Autonomous-regulation control method and system for internal chamber pressure of mass spectrometer

Abstract

The present invention relates to the technical field of mass spectrometers. Disclosed are an autonomous-regulation control method and system for the internal chamber pressure of a mass spectrometer. The method specifically comprises: associating a first test mass spectrum group, sample components, component proportions and chamber pressure regulation parameters, so as to obtain test data groups; and when a mass spectrometer is used to test a sample, performing feature factor identification on a first real-time mass spectrum generated in real time, so as to obtain several first real-time feature factors, matching the first real-time feature factors with different test data groups, and if there is a test data group with a degree of matching greater than or equal to a preset value, regulating the internal chamber pressure of the mass spectrometer on the basis of the chamber pressure regulation parameters in the test data group. In the present invention, by means of the technical solution, chamber pressure regulation parameters are automatically determined, thereby improving the working efficiency, and ensuring the quality of a generated mass spectrum.

Description

Mass spectrometer internal chamber gas pressure self-adjusting control method and system TECHNICAL FIELD

[0001] The present application relates to the technical field of mass spectrometers, in particular to a mass spectrometer internal chamber gas pressure self-adjusting control method and system. BACKGROUND

[0002] A mass spectrometer is an instrument for analyzing the chemical composition of a sample, widely used in scientific research, environmental monitoring, biomedicine, food safety and other fields. In a mass spectrometer, the sample is ionized in an ion source, and then the ions are separated and detected under the action of magnetic and electric fields, generating a mass spectrum. The accuracy and resolution of the mass spectrum directly affect the reliability of the analysis results.

[0003] The gas pressure in the internal chamber of a mass spectrometer is one of the important factors affecting the quality of the mass spectrum. Under different experimental conditions, such as changes in sample composition and proportion, the chamber gas pressure needs to be adjusted accordingly to ensure the quality of the mass spectrum. However, in traditional mass spectrometer operation, the adjustment of the chamber gas pressure mainly depends on the experience and intuition of the operator, often requiring multiple attempts and adjustments to achieve the ideal gas pressure conditions, which is time-consuming and inefficient. SUMMARY

[0004] The purpose of the present application is to provide a mass spectrometer internal chamber gas pressure control method and system that can automatically adjust the gas pressure.

[0005] To achieve the above purpose, the present application adopts the following technical solutions:

[0006] A mass spectrometer internal chamber gas pressure self-adjusting control method, comprising:

[0007] A gas pressure adjustment test is constructed for the mass spectrometer, including determining the sample composition and proportion for each test according to a pre-set sample composition test table, conducting chamber gas pressure adjustment tests for the mass spectrometer for the determined sample composition and proportion, recording the first initial mass spectrum and the first steady-state mass spectrum generated by each chamber gas pressure adjustment test, obtaining a first test mass spectrum group, and correlating the first test mass spectrum group, the sample composition, the proportion and the chamber gas pressure adjustment parameters to obtain a test data group;

[0008] When a mass spectrometer is used for sample detection, the first real-time mass spectrum generated in real time is subjected to feature factor identification to obtain a plurality of first real-time feature factors, and the first real-time feature factors are matched with different test data groups. If there is a test data group with a matching degree greater than or equal to a pre-set value, the chamber gas pressure of the mass spectrometer is adjusted based on the chamber gas pressure adjustment parameters in the test data group.

[0009] In some embodiments of the present disclosure, the method for adjusting the chamber pressure of a mass spectrometer based on the determined sample components and component proportions comprises:

[0010] adjusting the chamber pressure based on the preset initial pressure adjustment parameter, analyzing the first initial mass spectrum generated after the pressure adjustment, and determining a correction coefficient for the initial pressure adjustment parameter based on the analysis result;

[0011] adjusting the chamber pressure based on the corrected initial pressure adjustment parameter, repeating the above pressure adjustment steps until a first steady-state mass spectrum is obtained, the first steady-state mass spectrum being a mass spectrum with accuracy meeting the preset standard, and recording the pressure adjustment parameter at this time.

[0012] In some embodiments of the present disclosure, the method for analyzing the first initial mass spectrum generated after the pressure adjustment comprises:

[0013] determining the test position parameter, test peak shape parameter, test peak width parameter and test peak area parameter of different peaks in the first initial mass spectrum to obtain a first peak characteristic parameter group;

[0014] Based on the determined sample components and component proportions, the best mass spectrum is constructed, and the best test position parameter, best peak shape parameter, best peak width parameter and best peak area parameter of different peaks in the best mass spectrum are determined to obtain a best peak characteristic parameter group;

[0015] comparing and analyzing the first peak characteristic parameter group and the best peak characteristic parameter group to obtain a first peak characteristic difference parameter group, the first peak characteristic difference parameter group comprising a first position difference vector, a first peak shape difference vector, a first peak width difference vector and a first peak area difference vector of different peaks;

[0016] calculating the position vector ratio of the first position difference vector of the corresponding peak to the test position parameter, the peak shape vector ratio of the first peak shape difference vector to the test peak shape parameter, the peak width vector ratio of the first peak width difference vector to the test peak width parameter, and the peak area vector ratio of the first peak area difference vector to the test peak area parameter;

[0017] Based on the position vector ratio, peak shape vector ratio, peak width vector ratio and peak area vector ratio corresponding to each peak in the first initial mass spectrum, a correction coefficient for the initial pressure adjustment parameter is determined.

