A method and system for on-line detection of carbon dioxide concentration in flue gas

Abstract

The application belongs to the field of flue gas carbon dioxide concentration determination, and particularly discloses a flue gas carbon dioxide concentration online detection method and system, which comprises the following steps: obtaining the average absorption coefficients of carbon dioxide and water vapor under different temperatures and concentrations respectively, and obtaining the relationship between the flue gas average absorption coefficient and the temperature and concentration; constructing the relationship between the theoretical spectral radiation intensity of the gas layer outward emission and the flue gas average absorption coefficient, and obtaining the relationship between the theoretical spectral radiation intensity and the gas temperature and concentration; collecting the actual spectral radiation intensity of the flue gas emission along the direction perpendicular to the airflow direction in real time through an infrared spectrum measuring device; constructing a target function with the difference between the actual spectral radiation intensity and the theoretical spectral radiation intensity; solving the target function by using an optimization algorithm, and obtaining the temperature and concentration of carbon dioxide and water vapor corresponding to the lowest target function value. The application can realize carbon dioxide concentration measurement without an additional light source emission device, and has simple structure and efficient collection.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of flue gas carbon dioxide concentration determination, more particularly, to a flue gas carbon dioxide concentration online detection method and system. BACKGROUND

[0002] The coal-fired carbon emission quantification method can be divided into carbon balance method, emission factor method and measurement method. The carbon balance method and the emission factor method belong to the accounting method, which is simple to calculate and has high authority. The measurement method directly obtains the total gas emission amount through the continuous emission monitoring system, which is efficient and less disturbed by human beings.

[0003] At present, the outstanding representative of the measurement method at home and abroad is the optical detection technology, the basic principle of which is the absorption spectrum of molecules. The concentration of gas is inversely calculated by using the difference of gas absorption spectrum. The response is rapid, and non-contact measurement can be realized, so it is widely developed and tested. Among them, for the detection of carbon dioxide in flue gas, common modern optical measurement technologies include tunable diode laser absorption spectroscopy (TDLAS), non-dispersive infrared detection technology (NDIR) and active differential optical absorption spectroscopy (DOAS). However, these methods are active detection methods, which need to set up an additional light source emitting device and a signal receiving device on the spectrum acquisition equipment, and the system structure is relatively complex. When collecting spectral radiation signals, the alignment of the light path between the emitting and receiving devices is very important, but the dust, fly ash barrier and vibration in the industrial field will interfere with the measurement results. SUMMARY

[0004] In view of the above defects or improvement needs of the prior art, the present application provides a flue gas carbon dioxide concentration online detection method and system, which aims to reduce external interference and improve the detection effect of flue gas carbon dioxide concentration.

[0005] To achieve the above-mentioned purpose, according to the first aspect of the present application, a flue gas carbon dioxide concentration online detection method is provided, which comprises the following steps:

[0006] The flue gas includes carbon dioxide and water vapor, the average absorption coefficients of carbon dioxide and water vapor at different temperatures and component concentrations are obtained respectively, and then the relationship between the average absorption coefficient of the flue gas and the temperature and component concentration of the flue gas is obtained;

[0007] A gas spectral radiation model, i.e. the relationship between the theoretical spectral radiation intensity emitted outward by the gas layer and the average absorption coefficient of the flue gas, is constructed, so as to obtain the relationship between the theoretical spectral radiation intensity emitted outward by the gas layer and the temperature and component concentration of the flue gas;

[0008] The actual spectral radiation intensity emitted by the flue gas along the direction perpendicular to the airflow is collected in real time by an infrared spectrum measuring device;

[0009] A target function is constructed by the difference between the actual spectral radiation intensity and the theoretical spectral radiation intensity of the gas layer outward emission; an optimization algorithm is used to iteratively solve the target function, and the flue gas temperature and component concentration corresponding to the lowest target function value are obtained, so as to realize online detection of the carbon dioxide concentration in the flue gas.

[0010] As a further preferred, the calculation method of the average absorption coefficient of carbon dioxide and water vapor at different temperatures and component concentrations is as follows:

[0011] Based on the gas radiation characteristic database and the line-by-line method, the spectral absorption coefficient κ of gas i at different temperatures, component concentrations and different wavelengths λ is obtained a,λ,i , so as to obtain the average absorption coefficient of gas i in each spectral interval Δλ j at different temperatures and component concentrations When the gas is carbon dioxide, i=2, the gas is water vapor; the spectral interval Δλ j is the collection interval of the infrared spectrum measuring device.

