Fischer-Tropsch synthesis process gas online detection system and method

Abstract

A Fischer-Tropsch synthesis process gas online detection system and method, the Fischer-Tropsch synthesis process gas online detection system comprises an air intake control unit, a spectral measurement core unit, a gas exhaust module and an industrial computer; the spectral measurement core unit comprises an infrared absorption spectrum measurement module, a Raman spectrum measurement module, a temperature sensor and a pressure sensor; the infrared absorption spectrum measurement module comprises an interferometer, an infrared absorption spectrum measurement sample cell cabin and an infrared signal detection module, and the infrared absorption spectrum measurement sample cell cabin comprises an infrared absorption spectrum measurement flow cell, a blank sample cell and a displacement stage; the Raman spectrum measurement module comprises a laser, a Raman spectrum measurement flow cell, a Raman signal collection device, an optical fiber and a spectrometer; the industrial computer comprises a hardware control system, a database, a quantification module and a display and communication module; the database comprises an infrared absorption spectrum database and a Raman spectrum database, and the database and the quantification module are used for quantitative analysis of data measured by the spectral measurement core unit.

Description

Technical Field

[0001] The present invention relates to an online detection system and method for Fischer-Tropsch synthesis process gas, and in particular to an online detection system and method for Fischer-Tropsch synthesis process gas based on the combination of infrared absorption spectrum and Raman spectrum, belonging to the technical field of gas analysis and testing. Background Art

[0002] In the petrochemical and coal chemical industries, in-situ real-time measurement of the composition of mixed gases in the process is of great significance for optimizing the process flow and improving production efficiency. Coal-to-liquids is one of the key industries in the coal chemical industry, and Fischer-Tropsch synthesis is the core process of coal-to-liquids. In this process, the composition of process gases such as inlet gas, reaction tail gas, decarbonization return gas, decarbonization tail gas, and oil washing tail gas has an important influence on the efficiency of Fischer-Tropsch synthesis. The above process gas contains a variety of hydrocarbons (C x H y , x=1-6, y=2x or 2x+2) and CO, CO2, H2, N2 and other components. At present, the above gases can only be detected by chromatography technology, but chromatography technology needs to be collected and sent to the analysis room for testing. The analysis time of a single data point takes 1-2 hours, which has low timeliness and cannot realize continuous flow sampling. It is not a real online analysis equipment and cannot realize in-situ and rapid analysis.

[0003] Spectral detection has been widely used in the industrial field because of its advantages such as non-destructive and rapid detection, no need for sample pretreatment, low detection cost, and simultaneous online detection of multiple components. Among them, infrared absorption spectroscopy and Raman spectroscopy are commonly used spectral detection methods. Infrared absorption spectroscopy has the advantage of high sensitivity, but when infrared absorption spectroscopy technology is used for the detection of mixed hydrocarbons, there is a serious overlap in the absorption peaks of hydrocarbons with different carbon numbers, resulting in errors in the test results. There is currently no effective solution. The existing infrared absorption spectroscopy technology is limited to semi-quantitative analysis of molecules with large differences in infrared absorption spectral characteristics. However, the composition of the Fischer-Tropsch synthesis process gas is complex, and the non-polar molecules in the process gas lack infrared absorption characteristics. It is challenging to use infrared absorption spectroscopy technology to perform quantitative analysis of complex multi-component mixed hydrocarbon gases, and no relevant reports have been seen. In addition, infrared spectroscopy has no infrared activity for symmetrical molecules such as H2 and N2 in the mixed gas. Raman spectroscopy is responsive to hydrocarbons and molecules such as H2 and N2, but the Raman signal is very weak, and the signal strength is affected by many factors such as laser intensity, Raman scattered light signal collection efficiency, detector efficiency, etc., and the low resolution of the Raman signal causes serious overlap of the Raman signals corresponding to hydrocarbon components. Therefore, it is impossible to quantitatively analyze complex gas components using Raman spectroscopy. Therefore, it is urgent to develop relevant technologies in a targeted manner to achieve the measurement of all gas components in the complex Fischer-Tropsch synthesis process gas. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide an online detection system and method for Fischer-Tropsch synthesis process gas in view of the deficiencies in the prior art, which can realize calibration-free quantitative detection of all components of Fischer-Tropsch synthesis process gas.

[0005] The technical problem to be solved by the present invention is achieved through the following technical solutions:

[0006] The present invention provides an online detection system for Fischer-Tropsch synthesis process gas, the online detection system for Fischer-Tropsch synthesis process gas comprising:

[0007] An air intake control unit, including a pressure controller and a flow controller;

[0008] Spectroscopic measurement core unit, including:

[0009] The infrared absorption spectrum measurement module comprises an interferometer, an infrared absorption spectrum measurement sample cell cabin and an infrared signal detection module.

[0010] Absorption spectrum measurement flow cell, blank sample cell and translation stage;

[0011] Raman spectrum measurement module, including laser, Raman spectrum measurement flow cell,

[0012] Mann signal collection device, optical fiber and spectrometer;

[0013] The temperature sensor is used to measure the infrared absorption spectrum measurement flow cell and the pull

[0014] Mann Spectroscopy measures the temperature of the flow cell; and

[0015] A pressure sensor, used to measure the pressure of the infrared absorption spectrum measurement flow cell and the Raman spectrum measurement flow cell;

[0016] Gas evacuation module, and

[0017] The industrial computer is electrically connected to the air intake control unit, the spectral measurement core unit and the gas exhaust module, and includes a hardware control system, a database, a quantification module and a display and communication module; the database includes an infrared absorption spectrum database and a Raman spectrum database, the infrared absorption spectrum database includes an absolute absorption cross-section sub-database and an infrared characteristic fingerprint peak sub-database, the Raman spectrum database includes a Raman characteristic fingerprint peak sub-database and a Raman spectrum quantification sub-database, and the database and the quantification module are used to perform quantitative analysis on the data measured by the spectral measurement core unit.

[0018] In order to control whether the test gas passes through the detection system, filter out solid particles in the original gas and protect the pressure controller, the air intake control unit also includes a valve, a filtering system and a pressure reducing valve.

[0019] In order to increase the accuracy and range of measurement, the number of the infrared absorption spectrum measurement flow cells is multiple, and different infrared absorption spectrum measurement flow cells have different optical path lengths; the infrared absorption spectrum measurement sample cell cabin also includes a standard gas sample cell.

[0020] In order to improve the Raman signal intensity, the Raman spectrum measurement flow cell is a gas flow cell with a laser focusing lens as an optical window, and the Raman spectrum measurement module also includes a reflector, which reflects the laser output light beam passing through the Raman spectrum measurement flow cell into the Raman spectrum measurement flow cell.