[0018] In some embodiments of the present disclosure, the method for determining the correction coefficient for the initial pressure adjustment parameter comprises:

[0019] Obtain a mass spectrometer chamber gas pressure regulation record, and based on the mass spectrometer chamber gas pressure regulation record, determine a plurality of historical correction coefficient judgment data sets, the historical correction coefficient judgment data set including a position vector ratio corresponding to different peaks, a peak shape vector ratio, a peak width vector ratio, a peak area vector ratio, an initial gas pressure regulation parameter, and a correction coefficient;

[0020] According to the similarity between the initial gas pressure regulation parameters, the historical correction coefficient judgment data sets are classified for the first time, the historical correction coefficient judgment data sets classified for the first time are classified for the second time according to the similarity between the peak characteristic parameters, and the first classification label is configured for the first classification mode, and the second classification label is configured for the second classification mode;

[0021] The first peak characteristic parameter group is adapted to the first classification label and the second classification label, a plurality of corresponding historical correction coefficient judgment data sets are determined, and the degree of coincidence of each correction coefficient judgment data set and the first peak characteristic parameter is calculated respectively;

[0022] The expression for calculating the degree of coincidence is:

[0023] ;

[0024] Wherein, X is the degree of coincidence, is the preset maximum degree of coincidence, is the component comparison weight coefficient, is the number of peaks in the first initial mass spectrum, is the number of peaks in the historical correction coefficient judgment data set, is the number of peaks corresponding to the first initial mass spectrum and the historical correction coefficient judgment data set, is the xth value weight coefficient corresponding to the position vector ratio, the peak shape vector ratio, the peak width vector ratio, and the peak area vector ratio, is the xth vector ratio corresponding to the position vector ratio, the peak shape vector ratio, the peak width vector ratio, and the peak area vector ratio, is the coincidence difference adjustment constant.

[0025] In some embodiments disclosed in the present application, the method of classifying the historical correction coefficient judgment data set for the first time and the second time includes:

[0026] There is an initial gas pressure regulation parameter table, including a plurality of initial gas pressure regulation parameter intervals, according to the initial gas pressure regulation parameter interval to which the initial gas pressure regulation parameter in the historical correction coefficient judgment data set belongs, the historical correction coefficient judgment data set is classified, and the corresponding initial gas pressure regulation parameter interval is identified as the first classification label;

[0027] The historical correction coefficient judgment data group in each category group after the first classification is subjected to cluster analysis, and the cluster analysis method comprises setting different cluster attention weights for the position vector ratio, the peak shape vector ratio, the peak width vector ratio and the peak area vector ratio, and based on the cluster attention weights, hierarchical clustering is sequentially performed, and each hierarchical clustering center of each hierarchical clustering of the historical correction coefficient judgment data group to which the historical correction coefficient judgment data group belongs is recorded, and each hierarchical clustering center is identified as a second classification label.

[0028] In some embodiments disclosed in the present application, the method for identifying feature factors from the first real-time mass spectrum generated in real time comprises:

[0029] The real-time peak number, the real-time peak vertex coordinate and the real-time horizontal axis mapping width of the peak in the first real-time mass spectrum are determined, and the real-time peak number reference interval is set for the real-time peak number, the real-time peak vertex coordinate reference interval is set for the real-time peak vertex coordinate, and the real-time horizontal axis mapping width reference interval is set for the real-time horizontal axis mapping width;

[0030] The test peak number, the test peak vertex coordinate and the test horizontal axis mapping width of the peak in the first initial mass spectrum or the first steady-state mass spectrum in each test data group are determined, and the first initial mass spectrum or the first steady-state mass spectrum in which the test peak number is located in the real-time peak data reference interval, the test peak vertex coordinate is located in the real-time peak vertex coordinate reference interval, and the test horizontal axis mapping width is located in the real-time horizontal axis mapping width reference interval is screened out;

[0031] The screened first initial mass spectrum or first steady-state mass spectrum is compared with the first real-time mass spectrum to obtain a matching degree.

[0032] In some embodiments disclosed in the present application, the method for calculating the matching degree comprises:

[0033] The peak number difference amount between the test peak number and the real-time peak number is calculated, and the peak number difference reference ratio of the peak number difference amount to the test peak number is calculated, the peak vertex distance between the test peak vertex coordinate and the real-time peak vertex coordinate is calculated, and the peak vertex distance reference ratio of the peak vertex distance to the preset maximum peak vertex distance is calculated, the peak width difference amount between the test horizontal axis mapping width and the real-time horizontal axis mapping width is calculated, and the peak width reference ratio of the peak width difference amount to the test horizontal axis mapping width is calculated;

[0034] The matching degree of the first initial mass spectrum or the first steady mass spectrum and the first real-time mass spectrum is determined based on a peak number difference reference ratio, a peak vertex distance reference ratio, and a peak width reference ratio, wherein the method for calculating the matching degree comprises configuring a difference attention weight for the peak number difference reference ratio, the peak vertex distance reference ratio, and the peak width reference ratio respectively, and calculating a difference reference degree of the first initial mass spectrum or the first steady mass spectrum and the first real-time mass spectrum by combining each corresponding difference attention weight, and then performing a difference operation on a preset maximum matching degree to obtain the matching degree.