[0012] As a further preferred, the calculation method of the average absorption coefficient of gas i in each spectral interval Δλ j is as follows:

[0013]

[0014] Wherein, L is the flue gas width, λ j is the length of the spectral interval Δλ j .

[0015] As a further preferred, the determination method of the relationship between the average absorption coefficient of the flue gas and the temperature and component concentration is as follows:

[0016] According to the average absorption coefficient , the average absorption coefficient of the flue gas in each spectral interval Δλ j at different temperatures and component concentrations is obtained , and the least square method is used to fit to obtain the relationship between the average absorption coefficient of the flue gas and the temperature and component concentration.

[0017] As a further preferred, the gas spectral radiation model is:

[0018]

[0019] Wherein, is the theoretical spectral radiation intensity of the gas layer outward emission in the spectral interval Δλ j when the temperature is T, the carbon dioxide and water vapor concentrations in the flue gas are X1 and X2; f is a correlation function; is the actual spectral radiation intensity of the gas layer outward emission in the spectral interval Δλ c,j ​the blackbody spectral radiation intensity at wavelength λ c,j is the center wavelength of the spectral interval Δλ j . is the average absorption coefficient of the flue gas in the spectral interval Δλ j when the temperature is T and the concentrations of carbon dioxide and water vapor in the flue gas are X1 and X2.

[0020] As a further preferred, the gas spectral radiation model is specifically:

[0021]

[0022] wherein, is the theoretical spectral radiation intensity of the gas layer outward emission in the spectral interval Δλ j , is the blackbody spectral radiation intensity at wavelength λ c,j , is the average absorption coefficient of the flue gas in the spectral interval Δλ j , and L is the width of the flue gas.

[0023] As a further preferred, the objective function is as follows:

[0024]

[0025] wherein, is the objective function value, N is the total number of spectral intervals, is the actual spectral radiation intensity of the jth spectral interval Δλ j collected, is the theoretical spectral radiation intensity of the gas layer outward emission in the jth spectral interval Δλ j .

[0026] As a further preferred, the optimization algorithm is a particle swarm optimization algorithm.

[0027] According to a second aspect of the present application, there is provided a flue gas carbon dioxide concentration online detection system, comprising a processor, which is configured to execute the above flue gas carbon dioxide concentration online detection method.

[0028] According to a third aspect of the present application, there is provided a computer readable storage medium, which stores a computer program, and the computer program is configured to be executed by a processor to implement the above flue gas carbon dioxide concentration online detection method.

[0029] In general, the above technical solutions conceived by the present application have the following technical advantages compared with the prior art:

[0030] 1.The present application obtains the relationship between the gas temperature, concentration and the theoretical spectral radiation intensity distribution emitted by the gas by constructing the relationship between the spectral radiation characteristics of the gas and the gas temperature, concentration, and the radiation heat transfer model; and then calculates the carbon dioxide concentration in the flue gas by using the theoretical spectral radiation intensity and the collected emission spectrum based on the optimization algorithm.

[0031] 2.The present application obtains the high spectral resolution absorption coefficient by the gas radiation characteristic database, and then converts it into the low resolution spectral interval corresponding to the spectral collection device, and calculates the average absorption coefficient of the flue gas according to the absorption coefficients of carbon dioxide and water vapor; compared with the existing measurement method (such as the gas concentration measurement method based on the Fourier transform infrared absorption spectrum collection technology), the method realizes the measurement of gas concentration and temperature by low resolution spectral collection technology, reduces the requirements and cost of measurement technology, and improves the measurement efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0032] Figure 1 The present application provides a flue gas carbon dioxide concentration online detection method flow chart;

[0033] Figure 2 The present application provides an infrared spectrum measurement device for collecting actual spectral radiation intensity schematic diagram;

[0034] Figure 3 The present application provides an optimal estimation of actual spectral intensity and theoretical intensity comparison diagram. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical scheme and advantages of the present application more clear, the present application is further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application, and are not used to limit the present application. In addition, the technical features involved in each embodiment of the present application described below can be combined with each other as long as they do not conflict with each other.

