1029 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 purpose of the present invention is to provide a technique for optically quantifying a compound of which a color does not change due to oxidative degradation.　Another aspect of the present invention provides a method for diagnosing oil characteristics, the method being characterized by: using an optical sensor having a light source and a detector that detects light emitted from the light source to acquire an absorption spectrum in a wavelength range of 800 nm to 3000 nm of an oil containing an additive having a maximum molar absorption coefficient value of 50 or less in the ultraviolet visible wavelength range of 250 nm to 800 nm; and inputting data based on the absorption spectrum into an estimation model implemented in an information processing device to predict the concentration of the additive.

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 discloses a space-space-ground-well integrated carbon dioxide sequestration leakage monitoring method and system, and relates to the technical field of carbon dioxide sequestration leakage monitoring, and the method comprises the steps: carrying out the remote sensing measurement of a target region through a synthetic aperture radar and a satellite, and determining a carbon dioxide sequestration leakage monitoring boundary; performing photogrammetry by using an unmanned aerial vehicle, and constructing a three-dimensional real scene model Surveying the target area on site to obtain surveying and mapping data; based on the key monitoring area, an absorption spectrum and earth surface leakage flux are obtained through infrared spectrum monitoring and vorticity monitoring; gravity monitoring data, storage area underground water parameters, carbon dioxide plume distribution conditions and logging sound wave frequency distribution characteristic graphs are obtained through gravity monitoring, underground water monitoring, optical fiber monitoring and sound wave logging monitoring. And through comprehensive analysis, according to a comprehensive analysis result, whether carbon dioxide leaks is judged, and a carbon dioxide sequestration leakage monitoring result is obtained. The accuracy of carbon dioxide sequestration monitoring can be effectively improved.

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 provides a gaseous pollutant Fourier transform infrared spectroscopic analysis method based on deep learning. The gaseous pollutant Fourier transform infrared spectroscopic analysis method comprises the following steps: acquiring infrared absorbance spectrums of different gases to be detected by utilizing a Fourier transform infrared gas analyzer; the method comprises the following steps of: preprocessing the collected spectral data, namely carrying out segmented denoising on the original spectral data by adopting a self-adaptive Savitzky-Golay filter, and carrying out normalization processing to balance a data range; carrying out feature extraction on the preprocessed spectral data by utilizing a one-dimensional convolution deep learning model so as to adapt to one-dimensional FTIR spectral features and realize feature extraction of multiple components of gas; mapping the extracted features to a prediction result of the to-be-detected component by applying a full connection layer of the model; and training and optimizing the model by adopting an MSE regression loss function. According to the invention, the processing capability of the gaseous pollutant spectral signal can be effectively improved, and high-precision multi-component quantitative analysis 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 relates to the technical field of gas detection, and discloses a high-sensitivity sulfur hexafluoride detection method and a high-sensitivity sulfur hexafluoride detection system based on cooperation of a long-wave infrared absorption spectrum and a thermal infrared spectrum, which are used for solving the problem that water vapor in a detection area affects a sulfur hexafluoride detection result during sulfur hexafluoride detection. The method comprises the following steps: acquiring long-wave infrared absorption spectrum data and environment abnormal data, acquiring an infrared radiation space distribution diagram of a to-be-detected area, acquiring environment humidity and dew point temperature, obtaining initial detection concentration of sulfur hexafluoride according to the long-wave infrared absorption spectrum data, and calculating the concentration of sulfur hexafluoride according to the environment abnormal data, the environment humidity and the dew point temperature. The method comprises the following steps: acquiring an environmental water vapor influence index through evaluation, performing water vapor interference judgment, and if judging that water vapor interference exists in a current detection environment, correcting an initial detection concentration according to the environmental water vapor influence index to obtain an actual detection concentration, thereby effectively improving the accuracy of a sulfur hexafluoride detection result and reducing the problems of missing detection and false detection.

A system that reduces the buildup of film on a movable shaft that enters and is retracted from a process chamber is disclosed. A ring heater is disposed around the shaft inside the process chamber proximate the air bearing. The ring heater includes a plurality of optical energy emitters arranged around the shaft. The wavelength emitted by the ring heater may be selected to align with the absorption spectrum of the film. In this way, the optical energy serves to heat the film and lower the tendency for the film to adhere to the movable shaft and enter the air bearing.

The present invention relates to the technical field of hydrogen concentration detection, and specifically discloses a trace hydrogen concentration sensing system based on TDLAS absorption spectroscopy, which is used to solve the problems of low detection sensitivity, narrow linear range, large system drift and dependence on external calibration in TDLAS hydrogen detection. The system comprises a laser emission module and a photoelectric detection module, wherein the laser emission module and the photoelectric detection module are connected via a dual-light path absorption module, the photoelectric detection module is connected to a harmonic extraction module, the harmonic extraction module is connected to a normalization processing module, and the normalization processing module is connected to a concentration inversion module. The present invention realizes high linearity, high sensitivity, and calibration-free concentration detection of hydrogen within 0.01% to 100% by constructing a symmetrical dual-light path structure, adopting a harmonic signal normalization and differential compensation algorithm, and combining a high-pressure reference gas cell with a segmented fitting model, thereby improving the trace hydrogen identification capability.