[0035] In some embodiments disclosed in the present application, the expression for determining the matching degree of the first initial mass spectrum or the first steady mass spectrum and the first real-time mass spectrum is:

[0036] ;

[0037] wherein P is the matching degree, is the preset maximum matching degree, is the first difference attention weight, is the second difference attention weight, is the third difference attention weight, is the peak number difference reference ratio judgment function, if the peak number difference reference ratio is greater than or equal to a preset value, then a preset constant is output, is the peak vertex distance reference ratio corresponding to the vth peak, is the peak width reference ratio corresponding to the vth peak, is the total number of peaks corresponding to the first initial mass spectrum or the first steady mass spectrum and the first real-time mass spectrum, is a difference degree adjustment constant.

[0038] In some embodiments disclosed in the present application, a mass spectrometer internal chamber gas pressure self-adjusting control system is also disclosed, comprising:

[0039] The first module is configured to construct a gas pressure adjustment test for the mass spectrometer, comprising determining the sample composition and the composition ratio of each test according to a preset sample composition test table, performing chamber gas pressure adjustment test of the mass spectrometer for the determined sample composition and the composition ratio, recording the first initial mass spectrum and the first steady mass spectrum generated by each chamber gas pressure adjustment test to obtain a first test mass spectrum group, and associating the first test mass spectrum group, the sample composition, the composition ratio, and the chamber gas pressure adjustment parameter to obtain a test data group.

[0040] The second module is used for identifying characteristic factors of the first real-time mass spectrum generated in real time when the mass spectrometer is used to detect samples, obtaining a plurality of first real-time characteristic factors, and matching the first real-time characteristic factors with different test data groups, and if there is a test data group with a matching degree greater than or equal to a preset value, adjusting the internal chamber pressure of the mass spectrometer based on the chamber pressure adjustment parameter in the test data group.

[0041] The application discloses a mass spectrometer internal chamber pressure self-adjusting control method, and relates to the technical field of mass spectrometers. BRIEF DESCRIPTION OF DRAWINGS

[0042] FIG. 1 is a method step of a mass spectrometer internal chamber pressure self-adjusting control method according to an embodiment of the application. DETAILED DESCRIPTION

[0043] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application.

[0044] In order to achieve the above-mentioned purpose, the application adopts the following technical solutions:

[0045] Referring to FIG. 1, a mass spectrometer internal chamber pressure self-adjusting control method comprises the following steps.

[0046] In step S100, the chamber pressure adjustment test is constructed for the mass spectrometer, including determining the sample composition and the composition ratio of each test according to a preset sample composition test table, performing the chamber pressure adjustment test of the mass spectrometer for the determined sample composition and the composition ratio, recording the first initial mass spectrum and the first steady-state mass spectrum generated by each chamber pressure adjustment test, obtaining a first test mass spectrum group, and associating the first test mass spectrum group, the sample composition, the composition ratio and the chamber pressure adjustment parameter to obtain a test data group.

[0047] In this step, a database of ideal gas pressure conditions corresponding to different sample compositions and proportions is established. First, a sample composition test table is developed based on experimental requirements, including the sample components to be analyzed and their proportions. Then, for each sample composition and proportion in the test table, a mass spectrometer chamber pressure adjustment test is performed. This means adjusting the pressure in the mass spectrometer's internal chamber to find the optimal pressure conditions for that particular sample. After each pressure adjustment, the initial mass spectrum and the mass spectrum after reaching steady state are recorded, forming the first test mass spectrum set. These mass spectra reflect the behavior of sample ions under different pressure conditions. Finally, the recorded test mass spectrum set is associated with the corresponding sample composition, composition proportion, and parameters used to adjust the pressure, establishing a test data set. This data set serves as the basis for subsequent automatic pressure adjustment.

[0048] For a better understanding of the above technical solutions, the following examples can be used for reference:

[0049] Mass spectrometers are widely used in environmental detection, particularly in analyzing volatile organic compounds (VOCs) in the air. VOCs are a class of organic compounds that are volatile at room temperature. They exist in the air and come from various sources such as industrial emissions, automobile exhaust, and indoor decoration materials. The concentration of these compounds directly affects air quality, so accurate detection is necessary.

[0050] The specific implementation method is as follows:

[0051] Conducting gas pressure adjustment tests:

[0052] First, a sample composition test table is developed based on various VOCs compositions and proportions that may be encountered in environmental detection.

[0053] Then, for each VOCs composition and proportion, a mass spectrometer chamber pressure adjustment test is performed. In each test, the chamber pressure is adjusted, and the initial mass spectrum and the mass spectrum after reaching steady state are recorded, forming the first test mass spectrum set.