[0036] The present application provides a flue gas carbon dioxide concentration online detection method, as shown in Figure 1 The present application provides a flue gas carbon dioxide concentration online detection method, as shown in

[0037] S1, establishing a gas radiation characteristic database: obtaining the spectral radiation characteristic distribution of carbon dioxide and water vapor with high spectral resolution from the gas radiation characteristic database, and fitting the relationship between the spectral radiation characteristic of the gas, the temperature and the concentration of the gas under each collection interval based on the collection interval of the low spectral resolution infrared spectrum collection device to establish a low spectral resolution gas radiation characteristic database.

[0038] Specifically, step S1 includes:

[0039] S11, the emission spectral radiation intensity of the gas layer in the flue gas in the mid-infrared band is mainly from a large amount of carbon dioxide and water vapor generated in the combustion process, and the high-resolution spectral absorption coefficient κ of carbon dioxide and water vapor at wavelength λ under different concentrations and temperatures is obtained based on the gas radiation characteristic database and the line-by-line method. a,λ,i (i=1 is CO2, i=2 is H2O).

[0040] S12, since the low-resolution spectral collection device actually used cannot reflect the detailed distribution characteristics of the gas emission spectrum, it is necessary to convert it to the spectral interval Δλ j , where Δλ j is the jth spectral interval collected by the spectral collection device.

[0041] According to step S11, the spectral absorption coefficient κ a,λ,i is obtained, and the average absorption coefficient of the gas in the spectral interval Δλ j is calculated, as shown in the following formula:

[0042]

[0043] In the formula, is the average absorption coefficient of gas i in the spectral interval Δλ j , L is the width of the flue gas; λ j is the length of the spectral interval Δλ j , that is, the absolute value of the upper and lower limits of the wavelength of the spectral interval Δλ j .

[0044] Further, for the N collected spectral intervals, the average absorption coefficient of the gas in each spectral interval under different temperatures and concentrations can be obtained according to formula (1). Further, the least square method is used to fit the relationship between the average absorption coefficient of the gas in each spectral interval and the temperature and concentration of the gas, and a low-resolution gas radiation characteristic database corresponding to the spectral collection device used is established.

[0045] S2, constructing a gas spectrum radiation model: combining the low-spectral-resolution gas radiation database established in step S1, further establishing a spectrum radiation model for gas layers with different pressures and thicknesses, to obtain the relationship between gas temperature, concentration and the spectrum radiation intensity distribution emitted thereby.

[0046] Specifically, step S2 includes:

[0047] S21, the spectrum absorption coefficient of the flue gas is equal to the sum of the absorption coefficients of each component, so the average absorption coefficient of the flue gas in the spectrum interval Δλ j which can be calculated by the following formula:

[0048]

[0049] In the formula, is the average absorption coefficient of the flue gas in the spectrum interval Δλ j and are the average absorption coefficients of CO2 and H2O in the spectrum interval Δλ j , which can be obtained according to the low-resolution gas radiation characteristic database established in step S1.

[0050] S22, for a gas layer with a temperature distribution of T, the average absorption coefficient of the gas layer in the spectrum interval Δλ j is , the thickness of the gas layer is L and the self-absorption effect inside the gas flow is considered but the scattering effect of the gas on incident radiation is ignored, and it is assumed that the spectrum blackbody radiation intensity emitted outward by the gas in each spectrum interval is constant. The theoretical spectrum radiation intensity emitted outward by the gas layer can be further established, and the relationship f between the blackbody spectrum radiation intensity and the average absorption coefficient

[0051]

[0052] S3, gas emission spectrum acquisition: placing a spectrum measurement device outside the flue gas flow to acquire the actual spectrum radiation intensity

[0053] S4, gas concentration calculation: calculating the gas temperature and component concentration according to the actual spectrum radiation intensity emitted by the gas acquired in step S3 and the gas spectrum radiation model constructed in step S2. Taking the difference between the actual spectrum radiation intensity acquired and the theoretical spectrum radiation intensity calculated by the gas spectrum radiation model as the objective function, using an optimization algorithm to obtain the minimum value of the objective function, and then obtaining the carbon dioxide concentration in the flue gas.​​​

[0054] Specifically, step S4 comprises:

[0055] S41: based on the gas spectral radiation model, when the temperature T of the flue gas flow, the concentrations X1 and X2 of the flue gas components CO2 and H2O are obtained, the theoretical radiation intensity of the flue gas emitted in the jth spectral interval is At the same time, according to the actual spectral radiation intensity measured The objective function for calculating the temperature and concentration of the flue gas flow can be established, as shown in the following formula:

[0056]

[0057] In the formula, The objective function value is N, and the total number of spectral intervals.

