A method and device for detecting concentration of nitrous oxide based on a Raman spectrometer

Abstract

The application discloses a kind of based on Raman spectrometer nitrous oxide concentration detection method and device, wherein, detection method includes: (1) the Raman spectrum and ambient temperature of the mixed gas to be measured containing N2O are obtained, and the Raman spectrum is pretreated;(2) for the CO2 component existing in the mixed gas to be measured, construct quantum vibration model, calculate the frequency interval and relative intensity of CO2 double peak under current temperature in combination with ambient temperature;(3) based on the frequency interval and relative intensity of CO2 double peak, carry out peak position calibration and intensity distribution in overlapping area, and use function to carry out N2O spectrum peak fitting and extraction;(4) determine the spectrum peak intensity of N2O based on spectrum peak extraction result, and carry out N2O in the component ratio calculation and gas concentration detection of the mixed gas to be measured.The application can realize N2O Raman spectrum peak extraction in CO2 background, to accurately detect concentration.

Description

Technical Field

[0001] This application relates to the field of molecular spectroscopy, and in particular to a method and apparatus for detecting nitrous oxide concentration based on a Raman spectrometer. Background Technology

[0002] Raman spectroscopy is an important tool for online monitoring of mixed gases, enabling component identification by detecting the frequency shift characteristics of the Raman scattered light from gas molecules. For example, Chinese patent document CN113984735A discloses a quantitative detection method, system, and Raman spectrometer based on Raman spectroscopy; Chinese patent document CN114384059A discloses a gas detection device and method.

[0003] In online Raman spectroscopy monitoring and quantitative analysis of gas samples containing N2O, when CO2 is present in the gas mixture, the CO2 molecules exhibit a characteristic double peak due to the Fermi resonance effect, while N2O has a single characteristic peak within the same spectral range. This severe overlap of the two peaks causes aliasing interference in the Raman spectral signals, making it difficult to accurately extract the N2O peak signal directly from the overlapping spectrum. Furthermore, under actual monitoring conditions, ambient temperature significantly and regularly modulates the relative intensity of the CO2 Fermi resonance double peak. Ignoring the intensity redistribution effect caused by temperature leads to peak splitting distortion and peak intensity integration deviation within the overlapping region, ultimately resulting in severely inaccurate peak extraction and concentration detection of N2O.

[0004] Existing Raman detection methods for N2O gas fall into two categories: one uses a quantum static model with fixed parameters at room temperature to handle CO2 interference, which fails to characterize the modulation of CO2 bimodal spectrum features by temperature changes; the other relies on batch experiments at multiple temperature points for calibration, which is costly and time-consuming. Furthermore, neither of these methods establishes a mechanistic, continuous mapping relationship between temperature and the relative intensity of the bimodal spectrum. In addition, existing methods extract N2O peaks in overlapping spectral regions based solely on simple peak height ratios or linear interpolation, failing to fully utilize spectral fitting algorithms. This results in low accuracy in N2O peak extraction, consequently affecting the accuracy of N2O gas concentration detection.

[0005] Therefore, there is an urgent need for a method that comprehensively considers temperature-adaptive modeling and spectral fitting optimization to achieve accurate extraction of N2O Raman peaks and detection of component concentrations in a CO2-containing background. Summary of the Invention

[0006] This invention provides a method and device for detecting nitrous oxide concentration based on Raman spectrometer, which can extract N2O Raman peaks in a CO2 background and thus accurately detect the concentration.

[0007] A method for detecting nitrous oxide concentration based on Raman spectroscopy includes the following steps: (1) Obtain the Raman spectrum and ambient temperature of the gas mixture containing N2O, and preprocess the Raman spectrum; identify the high-frequency shift characteristic peak and low-frequency shift characteristic peak in the Fermi resonance double peak of CO2, wherein the low-frequency shift characteristic peak of CO2 overlaps with the N2O spectral peak in the overlapping region of the spectral peaks. (2) For the CO2 component present in the gas mixture to be tested, a quantum vibration model is constructed, and the frequency interval and relative intensity of the CO2 double peaks at the current temperature are calculated in combination with the ambient temperature; (3) Based on the frequency interval and relative intensity of the CO2 double peaks, peak position calibration and intensity allocation are performed in the overlapping region of the spectral peaks, and N2O spectral peak fitting and extraction are performed using functions; (4) Determine the peak intensity of N2O based on the N2O peak extraction results, and calculate the component ratio of N2O in the gas mixture to be tested and detect the gas concentration.

[0008] Preferably, in step (1), the ambient temperature range is 268~318 K.