[0054] Finally, the recorded test mass spectrum set is associated with the corresponding VOCs composition, composition proportion, and parameters used to adjust the pressure, establishing a test data set.

[0055] Real-time mass spectrum feature factor identification and gas pressure self-adjustment:

[0056] During actual environmental air sample detection, the mass spectrometer generates real-time mass spectra.

[0057] The system analyzes these real-time mass spectra and identifies characteristic factors such as the number, position, shape, and area of peaks.

[0058] The identified characteristic factors are matched with the previously established test data set to find the closest VOC composition and proportion.

[0059] If a test data set with a matching degree greater than or equal to a preset value is found, the system will automatically adjust the internal chamber pressure of the mass spectrometer according to the gas pressure adjustment parameters recorded in the data set.

[0060] In this way, the mass spectrometer can automatically optimize its internal chamber pressure in environmental detection, improve the accuracy and repeatability of detection, and thus provide more reliable data support for environmental monitoring.

[0061] In some embodiments disclosed in the present application, the method for adjusting the chamber pressure of the mass spectrometer based on the determined sample composition and composition ratio includes:

[0062] Step S101, adjust the chamber pressure based on the preset initial gas pressure adjustment parameters, analyze the first initial mass spectrum generated after the pressure adjustment, and determine the correction coefficient of the initial gas pressure adjustment parameters based on the analysis results.

[0063] In some embodiments disclosed in the present application, the method for analyzing the first initial mass spectrum generated after the pressure adjustment includes:

[0064] Step S1011, determine the test position parameters, test peak shape parameters, test peak width parameters and test peak area parameters of different peaks in the first initial mass spectrum to obtain the first peak characteristic parameter set.

[0065] Step S1012, based on the determined sample composition and composition ratio, construct the best mass spectrum and determine the best test position parameters, best peak shape parameters, best peak width parameters and best peak area parameters of different peaks in the best mass spectrum to obtain the best peak characteristic parameter set.

[0066] In this step, the method for determining the best mass spectrum includes:

[0067] (1) Select or design a standard material, select a standard material with known composition and proportion, or design a synthetic standard mixture to ensure that the composition and proportion of the sample match the experimental requirements. (2) Determine the generation and transmission characteristics of ions, according to the known chemical reactions and ionization techniques, predict the ionization efficiency of each component in the sample in the mass spectrometer, and the transmission characteristics of ions inside the mass spectrometer, including collision, scattering and focusing effect. (3) Calculate the theoretical fragmentation pattern: for each molecule, according to its chemical structure and possible fragmentation pathways, calculate the expected fragment ions. (4) Simulate mass spectrum, using mass spectrum simulation software, simulate the theoretical mass spectrum according to the above information; this simulation will show all the expected ion peaks, including their retention time, intensity and possible isotope distribution. (5) Optimize parameters, according to the specific model and configuration of the mass spectrometer, adjust the simulation parameters, such as collision energy, ion transmission efficiency, mass analyzer settings, etc., to optimize the theoretical mass spectrum. (6) Construct the best peak characteristic parameter set: extract the characteristic parameters of each peak from the simulated mass spectrum, such as peak position (m / z value), peak shape, peak width and peak area, which constitute the best peak characteristic parameter set.

[0068] Among them, the method of calculating the theoretical fragmentation pattern includes: the formation of parent ions, first, the molecules in the sample are ionized in the ion source, usually by electron impact (EI), electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI) or matrix assisted laser desorption / ionization (MALDI) and other methods. In this process, the molecule loses one or more electrons to form a positively charged molecular ion. Prediction of fragmentation pattern, the molecular ion further undergoes fragmentation in the mass spectrometer to produce a series of fragment ions. These fragments are caused by the breaking of chemical bonds in the molecular ion, which can be the breaking of a single bond or the continuous breaking of multiple bonds.

[0069] Prediction of fragmentation pattern involves bond energy, different types of chemical bonds (such as C-C, C-H, C-O, etc.) have different bond energies, which determine which bonds are easy to break during ionization; stability and charge distribution, the stability and charge distribution of fragment ions affect the formation of fragments. Positive charge usually makes some parts of the molecule more stable, affecting the fragmentation pathway. Mass spectrometry fragmentation rules, some types of compounds tend to produce specific fragmentation patterns, which can be obtained through literature research or database query.

[0070] Computational methods: There are different methods to calculate the theoretical fragment pattern, including: empirical rules, based on known mass spectrometry fragmentation rules and experience, to predict the possible fragments of the molecular ion. Computer-aided calculation, using special software tools such as Mass Frontier, MM2, etc., which can calculate all possible fragment ions according to the structure of the molecule and ionization method. Quantum chemical calculation, a more advanced method is to use quantum chemical software such as Gaussian to perform molecular orbital calculation to predict the lowest energy path in the fragmentation process, thereby obtaining the most likely fragment ions.

[0071] Step S1013, comparing and analyzing the first peak characteristic parameter set and the optimal peak characteristic parameter set to obtain a first peak characteristic difference parameter set, the first peak characteristic difference parameter set including a first position difference vector, a first peak shape difference vector, a first peak width difference vector, and a first peak area difference vector of different peaks.