[0058] S42: using the optimization algorithm to iteratively solve the temperature and component concentration in the flue gas flow, the minimum value of the objective function value is obtained, and the corresponding gas temperature and component concentration (T, X1, X2) are the calculated flue gas temperature and component concentration values, so as to obtain the carbon dioxide concentration in the flue gas.

[0059] The following is a specific embodiment:

[0060] (1) Establish a gas radiation characteristic database:

[0061] The radiation of the gas layer in the hydrocarbon diffusion flame mainly comes from a large amount of H2O and CO2 generated by the combustion process. The absorption coefficient κ of the exhaust gas a,λ is equal to the sum of the H2O line absorption coefficient and the CO2 line absorption coefficient . Among them, for a single component gas, the spectral radiation characteristics of the gas are related to parameters such as the diameter of the gas molecules, which can be obtained in the database HITEMP 2010. According to the measurement wavelength interval (2500-4500nm) of the mid-infrared spectrometer used and the related parameters given in the database HITEMP 2010, the spectral absorption coefficient of H2O and CO2 is calculated by using the line-by-line method under different temperatures and different concentrations.

[0062] Based on the range of each wavelength interval of the low-resolution infrared spectrum acquisition device used, the least square method is used to fit the fitting formula of the average spectral absorption coefficient of H2O and CO2 in the exhaust gas with respect to the gas component concentration and the temperature of the exhaust gas in each spectral interval. The fitting method of binary four-order is used in the present application, and for the ith spectral interval, the fitting relationship of H2O or CO2 is:

[0063]

[0064] where, is the average spectral absorption coefficient of gas component i in the jth spectral interval, T gas is the temperature of the gas, X i is the concentration of gas component i, a 0,j , a 1,j , a 2,j and are the fitting coefficients of the least square method in the ith spectral interval. The fitting coefficient values of the fitting relationship of the average spectral absorption coefficient of CO2 in different spectral intervals are listed in Table 1.

[0065] Table 1 Fitting coefficient values of the fitting relationship of the average spectral absorption coefficient of CO2 in different spectral intervals

[0066] 2995 - 3006 nm 3496 - 3507 nm 3998 - 4009 nm 4499 - 4510 nm [a0] 8.7576E-8 -2.6898E-7 -2.6578E-6 -3.46710E-6 [a1] 7.7321E-13 9.19281E-12 -1.0847E-11 -3.52885E-11 [a2] 4.7532E-12 1.8076E-12 5.33860E-11 -8.42858E-8 [a3] -1.8215E-14 -3.0601E-14 -2.30971E-13 4.52390E-13 [a4] -4.3460E-9 -4.6203E-8 2.48077E-8 1.46164E-7 [a5] -2.9043E-8 -9.6853E-9 -2.89422E-7 1.94939E-4 [a6] 7.8985E-11 1.8363E-10 1.59010E-9 -3.28106E-10 [a7] 5.7789E-6 5.8499E-5 3.12353E-5 -4.55751E-5 [a8] 4.6771E-5 1.2773E-5 3.93891E-4 0.32712

[0067] (2) Constructing the gas spectral radiation model:

[0068] The measured gas temperature and component concentration in the burnout gas are considered to be uniform, the self-absorption effect inside the gas flow is considered but the scattering effect of the gas on the incident radiation is ignored, the width of the burnout gas is L, and it is assumed that the spectral blackbody radiation intensity emitted outward by the gas in each spectral interval Δλ j is constant. Then the spectral radiation intensity emitted by the burnout gas flow along the direction perpendicular to the flow direction can be expressed as

[0069]

[0070] where, is the blackbody spectral radiation intensity at a wavelength of λ c,j , λ c,j is the center wavelength of the spectral interval Δλ j ; and is the average absorption coefficient of the flue gas in the spectral interval Δλ j , and L is the width of the gas layer.

