A method for obtaining spectral line parameters of TDLAS measurement signal under high pressure environment

Abstract

The present invention relates to a tunable semiconductor laser absorption spectroscopy (TDLAS) method, and more particularly to a method for obtaining spectral line parameters of a TDLAS measurement signal in a high-pressure environment. The method solves the technical problems of existing TDLAS technology in a high-pressure environment, such as difficulty in removing the baseline and large errors in calculating spectral line parameters. The method for obtaining spectral line parameters of a TDLAS measurement signal in a high-pressure environment comprises the following steps: Step 1) obtaining a TDLAS measurement signal I exp (v x ); step 2) constructing an overall fitting model; step 3) determining the initial values ​​and limit intervals of the variable parameters in the overall fitting model; step 4) optimizing the variable parameters in the overall fitting model according to the initial values ​​and limit intervals of the variable parameters, and inverting the overall fitting model and the TDLAS measurement signal I exp (v x ) spectral line parameters under optimal matching; effectively avoid the complex baseline removal process of the original signal, improve the applicability of TDLAS technology in high-pressure environments, and significantly reduce the calculation error of spectral line parameters.

Description

Technical Field

[0001] The present invention relates to a tunable semiconductor laser absorption spectroscopy (TDLAS) method, and in particular to a method for obtaining TDLAS measurement signal spectral line parameters under a high-pressure environment. Background Art

[0002] TDLAS (Tunable Diode Laser Absorption Spectroscopy) technology, also known as tunable semiconductor laser absorption spectroscopy, uses an extremely narrow linewidth laser to scan the characteristic absorption lines of the gas molecules to achieve in-situ, online, non-contact measurement of physical quantities such as the temperature, concentration, and pressure of the measured components. In recent years, the rapid development of miniaturized light sources such as DFB (Distributed Feed Back) diode lasers in the near-infrared band has gradually solved the laser source and laser detection problems of TDLAS technology. At the same time, with the continuous improvement of the molecular absorption spectrum database, TDLAS technology has become an important development direction in the field of non-contact diagnosis of complex physical fields due to its advantages such as high measurement accuracy, high sensitivity, strong anti-interference ability, and compact measurement device structure, and has been widely used in gas parameter measurement.

[0003] As an application of absorption spectroscopy, TDLAS follows the Beer-Lambert law, which can be simply stated as follows: when monochromatic light of frequency v propagates in a uniform medium for a distance L, the outgoing light intensity I(v) of the monochromatic light can be expressed by the incident light intensity I0(v) that has passed through the same path but has not been absorbed, the spectral absorption coefficient α(v), and the absorption path length L, that is, I(ν) = I0(ν)·e -α(ν)·L The spectral absorption coefficient α(v) is related to the ambient temperature T, pressure P, and the type of components of the medium to be measured and their molar fraction X. When only a single spectral line is considered, the spectral absorption coefficient α(v) is the product of the pressure P, molar fraction X, spectral line intensity S(T) and the normalized linear function f(ν), that is, I(ν)=I0(ν)·e -PXS(T)f(ν)L In order to achieve spectral line parameter inversion, it is usually necessary to calculate the logarithmic difference between the outgoing light intensity and the incident light intensity to obtain the spectral line shape distribution. This step is also called the "baseline removal" process of the original signal, and the mathematical expression is: In principle, TDLAS signal processing requires two known physical quantities: one is the outgoing light intensity I(v) of the signal light passing through the medium to be measured, and the other is the incident light intensity I0(v) that passes through the same path but is not absorbed.

[0004] Accurately obtaining the incident light intensity I0(v) is extremely difficult in harsh application environments, such as engine combustion flow fields. Commonly used methods include: 1) fitting the incident light intensity I0(v) using the weak absorption portion of the original signal's edge; 2) measuring the non-absorption optical path signal as the reference incident light intensity I0(v); and 3) smoothing or filtering the original signal to approximate the incident light intensity I0(v). These methods require that the laser's output stability, wavelength scanning range, gas pressure, and component concentrations meet certain conditions. For example, method 1) requires the laser's wavelength scanning range to cover at least 10 times the linewidth to reduce fitting errors; method 2) requires good laser scanning repeatability and identical environmental conditions between the reference and signal optical paths; and method 3) requires that the frequency component of the absorption signal be significantly higher than the light source intensity spectrum to effectively extract the incident light intensity I0(v). In high-pressure environments, optical path offsets and line pressure broadening can increase the calculation errors of these methods, making experimental solutions to this problem often complex. In order to efficiently invert the characteristic parameters of the absorption spectrum while avoiding the baseline removal process of the original signal, Georg Schulze and others from the University of British Columbia tried to automatically identify the incident light intensity I0(v) by training a convolutional neural network, but judging from the results, it is still difficult to achieve the ideal effect.