[0072] Step S1014, calculating a position vector ratio of the first position difference vector of the corresponding peak to the test position parameter, a peak shape vector ratio of the first peak shape difference vector to the test peak shape parameter, a peak width vector ratio of the first peak width difference vector to the test peak width parameter, and a peak area vector ratio of the first peak area difference vector to the test peak area parameter.

[0073] Step S1015, determining a correction coefficient of the initial gas pressure adjustment parameter based on the position vector ratio, the peak shape vector ratio, the peak width vector ratio, and the peak area vector ratio corresponding to each peak in the first initial mass spectrum.

[0074] In some embodiments disclosed in the present application, the method for determining the correction coefficient of the initial gas pressure adjustment parameter comprises:

[0075] Step S10151, obtaining a mass spectrometer chamber gas pressure adjustment record, and determining a plurality of historical correction coefficient judgment data sets based on the mass spectrometer chamber gas pressure adjustment record, the historical correction coefficient judgment data set including a position vector ratio, a peak shape vector ratio, a peak width vector ratio, a peak area vector ratio corresponding to different peaks, an initial gas pressure adjustment parameter, and a correction coefficient.

[0076] Step S10152, classifying the historical correction coefficient judgment data set according to the similarity between the initial gas pressure adjustment parameters for the first time, classifying the historical correction coefficient judgment data set classified for the first time according to the similarity between the peak characteristic parameters for the second time, and configuring a first classification tag for the first classification method and a second classification tag for the second classification method.

[0077] Step S10153, the first peak characteristic parameter set is subjected to the adaptation of the first classification label and the second classification label, a plurality of historical correction coefficient judgment data sets are determined, and the degree of coincidence of each correction coefficient judgment data set and the first peak characteristic parameter is calculated respectively;

[0078] The expression for calculating the degree of coincidence is:

[0079] 。

[0080] X is the degree of coincidence, is a preset maximum degree of coincidence, is a component ratio comparison weight coefficient, is the number of peaks in the first initial mass spectrum, is the number of peaks in the historical correction coefficient judgment data set, is the number of peaks corresponding to the first initial mass spectrum and the historical correction coefficient judgment data set, is the xth value weight coefficient corresponding to the position vector ratio, the peak shape vector ratio, the peak width vector ratio, and the peak area vector ratio, is the xth vector value corresponding to the position vector ratio, the peak shape vector ratio, the peak width vector ratio, and the peak area vector ratio, is a coincidence difference adjustment constant.

[0081] In some embodiments disclosed in the present application, the method for first classification and second classification of the historical correction coefficient judgment data set comprises:

[0082] Step S101521, an initial air pressure adjustment parameter table is preset, the initial air pressure adjustment parameter table comprises a plurality of initial air pressure adjustment parameter intervals, the historical correction coefficient judgment data set is classified according to the initial air pressure adjustment parameter interval to which the initial air pressure adjustment parameter in the historical correction coefficient judgment data set belongs, and the corresponding initial air pressure adjustment parameter interval is identified as the first classification label.

[0083] Step S101522, the clustering analysis is performed on the plurality of historical correction coefficient judgment data sets in each category group after the first classification, the clustering analysis method comprises setting different clustering attention weights for the position vector ratio, the peak shape vector ratio, the peak width vector ratio, and the peak area vector ratio, and based on the clustering attention weights, hierarchical clustering is sequentially performed, the clustering center of each hierarchical clustering to which the historical correction coefficient judgment data set belongs is recorded, and each clustering center is identified as the second classification label.

[0084] Step S102, based on the adjusted initial air pressure adjustment parameter, the air pressure of the chamber is adjusted, and the above-mentioned air pressure adjustment step of the chamber is repeated until a first steady-state mass spectrum is obtained, the first steady-state mass spectrum is a mass spectrum with accuracy performance meeting a preset standard, and the air pressure adjustment parameter at this time is recorded.

[0085] Step S200, when the mass spectrometer is applied to sample detection, a first real-time mass spectrum generated in real time is subjected to feature factor identification to obtain a plurality of first real-time feature factors, and the first real-time feature factors are matched with different test data groups, if there is a test data group with a matching degree greater than or equal to a preset value, the chamber air pressure adjustment parameter in the test data group is used to adjust the air pressure of the chamber in the mass spectrometer.

[0086] In this step, the system analyzes these real-time mass spectra and identifies feature factors, which may include the number, position, shape and area of peaks; then, the identified feature factors are matched with the previously established test data groups to find the closest sample components and proportions; this step is realized by comparing the similarity between the real-time mass spectrum and the test mass spectrum group; if a test data group with a matching degree greater than or equal to a preset value is found, the system will automatically adjust the air pressure of the chamber in the mass spectrometer according to the air pressure adjustment parameter recorded in the data group; in this way, it can be ensured that the air pressure of the chamber in the mass spectrometer is always in the best state during actual detection, thereby improving the accuracy and repeatability of detection.

