Gas concentration detection method, device and system

Abstract

The present application relates to the technical field of gas concentration detection, and particularly provides a gas concentration detection method, device and system, aiming at solving the technical problem of long detection time and large detection error in the prior art for detecting gas concentration, thereby causing low gas concentration detection efficiency. The gas concentration detection method comprises: obtaining a signal intensity of a to-be-detected mixed gas from a mass spectrometer, wherein the to-be-detected mixed gas is mixed by flowing a plurality of gases through a competitive adsorption instrument, and the signal intensity is a characteristic peak intensity obtained by inputting the to-be-detected mixed gas into the mass spectrometer; and inputting the signal intensity into a preset mathematical model to obtain the respective gas concentrations of the plurality of gases in the to-be-detected mixed gas.

Description

Technical Field

[0001] This invention relates to the field of gas concentration detection technology, and specifically provides a gas concentration detection method, device and system. Background Technology

[0002] After the two gases undergo a physical reaction, the concentrations of both gases change. In order to obtain information about the reaction, it is necessary to detect the concentrations of the two gases after the reaction.

[0003] In existing technologies, the concentration of two mixed gases can be detected using infrared absorption spectroscopy, gas chromatography, and semiconductor sensors. However, infrared absorption spectroscopy and gas chromatography require large equipment and have long detection times, while semiconductor sensors are easily affected by temperature and humidity, resulting in large errors in the detection results. This leads to the technical problem of low gas concentration detection efficiency. Summary of the Invention

[0004] In order to overcome the above-mentioned defects, this application is made to provide a solution or at least a partial solution to the technical problem that the gas concentration detection efficiency is low due to long detection time and large detection error when the prior art detects gas concentration.

[0005] In a first aspect, the present invention provides a gas concentration detection method, comprising:

[0006] The signal intensity of the gas mixture to be tested is obtained by the mass spectrometer, wherein the gas mixture to be tested is formed by mixing multiple gases in a competitive adsorption instrument, and the signal intensity is the characteristic peak intensity obtained by passing the gas mixture to be tested into the mass spectrometer.

[0007] The signal strength is input into a preset mathematical model to obtain the gas concentrations of each gas in the gas mixture to be tested.

[0008] In one technical solution of the above-mentioned gas concentration detection method, the preset mathematical model is constructed through the following steps:

[0009] The mass spectrometer acquires the signal intensity of the sample gas mixture, wherein the sample gas mixture includes at least two sample gases with known concentrations of each gas, and the signal intensity is the intensity of a characteristic peak measured by the mass spectrometer.

[0010] Construct a system of simultaneous equations for the gas concentration and the characteristic peak intensity, wherein the gas concentration is the independent variable, the characteristic peak intensity is the dependent variable, and the coefficients of the independent variables are to be determined.

[0011] Based on the gas concentration and the characteristic peak intensity, the simultaneous equations are solved to obtain the coefficients of the simultaneous equations;

[0012] Substituting the coefficients into the system of simultaneous equations yields the preset mathematical model.

[0013] In one technical solution of the above gas concentration detection method, constructing the simultaneous equations of the gas concentration and the characteristic peak intensity includes:

[0014] Identify the positions of characteristic peaks in the mass spectrum of the sample gas mixture;

[0015] Determine if there are overlapping characteristic peaks;

[0016] Construct a system of simultaneous equations based on the judgment results.

[0017] In one technical solution of the above gas concentration detection method, the step of constructing a corresponding system of simultaneous equations based on the judgment result includes:

[0018] For overlapping feature peaks, the signal intensity of the overlapping feature peaks is used as the dependent variable, and the gas concentration of the sample gas corresponding to the overlapping feature peaks is used as the independent variable to construct an equation.

[0019] For non-overlapping feature peaks, the signal intensity of the non-overlapping feature peaks is used as the dependent variable, and the gas concentration of the sample gas corresponding to the non-overlapping feature peaks is used as the independent variable to construct an equation.