[0009] Furthermore, in step (1), the Raman spectrum is preprocessed, specifically including: By performing baseline removal and filtering operations on the raw Raman spectrum data, the Raman spectrum data to be analyzed is obtained; Raman peaks and their corresponding components are identified using a peak-finding algorithm. If a CO2 component is identified, the peak position of the Raman peak with a higher wavenumber within the target range is taken as the wavenumber position of the high-frequency shift characteristic peak of CO2, and the peak position of the Raman peak with a lower wavenumber within the target range is taken as the wavenumber reference position of the characteristic peak of N2O and the low-frequency shift characteristic peak of CO2.

[0010] Furthermore, in step (2), a quantum vibration model is constructed for the CO2 component present in the gas mixture to be tested, specifically as follows: Based on the generalized eigenvalue equation under quantum vibration theory and the structural characteristics of CO2 molecules, a temperature-dependent CO2 quantum vibration model is constructed by introducing the Boltzmann factor.

[0011] Further, in step (2), the frequency interval and relative intensity of the CO2 bimodal peaks at the current temperature are calculated, specifically as follows: Substituting ambient temperature into the CO2 quantum vibration model, the eigenvalue equation is solved in the subspace consisting of the symmetric stretching vibration ground state and the degenerate bending vibration overtone state, yielding the frequency interval of the CO2 bimodal peaks and the mixing angle characterizing the mixing ratio of the two modes. The polarizability derivatives of the symmetric stretching vibration mode and the degenerate bending vibration mode at the high-frequency and low-frequency peak shifts are obtained. Then, the effective polarizability derivatives characterizing the spectral transition probability are obtained by weighted summation using the mixing angle and normalization factor. The relative intensities of the CO2 double peaks were calculated using the frequency of the Fermi resonance double peak positions, the incident laser frequency, the reduced Planck constant, the Boltzmann factor, the experimental ambient temperature, the mixing angle, and the effective polarizability derivatives of the vibration mode at different frequency shifts.

[0012] Furthermore, the specific process of step (3) is as follows: The peak position of the low-frequency shift characteristic peak of CO2 in the overlapping region of the spectral peaks is determined based on the frequency interval of the CO2 double peaks; The intensity distribution of the low-frequency shift characteristic peak of CO2 within the overlapping region of the spectral peaks is determined based on the relative intensity of the CO2 double peaks. The peak position and intensity distribution of the low-frequency shift characteristic peak of CO2 are used as constraints to be imported into the overlapping peak separation function model to fit the N2O spectrum peak, and then the N2O spectrum peak is extracted from the overlapping region.

[0013] Furthermore, the specific process of step (4) is as follows: Based on the N2O peak extraction results, the peak intensity of N2O in the gas mixture to be tested was determined. Based on the Raman spectral data of the gas mixture to be tested, the peak intensities of other components are analyzed and determined, and the component ratio and gas concentration of N2O in the gas mixture to be tested are calculated.

[0014] A nitrous oxide concentration detection device based on a Raman spectrometer, used to implement the above-mentioned nitrous oxide concentration detection method, includes an acquisition module, a calculation module, and an analysis module; The acquisition module is used to acquire the Raman spectrum and ambient temperature of the N2O-containing gas mixture to be tested, and to preprocess the Raman spectrum. The solution module is used to construct a CO2 quantum vibration model, solve the eigenvalue equation in combination with the ambient temperature, and calculate the frequency interval and relative intensity of the CO2 double peaks at the current temperature; The analysis module is used to perform peak position calibration and intensity allocation in the peak overlap region based on the frequency interval and relative intensity of the CO2 double peaks. For the spectral overlap region, a function model is used to fit and extract the N2O spectral peak. Based on the spectral peak separation results, the spectral peak intensity of N2O is determined, and its component ratio in the gas mixture to be tested is calculated to realize gas concentration detection.

[0015] Compared with the prior art, the present invention has the following beneficial effects: Firstly, by directly integrating temperature parameters into the calculation of the model matrix elements and describing the vibrational energy level population of CO2 molecules through the Boltzmann factor, the generated matrix elements inherently carry information about the ambient temperature. This elevates temperature from an external correction factor to an internal variable of the CO2 molecular vibration model, fundamentally solving the problem of model-temperature decoupling in existing technologies. Secondly, by accurately calculating the double-peak characteristics of CO2, a real-time and adaptive theoretical basis is provided for eliminating the interference of CO2 on the detection of N2O spectral peaks.