[0087] In some embodiments disclosed in the present application, the method for identifying feature factors from the first real-time mass spectrum generated in real time comprises:

[0088] Step S201, the real-time peak number, real-time peak vertex coordinates and real-time horizontal axis mapping width of the peaks in the first real-time mass spectrum are determined, the real-time peak number reference interval is set for the real-time peak number, the real-time peak vertex coordinate reference interval is set for the real-time peak vertex coordinates, and the real-time horizontal axis mapping width reference interval is set for the real-time horizontal axis mapping width.

[0089] Step S202, a plurality of test data groups are analyzed to determine the test peak number, test peak vertex coordinates and test horizontal axis mapping width of the peaks in the first initial mass spectrum or the first steady-state mass spectrum in each test data group, and the first initial mass spectrum or the first steady-state mass spectrum with the test peak number located in the real-time peak data reference interval, the test peak vertex coordinates located in the real-time peak vertex coordinate reference interval, and the test horizontal axis mapping width located in the real-time horizontal axis mapping width reference interval are screened out.

[0090] Step S203, the screened first initial mass spectrum or first steady-state mass spectrum is compared with the first real-time mass spectrum to obtain a matching degree.

[0091] In some embodiments of the present disclosure, the method for calculating the matching degree comprises:

[0092] In step S2031, the peak number difference between the test peak number and the real-time peak number is calculated, and the peak number difference reference ratio between the peak number difference and the test peak number is calculated. The peak vertex distance between the test peak vertex coordinates and the real-time peak vertex coordinates is calculated, and the peak vertex distance reference ratio between the peak vertex distance and the preset maximum peak vertex distance is calculated. The peak width difference between the test horizontal axis mapping width and the real-time horizontal axis mapping width is calculated, and the peak width reference ratio between the peak width difference and the test horizontal axis mapping width is calculated.

[0093] In step S2032, the matching degree of the first initial mass spectrum or the first steady-state mass spectrum and the first real-time mass spectrum is determined based on the peak number difference reference ratio, the peak vertex distance reference ratio, and the peak width reference ratio. The method for calculating the matching degree comprises configuring a difference attention weight for the peak number difference reference ratio, the peak vertex distance reference ratio, and the peak width reference ratio, respectively, and calculating the difference reference degree of the first initial mass spectrum or the first steady-state mass spectrum and the first real-time mass spectrum by combining each corresponding difference attention weight, respectively. The difference reference degree is subtracted from the preset maximum matching degree to obtain the matching degree.

[0094] In some embodiments of the present disclosure, the expression for determining the matching degree of the first initial mass spectrum or the first steady-state mass spectrum and the first real-time mass spectrum is:

[0095] 。

[0096] wherein P is the matching degree, is the preset maximum matching degree, is the first difference attention weight, is the second difference attention weight, is the third difference attention weight, is the peak number difference reference ratio judgment function, if the peak number difference reference ratio is greater than or equal to the preset value, then a preset constant is output, is the peak vertex distance reference ratio corresponding to the vth peak, is the peak width reference ratio corresponding to the vth peak, is the total number of peaks corresponding to the first initial mass spectrum or the first steady-state mass spectrum and the first real-time mass spectrum, is the difference degree adjustment constant.

[0097] In some embodiments of the present disclosure, a mass spectrometer internal chamber gas pressure self-adjusting control system is also disclosed, comprising:

[0098] The first module is used for constructing a gas pressure adjustment test for the mass spectrometer, comprising determining sample components and component proportions for each test according to a preset sample component test table, performing chamber gas pressure adjustment test of the mass spectrometer for the determined sample components and component proportions, recording a first initial mass spectrum and a first steady-state mass spectrum generated by each chamber gas pressure adjustment test to obtain a first test mass spectrum group, and associating the first test mass spectrum group, the sample components, the component proportions and chamber gas pressure adjustment parameters to obtain a test data group.

[0099] The second module is used for identifying feature factors of a first real-time mass spectrum generated in real time when the mass spectrometer is used for sample detection to obtain a plurality of first real-time feature factors, matching the first real-time feature factors with different test data groups, and if there is a test data group with a matching degree greater than or equal to a preset value, adjusting the internal chamber gas pressure of the mass spectrometer based on the chamber gas pressure adjustment parameters in the test data group.

[0100] The application discloses a mass spectrometer internal chamber gas pressure self-adjusting control method, and relates to the technical field of mass spectrometers, and specifically discloses that a first test mass spectrum group, sample components, component proportions and chamber gas pressure adjustment parameters are associated to obtain a test data group, when a mass spectrometer is used for sample detection, feature factors of a first real-time mass spectrum generated in real time are identified to obtain a plurality of first real-time feature factors, the first real-time feature factors are matched with different test data groups, if there is a test data group with a matching degree greater than or equal to a preset value, the internal chamber gas pressure of the mass spectrometer is adjusted based on the chamber gas pressure adjustment parameters in the test data group, and the application realizes automatic determination of chamber gas pressure adjustment parameters, improves work efficiency, and ensures the quality of generated mass spectra.

[0101] The above only describes the preferred embodiments of the application, but the protection scope of the application is not limited to this, any person skilled in the art can make equivalent replacement, change or modification to the technical scheme and the inventive concept of the application within the technical range disclosed by the application, which should be covered in the protection scope of the application.