[0020] Based on the number of sample gases, an equal number of equations are constructed to form the simultaneous equation system.

[0021] In one technical solution of the above gas concentration detection method, the step of constructing a corresponding system of simultaneous equations based on the judgment result includes:

[0022] Based on the first assumption, the equations in the simultaneous equation system are linear equations, wherein the first assumption is that the signal intensity and gas concentration of each sample gas have a linear relationship.

[0023] In one technical solution of the above-mentioned gas concentration detection method, the sample gas is of two types, and the simultaneous equations include:

[0024] The first linear equation is: a1x + b1y = z1.

[0025] The second linear equation is: b1y = z2.

[0026] Where x is the gas concentration of the first sample gas; y is the gas concentration of the second sample gas; z1 is the signal intensity of the overlapping characteristic peak; z2 is the signal intensity of the non-overlapping characteristic peak; and a1 and b1 are constants.

[0027] In one technical solution of the above gas concentration detection method, the step of constructing a corresponding system of simultaneous equations based on the judgment result includes:

[0028] Based on the second assumption, the equations in the simultaneous equation system are nonlinear equations, wherein the second assumption is that the signal intensity and gas concentration of each sample gas have a nonlinear relationship.

[0029] In one technical solution of the above-mentioned gas concentration detection method, the sample gas is of two types, and the simultaneous equations include:

[0030]

[0031]

[0032] Where x is the gas concentration of the first gas, y is the gas concentration of the second gas, z3 is the signal intensity of the first overlapping characteristic peak of the two sample gases, z4 is the signal intensity of the second overlapping characteristic peak of the two sample gases; a3, b3, c3, d3, e3, f3, a4, b4, c4, d4, e4 and f4 are constants.

[0033] In one technical solution of the above-mentioned gas concentration detection method, the method further includes:

[0034] Establish a mapping relationship between the preset mathematical model and the sample gas;

[0035] The mapping relationship is stored in memory.

[0036] In one technical solution of the above-mentioned gas concentration detection method, the method further includes:

[0037] Establish a mapping relationship between the coefficients, the system of simultaneous equations, and the sample gas;

[0038] The mapping relationship is stored in memory.

[0039] In one technical solution of the above-mentioned gas concentration detection method, the step of inputting the signal intensity into a preset mathematical model to obtain the gas concentrations of each gas in the gas mixture to be tested includes:

[0040] For the gas mixture to be tested, find the mapping relationship;

[0041] Based on the mapping relationship, the gas concentration of each gas is obtained.

[0042] Secondly, this application provides a gas concentration detection device, comprising:

[0043] The acquisition module is used to acquire the signal intensity of the mixed gas to be tested from the mass spectrometer. The mixed gas to be tested is formed by mixing multiple gases in a competitive adsorption instrument. The signal intensity is the characteristic peak intensity obtained by passing the mixed gas to be tested into the mass spectrometer.

[0044] The processing module is used to input the signal strength into a preset mathematical model to obtain the gas concentrations of each gas in the gas mixture to be tested.

[0045] Thirdly, this application provides a gas concentration detection system, including a competitive adsorption analyzer, a mass spectrometer, and a computer, wherein...

[0046] The competitive adsorption apparatus is used to pass multiple gases through the apparatus to obtain a mixed gas to be tested.

[0047] The mass spectrometer is used to pass the gas mixture to be tested into the mass spectrometer to obtain the characteristic peak intensity;

[0048] The computer is used to perform the method described in any one of the first aspects.

