Method and system for quantitative analysis of lubricating oil additive

Abstract

The invention relates to the technical field of lubricating oil analysis, in particular to a method and system for quantitative analysis of a lubricating oil additive. The method comprises the following steps: acquiring base oil data and lubricating oil additive data; performing mixed oil treatment based on the base oil data and the lubricating oil additive data to generate mixed lubricating oil additive data; performing mixed oil concentration detection on the mixed lubricating oil additive data to generate mixed oil concentration detection data; performing chromatographic column selection on the mixed lubricating oil additive data based on the mixed oil concentration detection data to generate chromatographic column selection data; and performing boiling point heating on the chromatographic column selection data to obtain mixed oil boiling point heating data. By optimizing data acquisition, chromatographic separation, component identification and quantitative analysis as well as result analysis and visualization, the accuracy of quantitative analysis of the lubricating oil additive is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of lubricating oil analysis, and in particular to a method and system for quantitative analysis of lubricating oil additives. Background Art

[0002] In the early days, the analysis of lubricant additives mainly relied on physical and chemical detection methods, such as viscosity measurement, acid value analysis and infrared spectroscopy. Although these methods are simple and intuitive, they have limited quantitative analysis capabilities for multi-component additive systems. With the development of chromatographic technology, gas chromatography (GC) and high performance liquid chromatography (HPLC) were introduced to separate and detect complex additive components. The high resolution and high sensitivity of these technologies significantly improved the accuracy of quantitative analysis. In recent years, the rise of mass spectrometry has further promoted the development of quantitative analysis of lubricant additives. Mass spectrometry combined with gas chromatography or liquid chromatography (GC-MS, LC-MS) has achieved structural identification and content determination of additive molecules. At the same time, nuclear magnetic resonance (NMR) technology and atomic absorption spectroscopy (AAS) and other methods have also been used for elemental analysis and molecular property research of additives. However, the current traditional chromatographic technology lacks specificity in chromatographic column selection and parameter optimization, which can easily lead to poor separation effect or loss of specific components. At the same time, component identification and content quantitative analysis often rely on a single method, which is prone to errors due to insufficient sensitivity or resolution, resulting in low accuracy of quantitative analysis of lubricant additives. Summary of the invention

[0003] Based on this, it is necessary to provide a method and system for quantitative analysis of lubricant additives to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for quantitative analysis of lubricating oil additives is provided, the method comprising the following steps: Step S1: acquiring base oil data and lubricant additive data; performing mixed oil processing based on the base oil data and the lubricant additive data to generate mixed lubricant additive data; performing mixed oil concentration detection on the mixed lubricant additive data to generate mixed oil concentration detection data; Step S2: performing chromatographic column selection on the mixed lubricant additive data based on the mixed oil concentration detection data to generate chromatographic column selection data; performing boiling point heating on the chromatographic column selection data to obtain mixed oil boiling point heating data; performing gas chromatography separation on the chromatographic column selection data according to the mixed oil boiling point heating data to generate standard mixed oil gas chromatography separation data; Step S3: converting the standard mixed oil gas chromatography separation data into a mass spectrum to generate a mixed oil component mass spectrum; performing a lubricant oil additive type analysis on the mixed oil component mass spectrum to generate lubricant oil additive type data; performing a quantitative analysis of the additive component content on the lubricant oil additive type data to generate mixed oil additive component content data; Step S4: Analyze the mixed oil additive component content data to generate classified additive component data; visualize the classified additive component data to generate a lubricant additive component analysis report to perform a lubricant additive quantitative analysis operation.

[0005] The present invention obtains base oil and additive data and performs mixed processing to provide accurate input data for analysis and ensure the consistency of subsequent experiments. The mixed oil concentration detection data provides a reliable basis for the optimization of subsequent chromatographic separation conditions, which improves the pertinence and effectiveness of the analysis. Based on the concentration detection data, a suitable chromatographic column is selected to avoid the problem of blind column selection in traditional methods and improve the separation efficiency. The gas chromatography separation parameters are optimized by boiling point heating to achieve efficient separation of complex components and avoid component loss or cross contamination. High-quality separation results are provided for subsequent mass spectrometry analysis to ensure data stability and repeatability. Mass spectrum conversion and component type analysis are combined to achieve accurate identification of lubricant additive types. Content data is generated by component quantitative analysis to provide a scientific basis for lubricant performance evaluation and formulation optimization. Combining the advantages of gas chromatography and mass spectrometry, the sensitivity and resolution of the analysis are significantly improved. Classification data analysis and visualization present complex quantitative analysis results as clear graphical reports, which are convenient for users to understand and apply. The analysis report provides strong technical support for lubricant formulation design, performance improvement and industrial application, and enhances the value of analysis operations. The complete chain from data collection to report generation is formed, which significantly improves the efficiency and accuracy of quantitative analysis of lubricant additives. Therefore, the present invention improves the accuracy of quantitative analysis of lubricant additives by optimizing data acquisition, chromatographic separation, component identification and quantitative analysis, and result interpretation and visualization.