[0021] To prevent reflected light from entering the laser, an optical isolator is placed in the path of the laser output beam.

[0022] In order to further increase the intensity of the Raman signal, the Raman spectrum measurement flow cell is a cascade Raman spectrum measurement flow cell.

[0023] Preferably, the Raman signal collecting device comprises a first focusing lens, a filter and a second focusing lens which are sequentially arranged along the transmission path of the Raman signal light. The Raman signal light excited by the laser at the laser focal point is collimated by the first focusing lens, passes through the filter and is then focused by the second focusing lens to the Raman signal light focal point position. The Raman signal light focal point position coincides with the end face of the optical fiber.

[0024] In order to further improve the collection efficiency of Raman signal light, the Raman signal collection device is a multi-channel Raman signal collection device.

[0025] In order to increase the collection efficiency of the Raman signal, the Raman signal collection device further comprises a concave reflector, and the focus of the concave reflector coincides with the laser focusing point.

[0026] The present invention also provides a Fischer-Tropsch synthesis process gas online detection method based on the above-mentioned Fischer-Tropsch synthesis process gas online detection system, the method comprising the following steps:

[0027] S1: Start measuring and obtain the infrared absorption spectrum and Raman spectrum corresponding to the process gas;

[0028] S2: Determine whether there are abnormal peaks in the infrared absorption spectrum and the Raman spectrum;

[0029] S3: If the abnormal peak in the infrared absorption spectrum is a saturation peak, change the pressure of the infrared absorption spectrum measurement sample cell cabin or replace the infrared absorption spectrum measurement flow cell, and return to S1 to re-measure;

[0030] S4: If the abnormal peak in the Raman spectrum is a saturation peak, reduce the exposure time and return to S1 to re-measure;

[0031] S5: If the abnormal peak in the infrared absorption spectrum or Raman spectrum is an invalid data point, the invalid data point is replaced by taking the average value of adjacent valid data points;

[0032] S6: According to the infrared characteristic fingerprint peak database and the Raman characteristic fingerprint peak database, the test gas composition is qualitatively analyzed to determine the species in the test gas;

[0033] S7: Read the temperature and pressure during infrared absorption and Raman spectrum measurements;

[0034] S8: Conduct quantitative analysis of step-by-step infrared absorption spectra;

[0035] S9: Obtain quantification results of infrared active gas species;

[0036] S10: selecting an internal standard substance according to the obtained quantification results of infrared active gas species;

[0037] S11: confirm whether the Raman spectrum of the internal standard substance is interfered by other species. If the Raman spectrum of the internal standard substance is interfered by other species, reconstruct the Raman spectrum of the internal standard substance until it is not interfered;

[0038] S12: comparing the intensity of the Raman spectrum of the internal standard substance and the Raman spectrum of the gas species with only Raman activity to obtain the intensity ratio of the two Raman spectra, and using the quantified spectrum data corresponding to the temperature and pressure during the Raman spectrum measurement in the Raman spectrum quantification sub-database to obtain the quantification result of the gas species with only Raman activity;

[0039] S13: According to S12, quantitative analysis of other gas species that are only Raman active is performed;

[0040] S14: Integrate the quantification results of infrared absorption spectrum and Raman spectrum to output the quantification results of all components.

[0041] Preferably, the infrared absorption spectrum quantitative analysis is carried out according to the following method:

[0042] By linearly combining the standard infrared absorption spectra of each component and comparing them with the measured infrared absorption spectra, the minimum comparison residual method is used to quantify the measured infrared absorption spectra. The specific implementation algorithm is as follows:

[0043] σ test =C1σ1+C2σ2+C3σ3+C4σ4+…C N σ N +δ,

[0044] Among them, σ test is the measured infrared absorption spectrum, σ x(x = 1-N) is the absorbance corresponding to the unit concentration of gas under the condition of unit absorption path of a single substance in the absolute absorption cross section sub-database of the infrared absorption spectrum database, C x is x The concentration corresponding to the species, and δ is the residual.

[0045] Preferably, in S11, when the characteristic Raman spectrum peak of the internal standard substance overlaps with the Raman spectrum peak of other substances, it is considered that interference exists.

[0046] Preferably, the algorithm for reconstructing the Raman spectrum of the internal standard substance is:

[0047] I(λ)=C0I(λ)0+C1I(λ)1+C2I(λ)2+…+C n I(λ) n +δ(λ),

[0048] Where, I(λ) is the Raman spectrum of the process gas measured experimentally, I(λ)0 is the normalized Raman spectrum of the internal standard substance, and I(λ)1 to I(λ) n is the normalized Raman spectrum of the interfering species, C0 to C n is the fitting coefficient, and δ(λ) is the residual.

[0049] In summary, the present invention adopts a quantification method combining infrared absorption spectrum and Raman spectrum, without adding internal standard substances and establishing calibration curves. All quantification methods are based on infrared absorption spectrum measurement, Raman spectrum measurement and established database, are independent of devices, have universal applicability, and can be effectively used for quantitative analysis of hydrocarbon mixtures with longer carbon chains, thereby realizing calibration-free quantitative detection of all components of Fischer-Tropsch synthesis process gas.

[0050] The technical solution of the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a schematic diagram of an online detection system for Fischer-Tropsch synthesis process gas;

[0052] Figure 2 is a schematic diagram of an intake control unit;

[0053] Figure 3 Schematic diagram of the core unit for spectroscopy measurements;

[0054] Figure 4 It is a schematic diagram of the infrared absorption spectrum measurement module;

[0055] Figure 5 is a schematic diagram of a Raman spectroscopy measurement module;

[0056] Figure 6is a schematic diagram of another Raman spectroscopy measurement module;

[0057] Figure 7 is a schematic diagram of a Raman signal collection device;

[0058] Figure 8 A schematic diagram of coupling a multi-channel Raman signal collection device with an optical fiber;

[0059] Fig. 9 is a schematic diagram of a Raman spectroscopy measurement module including a cascade Raman spectroscopy measurement flow cell;

[0060] Fig.10 is a schematic diagram of another Raman signal collection device;

[0061] Fig.11 A schematic diagram of another Raman signal collection device applied to a cascade Raman spectroscopy measurement flow cell;

[0062] Fig.12 Schematic diagram of an online detection method for Fischer-Tropsch synthesis process gas;

[0063] Fig.13 Raman signal diagram measured for different Raman spectroscopy measurement modules. DETAILED DESCRIPTION

[0064] Figure 1 Schematic diagram of the online detection system for Fischer-Tropsch synthesis process gas. Figure 1 As shown, the present invention provides an online detection system for Fischer-Tropsch synthesis process gas, which comprises an intake control unit, a spectroscopy measurement core unit, a gas exhaust module and an industrial computer. The online detection system for Fischer-Tropsch synthesis process gas is installed in the gas pipeline part of the Fischer-Tropsch synthesis equipment, for example, it can be installed in the pipeline bypass, and the gas is measured when it flows through the spectroscopy measurement core unit through the intake control unit.