[0049] This application provides a gas concentration detection method, apparatus, and system. The method specifically involves: acquiring the signal intensity of a mixed gas to be tested from a mass spectrometer, wherein the mixed gas to be tested is formed by mixing multiple gases in a competitive adsorption analyzer, and the signal intensity is the characteristic peak intensity obtained by passing the mixed gas to be tested into the mass spectrometer; inputting the signal intensity into a preset mathematical model to obtain the gas concentrations of each gas in the mixed gas to be tested, thereby improving the gas concentration detection efficiency. Attached Figure Description

[0050] The disclosure of this application will become more readily understood with reference to the accompanying drawings. It will be readily understood by those skilled in the art that these drawings are for illustrative purposes only and are not intended to limit the scope of protection of this application. Furthermore, similar numbers in the drawings are used to denote similar components, wherein:

[0051] Figure 1 This is a schematic flowchart of a gas concentration detection method according to an embodiment of this application.

[0052] Figure 2 This is a schematic flowchart of a second embodiment of a gas concentration detection method provided in this application.

[0053] Figure 3 This is a schematic flowchart of a third embodiment of a gas concentration detection method provided in this application.

[0054] Figure 4 This is a schematic flowchart of Embodiment 4 of a gas concentration detection method provided in this application;

[0055] Figure 5 This is a schematic flowchart of Embodiment 5 of a gas concentration detection method provided in this application;

[0056] Figure 6 This is a schematic flowchart of Embodiment Six of a gas concentration detection method provided in this application;

[0057] Figure 7 This is a schematic diagram of the structure of a gas concentration detection device provided in an embodiment of this application;

[0058] Figure 8 This is a schematic diagram of the structure of a gas concentration detection system provided in an embodiment of this application.

[0059] List of reference numerals in the attached diagram:

[0060] 11: Acquisition module; 12: Processing module; 21: Competitive adsorption instrument; 22: Mass spectrometer; 23: Computer. Detailed Implementation

[0061] Some embodiments of this application are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of this application and are not intended to limit the scope of protection of this application.

[0062] In the description of this application, "module" and "processor" can include hardware, software, or a combination of both. A module can include hardware circuitry, various suitable sensors, communication ports, memory, and can also include software components, such as program code, or a combination of software and hardware. A processor can be a central processing unit, microprocessor, image processor, digital signal processor, or any other suitable processor. The processor has data and / or signal processing capabilities. The processor can be implemented in software, in hardware, or a combination of both. Non-transitory computer-readable storage media includes any suitable medium capable of storing program code, such as magnetic disks, hard disks, optical disks, flash memory, read-only memory, random access memory, etc. The term "A and / or B" means all possible combinations of A and B, such as only A, only B, or A and B. The terms "at least one A or B" or "at least one of A and B" have a similar meaning to "A and / or B" and can include only A, only B, or A and B. The singular terms "a" or "this" can also include plural forms.

[0063] In existing technologies, the concentrations of individual gases in a gas mixture can be detected using infrared absorption spectroscopy, gas chromatography, and semiconductor sensors. However, infrared absorption spectroscopy and gas chromatography require large, expensive equipment and take a long time to detect gases, while the results from semiconductor sensors are easily affected by external temperature and humidity, leading to inaccurate results. All of these existing technologies result in low gas concentration detection efficiency.

[0064] Based on this, in order to solve the above-mentioned technical problems, the technical concept of this application is to provide a new gas concentration detection method to improve the gas concentration detection efficiency.

[0065] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0066] Figure 1 This is a schematic flowchart of a gas concentration detection method according to Embodiment 1 of this application. Figure 1 As shown, specifically, the method includes:

[0067] Step S101: Obtain the signal intensity of the gas mixture to be tested using a mass spectrometer.

[0068] In this embodiment, the gas mixture to be tested is formed by mixing multiple gases in a competitive adsorption analyzer. Specifically, each gas is introduced into the competitive adsorption analyzer, and after competing for active sites on the adsorbent surface, a gas mixture is obtained. The gas mixture is then passed into a mass spectrometer to obtain the intensity of a characteristic peak, which is the signal intensity of the gas mixture to be tested.

[0069] Step S102: Input the signal strength into the preset mathematical model to obtain the gas concentrations of each gas in the gas mixture to be tested.

[0070] The preset mathematical model is the relationship between signal strength and the concentration of each gas. By inputting the signal strength into the preset mathematical model, the gas concentrations of each gas in the gas mixture to be tested can be obtained.