[0006] Preferably, step S1 comprises the following steps: Step S11: acquiring base oil data and lubricant additive data; Step S12: performing base oil concentration detection on the base oil data to generate base oil concentration detection data; Step S13: pre-processing the lubricating oil additive data based on the base oil concentration detection data to generate standard lubricating oil additive data, wherein the pre-processing includes filtering and solid phase extraction; performing mixed oil processing based on the standard lubricating oil additive data and the base oil concentration detection data to generate mixed lubricating oil additive data; Step S14: performing mixed oil concentration detection on the mixed lubricating oil additive data to generate mixed oil concentration detection data.

[0007] The present invention can accurately grasp the concentration and quality of each component by performing concentration detection and pretreatment on the base oil and lubricating oil additives, thereby ensuring that the quality of the final mixed lubricating oil is more uniform and stable. By pre-treating the lubricating oil additives (such as filtration and solid phase extraction), impurities can be removed, the performance of the lubricating oil can be improved, and its effectiveness in practical applications can be ensured. By mixing oil treatment and mixing oil concentration detection, the quality and concentration of the final lubricating oil can be ensured to meet the standards, the fluctuations in the production process can be reduced, and the consistency between batches can be improved. Through standardized processes (including data detection and pre-treatment, etc.), not only the scientific nature of the lubricating oil formula can be improved, but also manual operation errors can be reduced, production efficiency can be improved, and production costs can be reduced. Monitoring and data recording for each key link (such as base oil concentration detection and mixed oil concentration detection) in the steps are helpful to adjust and control the production process in real time, and improve the accuracy and controllability of production.

[0008] Preferably, step S2 comprises the following steps: Step S21: performing chemical property analysis on the mixed lubricant additive data based on the mixed oil concentration detection data to generate mixed oil chemical property data; performing chromatographic column selection based on the mixed oil chemical property data to generate chromatographic column selection data, wherein the chromatographic column selection includes a polar chromatographic column and a neutral non-polar chromatographic column; Step S22: performing temperature program setting on the chromatographic column selection data to generate chromatographic column temperature program setting data; performing boiling point heating on the mixed lubricating oil additive data using the chromatographic column temperature program setting data to obtain mixed oil boiling point heating data; Step S23: performing mobile phase adjustment on the chromatographic column selection data according to the mixed oil boiling point heating data to generate chromatographic column mobile phase adjustment data; performing gas chromatography separation on the mixed lubricating oil additive data based on the chromatographic column mobile phase adjustment data to generate mixed oil gas chromatography separation data; Step S24: preprocessing the mixed oil and gas chromatography separation data to generate standard mixed oil and gas chromatography separation data, wherein the data preprocessing includes data cleaning, data denoising, data missing value filling and data standardization.

[0009] The present invention can deeply understand the composition and chemical properties of the mixed oil by analyzing the chemical characteristics of the mixed oil concentration detection data, provide an accurate basis for subsequent separation and processing, thereby improving the accuracy and reliability of the analysis results. Through the optimization of the chromatographic column selection (such as the selection of polar chromatographic columns and neutral non-polar chromatographic columns), the most suitable chromatographic column can be selected according to the characteristics of the lubricating oil additives, improve the separation effect, and reduce the error in the separation process. Through reasonable temperature program setting and boiling point heating, the separation of the components of the mixed oil in the chromatographic column is more efficient, while reducing the separation time and cost. Boiling point heating can promote the volatilization of components and ensure that different components can be well separated. By pre-processing the gas chromatography separation data (including data cleaning, denoising, missing value filling and standardization), invalid information can be removed, the accuracy and availability of the analysis data can be guaranteed, and the credibility of the final analysis results can be improved. Each step (such as temperature program setting, mobile phase adjustment, etc.) is accurately set and adjusted to ensure the stability of the chromatographic analysis and the repeatability of the results, thereby reducing the fluctuation and uncertainty between batches. By gradually adjusting parameters such as the selection of chromatographic columns and mobile phase settings, conditions can be optimized in real time during the production process, oil quality can be controlled, and various properties of the lubricant can be ensured to meet standard requirements.