[0005] In summary, the existing TDLAS technology has problems such as complex signal baseline removal process and large errors in spectral line parameter calculation under high-pressure environment. Summary of the Invention

[0006] The purpose of the present invention is to solve the technical problems of difficulty in baseline removal and large errors in spectrum line parameter calculation in the existing TDLAS technology under high-pressure environment, and to provide a method for obtaining spectrum line parameters of TDLAS measurement signals under high-pressure environment, which can effectively avoid the complex baseline removal process of the original signal, improve the applicability of TDLAS technology under high-pressure environment, and significantly reduce the calculation error of spectrum line parameters.

[0007] The concept of the present invention is:

[0008] Based on the wavelength response characteristics of the linear tuning region of the DFB laser, an overall fitting model including baseline and spectral lines is constructed, which can be used to directly fit the TDLAS raw signal, thereby inverting all spectral line parameters at one time.

[0009] In order to solve the above technical problems and realize the above inventive concept, the technical solution adopted by the present invention is:

[0010] A method for obtaining spectral line parameters of a TDLAS measurement signal under a high-pressure environment is characterized in that it includes the following steps:

[0011] Step 1) Use linear current to drive the DFB laser to obtain an output beam whose light intensity changes linearly with time. At the same time, control the temperature of the DFB laser so that the wavelength tuning range of the output beam covers any spectral line. After the output beam is transmitted through the absorbing medium in the environment to be measured, the TDLAS measurement signal I is obtained. exp (v x );

[0012] Step 2) Construct a x ), spectral absorption coefficient α(v x ) and the absorption path length L act together to form the overall fitting model:

[0013]

[0014] Among them, I(v x ) is the outgoing light intensity, k3, k2, k1, k0 are the incident light intensity I0(v x ), A is the area corresponding to the spectral line approximation Lorentz function, Δv is the line width corresponding to the spectral line approximation Lorentz function, v0 is the sampling point coordinate corresponding to the center of the spectral line approximation Lorentz function, v x The single-cycle TDLAS measurement signal I exp (v x ) The horizontal coordinate of the sampling point, x represents the number of the sampling point, and 0 represents the center of the spectral line approximation Lorentz function;

[0015] Step 3) According to the environment to be tested and TDLAS measurement signal I exp (v x ), determine the initial value and limit range of the variable parameters in the overall fitting model; the variable parameters specifically include the incident light intensity I0 (v x )’s cubic polynomial fitting coefficients k3, k2, k1, k0 and the area A, line width Δv, and center v0 of the spectral line approximation Lorentz function;

[0016] 3.1) Preprocessing TDLAS measurement signal I using baseline fitting method exp (v x ), and the incident light intensity I0(v x )’s initial values ​​of cubic polynomial fitting coefficients k3, k2, k1, and k0;

[0017] 3.2) By calculating ln(I0(v x ) / I exp (v x )) Get the spectral line shape distribution Spectral line shape distribution The integral of the horizontal axis is used as the initial value of area A, and the line shape distribution of the spectrum is The full width at half maximum is taken as the initial value of the line width Δv, and the line shape distribution of the spectrum is The horizontal coordinate corresponding to the peak value is taken as the initial value of the center v0;

[0018] 3.3) Using the initial values ​​of the fitting coefficients k3, k2, k1, and k0, the initial values ​​of the area A, the initial values ​​of the line width Δv, and the initial values ​​of the center v0 as a reference, and combining the dynamic range of the measured environmental changes to set the limit intervals of the fitting coefficients k3, k2, k1, k0, area A, line width Δv, and center v0; the dynamic range of the measured environmental changes includes temperature, pressure, and the concentration of the measured component.