[0071] In this embodiment, compared with the low detection efficiency of existing technologies when detecting gas concentration, this application uses a mass spectrometer to obtain the signal intensity of the mixed gas to be tested, and then inputs the signal intensity into a preset mathematical model to obtain the gas concentration of each gas in the mixed gas. The preset mathematical model in this application is obtained through multiple experiments and has high accuracy and reliability, thereby improving the detection efficiency of mixed gas concentration.

[0072] Figure 2 This is a schematic flowchart of Embodiment 2 of a gas concentration detection method provided in this application. Figure 2 As shown, specifically, the construction of the preset mathematical model in step S102 includes:

[0073] Step S201: Obtain the signal intensity of the sample mixed gas using a mass spectrometer.

[0074] In this embodiment, the sample gas mixture includes at least two sample gases, and the concentrations of the sample gases are known. The signal intensity is the characteristic peak intensity of the sample gas mixture as measured by a mass spectrometer.

[0075] Step S202: Construct a system of simultaneous equations for gas concentration and characteristic peak intensity.

[0076] In this embodiment, the gas concentration is the independent variable, the characteristic peak intensity is the dependent variable, and the coefficient of the independent variable is to be determined.

[0077] The simultaneous equations are the relationship between gas concentration and characteristic peak intensity. This relationship can be constructed by obtaining multiple sets of gas concentration and corresponding characteristic peak intensity data, plotting points in a coordinate system, connecting multiple points in sequence to obtain a curve, and then fitting the curve using a fitting algorithm to obtain the simultaneous equations.

[0078] Step S203: Based on the gas concentration and characteristic peak intensity, solve the simultaneous equations to obtain the coefficients of the simultaneous equations.

[0079] Substitute the known gas concentrations and corresponding signal intensities of each gas in the gas mixture into a system of simultaneous equations, and solve for the coefficients in the system of simultaneous equations.

[0080] Step S204: Substitute the coefficients into the system of simultaneous equations to obtain the preset mathematical model.

[0081] Substitute the coefficients obtained from the solution into the system of simultaneous equations. The system of simultaneous equations with known coefficients is the preset mathematical model.

[0082] In this embodiment, a mapping relationship between a preset mathematical model and the sample gas can also be established and stored in a memory.

[0083] In this embodiment, a mapping relationship between coefficients, simultaneous equations, and sample gas can also be established and stored in memory.

[0084] In this embodiment, the signal intensity of the sample mixed gas is acquired by a mass spectrometer; a system of simultaneous equations is constructed to determine the gas concentration and characteristic peak intensity; the system of simultaneous equations is solved based on the gas concentration and characteristic peak intensity to obtain the coefficients; the coefficients are substituted into the system of simultaneous equations to obtain a preset mathematical model, which quantifies the gas concentration and signal intensity mathematically, thereby improving the accuracy of the relationship between the gas concentration and characteristic peak intensity.

[0085] Figure 3 This is a schematic flowchart of a third embodiment of a gas concentration detection method provided in this application. Based on the above embodiments, as follows... Figure 3 As shown, the specific implementation of step S202 includes:

[0086] Step S301: Identify the positions of characteristic peaks in the mass spectrum of the sample gas mixture.

[0087] The horizontal axis of the mass spectrum represents the mass-to-charge ratio of gaseous ions, and the vertical axis represents the intensity of characteristic peaks.

[0088] In this embodiment, the position of the characteristic peak in the mass spectrum is determined by calculating the first derivative of the mass spectrum data and by determining the zero point where the first derivative changes from negative to positive based on the starting boundary of the characteristic peak and the zero point where the first derivative changes from positive to negative based on the ending boundary of the characteristic peak.

[0089] Step S302: Determine whether there are overlapping characteristic peaks.