[0010] Preferably, using the chromatographic column temperature program setting data to perform boiling point heating on the mixed lubricating oil additive data comprises: Using the chromatographic column temperature program setting data to collect sample separation data of the mixed lubricating oil additive data, to obtain initial chromatographic data, wherein the initial chromatographic data includes retention time and basic peak information data; The basic peak information data and the chromatographic column temperature program setting data are subjected to temperature program linear mapping according to the retention time to generate temperature program linear mapping data; wherein the temperature program linear mapping formula is as follows: In the formula, Linearly map data for the temperature program, is the initial temperature, Expressed as the heating rate, It is expressed as the residence time; Based on the preset chromatographic column calibration data, the boiling point interpolation estimation is performed on the temperature program linear mapping data to obtain the component boiling point data; the initial chromatographic data is used to calculate the mixed oil heating behavior using the component boiling point data through the cumulative weighted method to generate the mixed oil boiling point heating data; the formula of the cumulative weighted method is as follows: In the formula, The boiling point heating data of the mixed oil is Expressed as The mass percentage of each component, Expressed as The boiling points of the components, Expressed as the number of components.

[0011] The present invention heats the mixed oil at the boiling point by setting data of the chromatographic column temperature program, and accurately controls the temperature change by a linear mapping formula. The method ensures the stability of the heating process, so that the boiling point of each component can be accurately estimated, thereby ensuring the effect of separation and heating. The boiling point of each component can be accurately calculated by temperature program linear mapping and boiling point interpolation estimation, which provides accurate physical parameters for subsequent oil component analysis and helps to improve the accuracy of lubricating oil quality analysis. By collecting sample separation data (such as retention time and basic peak information data), preliminary information can be provided for gas chromatography analysis, which helps to further optimize the chromatographic column selection and analysis process and improve separation efficiency. The boiling point and mass percentage of each component are calculated by the cumulative weighted method, which can more accurately simulate the behavior of the mixed oil during the heating process. This method not only considers the boiling point of each component, but also integrates their mass distribution in the mixed oil, providing a more comprehensive heating behavior analysis. The boiling point of each component is combined with its mass percentage by the cumulative weighted method, ensuring that the boiling point heating data is more consistent with the behavior of the actual oil, so that the final analysis result has higher reliability and scientificity. This method can accurately calculate the various parameters of the mixed oil during the boiling point heating process, providing effective technical support for the production, adjustment and optimization of lubricating oil, and helping to improve production efficiency and oil quality.

[0012] Preferably, performing mobile phase adjustment on the chromatographic column selection data according to the mixed oil boiling point heating data comprises: Perform boiling point distribution characteristic analysis on key components of mixed oil boiling point heating data to generate boiling point distribution characteristic data of key components; perform chromatographic column performance matching analysis on chromatographic column selection data based on boiling point distribution characteristic data of key components to generate chromatographic column performance matching data; The preliminary mobile phase parameters are set through the chromatographic column performance matching data to generate preliminary mobile phase setting data, wherein the preliminary mobile phase parameter setting includes the mobile phase type setting and the initial flow rate range setting; the preliminary mobile phase setting data is dynamically adjusted using the boiling point distribution characteristic data of the key components to generate chromatographic column mobile phase adjustment data.

[0013] The present invention can accurately understand the boiling point characteristics of each component in the mixed oil by analyzing the boiling point distribution characteristics of the key components, thereby providing a scientific basis for the performance matching of the chromatographic column, optimizing the mobile phase adjustment process, and ensuring that the separation effect is more accurate. Based on the boiling point distribution characteristic data of the key components, the chromatographic column performance matching analysis can be carried out, and the most suitable chromatographic column type can be effectively selected. This process helps to improve the separation efficiency, reduce the blindness of the chromatographic column selection, and ensure that the chromatographic column performance is maximized. Through the initial parameter setting of the mobile phase (such as the setting of the mobile phase type and the initial flow rate range), a reasonable parameter framework can be provided for chromatographic separation in the initial stage, which not only improves the scientific nature of the mobile phase selection, but also can lay the foundation for subsequent dynamic adjustment. The preliminary mobile phase setting data is dynamically adjusted using the boiling point distribution characteristic data of the key components, and the mobile phase parameters can be optimized in real time according to the changes in the actual separation process. This flexible adjustment ability can greatly improve the adaptability and efficiency in the separation process and ensure the best separation effect. The method makes the separation process more controllable through multi-stage optimization and dynamic adjustment (such as chromatographic column performance matching analysis and mobile phase adjustment). The adjusted mobile phase parameters can better meet the separation requirements of different components, reducing the errors and instability caused by parameter mismatch. The dynamic nature of mobile phase adjustment ensures that the separation process can respond to changes in the components of the mixed oil in a timely manner, avoiding analytical errors caused by inappropriate mobile phase settings, and further improving the accuracy and reliability of the analysis results.