[0071] where, the blackbody spectral radiation intensity is calculated by the following formula:

[0072]

[0073] where, c1 and c2 are constants, which are 3.7418x10 -16 Wm 2 and 1.4388 cmK, respectively.

[0074] (3) Gas emission spectrum acquisition:

[0075] The emission spectrum of the gas in the burnout gas stream was measured using a mid-infrared spectrometer, model SM301, with a spectral range of 2500–4500 nm and a spectral resolution of approximately 20 nm. The spectrometer converts the light signal carried by the incident radiation into an electrical signal. Before the measurement experiment, the electrical signal values ​​collected by the spectrometer need to be calibrated into radiation intensity values ​​based on an accurate radiation source. Therefore, this invention first calibrated the spectrometer using a high-temperature blackbody furnace, obtaining the relationship between the spectrometer's electrical signal values ​​and the radiation intensity. Then, the spectral measurement equipment was placed outside the burnout gas, and the emission spectral radiation intensity I of the high-temperature gas in the infrared band perpendicular to the gas flow direction was collected. Δλ,mea The data collection diagram is as follows: Figure 2 As shown, the integration time for data acquisition was set to 50 ms. The emitted spectral radiation intensity distribution was also measured. Simultaneously, the thickness L of the burnout gas flow was measured.

[0076] (4) Gas concentration calculation:

[0077] The temperature and gas fraction of the gas are calculated by combining the Particle Swarm Optimization (PSO) algorithm and the spectral radiation model established in step (2). This algorithm introduces the problem to be optimized through an objective function, searches for randomly distributed particles in the search space, and iterates multiple times to obtain the global optimum position, i.e., the optimal solution to the problem. During the iteration process, the extreme value of the previous iteration is used to update the random position of the particles, and the next iteration begins. The iteration formula is:

[0078] V n,t+1 =V n,t +B1R1(P n,t -Y n,t )+B2R2(P g,t -Y n,t (8)

[0079] Y n,t+1 =Y n,t +V n,t+1 (9)

[0080] In the formula, B1 and B2 are learning factors, with B1 = B2 = 2.0; R1 and R2 are random numbers in the interval [0, 1]; V n,t Y is the velocity vector of the nth particle in the tth iteration; n,t Let be the position vector of the nth particle in the tth iteration. Since this example requires solving for the temperature of the burnout gas and the concentrations of CO2 and H2O within it, therefore... P n,t is the individual extremum, i.e., the optimal solution found by the nth particle itself; is the global extremum, i.e., the optimal solution found by the entire population. Furthermore, the objective function for calculation is shown in equation (4).

[0081] According to the spectral radiation intensity distribution of the flame burned gas emission collected in step (2), the spectral radiation intensity distribution is introduced into the PSO algorithm for iterative solution, so that the temperature of the burned gas and the concentrations of CO2 and H2O are obtained. The measured gas temperature and the corresponding theoretical spectral radiation intensity of the component concentration are as shown in Figure 3 As shown in the figure, the theoretical spectral intensity curve and the actual spectral intensity curve are well fitted. At the same time, the calculated flame temperature is 1312K, and the concentrations of CO2 and H2O are 13.6% and 21.2%, respectively.

[0082] The present application firstly obtains the high-resolution spectral radiation characteristics of carbon dioxide and water vapor from the gas radiation characteristic database, and fits the relationship between the gas spectral radiation characteristics and the gas temperature and concentration in the collection interval, establishes the low-resolution gas radiation characteristic database corresponding to the spectral collection device, then based on the established database, further establishes the gas spectral radiation model, obtains the relationship between the gas temperature, concentration and the spectral radiation intensity distribution emitted thereby, collects the spectral radiation intensity distribution emitted by the high-temperature gas in the flue gas, and finally calculates the carbon dioxide concentration in the flue gas by using the gas spectral radiation model and the collected emission spectrum based on the optimization solving algorithm. The present application does not need an external light source emission device, has simple structure, high collection efficiency, can be widely applied in the industrial field of coal-fired power plants, and has great development prospect.