[0065] The air intake control unit is used to control the pressure and flow rate of the gas entering the Fischer-Tropsch synthesis process gas online detection system, thereby providing a constant flow and pressure environment for the measurement of infrared absorption spectrum and Raman spectrum. Figure 2 is a schematic diagram of the intake control unit, such as Figure 2 As shown, the air intake control unit includes a pressure controller and a flow controller.

[0066] The pressure controller is used to control the gas pressure of the infrared absorption spectrum measurement flow cell and the Raman spectrum measurement flow cell so that the two flow cells are in a constant pressure state. The pressure controller can be a mechanical pressure controller, an electronic pressure controller, a pneumatic pressure controller, etc.

[0067] The flow controller is used to control the gas flow rate of the gas flowing through the infrared absorption spectrum measurement flow cell and the Raman spectrum measurement flow cell. The flow controller can be a gas mass flow meter or the like.

[0068] In order to filter out solid particles in the original gas, the intake control unit may also include a filtering system; in order to control whether the test gas passes through the detection system, the intake control unit may also include a valve; in order to protect the pressure controller, reduce the upstream gas pressure, and prevent the pressure controller from having an excessively high gas pressure at the intake end, the intake control unit may also include a pressure reducing valve. Exemplarily, the pressure reducing valve is located in the front stage of the pressure controller, the filtering system is located in the front stage of the pressure reducing valve, and the valve is located in the front stage of the filtering system.

[0069] Figure 3 Schematic diagram of the core unit of spectroscopy measurement, such as Figure 3 As shown, the spectroscopy measurement core unit includes an infrared absorption spectrum measurement module, a Raman spectrum measurement module, a temperature sensor and a pressure sensor.

[0070] The spectroscopy measurement core unit is used to measure the infrared absorption spectrum and Raman spectrum of the gas flowing through the infrared absorption spectrum measurement flow cell and the Raman spectrum measurement flow cell, respectively. Specifically, the infrared absorption spectrum measurement module measures the infrared absorption spectrum of the gas flowing through the infrared absorption spectrum measurement flow cell, and the Raman spectrum measurement module measures the Raman spectrum of the gas flowing through the Raman spectrum measurement flow cell. The temperature sensor is used to measure the temperature of the infrared absorption spectrum measurement flow cell and the Raman spectrum measurement flow cell, and the pressure sensor is used to measure the pressure of the infrared absorption spectrum measurement flow cell and the Raman spectrum measurement flow cell. By accurately controlling the pressure, temperature and flow rate, the measurement accuracy and quantification accuracy can be effectively improved.

[0071] Figure 4 is a schematic diagram of the infrared absorption spectrum measurement module, such as Figure 4 As shown, the infrared absorption spectrum measurement module includes an interferometer 1, an infrared absorption spectrum measurement sample cell cabin 2 and an infrared signal detection module 3.

[0072] Specifically, the interferometer 1 is an interferometer with a built-in light source, for example, an infrared light source, which modulates the light of the infrared light source through interference. The infrared signal detection module 3 is a semiconductor or pyroelectric detector (such as an InGaAs detector) with a wide spectral range. The interferometer 1 and the infrared signal detection module 3 are prior art and are not described in detail here.

[0073] The infrared absorption spectrum measurement sample cell cabin 2 comprises an infrared absorption spectrum measurement flow cell, a blank sample cell 5 and a displacement stage 6 .

[0074] The blank sample pool 5 is characterized by being vacuum or pre-filled with a gas having no infrared activity, such as nitrogen or argon. Its optical transmission characteristics are the same as those of the infrared absorption spectrum measurement flow cell, and it can be used to measure the background.

[0075] The infrared absorption spectrum measurement flow cell is connected to the gas path of the air intake control unit, so that the gas can enter the infrared absorption spectrum measurement flow cell. When the gas flows to this position, the relevant spectroscopy test is carried out.

[0076] In order to increase the accuracy and range of the measurement, the number of the infrared absorption spectrum measurement flow cells can be multiple, for example, Figure 4 , an example of an infrared absorption spectrum measurement flow cell including a first infrared absorption spectrum measurement flow cell 4 and a second infrared absorption spectrum measurement flow cell 7 is shown, wherein different infrared absorption spectrum measurement flow cells have different optical path lengths, i.e., the first infrared absorption spectrum measurement flow cell 4 and the second infrared absorption spectrum measurement flow cell 7 have different optical path lengths. The present invention is not limited thereto, and only one infrared absorption spectrum measurement flow cell or more infrared absorption spectrum measurement flow cells may be provided. The configuration of multiple infrared absorption spectrum measurement flow cells can fully ensure that the system can operate continuously for a long time.

[0077] In order to calibrate the system, the infrared absorption spectrum measurement sample cell cabin 2 may further include a standard gas sample cell 8 .

[0078] The displacement stage 6 is, for example, a displacement stage 6 with a one-dimensional translation function. The circulation cell and the sample cell are fixed on the surface of the displacement stage 6. The optical axis directions of the circulation cell and the sample cell are parallel to the propagation direction of the infrared light beam. The moving direction of the surface of the displacement stage 6 is perpendicular to the direction of the infrared light beam. When measuring the infrared absorption spectrum, the circulation cell and the sample cell can be moved into or out of the optical path by translating the surface of the displacement stage 6.

[0079] Figure 5 is a schematic diagram of the Raman spectroscopy measurement module, such as Figure 5 As shown, the Raman spectrum measurement module includes a laser 9 , a Raman spectrum measurement flow cell 10 , a Raman signal collection device 12 , an optical fiber 13 and a spectrometer 14 .

[0080] The laser 9 serves to provide a Raman signal excitation source. The Raman spectrum measurement flow cell 10 is, for example, a gas flow cell with a laser focusing lens 11 as an optical window, which can be a Raman spectrum measurement flow cell in the prior art. The excitation light interacts with the test gas molecules in the Raman spectrum measurement flow cell 10 to generate a Raman signal. The Raman signal is coupled to the spectrometer 14 via the Raman signal collection device 12 and the optical fiber 13, thereby realizing the recording of the Raman signal.