[0019] Step 4) According to the initial value and limit interval of the variable parameter, a nonlinear curve is used to fit the TDLAS measurement signal I exp (v x ), with the minimum mean square error (MSE) as the goal, the variable parameters in the overall fitting model are optimized, and the overall fitting model and TDLAS measurement signal I are obtained by inversion. exp (v x ) Spectral line parameters under the best match:

[0020] 4.1) According to the initial values ​​and limit intervals of the fitting coefficients k3, k2, k1, k0 and the area A, line width Δv, and center v0, the Levenberg-Marquardt algorithm is used to fit the TDLAS measurement signal I exp (v x );

[0021] 4.2) With the goal of minimizing the mean square error (MSE), iteratively optimize the incident light intensity I0 (v x ) is a cubic polynomial fitting coefficient k3, k2, k1, k0 and area A, line width Δv, center v0, and the overall fitting model and TDLAS measurement signal I are obtained by inversion of the following formula exp (v x ) The area A, line width Δv, and center v0 under the best match:

[0022]

[0023] Where n is the single-cycle TDLAS measurement signal I exp (v x ) of the sampling points.

[0024] Furthermore, step 3.1) is specifically as follows:

[0025] Preprocessing TDLAS measurement signal using baseline fitting method exp (v x ), using TDLAS to measure signal I exp (v x) is fitted with a cubic polynomial on both sides of the weak absorption part, and the optimization iteration is performed with the minimum mean square error MSE as the goal to obtain the incident light intensity I0(v x )’s initial values ​​of the fitting coefficients k3, k2, k1, and k0;

[0026] The weak absorption part is measured by TDLAS signal I exp (v x ) as the starting point, and delete the remaining data of 5 times the line width length symmetrically, or select TDLAS measurement signal I exp (v x ) are taken as the weak absorption part.

[0027] Furthermore, in step 3.1), the number of optimization iterations is 200, and the incident light intensity I0(ν x ) The initial values ​​of the fitting coefficients k3, k2, k1, and k0 are 1.08E-10, -3.76E-7, 2.98E-3, and 0.68, respectively.

[0028] Furthermore, in step 3.2), the initial values ​​of area A, line width Δv, and center v0 are 8.95, 78.84, and 252, respectively.

[0029] Furthermore, in step 3.3), the limit intervals of the fitting coefficients k3, k2, k1, k0, area A, line width Δv and center v0 are [-1E-9, 1E-9], [-1E-6, 1E-6], [-0.01, 0.01], [-1, 1], [0, 100], [0, 400], [230, 270], respectively.

[0030] Furthermore, in step 4.2), the overall fitting model is combined with the TDLAS measurement signal I exp (v x ) The area A, line width Δv, and center v0 under the best match are 12.63, 83.48, and 250.08, respectively.

[0031] Compared with the prior art, the technical solution of the present invention has the following beneficial effects:

[0032] The present method for acquiring spectral line parameters from TDLAS measurement signals under high-pressure environments simultaneously obtains both the incident light intensity and the spectral line shape distribution by performing an overall fit on the original signal (i.e., the output beam). Compared to traditional data processing methods, this method significantly improves the accuracy of spectral line shape inversion under high-pressure environments and enhances the accuracy of spectral line parameter calculations.

[0033] 2. The method for obtaining spectral line parameters of TDLAS measurement signals under high-pressure environments of the present invention has a wide range of applications and can cover working conditions from negative pressure to high pressure. Accurate calculation of spectral line parameters can be achieved by setting a reasonable restriction interval without adding an optical path measurement reference signal, effectively solving the baseline removal problem of the TDLAS original signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 Flowchart of an embodiment of a method for obtaining spectral line parameters of a TDLAS measurement signal under a high-pressure environment according to the present invention;

[0035] Figure 2 The TDLAS measurement signal I of CO2 molecules measured at 1572.34 nm for 5 cycles under 1.3 atm in the embodiment of the present invention is exp (v x ) Schematic diagram;

[0036] Figure 3 The baseline fitting method in the embodiment of the present invention processes the TDLAS measurement signal I exp (v x )

[0037] Figure 4 In the embodiment of the present invention, ln(I0(v x ) / I exp (v x ))Inverted spectral line shape Schematic diagram;

[0038] Figure 5 The present invention measures the TDLAS signal I exp (v x ) schematic diagram of overall fitting;

[0039] Figure 6 The overall fitting model and TDLAS measurement signal I are obtained by inversion in the embodiment of the present invention. exp (v x ) Schematic diagram of the area A, line width Δv, and center v0 under optimal matching;