Claims

1. A method for self-regulating control of internal chamber gas pressure of a mass spectrometer, characterized by, The method comprises the following steps: A mass spectrometer is constructed, and a gas pressure adjustment test is performed on the mass spectrometer. The sample components and the component proportions of each test are determined according to a preset sample component test table. The chamber gas pressure adjustment test is performed on the mass spectrometer according to the determined sample components and the component proportions. The first initial mass spectrum and the first steady-state mass spectrum generated in each chamber gas pressure adjustment test are recorded to obtain a first test mass spectrum group. The first test mass spectrum group, the sample components, the component proportions, and the chamber gas pressure adjustment parameters are associated to obtain a test data group. When the mass spectrometer is used to detect a sample, the first real-time mass spectrum generated in real time is subjected to feature factor identification to obtain a plurality of first real-time feature factors. The first real-time feature factors are matched with different test data groups. If there is a test data group with a matching degree greater than or equal to a preset value, the chamber gas pressure of the mass spectrometer is adjusted based on the chamber gas pressure adjustment parameters in the test data group.

2. The method for self-regulating and controlling the internal chamber gas pressure of a mass spectrometer according to claim 1, wherein, The method for performing the chamber gas pressure adjustment test on the mass spectrometer based on the determined sample components and the component proportions comprises the following steps: The chamber is subjected to gas pressure adjustment based on the preset initial gas pressure adjustment parameters. The first initial mass spectrum generated after the gas pressure adjustment is analyzed. Based on the analysis result, a correction coefficient of the initial gas pressure adjustment parameters is determined. The chamber is subjected to gas pressure adjustment based on the corrected initial gas pressure adjustment parameters. The above-mentioned gas pressure adjustment step is repeated until the first steady-state mass spectrum is obtained. The first steady-state mass spectrum is a mass spectrum with a accuracy performance meeting a preset standard. The gas pressure adjustment parameters at this time are recorded.

3. The method for self-regulating and controlling the internal chamber gas pressure of a mass spectrometer according to claim 2, wherein, The method for analyzing the first initial mass spectrum generated after the gas pressure adjustment comprises the following steps: The test position parameters, the test peak shape parameters, the test peak width parameters, and the test peak area parameters of different peaks in the first initial mass spectrum are determined to obtain a first peak feature parameter group. Based on the determined sample components and the component proportions, an optimal mass spectrum is constructed, and the optimal test position parameters, the optimal peak shape parameters, the optimal peak width parameters, and the optimal peak area parameters of different peaks in the optimal mass spectrum are determined to obtain an optimal peak feature parameter group. The first peak feature parameter group and the optimal peak feature parameter group are compared and analyzed to obtain a first peak feature difference parameter group. The first peak feature difference parameter group comprises a first position difference vector, a first peak shape difference vector, a first peak width difference vector, and a first peak area difference vector of different peaks. The position vector ratio of the first position difference vector of the corresponding peak to the test position parameter, the peak shape vector ratio of the first peak shape difference vector to the test peak shape parameter, the peak width vector ratio of the first peak width difference vector to the test peak width parameter, and the peak area vector ratio of the first peak area difference vector to the test peak area parameter are calculated. Based on the position vector ratio, the peak shape vector ratio, the peak width vector ratio, and the peak area vector ratio of each peak in the first initial mass spectrum, the correction coefficient of the initial gas pressure adjustment parameters is determined.

4. The method for self-regulating and controlling the internal chamber gas pressure of a mass spectrometer according to claim 3, wherein, The method for determining the correction coefficient of the initial gas pressure adjustment parameters comprises the following steps: Obtaining a mass spectrometer chamber gas pressure regulation record, and determining a plurality of historical correction coefficient judgment data sets based on the mass spectrometer chamber gas pressure regulation record, the historical correction coefficient judgment data sets including position vector ratio, peak shape vector ratio, peak width vector ratio, peak area vector ratio, initial gas pressure regulation parameters, and correction coefficients corresponding to different peaks; According to the similarity between the initial gas pressure regulation parameters, the historical correction coefficient judgment data sets are classified for the first time, and the historical correction coefficient judgment data sets classified for the first time are classified for the second time according to the similarity between the peak characteristic parameters, and a first classification label is configured for the first classification method, and a second classification label is configured for the second classification method; The first peak characteristic parameter group is adapted to the first classification label and the second classification label, a plurality of corresponding historical correction coefficient judgment data sets are determined, and the degree of coincidence of each correction coefficient judgment data set and the first peak characteristic parameter is calculated respectively. The expression for calculating the degree of coincidence is: ； wherein X is the degree of conformity, for a predetermined maximum degree of correspondence, to weight coefficients for component ratios, the number of peaks in the first initial mass spectrum, to judge the number of peaks in the data set, determining the number of peaks corresponding to the first initial mass spectrum and the historical correction factor judgment data set, The xth weight coefficient corresponding to the position vector ratio, the peak shape vector ratio, the peak width vector ratio, and the peak area vector ratio, For the xthvector ratio in the position vector ratio, the peak shape vector ratio, the peak width vector ratio, the peak area vector ratio, The difference between the adjustment constant and the coincidence.