[0081] More specifically, the laser output beam 17 is focused at the laser focusing point 18 after passing through the laser focusing lens 11, and the laser focusing point 18 is located in the Raman spectrum measurement flow cell 10. The generated Raman signal is collected by the Raman signal collection device 12 and coupled to the spectrometer 14 through the optical fiber 13. The Raman spectrum measurement flow cell 10 also includes an air inlet 15 and an air outlet 16. The air inlet 15 and the air outlet 16 are connected to the air inlet control unit.

[0082] Since the Raman signal is a weak signal, the present invention also provides an example of increasing the strength of the Raman signal by multiple reflections. Figure 6 is a schematic diagram of another Raman spectrum measurement module, such as Figure 6 As shown, the Raman spectrum measurement module is Figure 5 Compared with the Raman spectrum measurement module shown in FIG. 1 , a reflector 19 and another laser focusing lens 11 are additionally provided. The other laser focusing lens 11 is located behind the laser focusing point 18 and its focal position coincides with the laser focusing point 18. Figure 6 The two laser focusing lenses 11 shown in the figure are coaxial. The laser output beam 17 becomes parallel light after passing through the two laser focusing lenses 11, and then acts on the reflector 19. By adding the reflector 19 and the laser focusing lens 11, the laser output beam passing through the Raman spectrum measurement flow cell 10 is reflected into the Raman spectrum measurement flow cell 10 and focused on the laser focusing point 18, thereby improving the Raman signal intensity.

[0083] In order to prevent reflected light from entering the laser 9, an optical isolator 20 is placed in the path of the laser output beam 17.

[0084] Figure 7 is a schematic diagram of a Raman signal collection device, such as Figure 7 As shown, the Raman signal collection device 12 includes a first focusing lens 22, a filter 23, and a second focusing lens 24 which are sequentially arranged along the transmission path of the Raman signal light 21. The Raman signal light 21 excited by the laser at the laser focal point 18 is collimated by the first focusing lens 22, passes through the filter 23, and is then focused by the second focusing lens 24 to the position of the Raman signal light focal point 25. The position of the Raman signal light focal point 25 coincides with the end face of the optical fiber 13.

[0085] Figure 8 Schematic diagram of the multi-channel Raman signal collection device coupled with optical fiber, Figure 8 As shown, in order to further improve the collection efficiency of the Raman signal light 21, the present invention can use a multi-channel Raman signal collection device composed of multiple Raman signal collection devices 12 to collect Raman signals. Figure 8An embodiment using six Raman signal collecting devices 12 is schematically shown. The six Raman signal collecting devices 12 respectively collect the Raman signal light 21 generated by the laser focus point 18, and couple them to the spectrometer 14 through multiple optical fibers 13. Exemplarily, at the slit of the spectrometer 14, the end faces of the multiple optical fibers 13 are arranged in a line to form an optical fiber line array 28.

[0086] Fig. 9 Schematic diagram of a Raman spectrum measurement module including a cascade Raman spectrum measurement flow cell. Components such as the Raman signal collection device 12 are omitted in the figure. In order to further increase the intensity of the Raman signal, a plurality of Raman spectrum measurement flow cells can be cascaded to form a cascade Raman spectrum measurement flow cell. The present invention does not limit the number of cascaded Raman spectrum measurement flow cells. For example, Fig. 9 As shown, an embodiment in which a first Raman spectrum measurement flow cell 261 and a second Raman spectrum measurement flow cell 262 are cascaded is shown.

[0087] Specifically, the laser output beam 17 for exciting the Raman signal converges to the first Raman spectrum measurement flow cell 261 and is converted into parallel light through the laser focusing lens 11. The parallel light is then focused by another laser focusing lens 11 to the second Raman spectrum measurement flow cell 262, and then converted into parallel light through another laser focusing lens 11. The parallel light is reflected by the reflector 19 and then refocused in the second Raman spectrum measurement flow cell 262 and the first Raman spectrum measurement flow cell 261 in turn, thereby achieving the gain of the Raman signal.

[0088] In the present invention, the use of multiple Raman signal collecting devices 12 will lead to an increase in the number of optical fibers 13. The increase in the number of optical fibers 13 may cause the length of the optical fiber end face of the optical fiber line array to exceed the maximum range allowed by the spectrometer 14. In order to reduce the number of optical fibers 13, a Raman signal reflection device and a Raman signal collecting device 12 can be combined to achieve this.

[0089] Fig.10 Schematic diagram of another Raman signal collection device. Fig.10 The improved single-channel Raman signal collection device is schematically shown. Figure 7 Compared with the Raman signal collection device shown in , the improved single-channel Raman signal collection device adds a concave reflector 27, and the focus of the concave reflector 27 coincides with the laser focusing point 18. The Raman scattered light radiated by the laser focusing point 18 is refocused at the position of the laser focusing point 18 after being reflected by the concave reflector 27, and this part of the Raman signal light further enters the Raman signal collection device 12, thereby achieving an increase in the Raman signal collection efficiency.

[0090] A single Raman spectrum measurement flow cell 10 can be equipped with multiple Raman signal collection devices 12 to form a multi-channel Raman signal collection device 12. A Raman spectrum measurement module in which multiple Raman spectrum measurement flow cells are cascaded can also include multiple Raman signal collection devices 12.

[0091] Fig.11 Schematic diagram of another Raman signal collection device applied to a cascade Raman spectroscopy measurement flow cell. Fig.11 The improved Raman signal collecting device (including the concave reflector 27) is schematically used to simultaneously collect the Raman signals of the first Raman spectrum measurement flow cell 261 and the second Raman spectrum measurement flow cell 262, such as Fig.11 As shown, the first multi-channel Raman signal collection module 101 and the second multi-channel Raman signal collection module 102 are respectively used to collect Raman signals of the first Raman spectrum measurement flow cell 261 and the second Raman spectrum measurement flow cell 262. The six Raman signals are composed of six optical fibers 13 forming an optical fiber line array 28.

[0092] In the present invention, the cascade optical cavity and multi-channel Raman signal collection device are used to effectively improve the Raman signal collection efficiency and reduce the single data point collection time. The cascade sample pool is used for multiple reflections and multi-channel Raman signal collection, which effectively increases the Raman signal intensity and the Raman signal collection efficiency, and has a small size, is easy to integrate, and has high stability.

[0093] The gas exhaust module is used to exhaust the test gas or return the test gas to the main pipeline through a booster device. The gas exhaust module at least includes a gas booster, and the function of the gas exhaust module is to recover the gas exhausted by the above-mentioned measuring device, or return it to the process gas flow pipeline through a booster.