[0040] Figure 7 The conventional baseline fitting and the overall fitting in the embodiment are used to process the TDLAS measurement signal I at 5.3 atm. exp (v x ) comparison diagram;

[0041] Figure 8 Schematic diagram comparing the spectral line shapes inverted by traditional baseline fitting and overall fitting in the embodiment at 5.3 atm. DETAILED DESCRIPTION

[0042] like Figure 1As shown, a method for obtaining TDLAS measurement signal line parameters under high pressure environment is characterized by comprising the following steps:

[0043] Step 1) driving the DFB laser with a sawtooth current having a linear current of 30 mA and a frequency of 200 Hz to obtain an output beam whose intensity varies linearly with time, while controlling the temperature of the DFB laser so that the wavelength tuning range of the output beam covers the spectral line with a central wavelength of 1572.34 nm for the CO2 molecule;

[0044] like Figure 2 As shown, at room temperature of 1.3 atm, a photodetector is used to receive the output signal of a CO2 concentration of 50% and an absorption path length of 1.3 m. At the same time, a data acquisition device is used to record the output signal of the photodetector in real time. The sampling rate is set to 100 kHz to obtain the TDLAS measurement signal I exp (v x ).

[0045] Step 2) Construct a x ), spectral absorption coefficient α(v x ) and the absorption path length L act together to form the overall fitting model:

[0046]

[0047] Among them, I(v x ) is the outgoing light intensity, k3, k2, k1, k0 are the incident light intensity I0(v x ), A is the area corresponding to the spectral line approximation Lorentz function, Δv is the line width corresponding to the spectral line approximation Lorentz function, v0 is the sampling point coordinate corresponding to the center of the spectral line approximation Lorentz function, v x The TDLAS measurement signal I exp (v x ) is the horizontal coordinate of the sampling point, x represents the serial number of the sampling point, and 0 represents the center of the spectral line approximation Lorentz function.

[0048] Step 3) According to the test environment, DFB laser characteristics and TDLAS measurement signal I exp (v x ) shows that the DFB laser is in a linear tuning state, and the output light intensity and wavelength change linearly with time. exp (v x ), set the initial values ​​and limit ranges of the variable parameters in the overall fitting model, where the variable parameters are the initial values ​​of the fitting coefficients k3, k2, k1, k0, the initial value of the area A, the initial value of the line width Δv, and the center v0. Specifically:

[0049] 3.1) If Figure 3 As shown, the TDLAS measurement signal I is first processed using the baseline fitting method. exp (v x ), for the convenience of calculation, directly select the TDLAS measurement signal I exp (v x ) is used as the weak absorption part to perform cubic polynomial fitting (in other embodiments, the TDLAS measurement signal I can also be used to measure the signal exp (v x ) is taken as the starting point, and the remaining data of 5 times the line width are symmetrically deleted as the weak absorption part, and a cubic polynomial fitting is performed. The minimum mean square error (MSE) is taken as the goal, and the maximum number of optimization iterations is set to 200. The incident light intensity I0 (v x ) The initial values ​​of the fitting coefficients k3, k2, k1, and k0 are 1.08E-10, -3.76E-7, 2.98E-3, and 0.68, respectively;

[0050] 3.2) If Figure 4 As shown, calculate ln(I0(v x ) / I exp (v x )) Get the spectral line shape distribution Will The initial value of area A is obtained by integrating the horizontal axis. The full width at half maximum of is taken as the initial value of the line width Δv, The horizontal coordinate corresponding to the peak value is used as the initial value of the center v0. The results are calculated by the following formula: 8.95, 78.84, 252;

[0051]

[0052] Δv=|v x1 -v x2 |

[0053]

[0054] 3.3) The initial values ​​of the fitting coefficients k3, k2, k1, and k0, the initial values ​​of the area A, the initial values ​​of the line width Δv, and the initial values ​​of the center v0 are used as references. At the same time, the limit intervals of the fitting coefficients k3, k2, k1, k0, area A, line width Δv, and center v0 are set according to the dynamic range of the environmental changes to be measured. The results are: [-1E-9, 1E-9], [-1E-6, 1E-6], [-0.01, 0.01], [-1, 1], [0, 100], [0, 400], [230, 270], respectively. In this embodiment, the dynamic range of the environmental changes to be measured includes pressure and CO2 concentration.