[0016] Secondly, a two-stage separation strategy of "characteristic solution guidance + spectral fitting optimization" is adopted. First, the peak position is calibrated and the intensity is allocated by using the frequency interval and relative intensity of the CO2 double peak. Fitting constraints are applied to the CO2 characteristic peaks in the overlapping region. Then, a function model is used to fit the N2O gas Raman spectrum peaks in the overlapping region, thereby realizing the detection of N2O gas concentration in the mixed gas, which makes up for the shortcomings of the traditional method that relies solely on intensity allocation in the spectral overlapping region. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart of a method for detecting nitrous oxide concentration based on a Raman spectrometer is provided for an embodiment of the present invention.

[0019] Figure 2 This is a schematic diagram of a nitrous oxide concentration detection device based on a Raman spectrometer, provided as an embodiment of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] It should be noted that, unless otherwise specified, the features in the following embodiments and implementation methods can be combined with each other.

[0022] like Figure 1 As shown, a method for detecting nitrous oxide concentration based on Raman spectroscopy includes the following steps: S101. Obtain the Raman spectrum of N2O gas and the ambient temperature, and perform preprocessing such as baseline removal on the Raman spectrum.

[0023] The gas mixture to be tested is a gas sample containing N2O, which may contain CO2 components.

[0024] Specifically, in Raman spectroscopy monitoring scenarios, if both N2O and CO2 are present in the gas mixture being tested, the Raman characteristic peaks of the two gas components overlap significantly within a specific wavenumber range. CO2 exhibits a characteristic double-peak structure due to the Fermi resonance effect, while N2O has a single peak overlapping with it in this range. This makes it difficult to effectively extract and accurately quantify the N2O peak directly using Raman spectroscopy. This application aims to achieve accurate extraction of the N2O peak and calculation of its concentration in such gas mixtures with CO2 background interference.

[0025] Raman spectroscopy is a spectrum obtained based on the Raman scattering effect, recording the distribution of scattered light intensity as a function of the Raman frequency shift (wavenumber). When an incident laser irradiates gas molecules, molecular vibrations cause a characteristic shift in the frequency of the scattered light relative to the incident light. Different molecules exhibit different characteristic peaks in the Raman spectrum due to their different vibrational modes. Ambient temperature refers to the experimental environment temperature simultaneously measured by a temperature sensor at the same moment the Raman spectral data of the mixed gas are acquired.

[0026] In practice, a Raman spectrometer is used to measure the N₂O-containing gas to be analyzed, acquiring the raw Raman spectral signal. The raw signal is then preprocessed by baseline removal to obtain the Raman spectral data to be analyzed. Simultaneously, a temperature sensor collects the ambient temperature at the time of measurement, providing the real-time ambient temperature.

[0027] Preprocessing of the Raman spectrum includes baseline removal and other operations to eliminate the influence of instrument background drift on the spectral signal; filtering and other operations to achieve smoothing and noise reduction, while preserving spectral peak characteristics while suppressing noise.

[0028] In the acquired Raman spectrum of the gas mixture, Raman peaks and corresponding components are identified using a peak-finding algorithm to determine whether CO2 is present in the gas mixture. Its high-frequency shift characteristic peak is typically located at approximately 1380 cm⁻¹. -1 Up to 1410 cm -1 Within the spectral range of wavenumbers. If the presence of CO2 in the gas mixture is determined, then within the spectral range of approximately 1200 cm⁻¹. -1 Up to 1350 cm -1There is an overlapping region within the target spectral range of wavenumbers, containing a single characteristic peak of N₂O and a low-frequency shifted characteristic peak from the two characteristic peaks of CO₂ generated by the Fermi resonance effect. Within the target range, a peak-finding algorithm identifies two Raman peaks with significant intensity and relatively fixed spacing. The position of the Raman peak with the higher wavenumber within the target range is used as the wavenumber position of the high-frequency shifted CO₂ peak, while the position of the Raman peak with the lower wavenumber within the target range is used as the wavenumber reference position for the N₂O characteristic peak and the low-frequency shifted CO₂ peak. In practice, the specific wavenumbers of the Raman peaks can be located in the spectrum by combining second-derivative spectral analysis or curve fitting methods.

[0029] S102. For the CO2 component present in the gas mixture to be tested, construct a quantum vibration model and, in conjunction with the real-time temperature, calculate the frequency interval and relative intensity of the CO2 double peaks at the current temperature.