[0090] In this embodiment, the resolution of the characteristic peaks can be calculated. If the resolution is less than 1, the characteristic peak is considered an overlapping characteristic peak. Alternatively, the morphology of the characteristic peaks in the mass spectrum can be observed. If the characteristic peak exhibits an abnormally wide peak shape, an asymmetrical profile, or a raised baseline in the mass spectrum, then the characteristic peak is considered an overlapping characteristic peak.

[0091] Step S303: Construct the corresponding system of simultaneous equations based on the judgment results.

[0092] Based on whether there are overlapping characteristic peaks in the mass spectrum, construct the corresponding system of simultaneous equations.

[0093] In this embodiment, the positions of characteristic peaks in the mass spectrum are determined, and it is then determined whether the characteristic peaks are overlapping. Based on the determination results, a corresponding set of simultaneous equations is constructed. Different sets of simultaneous equations are constructed for different characteristic peaks. In this way, a set of simultaneous equations can be constructed in a targeted manner according to the characteristics of different mixed gases, thereby improving the accuracy of the correspondence between gas concentration and characteristic peak intensity.

[0094] Figure 4 This is a schematic flowchart of Embodiment 4 of a gas concentration detection method provided in this application. Based on the above embodiments, as follows... Figure 4 As shown, the specific implementation of step S303 includes:

[0095] Step S401: For overlapping characteristic peaks, construct an equation by using the signal intensity of the overlapping characteristic peaks as the dependent variable and the gas concentration of the sample gas corresponding to the overlapping characteristic peaks as the independent variable.

[0096] Overlapping characteristic peaks are the superposition of characteristic peaks from two or more gases at the same mass-to-charge ratio. Therefore, the signal intensity of overlapping characteristic peaks is related to the corresponding two or more gases. Thus, if overlapping peaks exist in the mass spectrum, the gas concentration of the sample gas corresponding to the overlapping characteristic peak is used as the independent variable, multiplied by the corresponding coefficient, and the intensity of the overlapping characteristic peak is used as the dependent variable to construct an equation.

[0097] Step S402: For non-overlapping characteristic peaks, construct an equation by using the signal intensity of the non-overlapping characteristic peak as the dependent variable and the gas concentration of the sample gas corresponding to the non-overlapping characteristic peak as the independent variable.

[0098] In a mass spectrum, non-overlapping characteristic peaks represent the signal intensity corresponding to the mass-to-charge ratio of a single gas ion. Therefore, the intensity of a non-overlapping characteristic peak is only related to the gas concentration of the corresponding sample gas. Here, we construct an equation by using the signal intensity of the non-overlapping characteristic peak as the dependent variable and the gas concentration of the sample gas corresponding to the non-overlapping peak as the independent variable.

[0099] Step S403: Based on the number of sample gases, construct a system of simultaneous equations with an equal number of equations.

[0100] In this embodiment, for overlapping and non-overlapping characteristic peaks, the number of equations constructed is the same as the number of sample gases, and multiple equations are used to form a system of simultaneous equations.

[0101] In this embodiment, if the mass spectrum contains only overlapping characteristic peaks, the equation is constructed only according to step S401; if the mass spectrum contains only non-overlapping characteristic peaks, the equation is constructed only according to step S402; if the mass spectrum contains both overlapping and non-overlapping characteristic peaks, both equations are constructed according to steps S401 and S402.

[0102] In this embodiment, for overlapping characteristic peaks, the signal intensity of the overlapping characteristic peak is used as the dependent variable, and the gas concentration of the sample gas corresponding to the overlapping characteristic peak is used as the independent variable to construct an equation; for non-overlapping characteristic peaks, the signal intensity of the non-overlapping characteristic peak is used as the dependent variable, and the gas concentration of the sample gas corresponding to the non-overlapping characteristic peak is used as the independent variable to construct an equation; based on the number of sample gases, an equal number of equations are constructed to form a system of simultaneous equations. By associating the type of characteristic peak with the gas concentration, and depending on whether the characteristic peak is an overlapping peak or a non-overlapping peak, equations with the same number of sample gases are constructed and a system of equations is formed, thereby improving the accuracy of the correspondence between gas concentration and characteristic peak intensity.