[0055] Step 4) According to the initial value and limit interval of the variable parameter, a nonlinear curve is used to fit the TDLAS measurement signal I exp (v x ), with the minimum mean square error (MSE) as the goal, the variable parameters in the overall fitting model are optimized, and the overall fitting model and TDLAS measurement signal I are obtained by inversion. exp (v x ) Spectral line parameters under the best match, namely area A, line width Δv n and the optimal solution of center v0.

[0056] 4.1) Based on the initial values ​​of the fitting coefficients k3, k2, k1, k0, the initial values ​​of the area A, the initial values ​​of the line width Δv, the initial values ​​of the center v0 and the restriction interval, the Levenberg-Marquardt algorithm is used to fit the TDLAS measurement signal I exp (v x );

[0057] 4.2) With the goal of minimizing the mean square error (MSE), iteratively optimize the incident light intensity I0 (v x ) of the cubic polynomial fitting parameters k3, k2, k1, k0 and area A, line width Δv, center v0, and set the maximum number of optimization iterations to 200, as shown in Figure 5 、 Figure 6 As shown, the overall fitting model and TDLAS measurement signal I are obtained by inversion of the following formula: exp (v x ) The optimal solution for area A, line width Δv, and center v0 under the best match:

[0058]

[0059] Where n is the single-cycle TDLAS measurement signal I exp (v x ) of the sampling points.

[0060] To avoid TDLAS measuring signal I exp (v x) affects the calculation accuracy. The effective data point interval of the single-cycle signal selected during fitting is [30, 480]. The optimal solutions for the final area A, line width Δv, and center v0 are 12.63, 83.48, and 250.08, respectively. The method of the present invention solves the problem of TDLAS measurement signal I under high pressure environment. exp (v x ) and the problem of baseline removal and spectral line parameter extraction, which effectively improves the applicability of TDLAS technology in high-pressure environments. This method is suitable for absorption spectrum line shape calculation and parameter inversion under a wide range of working conditions.

[0061] In order to verify the reliability of the method of the present invention, the TDLAS measurement signal I under the same temperature, CO2 concentration and different pressure environments is exp (v x ) and perform steps 2) to 4) above. The results of the traditional baseline fitting method are used as a comparison. Combined with the predicted data from the absorption spectrum theoretical model, the measurement errors and variation trends of area A and line width Δv are obtained, as shown in Table 1, which compares the results of baseline fitting and overall fitting for TDLAS measurement signals at different pressures.

[0062] Table 1 Baseline fitting and overall fitting processing of TDLAS measurement signals at different pressures I exp (v x )Result comparison

[0063]

[0064] As shown in Table 1, it can be seen that as the pressure increases, the baseline fitting error gradually increases, while the overall fitting result error is small and is almost unaffected by the pressure change to a certain extent. exp (v x ) results are compared with Figure 7 、 Figure 8 As shown in the figure, the traditional baseline fitting method has a large I0(v x ) fitting amplitude is too low, which leads to weak absorption intensity of calculated spectrum line. By directly fitting I(v x ) can effectively improve this problem.

