing area quality detection. The method comprises the following steps: grinding and tabletting a dried orange peel sample to be detected, firstly detecting the dried orange peel sample in a nitrogen environment by adopting a terahertz time-domain spectroscopy system in a transmission mode to obtain a terahertz time-domain spectroscopy signal of the sample, and performing Fourier transform on the time-domain spectroscopy signal to obtain a frequency-domain spectrum of the sample; and obtaining a corresponding terahertz absorption spectrum according to the frequency domain spectrum. Savitzky-Golay smoothing preprocessing is carried out on the obtained terahertz absorption spectrum, the terahertz absorption spectrum is divided into a training set and a test set, and then feature extraction is carried out on data by utilizing sparse principal component analysis in combination with graph regularization. And taking the processed data as the input of a classification model. And finally, a combined parameter of an optimal regularization coefficient c and a kernel function parameter g of the support vector machine is obtained through a particle swarm optimization algorithm, so that an optimal pericarpium citri reticulatae producing area classification model is established. The method provided by the invention is convenient in sample preparation and simple in operation, can effectively realize rapid and accurate identification of dried orange peel from different producing areas, and provides a new method for identification of dried orange peel in high-value producing areas.

A method for differentiating gas sources based on temperature includes transmitting an optical beam through a plume emitted by a combustion system. The method includes detecting the optical beam, after propagating through the plume, to obtain an absorption spectrum. The method includes determining, based on the absorption spectrum, a first path-integrated concentration of a gas species, a first temperature of the first path-integrated concentration, a second path-integrated concentration of the gas species, and a second temperature of the second path-integrated concentration. The second temperature is different from the first temperature. The method may further include performing an inversion to obtain a sampled quantity of the gas species within the plume. The method may be implemented with dual-comb spectroscopy, in which case the optical beam is formed from two frequency combs having slightly different repetition rates.

The invention provides a thermal injection gas temperature measurement method and system based on spectral absorption, and the method comprises the steps: obtaining absorption spectrum signals before and after ignition of thermal injection gas, and carrying out the baseline correction of the absorption spectrum signals after ignition based on the absorption spectrum signals before ignition; performing environmental absorption interference processing on the corrected post-ignition absorption spectrum signal to obtain a target absorption signal reflecting the self absorption characteristic of the thermal injection gas; based on the target absorption signal, total integral absorbance in the two different measurement frequency bands is determined, and according to the ratio of the total integral absorbance of the two different measurement frequency bands, the pre-established mapping relation between the total integral absorbance ratio and the temperature is combined, and the temperature of the thermal injection gas is obtained through inversion. The invention provides a thermal injection fuel gas temperature measurement method based on a combined absorption spectral line so as to solve the problems of alignment of absorption signal base lines, interference removal of absorption components outside fuel gas jet flow, temperature inversion based on the combined absorption spectral line and the like, and a high-temperature fuel gas jet flow temperature measurement result is obtained.