[0014] Preferably, step S3 comprises the following steps: Step S31: Performing mass spectrometry scanning on the gas chromatography separation data of the standard mixed oil through the GC-MS system to generate a mass spectrum signal of the mixed oil component; performing mass spectrum conversion on the mass spectrum signal of the mixed oil component to generate a mass spectrum of the mixed oil component; Step S32: performing ion peak feature extraction on the mass spectrum of the mixed oil component to obtain ion peak feature data of the mixed oil component, wherein the ion peak feature extraction includes molecular ion peak feature extraction and fragment ion peak feature extraction; performing lubricant oil additive type analysis on the standard mixed oil gas chromatography separation data through the ion peak feature data of the mixed oil component to generate lubricant oil additive type data; Step S33: Calibrate the parameter standard curve based on the preset standard lubricant additive to generate the standard lubricant additive calibration curve; perform quantitative analysis on the additive component content of the lubricant additive type data according to the standard lubricant additive calibration curve to generate the mixed oil additive component content data.

[0015] The present invention performs mass spectrometry scanning on the mixed oil through the GC-MS system, and can obtain detailed component mass spectrometry signals and generate a mass spectrum of the mixed oil components. This process can accurately identify different components in the oil product, which is helpful for in-depth analysis of the types and contents of lubricating oil additives. By extracting ion peak features from the mass spectrum, including the extraction of molecular ion peaks and fragment ion peaks, the key components in the lubricating oil additive can be effectively identified. This ion peak feature extraction method improves the resolution and accuracy of the mixed oil components and provides accurate data support for subsequent additive type analysis. The types of lubricating oil additives are analyzed using the ion peak feature data of the mixed oil components, and different types of lubricating oil additives can be accurately identified, which is helpful for quality control and optimization of oil products, and also provides a basis for subsequent quantitative analysis of additive content. By calibrating the parameter standard curve based on the preset standard lubricant additive, reliable reference data can be provided for quantitative analysis. The establishment of the standard curve ensures that the quantitative analysis of the content of the additive components is more accurate, and avoids errors caused by inconsistent standard data. Quantitative analysis of lubricant additive type data based on standard lubricant additive calibration curves can accurately calculate the content of each component, which provides a reliable basis for lubricant formulation optimization, quality monitoring and production control. Through quantitative analysis of the content of lubricant additive components, the level of additives in the lubricant can be fully monitored to ensure that the performance of each batch of lubricants meets the requirements, which helps to ensure that the lubricant achieves the best lubrication effect and extends its service life during use. This method can provide detailed lubricant composition data, which is helpful for real-time adjustment and optimization during the production process to ensure the stability and consistency of the final product. At the same time, it reduces product quality fluctuations caused by improper additive ratios.

[0016] Preferably, extracting ion peak features from the mass spectrum of the mixed oil components includes: The mass-to-charge ratio of the ion peak is calculated for the mass spectrum of the mixed oil component to obtain the ion peak mass-to-charge ratio; based on the molecular ion peak screening rule, the candidate peaks of the mass spectrum of the mixed oil component are screened by the molecular ion peak mass-to-charge ratio to generate the molecular ion peak screening data of the mixed oil component; wherein the molecular ion peak screening rule is as follows: in, Expressed as the molecular peak intensity, It is expressed as the minimum range of mass-to-charge ratio of the molecular ion peak, Expressed as the maximum range of the mass-to-charge ratio of the molecular ion peak, Expressed as mass spectrum intensity, It is expressed as the response intensity of the relative abundance of the ion signal to the mass-to-charge ratio signal. Expressed as the mass of the ion, It is expressed as the charge number of the ion; Perform isotope peak comparison on the molecular ion peak screening data of the mixed oil components to generate molecular ion peak verification data; perform molecular ion peak shape feature extraction on the mass spectrum of the mixed oil components through the molecular ion peak verification data to obtain molecular ion peak feature extraction data; Based on the fragment ion peak screening rules, the candidate peaks of the mass spectrum of the mixed oil components are screened by the mass-to-charge ratio of the molecular ion peak to generate the fragment ion peak screening data of the mixed oil components; the fragment ion peak screening rules are as follows: in, Expressed as ion peak intensity, Expressed as the molecular peak intensity, is represented as the intensity threshold, Expressed as mass spectrum intensity, It is expressed as the response intensity of the relative abundance of the ion signal to the mass-to-charge ratio signal. Expressed as the mass of the ion, It is expressed as the charge number of the ion; The fragment ion peak feature extraction is performed on the fragment ion peak screening data of the mixed oil components to obtain the fragment ion peak feature extraction data; the molecular ion peak feature extraction data and the fragment ion peak feature extraction data are integrated to generate the mixed oil component ion peak feature data.