An apparatus and method of determining the concentration of first and second substances within a sample by exposing the sample to radiation and filtering the radiation transmitted from the sample using a first filter having a number of pass bands at wavelengths corresponding to absorption peaks in a desired quasi-periodic absorption spectrum of the first substance to be detected, and modulating the wavelengths of the pass bands of the first filter. Additionally, filtering the radiation transmitted from the sample using a second filter having a number of pass bands at wavelengths corresponding to absorption peaks in a desired quasi-periodic absorption spectrum of the second substance to be detected, and modulating the wavelengths of the pass bands of the second filter. The concentration of the first and second substances is determined by determining the difference in the maximum and the minimum intensities of the radiation transmitted by the sample.

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.

Sensor for sensing temperature and measuring the state of charge (SOC) of a fiber-optic accumulator comprising one or more thermoluminescent materials, at one or more emission peaks in a region of variation of the optical absorption spectrum of the insertion material of an electrode. A sensor for sensing temperature and measuring the state of charge (SOC) of a metal-ion accumulator, including an optical fiber one free end of which forms an optical probe including one or more thermoluminescent materials capable of emitting a light peak at at least two wavelengths, at least one of the two peaks being designed to be in at least one region of variation of the optical absorption spectrum of the metal ion insertion material of at least one electrode of the accumulator, the ratio of the two peaks depending on the temperature of the accumulator and the variation in intensity of at least one of the two peaks being dependent on the insertion of the metal ions into the electrode.

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 invention relates to the technical field of analytical chemistry, and particularly discloses a double-signal ratio type up-conversion luminescent probe, a preparation method thereof and application of the double-signal ratio type up-conversion luminescent probe in oxalate detection, and the double-signal ratio type up-conversion luminescent probe comprises up-conversion nanoparticles UCNPs and an iron-chromium cyanine R compound. The upconversion nanoparticles UCNPs are combined with the iron-chromium cyanine R compound to construct a double-emission-peak regulation and control system, when the system is used for oxalate detection, oxalate can be chelated with Fe < 3 + > in the iron-chromium cyanine R compound, blue shift of an induced absorption spectrum is achieved, green and red emission peaks of the UCNPs are synchronously regulated and controlled, and the detection sensitivity is high. The fluorescent-colorimetric bimodal high-sensitivity detection of the oxalate is realized.

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 invention relates to the technical field of hydrogen concentration detection, and particularly discloses a TDLAS (tunable diode laser absorption spectroscopy) absorption spectrum-based trace hydrogen concentration sensing system, which is used for solving the problems of low detection sensitivity, narrow linear range, large system drift and dependence on external calibration in TDLAS hydrogen detection, and comprises a laser emission module and a photoelectric detection module, the laser emission module and the photoelectric detection module are connected through the dual-optical-path absorption module, the photoelectric detection module is connected with a harmonic extraction module, the harmonic extraction module is connected with a normalization processing module, and the normalization processing module is connected with a concentration inversion module; according to the device and the method, a symmetrical double-light-path structure is constructed, a harmonic signal normalization and differential compensation algorithm is adopted, and a high-pressure reference gas pool and a segmented fitting model are combined, so that high-linearity, high-sensitivity and calibration-free concentration detection of hydrogen within 0.01-100% is realized, and the hydrogen trace recognition capability is improved.

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 provides a combustion temperature and component concentration rapid imaging measurement method based on frame rate increase, a high-frame-rate laser-induced fluorescence image is obtained by using a deep learning model, and high-speed imaging of combustion temperature and component concentration is realized by fusing laser absorption spectrum data. A flame turbulence image is obtained according to fluid mechanics simulation, a fluorescence image frame interpolation model is obtained through training, and a high-frame-rate fluorescence image is generated through low-speed laser-induced fluorescence data. Obtaining temperature distribution of a combustion field by using laser absorption spectrum data, and substituting the temperature distribution into a fluorescence model satisfied by fluorescent molecules / free radical groups to obtain high-frame-rate gas molecule / free radical group concentration distribution; the concentrations of other products are solved according to a reaction kinetic equation, and the combustion field temperature and a multi-component concentration image are solved through iterative calculation. The frame rate of low-speed fluorescence data is increased according to turbulence motion estimation, the response speed of temperature and concentration distribution imaging is increased, and the method has wide application prospects in the field of combustion reaction monitoring research.

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.