[0030] Specifically, the CO2 molecule is a linear triatomic molecule. One of its vibrational modes is that two oxygen atoms move simultaneously toward or away from the central carbon atom along the molecular axis, while the carbon atom remains stationary. In this mode, the carbon dioxide molecule maintains its symmetry and is therefore called a symmetric stretching vibration mode. In this application, it corresponds to a higher frequency vibration and is the source of the fundamental frequency peak in the Fermi resonance. The CO2 molecule also possesses vibrational modes that cause the molecular axis to bend. The molecule can bend in two mutually perpendicular planes. These two bending vibrational modes have the same energy, which is called "degeneracy" in quantum mechanics, hence they are collectively referred to as degenerate bending vibrational modes. In this application, they correspond to a lower frequency vibration and are the source of the overtone peak in the Fermi resonance—the energy of the two bending vibration quanta simultaneously excited is exactly close to the energy of one symmetric stretching vibration quantum, thus providing the conditions for the Fermi resonance to occur.

[0031] Fermi resonance coupling refers to the quantum mechanical interaction that occurs when the frequency of a fundamental vibration in a molecule is close to the overtone (or combination) frequency of another vibration. This interaction causes the two originally independent energy levels to repel and mix, resulting in two double peaks with redistributed intensities on the spectrum. In the CO2 molecule, this type of coupling exists between the symmetric stretching vibration (fundamental frequency) and the overtone of the bending vibration.

[0032] The quantum vibrational model of CO2 molecules refers to a mathematical and physical model that describes the vibrational behavior of CO2 molecules within a quantum mechanical framework and allows for the calibration of internal parameters using experimental data. Unlike classical mechanics, which treats vibrations as springs, this model quantizes vibrational energy, using the Hamiltonian to characterize the total energy of the system. The quantum vibrational model in this application is specifically constructed for the symmetric stretching and degenerate bending vibrational modes of CO2 molecules. Temperature is incorporated into the calculation of the model matrix elements through the Boltzmann distribution factor, making temperature an internal variable of the model.

[0033] In practice, a temperature-dependent molecular vibration model of CO2 molecules is constructed based on the Fermi resonance coupling between the symmetric stretching vibration mode and the degenerate bending vibration mode of CO2 molecules, and then the frequency interval and relative intensity of the CO2 bimodal vibration are calculated.

[0034] First, a molecular quantum vibration model of CO2 is constructed based on the generalized eigenvalue equation. This equation includes a transformation coefficient matrix, a reduced Planck constant, and frequency variables, and must satisfy specific constraints. Specifically, the Hamiltonian matrix elements and overlap matrix elements are defined as symmetric matrices. The construction of the overlap matrix elements includes determining the self-overlapping matrix elements of the symmetric stretching vibration mode, the self-overlapping matrix elements of the degenerate bending vibration mode, and the cross-overlapping matrix elements between them. Its calculation involves the effective mass, frequency, and reduced Fermi resonance coupling parameters of each mode. Correspondingly, the construction of the Hamiltonian matrix elements includes determining the self-Hamiltonian matrix elements and their cross-Hamiltonian matrix elements of the symmetric stretching vibration mode and the degenerate bending vibration mode. Its calculation is based on the effective mass, frequency, reduced Fermi resonance coupling parameters, and the experimental ambient temperature.

[0035] Secondly, the key spectral parameters of the CO2 Fermi resonance double peaks are derived. First, the frequency interval of the CO2 molecule's Fermi resonance double peaks is calculated. This interval depends on the effective coupling matrix element and the detuning, where the detuning characterizes the intrinsic frequency difference between the fundamental and harmonic frequencies. The effective coupling matrix element is specifically determined by the reduced Planck constant, the frequencies of symmetric stretching vibrational modes, and the frequencies of degenerate bending vibrational modes. Second, the mixing angle, which characterizes the proportion of vibrational modes, is calculated. This mixing angle reflects the degree of mixing between symmetric stretching and degenerate bending vibrational modes in the CO2 molecule. Based on the expression for the mixing angle and the generalized normalization condition, the corresponding normalization factor is simultaneously determined to ensure the physical rationality of the quantum state.

[0036] Next, the effective polarizability derivatives corresponding to the two new normal coordinates after the intramolecular modes of CO2 are calculated. Specifically, this involves obtaining the polarizability derivatives of the symmetric stretching vibration mode and the degenerate bending vibration mode at the high-frequency and low-frequency peak shifts, and then performing a weighted summation by combining the mixing angle and the normalization factor to obtain the effective polarizability derivatives characterizing the spectral transition probability.

[0037] Furthermore, a formula for calculating the relative intensity of the two peaks of the CO2 Fermi resonance was established and solved. This formula integrates the frequencies of the Fermi resonance bimodal positions, the incident laser frequency, the reduced Planck constant, the Boltzmann constant, the experimental ambient temperature, the mixing angle, and the effective polarizability derivatives of the vibration modes at different frequency shifts. In particular, the formula incorporates the previously calculated mixing angle to accurately correct the intensity redistribution caused by the interaction between the symmetric stretching vibration mode and the degenerate bending vibration mode, thereby outputting a realistic relative intensity ratio of the two Fermi resonance peaks.