[0017] The present invention can accurately screen out relevant ion peaks by calculating the mass-to-charge ratio of ion peaks on the mass spectrum of the mixed oil components, and based on the molecular ion peak screening rules and the fragment ion peak screening rules, this screening method effectively reduces the interference of irrelevant signals, ensures that only important signal data are retained, thereby improving the accuracy and reliability of the analysis results. Through the molecular ion peak screening rules based on the mass-to-charge ratio, the molecular ion peaks in the mixed oil components can be accurately identified and screened out. This process helps to extract key information from the mass spectrum data, further analyze the core components in the oil products, and provide accurate component information. By performing isotope peak comparison on the molecular ion peaks, the correctness of the screened molecular ion peaks can be verified to ensure their reliability. This step can further exclude false peaks and noise signals and improve the accuracy of the data. By performing peak shape feature extraction on the molecular ion peaks and the fragment ion peaks, the detailed features of the ion peaks can be extracted, and these features can help to deeply understand the properties and structures of the oil components, and further enhance the identification and quantitative analysis capabilities of lubricating oil additives. Based on the screening rules of fragment ion peaks, by extracting the characteristics of the fragment ion peaks of the mixed oil components, the structural information in the oil products can be further analyzed, which is helpful to distinguish and identify different lubricant additives and provide more detailed component analysis. The integration of molecular ion peak characteristic data and fragment ion peak characteristic data provides all-round data support for a comprehensive understanding of the composition and properties of the mixed oil. Through data integration, the comprehensiveness and accuracy of the analysis can be improved, providing a stronger data basis for lubricant quality control. This method can improve the recognition accuracy of lubricant additives and provide more reliable data support for the quality monitoring of lubricant products. Through fine peak analysis, the types and contents of different additives in oil products can be accurately determined, thereby ensuring the stability and controllability of oil performance.

[0018] Preferably, performing a quantitative analysis of the additive component content on the lubricant additive type data according to the standard lubricant additive calibration curve comprises: Verify the effective range of the standard lubricant additive calibration curve to generate the effective range data of the calibration curve; extract regression model parameters from the effective range data of the calibration curve to generate the calibration curve model parameter data; Performing concentration regression calculation on the sample additive type peak information data to generate sample additive concentration data; performing internal standard correction on the sample additive concentration data to generate corrected sample additive concentration data; performing concentration ratio calculation on the corrected sample additive concentration data to generate sample additive relative ratio data; Based on the calibration curve model parameter data, the relative proportion data of the sample additives are quantitatively analyzed to generate the component content data of the mixed oil additives.

[0019] The present invention can ensure the accuracy of the analysis results by using the standard lubricant additive calibration curve to perform quantitative analysis of the additive component content. By verifying the effective range of the calibration curve, the data applicability is ensured, thereby reducing errors and improving the reliability of the analysis results. By performing concentration regression calculation on the sample additive type peak information data, the concentration of each additive in the sample can be accurately calculated. The concentration regression method can automatically derive the actual concentration of each additive in the sample based on the existing standard calibration curve, thereby improving the efficiency and accuracy of the analysis. By performing internal standard correction on the sample additive concentration data, the systematic error or instrument drift occurring during the analysis process can be eliminated, thereby making the concentration data more accurate and reliable, which is very important for precision control in complex sample analysis and can effectively improve the accuracy of sample concentration determination. By performing concentration ratio calculation on the corrected sample additive concentration data, the relative content of each additive component in the sample can be obtained, and this ratio data provides valuable information for in-depth analysis of the relative concentration distribution of each component in the oil product, helping to better understand the performance characteristics of the lubricating oil. Based on the calibration curve model parameter data, the quantitative analysis of component content can scientifically determine the content of each component of lubricant additives, which not only provides reliable data support for lubricant quality control, but also provides a basis for optimizing lubricant formulation and improving lubrication performance. This method uses automated calibration curve verification, regression calculation, internal standard correction and other steps to reduce errors in manual operation and improve analysis efficiency, especially in large-scale sample testing.

[0020] Preferably, step S4 comprises the following steps: Step S41: analyzing the mixed oil additive component content data and extracting the additive quantitative result data; classifying the additive quantitative result data by additive function and generating classified additive component data; Step S42: Repeat the analysis and verification of the classified additive component data to generate lubricant additive quantitative analysis verification data; visualize the lubricant additive quantitative analysis verification data to generate a lubricant additive component analysis report to perform the lubricant additive quantitative analysis operation.