Claims

1. A method for obtaining TDLAS measurement signal line parameters under high pressure environment, characterized in that: The following steps are involved: Step 1) Use linear current to drive the DFB laser to obtain an output beam whose light intensity changes linearly with time. At the same time, control the temperature of the DFB laser so that the wavelength tuning range of the output beam covers any spectral line. After the output beam is transmitted through the absorbing medium in the environment to be measured, the TDLAS measurement signal I is obtained. exp (v x ); Step 2) Construct a x ), spectral absorption coefficient α(v x ) and the absorption path length L act together to form the overall fitting model: Among them, I(v x ) is the outgoing light intensity, k3, k2, k1, k0 are the incident light intensity I0(v x ), A is the area corresponding to the spectral line approximation Lorentz function, Δv is the line width corresponding to the spectral line approximation Lorentz function, v0 is the sampling point coordinate corresponding to the center of the spectral line approximation Lorentz function, v x The single-cycle TDLAS measurement signal I exp (v x ) The horizontal coordinate of the sampling point, x represents the number of the sampling point, and 0 represents the center of the spectral line approximation Lorentz function; Step 3) According to the environment to be tested and TDLAS measurement signal I exp (v x ), determine the initial value and limit range of the variable parameters in the overall fitting model; the variable parameters specifically include the incident light intensity I0 (v x )’s cubic polynomial fitting coefficients k3, k2, k1, k0 and the area A, line width Δv, and center v0 of the spectral line approximation Lorentz function; 3.1) Preprocessing TDLAS measurement signal I using baseline fitting method exp (v x ), and the incident light intensity I0(v x )’s initial values ​​of cubic polynomial fitting coefficients k3, k2, k1, and k0; 3.2) By calculating ln(I0(v x ) / I exp (v x )) Get the spectral line shape distribution Spectral line shape distribution The integral of the horizontal axis is used as the initial value of area A, and the line shape distribution of the spectrum is The full width at half maximum is taken as the initial value of the line width Δv, and the line shape distribution of the spectrum is The horizontal coordinate corresponding to the peak value is taken as the initial value of the center v0; 3.3) Using the initial values ​​of the fitting coefficients k3, k2, k1, and k0, as well as the initial values ​​of the area A, the initial values ​​of the line width Δv, and the initial values ​​of the center v0 as references, set the limits for the fitting coefficients k3, k2, k1, k0, the area A, the line width Δv, and the center v0 in combination with the dynamic range of the measured environmental changes; the dynamic range of the measured environmental changes includes temperature, pressure, and the concentration of the measured component; Step 4) According to the initial value and limit interval of the variable parameter, a nonlinear curve is used to fit the TDLAS measurement signal I exp (v x ), with the minimum mean square error (MSE) as the goal, the variable parameters in the overall fitting model are optimized, and the overall fitting model and TDLAS measurement signal I are obtained by inversion. exp (v x ) Spectral line parameters under the best match: 4.1) According to the initial values ​​and limit intervals of the fitting coefficients k3, k2, k1, k0 and the area A, line width Δv, and center v0, the Levenberg-Marquardt algorithm is used to fit the TDLAS measurement signal I exp (v x ); 4.2) With the goal of minimizing the mean square error (MSE), iteratively optimize the incident light intensity I0 (v x ) is a cubic polynomial fitting coefficient k3, k2, k1, k0 and area A, line width Δv, center v0, and the overall fitting model and TDLAS measurement signal I are obtained by inversion of the following formula exp (v x ) The area A, line width Δv, and center v0 under the best match: Where n is the single-cycle TDLAS measurement signal I exp (v x ) of the sampling points.

2. The method for obtaining TDLAS measurement signal line parameters under a high-pressure environment according to claim 1, characterized in that: Step 3.1) is specifically as follows: Preprocessing TDLAS measurement signal using baseline fitting method exp (v x ), using TDLAS to measure signal I exp (v x ) is fitted with a cubic polynomial on both sides of the weak absorption part, and the optimization iteration is performed with the minimum mean square error MSE as the goal to obtain the incident light intensity I0(v x )’s initial values ​​of the fitting coefficients k3, k2, k1, and k0; The weak absorption part is measured by TDLAS signal I exp (v x ) as the starting point, and delete the remaining data of 5 times the line width length symmetrically, or select TDLAS measurement signal I exp (v x ) are taken as the weak absorption part.

3. The method for obtaining TDLAS measurement signal line parameters under a high-pressure environment according to claim 2, characterized in that: In step 3.1), the number of optimization iterations is 200, and the incident light intensity I0 (ν x ) The initial values ​​of the fitting coefficients k3, k2, k1, and k0 are 1.08E-10, -3.76E-7, 2.98E-3, and 0.68, respectively.

4. The method for obtaining TDLAS measurement signal spectral line parameters under a high-pressure environment according to claim 3, characterized in that: In step 3.2), the initial values ​​of the area A, line width Δv and center v0 are 8.95, 78.84 and 252 respectively.

5. The method for obtaining TDLAS measurement signal line parameters under high-pressure environment according to claim 4, characterized in that: In step 3.3), the limit intervals of the fitting coefficients k3, k2, k1, k0, area A, line width Δv and center v0 are [-1E-9, 1E-9], [-1E-6, 1E-6], [-0.01, 0.01], [-1, 1], [0, 100], [0, 400], [230, 270], respectively.

6. The method for obtaining TDLAS measurement signal line parameters under high-pressure environment according to claim 5, characterized in that: In step 4.2), the overall fitting model is combined with the TDLAS measurement signal I exp (v x ) The area A, line width Δv, and center v0 under the best match are 12.63, 83.48, and 250.08, respectively.

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