[0103] Figure 5 This is a schematic flowchart of Embodiment 5 of a gas concentration detection method provided in this application. Based on the above embodiments, as follows... Figure 5 As shown, specifically, the implementation of step S303 also includes:

[0104] Step S501: Based on the first assumption, construct a system of simultaneous equations where the equations are linear equations.

[0105] In this embodiment, the first assumption is that the signal intensity and gas concentration of each sample gas have a linear relationship, so the equations in the system of simultaneous equations are linear equations.

[0106] In this embodiment, for example, there are two sample gases, and the simultaneous equations are as follows:

[0107] The first linear equation is: a1x + b1y = z1.

[0108] The second linear equation is: b1y = z2.

[0109] Where x is the gas concentration of the first sample gas; y is the gas concentration of the second sample gas; z1 is the signal intensity of the overlapping characteristic peak; z2 is the signal intensity of the non-overlapping characteristic peak; and a1 and b1 are constants.

[0110] For this system of simultaneous equations, given the gas concentration x of the first sample gas, the gas concentration y of the second sample gas, the signal intensity z1 of the overlapping characteristic peak, and the signal intensity z2 of the non-overlapping characteristic peak, substituting them into the system of simultaneous equations yields the values ​​of a1 and b1.

[0111] Step S502: Based on the second assumption, construct a system of simultaneous equations where the equations are nonlinear.

[0112] In this embodiment, the second assumption is that the signal intensity and gas concentration of each sample gas have a non-linear relationship. If the mass spectrum of each sample gas contains more than two overlapping peaks, then the signal intensity of any two overlapping peaks and the corresponding gas concentration are used to construct a system of simultaneous equations.

[0113] For example, if there are two sample gases, the simultaneous equations are as follows:

[0114]

[0115]

[0116] Where x is the gas concentration of the first gas, y is the gas concentration of the second gas, z3 is the signal intensity of the first overlapping characteristic peak of the two sample gases, z4 is the signal intensity of the second overlapping characteristic peak of the two sample gases; a3, b3, c3, d3, e3, f3, a4, b4, c4, d4, e4 and f4 are constants.

[0117] For this system of simultaneous equations, given the gas concentration x of the first gas, the gas concentration y of the second gas, the signal intensity z3 of the first overlapping characteristic peak of the two sample gases, and the signal intensity z4 of the second overlapping characteristic peak of the two sample gases, substituting them into the above system of simultaneous equations, we can obtain the values ​​of a3, b3, c3, d3, e3, f3, a4, b4, c4, d4, e4, and f4.

[0118] In this embodiment, based on the first assumption, the equations in the simultaneous equation system are linear equations; based on the second assumption, the equations in the simultaneous equation system are nonlinear equations. Different equations are constructed according to the relationship between signal strength and gas concentration to improve the accuracy of gas concentration.

[0119] Figure 6 This is a schematic flowchart of Embodiment Six of a gas concentration detection method provided in this application. Based on the above embodiments, as follows... Figure 6 As shown, the specific implementation of step S102 includes:

[0120] Step S601: Find the mapping relationship for the gas mixture to be tested.

[0121] In this embodiment, a mapping relationship between a preset mathematical model and a sample gas is stored, or a mapping relationship between coefficients, a system of simultaneous equations, and a sample gas is stored.

[0122] Step S602: Based on the mapping relationship, obtain the gas concentration of each gas.

[0123] In this embodiment, a preset mathematical model corresponding to the sample gas is obtained from the mapping relationship, and the characteristic peak intensity is substituted into the preset mathematical model to obtain the gas concentration of each gas. Alternatively, coefficients and a system of simultaneous equations corresponding to the sample gas can be obtained from the mapping relationship, and the coefficients and characteristic peak intensity can be substituted into the system of simultaneous equations to obtain the gas concentration of each gas.