[0021] The present invention can clearly distinguish the concentration and function of each additive by analyzing the results of the content data of the mixed oil additive component and extracting the quantitative results, so that the analysis results are more accurate. In addition, the functional classification of additives can ensure that additives with different functions are appropriately grouped, which is helpful for more detailed performance analysis. By repeatedly analyzing and verifying the classified additive component data, the consistency and reliability of the results can be confirmed. This step can effectively avoid errors in data analysis, ensure the stability of each analysis result, and improve the repeatability of the experiment. By visualizing the quantitative analysis and verification data of lubricating oil additives, the data can be presented in charts or other graphical forms, which can not only help technicians quickly identify key data points, but also provide intuitive information for decision makers, facilitating performance evaluation and quality control. The generation of the lubricating oil additive component analysis report makes the analysis results not only a collection of data, but also presents a technical report with clear structure and comprehensive content. The report can be used as a basis for quality control, product development, and technical improvement, enhancing the application value of the data. By analyzing the classified additive components, the functionality of different additives can be identified, thereby providing a basis for the optimization of lubricating oil formulations. Especially in the formulation adjustment and R&D stage of lubricants, targeted adjustments can be made according to the functional requirements of additives to improve the performance of lubricants. The automated quantitative analysis and verification process reduces errors caused by manual operations and improves work efficiency. In complex analysis tasks, this process not only improves accuracy, but also reduces manual intervention and reduces the workload of operators.

[0022] In the present specification, a system for quantitative analysis of lubricating oil additives is provided, which is used to perform the above-mentioned method for quantitative analysis of lubricating oil additives. The system for quantitative analysis of lubricating oil additives comprises: A mixing module is used to obtain base oil data and lubricant additive data; perform mixed oil processing based on the base oil data and the lubricant additive data to generate mixed lubricant additive data; perform mixed oil concentration detection on the mixed lubricant additive data to generate mixed oil concentration detection data; The chromatographic separation module is used to select a chromatographic column for the mixed lubricant additive data based on the mixed oil concentration detection data to generate chromatographic column selection data; perform boiling point heating on the chromatographic column selection data to obtain mixed oil boiling point heating data; perform gas chromatography separation on the chromatographic column selection data according to the mixed oil boiling point heating data to generate standard mixed oil gas chromatography separation data; The component content detection module is used to convert the standard mixed oil gas chromatography separation data into a mass spectrum to generate a mixed oil component mass spectrum; to analyze the types of lubricating oil additives on the mixed oil component mass spectrum to generate lubricating oil additive type data; to perform additive component content quantitative analysis on the lubricating oil additive type data to generate mixed oil additive component content data; The analysis module is used to analyze the results of the mixed oil additive component content data to generate classified additive component data; to visualize the classified additive component data, thereby generating a lubricant additive component analysis report to perform lubricant additive quantitative analysis operations.

[0023] The beneficial effect of the present invention is that the process covers the complete life cycle of lubricant analysis from the acquisition of base oil data and lubricant additive data to the generation of the final lubricant additive component analysis report, ensuring the systematicness of data processing and the consistency of results. Each step is closely linked, effectively avoiding the problem of step dispersion and data fragmentation in traditional analysis, and improving the analysis efficiency and consistency of results. Through the mixed oil processing and concentration detection in step S1, high-precision initial data is provided for subsequent chromatographic column selection and boiling point heating. The application of mass spectrum conversion and ion peak extraction (step S3) makes the identification of lubricant additive types and quantitative analysis of content more accurate, providing a reliable basis for functional evaluation and formulation optimization of lubricants. Based on the concentration detection and boiling point characteristics of the mixed oil (step S2), chromatographic column selection and heating parameter setting are performed to ensure the resolution and stability of gas chromatography separation and reduce the trial and error cost of the experiment. The standard gas chromatography separation data provided lays a solid foundation for the component identification and subsequent analysis of lubricant additives. By performing quantitative analysis of the component content of lubricant additive type data, combined with internal standard correction and concentration regression calculation, high-precision additive component content data is generated (step S3), which effectively improves the accuracy of the analysis and the credibility of the results. In step S4, through data analysis and classification, complex additive component information is displayed in an intuitive visual form, lowering the threshold for data understanding. Therefore, the present invention improves the accuracy of lubricant additive quantitative analysis by optimizing data acquisition, chromatographic separation, component identification and quantitative analysis, and result analysis and visualization. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A schematic diagram of a process flow of a method for quantitative analysis of lubricating oil additives; Figure 2 for Figure 1 Detailed implementation steps of step S2 in the flowchart; Figure 3 for Figure 1 Detailed implementation steps of step S3 in FIG. The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0025] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0026] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0027] It should be understood that although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit, and the term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0028] To achieve this, please refer to Figures 1 to 3 , a method for quantitative analysis of lubricating oil additives, the method comprising the following steps: Step S1: acquiring base oil data and lubricant additive data; performing mixed oil processing based on the base oil data and the lubricant additive data to generate mixed lubricant additive data; performing mixed oil concentration detection on the mixed lubricant additive data to generate mixed oil concentration detection data; Step S2: performing chromatographic column selection on the mixed lubricant additive data based on the mixed oil concentration detection data to generate chromatographic column selection data; performing boiling point heating on the chromatographic column selection data to obtain mixed oil boiling point heating data; performing gas chromatography separation on the chromatographic column selection data according to the mixed oil boiling point heating data to generate standard mixed oil gas chromatography separation data; Step S3: converting the standard mixed oil gas chromatography separation data into a mass spectrum to generate a mixed oil component mass spectrum; performing a lubricant oil additive type analysis on the mixed oil component mass spectrum to generate lubricant oil additive type data; performing a quantitative analysis of the additive component content on the lubricant oil additive type data to generate mixed oil additive component content data; Step S4: Analyze the mixed oil additive component content data to generate classified additive component data; visualize the classified additive component data to generate a lubricant additive component analysis report to perform a lubricant additive quantitative analysis operation.