[0094] Exemplarily, the gas exhaust module also includes a gas storage tank and a gas pressure sensor. The tested gas is first discharged into the gas storage tank, and the function of the gas pressure sensor is to measure the gas pressure in the gas storage tank. When the pressure in the gas storage tank is higher than the set high pressure value, the gas booster starts working; when the pressure in the gas storage tank is lower than the set low pressure value, the gas booster stops working. The function of the above device is to further stabilize the gas pressure in the infrared absorption spectrum measurement flow cell and the Raman spectrum measurement flow cell by controlling the fluctuation range of the pressure at the gas outlet end of the spectral measurement core unit.

[0095] The industrial computer is electrically connected to the air intake control unit, the spectroscopy measurement core unit and the gas exhaust module, and is used to control the air intake control unit, the spectroscopy measurement core unit and the gas exhaust module, and also has functions such as data acquisition and analysis, display and communication, etc. The industrial computer includes a hardware control system, a database, a quantification module and a display and communication module.

[0096] Exemplarily, the components that can be controlled by the hardware control system include but are not limited to: valves in the gas circuit, pressure controllers, flow controllers, temperature sensors, pressure sensors, translation stages, lasers, spectrometers, interferometers, infrared signal detection modules, etc. The database and quantification module are used to perform quantitative analysis on the data measured by the spectroscopy measurement core unit. The display and communication module has display and communication functions.

[0097] The database is used to support quantitative calculations, including an infrared absorption spectrum database and a Raman spectrum database. The infrared absorption spectrum database includes an absolute absorption cross-section sub-database and an infrared characteristic fingerprint peak sub-database, and the Raman spectrum database includes a Raman characteristic fingerprint peak sub-database and a Raman spectrum quantification sub-database. Among them, the absolute absorption cross-section sub-database in the infrared absorption spectrum database is an infrared absorption spectrum obtained by using an infrared absorption spectrum measurement device (such as the above-mentioned infrared absorption spectrum measurement module or other infrared absorption spectrum measurement devices in the prior art) for each single-component gas of a specific concentration under certain absorption path conditions, and a collection of infrared absorption spectra obtained by carrying out the above-mentioned measurements under a series of temperature and pressure conditions. It is configured as the absolute absorbance of a single species under specific temperature, pressure, and absorption path conditions, and can be directly used for infrared absorption spectrum quantitative analysis. The infrared characteristic fingerprint peak sub-database in the infrared absorption spectrum database is an infrared absorption spectrum corresponding to each single-component gas measured by an infrared absorption spectrum measurement device, and the position and relative intensity information of the main fingerprint peak are extracted from the obtained infrared absorption. The Raman spectrum quantification sub-database in the Raman spectrum database is a collection of Raman spectra obtained from two gas species, non-polar molecules and polar molecules, under a series of concentration ratios, temperatures, and pressure conditions. According to the test requirements, Raman spectrum tests are carried out on a variety of non-polar molecules and polar molecules to obtain a comprehensive Raman spectrum quantification sub-database. The characteristic of the Raman spectrum quantification sub-database is that the concentration ratio of the two corresponding substances in the test sample can be directly obtained based on the Raman spectrum characteristics of the two molecules. The Raman characteristic fingerprint peak sub-database is a collection of Raman spectra obtained by measuring multiple single gas standards, and its characteristics include the fingerprint peak position and relative intensity of the gas.

[0098] In the present invention, the following method can be used to establish an infrared absorption spectrum database.

[0099] S101: prepare gas standard samples;

[0100] In S101, the gas standard sample is characterized by containing only one infrared-active gas species with a known concentration. The dilution gas is a gas that is not infrared-active, such as N2 or Ar.

[0101] S102: preparing gas standard samples according to the specific components of the target gas;

[0102] S103: using an infrared absorption spectrum measuring device (such as the infrared absorption spectrum measuring module or other infrared absorption spectrum measuring devices in the prior art) to measure the gas under specific pressure P and temperature T conditions to obtain an infrared absorption spectrum under (P, T) conditions;

[0103] S104: respectively changing the pressure P and the temperature T, repeating S103, and finally obtaining a collection of infrared absorption spectra under a series of pressure and temperature conditions;

[0104] S105: According to the relationship between the absorption path length of the infrared absorption spectrum and the pressure and the density of gas molecules, the absolute absorption cross section of each infrared active molecule under the condition of unit density and unit absorption length is obtained, and an absolute absorption cross section sub-database is established;

[0105] S106: Establish an infrared characteristic fingerprint peak sub-database according to the position and relative intensity of the infrared absorption spectrum fingerprint peak of each gas standard sample.

[0106] In the present invention, the following method can be used to establish a Raman spectrum database.

[0107] S201: prepare gas standard samples;

[0108] In S201, gas standards are divided into two categories: one is a single gas standard, which is characterized by containing only one gas molecule with Raman activity, and the diluent gas is an inert gas such as Ar; the other is a mixed gas standard, which is characterized by containing at least two gas species with Raman activity, one of which is a symmetrical non-polar molecule with only Raman activity. Another feature of the gas standard is that the concentration of each substance is known. The diluent gas is an inert gas such as Ar.

[0109] S202: According to the specific components of the target gas, a single gas standard sample and a mixed gas standard sample are respectively configured;

[0110] In S202, illustratively, in this embodiment, the single gas standard prepared for the composition characteristics of the Fischer-Tropsch process gas includes all C1-C7 hydrocarbons, CO, CO2, H2, and N2. The configured mixed gas standards are (CH4 / H2 / Ar), (CH4 / N2 / Ar), (C2H4 / H2 / Ar), (C2H4 / N2 / Ar), (C3H6 / H2 / Ar), (C3H6 / N2 / Ar), (CO / H2 / Ar), (CO / N2 / Ar), (CO / H2 / Ar), and (CO / N2 / Ar). 10 types of gas standards.

[0111] S203: Using a Raman spectrum measurement device (such as the above-mentioned Raman spectrum measurement module or other Raman spectrum measurement devices in the prior art) to measure the mixed gas standard sample in the above-mentioned gas under specific pressure P and temperature T conditions, and obtain the Raman spectrum under (P, T) conditions.

[0112] S204: respectively changing the pressure P and the temperature T, repeating S203, and finally obtaining a collection of Raman spectra under a series of pressure and temperature conditions.