[0124] In this embodiment, the mass spectrometer acquires the signal intensity of the gas mixture to be tested, then finds a mapping relationship based on the gas mixture to be tested, and obtains the concentration of each gas based on the mapping relationship. This allows for the rapid determination of the concentration of each gas in the gas mixture, thereby improving the detection efficiency of the concentration of each component gas in the gas mixture.

[0125] It should be noted that although the steps in the above embodiments are described in a specific order, those skilled in the art will understand that in order to achieve the effect of this application, different steps do not necessarily have to be executed in such an order. They can be executed simultaneously (in parallel) or in other orders, and these variations are all within the scope of protection of this application.

[0126] Furthermore, this application also provides a gas concentration detection device.

[0127] Figure 7 This is a schematic diagram of the structure of a gas concentration detection device provided in an embodiment of this application. Figure 7As shown, the gas concentration detection device in this embodiment mainly includes an acquisition module 11 and a processing module 12. In some embodiments, one or more of the acquisition module 11 and the processing module 12 can be combined into a single module. In some embodiments, the acquisition module 11 can be configured to acquire the signal intensity of the gas mixture to be tested from a mass spectrometer, wherein the gas mixture to be tested is formed by mixing multiple gases in a competitive adsorption analyzer, and the signal intensity is the characteristic peak intensity obtained by passing the gas mixture to be tested into the mass spectrometer. The processing module 12 can be configured to input the signal intensity into a preset mathematical model to obtain the gas concentrations of each gas in the gas mixture to be tested.

[0128] The above-mentioned gas concentration detection device is used for performing Figures 1 to 6 The gas concentration detection method embodiments shown are similar in technical principle, the technical problems solved and the technical effects produced. Those skilled in the art can clearly understand that, for the sake of convenience and brevity, the specific working process and related descriptions of the gas concentration detection device can be referred to the content described in the gas concentration detection method embodiments, and will not be repeated here.

[0129] Those skilled in the art will understand that all or part of the processes in the method of the above-described embodiment can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable storage medium can include any entity or device capable of carrying the computer program code, a medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory, a random access memory, an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0130] Furthermore, this application also provides a gas concentration detection system.

[0131] Figure 8 This is a schematic diagram of the structure of a gas concentration detection system provided in an embodiment of this application. Figure 8 As shown, the gas concentration detection system includes a competitive adsorption unit 21, a mass spectrometer 22, and a computer 23. The competitive adsorption unit 21 can be configured to allow multiple gases to flow through it to obtain a analyte mixture. The mass spectrometer 22 can be configured to pass the analyte mixture into it to obtain the characteristic peak intensities. The computer 23 can be configured to execute... Figures 1 to 6 The illustrated gas concentration detection method is an example.

[0132] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A method for detecting gas concentration, characterized in that, include: The signal intensity of the gas mixture to be tested is obtained by the mass spectrometer, wherein the gas mixture to be tested is formed by mixing multiple gases in a competitive adsorption instrument, and the signal intensity is the characteristic peak intensity obtained by passing the gas mixture to be tested into the mass spectrometer. The signal strength is input into a preset mathematical model to obtain the gas concentrations of each gas in the gas mixture to be tested.

2. The method according to claim 1, characterized in that, The preset mathematical model is constructed through the following steps: The mass spectrometer acquires the signal intensity of the sample gas mixture, wherein the sample gas mixture includes at least two sample gases with known concentrations of each gas, and the signal intensity is the intensity of a characteristic peak measured by the mass spectrometer. Construct a system of simultaneous equations for the gas concentration and the characteristic peak intensity, wherein the gas concentration is the independent variable, the characteristic peak intensity is the dependent variable, and the coefficients of the independent variables are to be determined. Based on the gas concentration and the characteristic peak intensity, the simultaneous equations are solved to obtain the coefficients of the simultaneous equations; Substituting the coefficients into the system of simultaneous equations yields the preset mathematical model.