[0038] For example, in one embodiment, in the bright state subspace, the Hamiltonian matrix elements are... With overlapping matrix elements The constructed generalized eigenvalue equation can be expressed as: ; in, This is the transformation coefficient matrix; To reduce Planck's constant; The frequency is given; the generalized eigenvalue equation satisfies the constraints. .

[0039] For Hamiltonian matrix elements With overlapping matrix elements Both are symmetric matrices. Due to the permutation symmetry of the Fermi resonance bending mode, it satisfies... Overlapping matrix elements It can be represented as: ; ; ; in, For symmetric stretching vibration modes, there are self-overlapping matrix elements; To reduce Planck's constant; These are the effective mass and frequency of the symmetrical stretching vibration mode, respectively. Boltzmann's constant; The ambient temperature of the experiment; The matrix elements representing the cross-overlapping of symmetric stretching vibration modes and degenerate bending vibration modes; To reduce the Fermi resonance coupling parameters; These are the effective mass and frequency of the degenerate bending vibration mode, respectively. For the self-overlapping matrix elements of degenerate bending vibration modes.

[0040] Based on the generalized eigenvalue equation and overlapping matrix element The Hamiltonian matrix elements can be calculated. .

[0041] Therefore, by solving the eigenvalue equation, the frequency interval... It can be represented as: ; in, The frequency interval of the Fermi resonance bipeaks of carbon dioxide molecules; To reduce Planck's constant; For effective coupling matrix elements; , is the detuning quantity, which characterizes the inherent frequency difference between the fundamental frequency and the harmonics; and These are coupled symmetrical combinations of the Fermi resonance bimodal positions.

[0042] Effective coupling matrix elements It can be represented as: ; in, For effective coupling matrix elements; To reduce Planck's constant; The frequency of the symmetrical stretching vibration mode; The frequency of the degenerate bending vibration mode.

[0043] Mixed angle The ratio of symmetric stretching vibration modes to degenerate bending vibration modes in the CO2 molecule can be expressed as: ; According to Placzek theory, the Raman scattering intensity is proportional to the partial derivatives of the polarizability tensor with respect to normal coordinates. The sum of squares. For the Fermi resonance doublet of the CO2 molecule, the effective polarizability derivative after mode mixing needs to be considered: ; in, Molecular polarizability; These are the two new normal coordinates after coupling; The first-order polarizability derivative of the high-frequency shifting peak of the symmetrical stretching vibration mode; The first polarizability derivative for the low-frequency peak shift of the symmetrical stretching vibration mode; The effective polarizability derivative for high-frequency peak shifting of degenerate bending vibration modes; The effective polarizability derivative for low-frequency peak shifting of degenerate bending vibration modes; Normalization factor; It is a mixed angle.

[0044] According to Placzek theory, the relative intensities of the Fermi resonance doublets of the carbon dioxide molecule can be expressed as: ; in, The Raman peak intensity represents the highest frequency shift of the Fermi resonance double peak. The Raman peak intensity represents the lowest frequency shift of the Fermi resonance double peak. and These are the frequencies at the positions of the Fermi resonance double peaks; The frequency of the incident laser; To reduce Planck's constant; Boltzmann's constant; The ambient temperature of the experiment; The first-order polarizability derivative of the high-frequency shifting peak of the symmetrical stretching vibration mode; The first polarizability derivative for the low-frequency peak shift of the symmetrical stretching vibration mode; The effective polarizability derivative for high-frequency peak shifting of degenerate bending vibration modes; The effective polarizability derivative for low-frequency peak shifting of degenerate bending vibration modes; It is a mixed angle.

[0045] S103. Based on the frequency interval and relative intensity of the CO2 double peaks in the overlapping region, peak position calibration and intensity allocation are performed, and N2O spectrum peak fitting and extraction are performed using a function.

[0046] Specifically, Raman overlap peaks refer to the low-frequency shift of the Fermi resonance doublet of CO2 molecules in the Raman spectrum of a gas mixture containing N2O, which overlaps with the single characteristic peak of N2O molecules at approximately 1280–1310 cm⁻¹ due to their proximity in position. -1 Composite signals that overlap within the region and are difficult to distinguish directly.

[0047] Within the overlapping region, the low-frequency shift positions of the CO2 Fermi resonance double peaks are determined based on the calculated frequency interval of the CO2 double peaks and the high-frequency shift positions of the CO2 molecules: using the high-spectral peak of the Raman spectrum within the target range as a reference point, the frequency interval shifted towards lower wavenumbers is defined as the low-frequency shift positions of the CO2 Fermi resonance double peaks. The intensity distribution of the lowest and highest frequency shift peaks is determined based on their relative intensities, and fitting constraints are applied to the CO2 characteristic peaks within the overlapping region.