[0113] S205: establishing a relationship between the spectral intensity of two substances and the concentration of the corresponding substances from each spectrum;

[0114] Exemplarily, in S205, for a CH4 / H2 / Ar mixed gas, a relationship between the H2 Raman spectrum intensity and the CH4 spectrum intensity and the ratio of the gas concentrations thereof is established (I_H2(λ)=I_CH4(λ)×(n_H2 / n_CH4)), where I(λ) represents the Raman spectrum intensity of the corresponding substance, and n represents the concentration of the corresponding substance in the standard sample.

[0115] S206: establishing a Raman spectrum quantification sub-database according to the Raman spectrum characteristics of each gas standard sample;

[0116] S207: Using a Raman spectrometer to measure the single gas standard samples in the above gases, obtain the Raman spectrum of each single gas standard sample. Further, for each single gas standard sample Raman spectrum, extract the fingerprint peak position and relative intensity, and establish a Raman characteristic fingerprint peak sub-database.

[0117] The quantification module is used to quantify the infrared absorption spectrum and Raman spectrum measured by the spectroscopy measurement core unit according to the database. More specifically, the quantification module first reads the measurement temperature and pressure information of the infrared absorption spectrum and Raman spectrum, and on this basis, uses the infrared absorption spectrum and Raman spectrum corresponding to the temperature and pressure conditions in the database to carry out quantitative calculations.

[0118] Fig.12 Schematic diagram of the online detection method of Fischer-Tropsch synthesis process gas, Fig.12 As shown, the present invention also provides a Fischer-Tropsch synthesis process gas online detection method based on the above-mentioned Fischer-Tropsch synthesis process gas online detection system, and the method comprises the following steps:

[0119] S1: Start measuring and obtain the infrared absorption spectrum and Raman spectrum corresponding to the process gas;

[0120] S2: Determine whether there are abnormal peaks in the infrared absorption spectrum and the Raman spectrum;

[0121] S3: If the abnormal peak in the infrared absorption spectrum is a saturation peak, change the pressure of the infrared absorption spectrum measurement sample cell cabin or replace the infrared absorption spectrum measurement flow cell, and return to S1 to re-measure;

[0122] S4: If the abnormal peak in the Raman spectrum is a saturation peak, reduce the exposure time and return to S1 to re-measure;

[0123] S5: If the abnormal peak in the infrared absorption spectrum or Raman spectrum is an invalid data point, the invalid data point is replaced by taking the average value of adjacent valid data points;

[0124] S6: According to the infrared absorption spectrum database and Raman spectrum database, the test gas components are qualitatively analyzed to determine the species in the test gas;

[0125] S7: Read the temperature and pressure during infrared absorption and Raman spectrum measurements;

[0126] S8: Conduct quantitative analysis of step-by-step infrared absorption spectra;

[0127] S9: Obtain quantification results of infrared active gas species;

[0128] S10: selecting an internal standard substance according to the obtained quantification results of infrared active gas species;

[0129] S11: confirm whether the Raman spectrum of the internal standard substance is interfered by other species. If the Raman spectrum of the internal standard substance is interfered by other species, reconstruct the Raman spectrum of the internal standard substance until it is not interfered;

[0130] S12: comparing the intensity of the Raman spectrum of the internal standard substance and the Raman spectrum of the gas species with only Raman activity to obtain the intensity ratio of the two Raman spectra, and using the quantified spectrum data corresponding to the temperature and pressure during the Raman spectrum measurement in the Raman spectrum quantification sub-database to obtain the quantification result of the gas species with only Raman activity;

[0131] S13: According to S12, quantitative analysis of other gas species that are only Raman active is performed;

[0132] S14: Integrate the quantification results of infrared absorption spectrum and Raman spectrum to output the quantification results of all components.

[0133] On the basis of completing the quantification work, the display and communication module of the industrial computer is used to realize the real-time display and recording of the quantification results, and enter the collection and analysis of the next data point to realize the continuous observation of the process gas components.

[0134] In S2, when there is a saturated peak or there is no valid data at a certain wavelength position, it is determined that there is an abnormal peak.

[0135] In S6, the species in the test gas can be determined by using algorithms such as principal component analysis, support vector machine or convolutional neural network, which are prior art and will not be described in detail here. The above method can be used to achieve qualitative analysis of the test gas components, thereby obtaining the gas species contained in the test gas.

[0136] In S8, a stepwise infrared absorption spectrum quantitative analysis method is used. The stepwise infrared absorption spectrum quantitative analysis method is to divide all gas molecules in the sample to be tested into several categories according to the overlap between the infrared absorption spectrum database corresponding to each gas molecule and the infrared absorption spectrum database corresponding to other gas molecules. In this embodiment, the gas molecules are divided into three categories. The local infrared absorption spectrum is preferentially used to quantitatively analyze the Class I gas molecules in the mixed gas components. The characteristic of Class I gas molecules is that their corresponding infrared absorption spectrum database does not overlap with the infrared absorption spectrum database corresponding to other gas molecules. Typical Class I gas molecules include non-hydrocarbon gas molecules such as CO and CO2; the local infrared absorption spectrum is used again to quantitatively analyze the Class II gas molecules in the mixed gas components. The characteristic of Class II gas molecules is that their corresponding infrared absorption spectrum database has little overlap with the infrared absorption spectrum database corresponding to other gas molecules, and the specific overlapping range can be designed and selected according to actual conditions. Typical Class II gas molecules include non-saturated hydrocarbon gas molecules such as C2H4 and C3H6; finally, the local infrared absorption spectrum is used to quantitatively analyze the Class III gas molecules in the mixed gas components. The characteristic of Class III gas molecules is that their corresponding infrared absorption spectrum has serious overlap with the infrared absorption spectrum database corresponding to other gas molecules, and the specific overlapping range can be designed and selected according to actual conditions; typical Class III gas molecules include saturated hydrocarbons such as CH4 and C2H6. Since the quantification of Class III gas molecules is interfered by Class II gas molecules, in the above-mentioned step infrared absorption spectrum quantitative analysis method, when conducting the quantitative analysis of Class III gas molecules, the concentration corresponding to Class II gas molecules has been quantified as a constant.

[0137] Among them, each step of the quantification method in the step-by-step infrared absorption spectrum quantitative analysis adopts the following method: carry out infrared absorption spectrum quantification, and extract the absolute absorption cross-section data of gas species under corresponding pressure and temperature conditions in the absolute absorption cross-section sub-database according to the pressure and temperature information during the infrared absorption spectrum test.