3. The method according to claim 2, characterized in that, The simultaneous equations for constructing the gas concentration and the characteristic peak intensity include: Identify the positions of characteristic peaks in the mass spectrum of the sample gas mixture; Determine if there are overlapping characteristic peaks; Construct a system of simultaneous equations based on the judgment results.

4. The method according to claim 3, characterized in that, The construction of the corresponding system of simultaneous equations based on the judgment result includes: For overlapping feature peaks, the signal intensity of the overlapping feature peaks is used as the dependent variable, and the gas concentration of the sample gas corresponding to the overlapping feature peaks is used as the independent variable to construct an equation. For non-overlapping feature peaks, the signal intensity of the non-overlapping feature peaks is used as the dependent variable, and the gas concentration of the sample gas corresponding to the non-overlapping feature peaks is used as the independent variable to construct an equation. Based on the number of sample gases, an equal number of equations are constructed to form the simultaneous equation system.

5. The method according to claim 3, characterized in that, The construction of the corresponding system of simultaneous equations based on the judgment result includes: Based on the first assumption, the equations in the simultaneous equation system are linear equations, wherein the first assumption is that the signal intensity and gas concentration of each sample gas have a linear relationship.

6. The method according to claim 5, characterized in that, The sample gas consists of two types, and the simultaneous equations include: The first linear equation is: a1x + b1y = z1. The second linear equation is: b1y = z2. Where x is the gas concentration of the first sample gas; y is the gas concentration of the second sample gas; z1 is the signal intensity of the overlapping characteristic peak; z2 is the signal intensity of the non-overlapping characteristic peak; and a1 and b1 are constants.

7. The method according to claim 3, characterized in that, The construction of the corresponding system of simultaneous equations based on the judgment result includes: Based on the second assumption, the equations in the simultaneous equation system are nonlinear equations, wherein the second assumption is that the signal intensity and gas concentration of each sample gas have a nonlinear relationship.

8. The method according to claim 7, characterized in that, The sample gas consists of two types, and the simultaneous equations include: Where x is the gas concentration of the first gas, y is the gas concentration of the second gas, z3 is the signal intensity of the first overlapping characteristic peak of the two sample gases, z4 is the signal intensity of the second overlapping characteristic peak of the two sample gases; a3, b3, c3, d3, e3, f3, a4, b4, c4, d4, e4 and f4 are constants.

9. The method according to claim 2, characterized in that, The method further includes: Establish a mapping relationship between the preset mathematical model and the sample gas; The mapping relationship is stored in memory.

10. The method according to claim 2, characterized in that, The method further includes: Establish a mapping relationship between the coefficients, the system of simultaneous equations, and the sample gas; The mapping relationship is stored in memory.

11. The method according to claim 9 or 10, characterized in that, The step of inputting the signal intensity into a preset mathematical model to obtain the gas concentrations of each gas in the gas mixture to be tested includes: For the gas mixture to be tested, find the mapping relationship; Based on the mapping relationship, the gas concentration of each gas is obtained.

12. A gas concentration detection device, characterized in that, include: The acquisition module is used to acquire the signal intensity of the mixed gas to be tested from the mass spectrometer. The mixed gas to be tested is formed by mixing multiple gases in a competitive adsorption instrument. The signal intensity is the characteristic peak intensity obtained by passing the mixed gas to be tested into the mass spectrometer. The processing module is used to input the signal strength into a preset mathematical model to obtain the gas concentrations of each gas in the gas mixture to be tested.

13. A gas concentration detection system, characterized in that, Includes a competitive adsorption analyzer, a mass spectrometer, and a computer, among which, The competitive adsorption apparatus is used to pass multiple gases through the apparatus to obtain a mixed gas to be tested. The mass spectrometer is used to pass the gas mixture to be tested into the mass spectrometer to obtain the characteristic peak intensity; The computer is used to perform the method according to any one of claims 1 to 11.

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