[0048] For spectral overlap regions, simple intensity assignment methods may not be able to fully extract the contributions of N2O and other gas components. In such cases, a functional model is used to achieve more accurate fitting and separation of overlapping peaks.

[0049] The peak morphology of Raman spectra is essentially Lorentzian. However, due to the influence of the spectral monitoring instrument and the characteristics of the sample itself, the actual measured peak waveform usually needs to be approximated by a mixture model of different functions.

[0050] For example, in one embodiment, the obtained Raman spectrum is significantly affected by factors such as the Raman spectrometer. Therefore, the multi-peak function model can be expressed as: ; in, Peak position of the spectrum; For the first The width of the Gaussian peak corresponding to each peak; For the first The width of the Lorentz-type peaks corresponding to each peak; For the first The peak intensity corresponding to each peak.

[0051] In practice, the Raman overlapping peak spectrum in the overlapping region is decomposed into two components: a characteristic single peak of N2O and a low-frequency characteristic peak of CO2. Based on the peak position and maximum peak intensity constraints of the low-frequency characteristic peak of CO2, a multi-peak function is used to fit both components simultaneously. The parameters of each component are iteratively optimized using a least-squares optimization algorithm until the fitting residual is minimized. After the fitting converges, the function curves obtained by separating each component represent the independent spectral contributions of the corresponding components, and the function curve corresponding to the characteristic single peak of N2O is the extracted N2O spectral peak.

[0052] In practice, the peak position of the high-frequency shift in the CO2 Fermi resonance double peak is first extracted from the acquired spectral data (e.g., 1398 cm⁻¹). -1 ) and peak intensity (e.g., 2.44 × 10 5 Then, from the obtained bimodal frequency shift interval and peak intensity ratio at different ambient temperatures, the bimodal frequency shift interval of the CO2 Fermi resonance at the current temperature (e.g., 105 cm⁻¹) is extracted. -1 The peak intensity ratio (e.g., 1.65) was then calculated; subsequently, the peak position of the low-frequency shift in the CO2 Fermi resonance double peak was determined (1293 cm⁻¹). -1 ) and peak strength (1.48×10 5 The constraint condition is imported into the fitting function model; finally, the N2O spectral peak is extracted from the spectral peaks obtained by separating the overlapping Raman peaks.

[0053] S104. Based on the peak extraction results, determine the peak intensity of N2O and realize the calculation of N2O gas component ratio and concentration detection.

[0054] Specifically, based on the peak extraction results, the characteristic peaks of N2O are integrated by peak area or measured by peak height to obtain the peak intensity of N2O. Furthermore, based on the peak intensities of N2O and other gas components, the proportion of N2O in the gas mixture to be tested is calculated, thereby enabling the detection of N2O gas concentration in the gas mixture.

[0055] Specifically, based on the peak extraction results, the peak area integral value of the characteristic peak of N2O is calculated or its peak height is directly measured to obtain the peak intensity value reflecting the N2O content. Further, based on this quantitative analysis, it is necessary to comprehensively consider and incorporate the peak intensity data corresponding to other coexisting gas components (such as CO2, N2, O2, etc.) to construct a quantitative model for multi-component synergistic analysis. Through this model, the component proportion of N2O in the complex mixed gas sample can be systematically solved, and based on the pre-established calibration curve or theoretical conversion relationship, the gas concentration of N2O in the sample can be accurately calculated, thus completing the complete quantitative analysis process from obtaining the original spectral signal to detecting the specific gas concentration.

[0056] In practice, the peak height is first extracted from the acquired N2O spectral peak data as the peak intensity (e.g., 5.95 × 10⁻⁶). 4 Then, obtain the total spectral peak intensity of each component of the gas mixture to be tested (e.g., 2.34 × 10⁻⁶). 8 Divide the N2O peak intensity by the N2O to obtain the component ratio of N2O in the gas mixture to be tested (0.25‰), and convert it to obtain the gas detection concentration (254.27 ppm).