[0029] The present invention obtains base oil and additive data and performs mixed processing to provide accurate input data for analysis and ensure the consistency of subsequent experiments. The mixed oil concentration detection data provides a reliable basis for the optimization of subsequent chromatographic separation conditions, which improves the pertinence and effectiveness of the analysis. Based on the concentration detection data, a suitable chromatographic column is selected to avoid the problem of blind column selection in traditional methods and improve the separation efficiency. The gas chromatography separation parameters are optimized by boiling point heating to achieve efficient separation of complex components and avoid component loss or cross contamination. High-quality separation results are provided for subsequent mass spectrometry analysis to ensure data stability and repeatability. Mass spectrum conversion and component type analysis are combined to achieve accurate identification of lubricant additive types. Content data is generated by component quantitative analysis to provide a scientific basis for lubricant performance evaluation and formulation optimization. Combining the advantages of gas chromatography and mass spectrometry, the sensitivity and resolution of the analysis are significantly improved. Classification data analysis and visualization present complex quantitative analysis results as clear graphical reports, which are convenient for users to understand and apply. The analysis report provides strong technical support for lubricant formulation design, performance improvement and industrial application, and enhances the value of analysis operations. The complete chain from data collection to report generation is formed, which significantly improves the efficiency and accuracy of quantitative analysis of lubricant additives. Therefore, the present invention improves the accuracy of quantitative analysis of lubricant additives by optimizing data acquisition, chromatographic separation, component identification and quantitative analysis, and result interpretation and visualization.

[0030] In the embodiment of the present invention, reference Figure 1 FIG. 1 is a schematic diagram of a step flow chart of a method for quantitative analysis of lubricating oil additives according to the present invention. In this example, the method for quantitative analysis of lubricating oil additives comprises the following steps: Step S1: acquiring base oil data and lubricant additive data; performing mixed oil processing based on the base oil data and the lubricant additive data to generate mixed lubricant additive data; performing mixed oil concentration detection on the mixed lubricant additive data to generate mixed oil concentration detection data; In the embodiment of the present invention, the base oil data required for lubricant production are collected, including the physical properties (such as viscosity, density, flash point) and chemical properties (such as saturation, aromatic content, etc.) of the base oil. The base oil data can be obtained through the technical specifications provided by the supplier, laboratory analysis data or database query. The lubricant additive data used for lubricant formulations are collected, including the functions of the additives (such as anti-wear, anti-oxidation, clean dispersion, etc.), chemical properties, relative concentration requirements and supplier specification data. The additive data must ensure that the source is reliable and have batch numbers, purity and concentration parameters. The base oil and lubricant additives are mixed according to the formula ratio. The mixing process requires the use of precise weighing equipment to ensure the accuracy of the component ratio. The mixing process usually uses a stirring device or a heating device (such as a constant temperature stirrer) to ensure uniformity. If there is a solubility problem with the additive, it is necessary to select an appropriate solvent or adjust the temperature according to the physical property parameters. Record the preliminary physical and chemical property data of the mixed sample (such as color, odor, initial viscosity, etc.) to generate the mixed lubricant additive data, including the mixing ratio, preliminary properties and other relevant information. The mixed lubricant is sampled and the concentration is analyzed by a standardized detection procedure. The detection process usually uses precision instruments such as gas chromatograph (GC), liquid chromatograph (HPLC) or mass spectrometer (MS). Based on the standard curve or calibration method, the concentration of each additive in the sample is quantitatively analyzed. The mass concentration or molar concentration of each component is recorded to ensure that it is within the specified range of the formula. The test results are sorted and analyzed to generate mixed oil concentration test data, including the concentration value of each component, test error and concentration distribution diagram. If the concentration deviates from the formula requirements, the abnormal data needs to be recorded and marked to provide a basis for subsequent adjustments.