[0138] More specifically, the quantitative analysis of infrared absorption spectrum can be carried out in the following way: by linearly combining the standard infrared absorption spectrum of each component and comparing it with the measured infrared absorption spectrum, the quantification of the measured infrared absorption spectrum is realized in the way of minimum comparison residual. The specific implementation algorithm is as follows:

[0139] σ test =C1σ1+C2σ2+C3σ3+C4σ4+…C Nσ N +δ

[0140] Among them, σ test is the measured infrared absorption spectrum, σ x (x = 1-N) is the absorbance corresponding to the unit concentration of gas under the condition of unit absorption path of a single substance in the absolute absorption cross section sub-database of the infrared absorption spectrum database, C x is x The concentration corresponding to the species, δ is the residual. In actual spectral comparison, δ is minimized by algorithms such as PLS.

[0141] The step-by-step infrared absorption spectrum quantitative analysis is a quantitative method used to solve the problem of overlapping corresponding infrared absorption spectra of multiple substances in the infrared absorption spectrum. The step-by-step infrared absorption spectrum quantitative analysis method can effectively improve the influence of spectral overlap on the quantitative results, thereby achieving high-precision quantification.

[0142] In S10, the criteria for selecting the internal standard substance are: the Raman signal of the internal standard substance is relatively strong (for example, the signal-to-noise ratio is greater than 10), and there is no overlap or less overlap with the Raman signals of other gases (for example, the overlapping spectral range is less than 50% of the entire characteristic spectral range of the internal standard substance).

[0143] In S11, when the characteristic Raman spectrum peak of the internal standard substance overlaps with the Raman spectrum peak of other substances, it is considered that interference exists.

[0144] In an embodiment of the present invention, the reconstruction of the Raman spectrum of the internal standard substance can be performed according to the following method: The reconstruction algorithm of the Raman spectrum of the internal standard substance is as follows:

[0145] I(λ)=C0I(λ)0+C1I(λ)1+C2I(λ)2+…+C n I(λ) n +δ(λ), where I(λ) is the experimentally measured Raman spectrum of the process gas, I(λ)0 is the normalized Raman spectrum of the internal standard substance, and I(λ)1 to I(λ) n is the normalized Raman spectrum of the interfering species, C0 to C n is the fitting coefficient, and δ(λ) is the residual. In the reconstruction of the Raman spectrum of the internal standard substance, δ(λ) is minimized by algorithms such as PLS. Under this condition, C0I(λ)0 is the reconstructed Raman spectrum of the internal standard substance. The purpose of reconstruction is to remove the influence of the interfering substances in the Raman spectrum and obtain the Raman spectrum corresponding to the pure internal standard substance.

[0146] In S12, the intensities of the Raman spectrum of the internal standard substance and the Raman spectrum of the gas species having only Raman activity are compared to obtain the intensity ratio of the Raman spectra of the two. The relationship between the intensity ratio of the Raman spectrum of the binary mixed gas and the concentration of the binary gas is extracted using the quantified spectrum data corresponding to the temperature and pressure during the Raman spectrum measurement in the Raman spectrum quantification sub-database. For the sample to be tested, based on the known intensity ratio of the Raman spectra of the two gases and the quantification of one component of the two gases according to the infrared absorption spectrum, the quantification result of the gas species having only Raman activity is obtained in combination with the relationship between the extracted intensity ratio of the Raman spectrum of the binary mixed gas and the concentration of the binary gas.

[0147] In the measurement system of the present invention, the method of quantifying non-polar molecules using Raman signals is not affected by many factors such as laser intensity, Raman signal collection efficiency and detector quantum efficiency, thereby overcoming the disadvantage that a calibration curve must be established in traditional Raman quantitative analysis and that the calibration curve is strongly dependent on the experimental device.

[0148] The present invention can realize the measurement of the absolute absorbance of the substance to be measured and establish a database. Based on the database and the established quantification method, the accurate quantification of infrared active molecules in the mixed gas to be measured can be realized; on the basis of the accurate quantification of infrared active molecules, the corresponding relationship between the Raman spectral characteristics of non-polar molecules and polar molecules and the concentrations of the two is constructed through Raman spectroscopy technology, thereby realizing the accurate quantification of non-polar molecules in the mixed gas. According to the established method, all gas components are measured, and the obtained results are directly absolute quantification results, without calibration and independent of devices.

[0149] The infrared absorption spectrum and Raman spectrum combined quantification method of the present invention does not need to add internal standard substances and establish calibration curves. All quantification methods are based on infrared absorption spectrum measurement, Raman spectrum measurement and established databases, which are essentially different from other infrared or Raman quantification methods. In addition, the quantification method of the present invention does not rely on devices and has universal applicability. The present invention can be effectively used for quantitative analysis of hydrocarbon mixtures with longer carbon chains. In traditional methods, hydrocarbons with longer carbon chains cannot be accurately quantified due to serious overlap between Raman spectra and infrared absorption spectra.

[0150] The following is a further introduction to the online detection system and method for Fischer-Tropsch synthesis process gas of the present invention with reference to specific examples.

[0151] Taking the tail gas of Fischer-Tropsch reaction as an example, the online detection system and method of Fischer-Tropsch synthesis process gas of the present invention are used for analysis. Fig.13 Raman signal diagrams measured by different Raman spectrum measurement modules, such as Fig.13 As shown, Fig.11 The Raman signal obtained by the Raman spectroscopy measurement module shown is significantly better than Figure 5 The Raman signal obtained by the Raman spectrum measurement module is shown.

[0152] The composition of the Fischer-Tropsch reaction tail gas obtained by using the Fischer-Tropsch synthesis process gas online detection system and method of the present invention and the results obtained by calibration using a chromatographic method are shown in the following table:

[0153]

[0154] It can be seen from the above table that the Fischer-Tropsch synthesis process gas online detection system and method provided by the present invention can effectively detect the composition of the Fischer-Tropsch reaction tail gas online.

[0155] In summary, the present invention provides an online detection system and method for Fischer-Tropsch synthesis process gas based on the combination of infrared absorption spectroscopy and Raman spectroscopy, which can realize calibration-free quantitative detection of all components of Fischer-Tropsch synthesis process gas.