[0083] Those skilled in the art can easily understand that the above description is only a preferred embodiment of the present application, and is not intended to limit the present application, and any modification, equivalent replacement and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for online detection of carbon dioxide concentration in flue gas, characterized in that, Includes the following steps: Flue gas includes carbon dioxide and water vapor. The average absorption coefficients of carbon dioxide and water vapor at different temperatures and component concentrations are obtained, and then the relationship between the average absorption coefficient of flue gas and flue gas temperature and component concentration is obtained. A gas spectral radiation model is constructed, which is the relationship between the theoretical spectral radiation intensity emitted by the gas layer and the average absorption coefficient of the flue gas, thereby obtaining the relationship between the theoretical spectral radiation intensity emitted by the gas layer and the flue gas temperature and component concentration. The actual spectral radiation intensity emitted by the flue gas along the direction perpendicular to the airflow is collected in real time using an infrared spectroscopy measuring device. The objective function is constructed using the difference between the actual spectral radiance and the theoretical spectral radiance emitted outward from the gas layer; An optimization algorithm is used to iteratively solve the objective function to obtain the flue gas temperature and component concentration corresponding to the lowest objective function value, thereby realizing online detection of carbon dioxide concentration in flue gas.

2. The online detection method for carbon dioxide concentration in flue gas as described in claim 1, characterized in that, The average absorption coefficients of carbon dioxide and water vapor at different temperatures and component concentrations are calculated as follows: The spectral absorption coefficient κ of gas i at different temperatures, component concentrations, and wavelengths λ was obtained using a gas radiation characteristics database and the line-by-line method. a,λ,i Thus, the Δλ of gas i in each spectral range under different temperatures and component concentrations can be obtained. j Average absorption coefficient within When i = 1, the gas is carbon dioxide; when i = 2, the gas is water vapor; spectral range Δλ j These are the acquisition intervals of the infrared spectroscopy measurement device.

3. The online detection method for carbon dioxide concentration in flue gas as described in claim 2, characterized in that, Gas i in each spectral range Δλ j Average absorption coefficient within The calculation method is as follows: Where L is the flue gas width, λ j For the spectral range Δλ j The length.

4. The online detection method for carbon dioxide concentration in flue gas as described in claim 2, characterized in that, The relationship between the average absorption coefficient of flue gas and temperature and component concentration is determined as follows: Based on the average absorption coefficient The Δλ values ​​of flue gas in various spectral ranges at different temperatures and component concentrations were obtained. j Average absorption coefficient within The relationship between the average absorption coefficient of flue gas and temperature and component concentration was obtained by fitting the data using the least squares method.

5. The online detection method for carbon dioxide concentration in flue gas as described in claim 2, characterized in that, The gas spectral radiation model is as follows: in, When the temperature is T and the concentrations of carbon dioxide and water vapor in the flue gas are X1 and X2, respectively, the flue gas in the spectral range Δλ j The theoretical spectral radiation intensity emitted outward from the inner gas layer; f is the correlation function; For a temperature of T and a wavelength of λ c,j blackbody spectral radiance at time λ c,j For the spectral range Δλ j The center wavelength; When the temperature is T and the concentrations of carbon dioxide and water vapor in the flue gas are X1 and X2, respectively, the flue gas in the spectral range Δλ j The average absorption coefficient within.

6. The online detection method for carbon dioxide concentration in flue gas as described in claim 5, characterized in that, The specific gas spectral radiation model is as follows: in, For flue gas in the spectral range Δλ j The theoretical spectral radiation intensity emitted outward from the inner gas layer. For wavelength λ c,j Blackbody spectral radiation intensity at that time For flue gas in the spectral range Δλ j The average absorption coefficient within the flue gas, where L is the width of the flue gas.

7. The online detection method for carbon dioxide concentration in flue gas as described in claim 1, characterized in that, The objective function is shown in the following equation: In the formula, The objective function value is N, where N is the total number of spectral intervals. For the j-th spectral interval Δλ collected j The actual spectral radiance, For the flue gas in the j-th spectral interval Δλ j The theoretical spectral radiation intensity emitted outward from the inner gas layer.

8. The online detection method for carbon dioxide concentration in flue gas according to any one of claims 1-7, characterized in that, The optimization algorithm is the particle swarm optimization algorithm.

9. An online detection system for carbon dioxide concentration in flue gas, characterized in that, Includes a processor, said processor being configured to perform the online detection method for carbon dioxide concentration in flue gas as described in any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the online detection method for carbon dioxide concentration in flue gas as described in any one of claims 1-8.

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