[0057] The method provided in this embodiment, firstly, directly integrates temperature parameters into the calculation of model matrix elements. By statistically weighting the vibrational energy level population using the Boltzmann distribution factor, the matrix elements generated by the model inherently carry information about the ambient temperature. This elevates temperature from an external correction factor to an internal variable of the quantum vibration model, fundamentally solving the problem of model-temperature decoupling in existing technologies. Furthermore, based on these temperature-dependent matrix elements, eigenvalue equations are constructed and solved. Since the matrix elements are already functions of temperature, the obtained eigenvalues ​​and eigenvectors naturally inherit temperature dependence characteristics, eliminating the need for additional temperature corrections at the equation level and ensuring the consistency of the physical model and the coherence of the derivation. Finally, by utilizing these temperature-dependent eigenvalues ​​and eigenvectors, combined with the temperature parameters introduced in the model, the frequency interval and relative intensity of the CO2 bimodal peaks are calculated. This allows the final output bimodal characteristic parameters to analytically and continuously respond to changes in ambient temperature. The corresponding bimodal characteristics can be given at any measured temperature within the set temperature range, providing a real-time and adaptive theoretical basis for the accurate separation of overlapping Raman peaks and avoiding the limitations of traditional methods that rely on empirical calibration at discrete temperature points.

[0058] Secondly, a two-stage separation strategy of "feature calculation guidance + spectral fitting optimization" was adopted. This strategy first fully utilizes the bimodal characteristics of the CO2 characteristic spectrum, namely its specific frequency interval and relative intensity relationship, to perform preliminary calculations of the CO2 contribution within the spectral overlap region. Specifically, this stage accurately calculates the bimodal interval and analyzes its intensity ratio to precisely calibrate the peak positions of the CO2 characteristic peaks within the overlap region and rationally allocate their contribution intensities, thus providing crucial prior knowledge and physical constraints for the subsequent fitting process. Based on this, spectral fitting optimization is performed. This stage is not conducted in isolation but, guided by the peak position and intensity constraints obtained through feature calculation, uses a function model to perform global fitting and separation operations across the entire spectral overlap region. This optimization process can precisely describe the actual shape of the spectral lines and dynamically adjust the fitting parameters, thereby extracting the spectral characteristics of N2O and CO2 more accurately and completely from the overlapping peaks. Compared to traditional methods that mainly rely on simple intensity allocation or empirical criteria, the two-stage synergistic mechanism introduced in this strategy significantly improves the separation accuracy and reliability in challenging scenarios such as strong spectral overlap and complex baselines. It effectively compensates for the inherent defects of traditional methods, such as insufficient resolution in overlapping regions and susceptibility to interference, and provides a more robust and powerful solution for high-precision spectral detection and quantitative analysis of N2O in complex gas mixtures.

[0059] Corresponding to the aforementioned embodiment of the nitrous oxide concentration detection method based on Raman spectroscopy, this application also provides a nitrous oxide concentration detection device based on Raman spectroscopy. Please refer to... Figure 2 As shown, it includes an acquisition module 210, a solution module 220, and an analysis module 230.

[0060] The acquisition module 210 is used to acquire the Raman spectrum and ambient temperature of the test mixed gas containing N2O, and to perform preprocessing such as baseline removal on the Raman spectrum. Calculation module 220 is used to construct a CO2 quantum vibration model, solve the eigenvalue equation in combination with the ambient temperature, and calculate the frequency interval and relative intensity of the CO2 double peaks at the current temperature; The extraction module 230 is used to perform peak position calibration and intensity allocation in the peak position overlap region based on the frequency interval and relative intensity of the CO2 double peaks. For the spectral overlap region, a function model is used to fit and extract the N2O spectral peak. Based on the spectral peak extraction results, the spectral peak intensity of N2O is determined and its component ratio in the gas mixture to be tested is calculated to realize gas concentration detection.

[0061] The apparatus of this embodiment can be used to perform... Figure 1 The steps of the method embodiment shown are similar in principle and process, and will not be repeated here.

[0062] The specific implementation process of the functions and roles of each unit in the above device can be found in the implementation process of the corresponding steps in the above method, and will not be repeated here.

[0063] The embodiments described above provide a detailed explanation of the technical solutions and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, additions, and equivalent substitutions made within the scope of the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for detecting nitrous oxide concentration based on Raman spectroscopy, characterized in that, Includes the following steps: (1) Obtain the Raman spectrum and ambient temperature of the gas mixture containing N2O, preprocess the Raman spectrum, and identify the high-frequency shift characteristic peak and low-frequency shift characteristic peak in the Fermi resonance double peak of CO2. Among them, the low-frequency shift characteristic peak of CO2 and the N2O spectrum peak overlap each other in the spectrum peak overlap region. (2) For the CO2 component present in the gas mixture to be tested, a quantum vibration model is constructed, and the frequency interval and relative intensity of the CO2 double peaks at the current temperature are calculated in combination with the ambient temperature; (3) Based on the frequency interval and relative intensity of the CO2 double peaks, peak position calibration and intensity allocation are performed in the overlapping region of the spectral peaks, and N2O spectral peak fitting and extraction are performed using functions; (4) Determine the peak intensity of N2O based on the N2O peak extraction results, and calculate the component ratio of N2O in the gas mixture to be tested and detect the gas concentration.