5. The method for self-regulating and controlling the internal chamber gas pressure of a mass spectrometer according to claim 4, wherein, The method for classifying the historical correction coefficient judgment data sets for the first time and the second time includes: The initial gas pressure regulation parameter table is preset, and the initial gas pressure regulation parameter table includes a plurality of initial gas pressure regulation parameter intervals. According to the initial gas pressure regulation parameter interval to which the initial gas pressure regulation parameter in the historical correction coefficient judgment data set belongs, the historical correction coefficient judgment data set is classified, and the corresponding initial gas pressure regulation parameter interval is identified as the first classification label; The clustering analysis method includes setting different clustering attention weights for the position vector ratio, the peak shape vector ratio, the peak width vector ratio, and the peak area vector ratio, and performing hierarchical clustering based on the clustering attention weights, and recording the clustering center of each hierarchical clustering to which the historical correction coefficient judgment data set belongs, and identifying each clustering center as the second classification label.

6. The method for self-regulating and controlling the internal chamber gas pressure of a mass spectrometer according to claim 1, wherein, The method for identifying the characteristic factors of the first real-time mass spectrum includes: The real-time peak number, the real-time peak vertex coordinate, and the real-time horizontal axis mapping width of the peak in the first real-time mass spectrum are determined, and the real-time peak number reference interval is set for the real-time peak number, the real-time peak vertex coordinate reference interval is set for the real-time peak vertex coordinate, and the real-time horizontal axis mapping width reference interval is set for the real-time horizontal axis mapping width; The test peak number, the test peak vertex coordinate, and the test horizontal axis mapping width of the peak in the first initial mass spectrum or the first steady-state mass spectrum in each test data set are determined, and the first initial mass spectrum or the first steady-state mass spectrum in which the test peak number is located in the real-time peak data reference interval, the test peak vertex coordinate is located in the real-time peak vertex coordinate reference interval, and the test horizontal axis mapping width is located in the real-time horizontal axis mapping width reference interval is screened out; The screened first initial mass spectrum or first steady-state mass spectrum is compared with the first real-time mass spectrum to obtain the matching degree.

7. The method for self-regulating and controlling the internal chamber gas pressure of a mass spectrometer according to claim 6, wherein, The method for calculating the matching degree includes: a peak number difference amount between the test peak number and the real-time peak number is calculated, a peak number difference reference ratio of the peak number difference amount to the test peak number is calculated, a peak vertex distance between the test peak vertex coordinates and the real-time peak vertex coordinates is calculated, a peak vertex distance reference ratio of the peak vertex distance to a preset maximum peak vertex distance is calculated, a peak width difference amount between the test horizontal axis mapping width and the real-time horizontal axis mapping width is calculated, and a peak width reference ratio of the peak width difference amount to the test horizontal axis mapping width is calculated; based on the peak number difference reference ratio, the peak vertex distance reference ratio, and the peak width reference ratio, a matching degree of the first initial mass spectrum or the first steady mass spectrum and the first real-time mass spectrum is determined, wherein the method of calculating the matching degree includes configuring a difference attention weight for the peak number difference reference ratio, the peak vertex distance reference ratio, and the peak width reference ratio, respectively, and calculating a difference reference degree of the first initial mass spectrum or the first steady mass spectrum and the first real-time mass spectrum by combining each corresponding difference attention weight, and performing a difference operation with a preset maximum matching degree to obtain the matching degree.

8. The method for self-regulating and controlling the internal chamber gas pressure of a mass spectrometer according to claim 7, wherein, The expression of the matching degree of the first initial mass spectrum or the first steady mass spectrum and the first real-time mass spectrum is: ； wherein P is the degree of matching, for a preset maximum degree of matching, for the first difference attention weight, for the second difference attention weight, for the third difference attention weight, is a peak number difference reference ratio judgment function, if the peak number difference reference ratio is greater than or equal to a preset value, then outputting a preset constant, a reference ratio of peak top distance corresponding to the vth peak, a peak width reference ratio corresponding to the vth peak, the total number of peaks corresponding to the first initial mass spectrum or the first steady state mass spectrum and the first real time mass spectrum, is a difference degree adjustment constant.

9. A mass spectrometer internal chamber gas pressure self-regulating control system, characterized by, comprises: The first module is configured to construct a gas pressure adjustment test for the mass spectrometer, including determining sample components and component proportions for each test according to a preset sample component test table, performing chamber gas pressure adjustment tests for the mass spectrometer for the determined sample components and component proportions, recording first initial mass spectra and first steady mass spectra generated by each chamber gas pressure adjustment test to obtain a first test mass spectrum group, and associating the first test mass spectrum group, the sample components, the component proportions, and chamber gas pressure adjustment parameters to obtain a test data group. The second module is configured to identify first real-time characteristic factors from a first real-time mass spectrum generated in real time when the mass spectrometer is used to detect a sample, match the first real-time characteristic factors with different test data groups, and adjust the internal chamber gas pressure of the mass spectrometer based on the chamber gas pressure adjustment parameters in the test data group if there is a test data group with a matching degree greater than or equal to a preset value.

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