Claims

1. A method for online detection of Fischer-Tropsch synthesis process gas, characterized in that: The method comprises the following steps: S1: Start measuring and obtain the infrared absorption spectrum and Raman spectrum corresponding to the process gas; S2: Determine whether there are abnormal peaks in the infrared absorption spectrum and the Raman spectrum; S3: If the abnormal peak in the infrared absorption spectrum is a saturation peak, change the pressure of the infrared absorption spectrum measurement sample cell cabin or replace the infrared absorption spectrum measurement flow cell, and return to S1 to re-measure; S4: If the abnormal peak in the Raman spectrum is a saturation peak, reduce the exposure time and return to S1 to re-measure; S5: If the abnormal peak in the infrared absorption spectrum or Raman spectrum is an invalid data point, the invalid data point is replaced by taking the average value of adjacent valid data points; S6: According to the infrared characteristic fingerprint peak database and the Raman characteristic fingerprint peak database, the process gas composition is qualitatively analyzed to determine the species in the process gas; S7: Read the temperature and pressure during infrared absorption and Raman spectrum measurements; S8: Conduct quantitative analysis of step-by-step infrared absorption spectra; S9: Obtain quantification results of infrared active gas species; S10: selecting an internal standard substance according to the obtained quantification results of infrared active gas species; S11: confirm whether the Raman spectrum of the internal standard substance is interfered by other species. If the Raman spectrum of the internal standard substance is interfered by other species, reconstruct the Raman spectrum of the internal standard substance until it is not interfered; S12: comparing the intensity of the Raman spectrum of the internal standard substance and the Raman spectrum of the gas species with only Raman activity to obtain the intensity ratio of the two Raman spectra, and using the quantified spectrum data corresponding to the temperature and pressure during the Raman spectrum measurement in the Raman spectrum quantification sub-database to obtain the quantification result of the gas species with only Raman activity; S13: According to S12, quantitative analysis of other gas species that are only Raman active is performed; S14: Integrate the quantification results of infrared absorption spectrum and Raman spectrum to output the quantification results of all components.

2. The method for online detection of Fischer-Tropsch synthesis process gas according to claim 1, characterized in that: The quantitative analysis of infrared absorption spectrum was carried out according to the following method: By linearly combining the standard infrared absorption spectra of each component and comparing them with the measured infrared absorption spectra, the minimum comparison residual method is used to quantify the measured infrared absorption spectra. The specific implementation algorithm is as follows: s test =C1σ1+C2σ2+C3σ3+C4σ4+…C N s N +d, Among them, σ test is the measured infrared absorption spectrum, σ x , x = 1-N is the absorbance of the gas of unit concentration under the unit absorption path corresponding to substance X in the absolute absorption cross section sub-database of the infrared absorption spectrum database, C x is the concentration corresponding to substance X, and δ is the residual.

3. The method for online detection of Fischer-Tropsch synthesis process gas according to claim 1, characterized in that: In S11, when the characteristic Raman spectrum peak of the internal standard substance overlaps with the Raman spectrum peak of other substances, it is considered that interference exists.

4. The method for online detection of Fischer-Tropsch synthesis process gas according to claim 3, characterized in that: The algorithm for reconstructing the Raman spectrum of the internal standard substance is: I(λ)=C0I(λ)0+C1I(λ)1+C2I(λ)2+…+C n I(λ) n +δ(λ), Where, I(λ) is the Raman spectrum of the process gas measured experimentally, I(λ)0 is the normalized Raman spectrum of the internal standard substance, and I(λ)1 to I(λ) n is the normalized Raman spectrum of the interfering species, C0 to C n is the fitting coefficient, and δ(λ) is the residual.

5. A Fischer-Tropsch synthesis process gas online detection system using the Fischer-Tropsch synthesis process gas online detection method according to any one of claims 1 to 4, characterized in that: The Fischer-Tropsch synthesis process gas online detection system comprises: An air intake control unit, including a pressure controller and a flow controller; Spectroscopic measurement core unit, including: An infrared absorption spectrum measurement module, comprising an interferometer, an infrared absorption spectrum measurement sample cell cabin and an infrared signal detection module, wherein the infrared absorption spectrum measurement sample cell cabin comprises an infrared absorption spectrum measurement flow cell, a blank sample cell and a displacement stage; A Raman spectrum measurement module, comprising a laser, a Raman spectrum measurement flow cell, a Raman signal collection device, an optical fiber and a spectrometer; A temperature sensor, used to measure the temperature of the infrared absorption spectrum measurement flow cell and the Raman spectrum measurement flow cell; as well as A pressure sensor, used to measure the pressure of the infrared absorption spectrum measurement flow cell and the Raman spectrum measurement flow cell; Gas evacuation module, and The industrial computer is electrically connected to the air intake control unit, the spectral measurement core unit and the gas exhaust module, and includes a hardware control system, a database, a quantification module and a display and communication module; the database includes an infrared absorption spectrum database and a Raman spectrum database, the infrared absorption spectrum database includes an absolute absorption cross-section sub-database and an infrared characteristic fingerprint peak sub-database, the Raman spectrum database includes a Raman characteristic fingerprint peak sub-database and a Raman spectrum quantification sub-database, and the database and the quantification module are used to perform quantitative analysis on the data measured by the spectral measurement core unit.

6. The Fischer-Tropsch synthesis process gas online detection system according to claim 5, characterized in that: The air intake control unit also includes a valve, a filtering system and a pressure reducing valve.

7. The Fischer-Tropsch synthesis process gas online detection system according to claim 5, characterized in that: There are multiple infrared absorption spectrum measurement flow cells, and different infrared absorption spectrum measurement flow cells have different optical path lengths; the infrared absorption spectrum measurement sample cell cabin also includes a standard gas sample cell.

8. The Fischer-Tropsch synthesis process gas online detection system according to claim 5, characterized in that: The Raman spectrum measurement flow cell is a gas flow cell with a laser focusing lens as an optical window. The Raman spectrum measurement module further comprises a reflector, which reflects the laser output light beam passing through the Raman spectrum measurement flow cell into the Raman spectrum measurement flow cell.

9. The Fischer-Tropsch synthesis process gas online detection system according to claim 8, characterized in that: An optical isolator is placed in the path of the laser output beam.

10. The Fischer-Tropsch synthesis process gas online detection system according to claim 5 or 8, characterized in that: The Raman spectroscopy measurement flow cell is a cascade Raman spectroscopy measurement flow cell.

11. The Fischer-Tropsch synthesis process gas online detection system according to claim 5, characterized in that: The Raman signal collection device comprises a first focusing lens, a filter and a second focusing lens which are sequentially arranged along the transmission path of the Raman signal light. The Raman signal light excited by the laser at the laser focal point is collimated by the first focusing lens, passes through the filter and then is focused by the second focusing lens to the Raman signal light focal point position. The Raman signal light focal point position coincides with the end face of the optical fiber.

12. The Fischer-Tropsch synthesis process gas online detection system according to claim 11, characterized in that: The Raman signal collecting device is a multi-channel Raman signal collecting device.

13. The Fischer-Tropsch synthesis process gas online detection system according to claim 11 or 12, characterized in that: The Raman signal collection device also includes a concave reflecting mirror, and the focus of the concave reflecting mirror coincides with the laser focusing point.

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