2. The method for detecting nitrous oxide concentration based on Raman spectroscopy according to claim 1, characterized in that, In step (1), the ambient temperature range is 268~318 K.

3. The method for detecting nitrous oxide concentration based on Raman spectroscopy according to claim 1, characterized in that, In step (1), the Raman spectrum is preprocessed, specifically including: By performing baseline removal and filtering operations on the raw Raman spectrum data, the Raman spectrum data to be analyzed is obtained; Raman peaks and their corresponding components are identified using a peak-finding algorithm. If a CO2 component is identified, the peak position of the Raman peak with a higher wavenumber within the target range is taken as the wavenumber position of the high-frequency shift characteristic peak of CO2, and the peak position of the Raman peak with a lower wavenumber within the target range is taken as the wavenumber reference position of the characteristic peak of N2O and the low-frequency shift characteristic peak of CO2.

4. The method for detecting nitrous oxide concentration based on Raman spectroscopy according to claim 1, characterized in that, In step (2), a quantum vibration model is constructed for the CO2 component present in the gas mixture to be tested, specifically as follows: Based on the generalized eigenvalue equation under quantum vibration theory and the structural characteristics of CO2 molecules, a temperature-dependent CO2 quantum vibration model is constructed by introducing the Boltzmann factor.

5. The method for detecting nitrous oxide concentration based on Raman spectroscopy according to claim 4, characterized in that, In step (2), the frequency interval and relative intensity of the CO2 double peaks at the current temperature are calculated, specifically as follows: Substituting ambient temperature into the CO2 quantum vibration model, the eigenvalue equation is solved in the subspace consisting of the symmetric stretching vibration ground state and the degenerate bending vibration overtone state, yielding the frequency interval of the CO2 bimodal peaks and the mixing angle characterizing the mixing ratio of the two modes. The polarizability derivatives of the symmetric stretching vibration mode and the degenerate bending vibration mode at the high-frequency and low-frequency peak shifts are obtained. Then, the effective polarizability derivatives characterizing the spectral transition probability are obtained by weighted summation using the mixing angle and normalization factor. The relative intensities of the CO2 double peaks were calculated using the frequency of the Fermi resonance double peak positions, the incident laser frequency, the reduced Planck constant, the Boltzmann factor, the experimental ambient temperature, the mixing angle, and the effective polarizability derivatives of the vibration mode at different frequency shifts.

6. The method for detecting nitrous oxide concentration based on Raman spectroscopy according to claim 1, characterized in that, The specific process of step (3) is as follows: The peak position of the low-frequency shift characteristic peak of CO2 in the overlapping region of the spectral peaks is determined based on the frequency interval of the CO2 double peaks; The intensity distribution of the low-frequency shift characteristic peak of CO2 within the overlapping region of the spectral peaks is determined based on the relative intensity of the CO2 double peaks. The peak position and intensity distribution of the low-frequency shift characteristic peak of CO2 are used as constraints to be imported into the overlapping peak separation function model to fit the N2O spectrum peak, and then the N2O spectrum peak is extracted from the overlapping region.

7. The method for detecting nitrous oxide concentration based on Raman spectroscopy according to claim 1, characterized in that, The specific process of step (4) is as follows: Based on the N2O peak extraction results, the peak intensity of N2O in the gas mixture to be tested was determined. Based on the Raman spectral data of the gas mixture to be tested, the peak intensities of other components are analyzed and determined, and the component ratio and gas concentration of N2O in the gas mixture to be tested are calculated.

8. A nitrous oxide concentration detection device based on a Raman spectrometer, used to implement the nitrous oxide concentration detection method according to any one of claims 1 to 7, characterized in that, It includes an acquisition module, a solution module, and an analysis module; The acquisition module is used to acquire the Raman spectrum and ambient temperature of the N2O-containing gas mixture to be tested, and to preprocess the Raman spectrum. The solution module is used to construct a CO2 quantum vibration model, solve the eigenvalue equation in combination with the ambient temperature, and calculate the frequency interval and relative intensity of the CO2 double peaks at the current temperature; The analysis module is used to perform peak position calibration and intensity allocation in the peak overlap region based on the frequency interval and relative intensity of the CO2 double peaks. For the spectral overlap region, a function model is used to fit and extract the N2O spectral peak. Based on the spectral peak separation results, the spectral peak intensity of N2O is determined, and its component ratio in the gas mixture to be tested is calculated to realize gas concentration detection.

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