[0031] Step S2: performing chromatographic column selection on the mixed lubricant additive data based on the mixed oil concentration detection data to generate chromatographic column selection data; performing boiling point heating on the chromatographic column selection data to obtain mixed oil boiling point heating data; performing gas chromatography separation on the chromatographic column selection data according to the mixed oil boiling point heating data to generate standard mixed oil gas chromatography separation data; In an embodiment of the present invention, the component information of the mixed oil is analyzed by utilizing the mixed oil concentration detection data (including the concentration and distribution of each component), with special attention paid to the physicochemical properties of the key components (such as boiling point range, polarity, molecular weight, etc.). The key components that need to be separated first are identified to ensure the efficiency and accuracy of gas chromatography (GC) separation. According to the boiling point range and polarity of the components, a suitable chromatographic column type (such as a capillary column or a packed column) is selected, and the key parameters of the chromatographic column are matched and analyzed, including: stationary phase type (polar or non-polar), inner diameter, length and film thickness, and chromatographic column selection data is generated, including the recommended chromatographic column model and its parameter settings. Based on the chromatographic column selection data and the boiling point range of the mixed oil components, a suitable temperature program is designed, including: starting temperature (initial constant temperature stage), heating rate (linear or segmented heating), and maximum temperature (avoid exceeding the tolerance range of the chromatographic column). The calculation formula for the temperature program is as follows: ;in: For heating temperature, is the starting temperature, is the heating rate, is the retention time. The mixed oil is heated according to the designed temperature program, the evaporation characteristics of the components are recorded, and the boiling point heating data of the mixed oil is generated, including the evaporation starting temperature, peak temperature and boiling point of each component. Using the selected chromatographic column and the set temperature program, the mixed oil sample is injected into the gas chromatograph (GC) for separation. The chromatographic signal is collected by a detector (such as a flame ionization detector FID or a mass spectrometer MS). The signals of each component are separated according to the retention time to obtain the standard mixed oil gas chromatography separation data.

[0032] Step S3: converting the standard mixed oil gas chromatography separation data into a mass spectrum to generate a mixed oil component mass spectrum; performing a lubricant oil additive type analysis on the mixed oil component mass spectrum to generate lubricant oil additive type data; performing a quantitative analysis of the additive component content on the lubricant oil additive type data to generate mixed oil additive component content data; In an embodiment of the present invention, the gas chromatography separation data of the standard mixed oil is input into a mass spectrometer for combined analysis (GC-MS). The mass spectrometer captures the mass spectrometry signal generated by each component after gas chromatography separation, including the mass-to-charge ratio (m / z) and the ion intensity. The detected mass spectrometry signal is subjected to data conversion and visualization processing to generate a mass spectrum of the mixed oil component. The mass spectrum uses the mass-to-charge ratio (x-axis) and the ion signal intensity (y-axis) as coordinates to reflect the molecular ion peak and fragment ion peak characteristics of each component. The characteristics of the molecular ion peak and the fragment ion peak are extracted from the mass spectrum of the mixed oil component: the molecular ion peak is confirmed by screening the maximum intensity peak within the mass-to-charge ratio range. The fragment ion peak extracts the fragment peak with an intensity greater than the threshold according to a specific screening rule. The extracted ion peak feature data is compared with the mass spectrum database of lubricating oil additives. Based on the feature matching results, the type of additives, such as antioxidants, detergents, friction modifiers, etc., is identified to generate lubricating oil additive type data. The calibration curve of the standard lubricant additive is used to verify its effectiveness within the concentration range of the sample component, and the calibration curve effective range data is generated. Extract the regression model parameters (such as slope, intercept, etc.) of the calibration curve to generate calibration curve model parameter data. Calculate the concentration of each additive based on the peak area of ​​the additive type in the sample and the calibration curve to generate sample additive concentration data. Introduce internal standards (standard substances with known concentrations) to calibrate the sample additive concentration data, eliminate the effects of injection errors and instrument drift, and generate calibrated sample additive concentration data. Calculate the concentration ratio of each component after correction to generate sample additive relative proportion data. Based on the calibration curve model parameter data and sample additive relative proportion data, perform quantitative analysis of the components to generate mixed oil additive component content data, including the mass fraction or mole fraction of each additive.

[0033] Step S4: Analyze the mixed oil additive component content data to generate classified additive component data; visualize the classified additive component data to generate a lubricant additive component analysis report to perform a lubricant additive quantitative analysis operation.

[0034] In the embodiment of the present invention, by inputting the content data of the components of the mixed oil additives, the original quantitative analysis results are classified and sorted, including information such as the type, concentration, and relative proportion of the additives. The component data is classified according to the functional properties of the lubricant additives to generate classified additive component data. Typical classifications include: antioxidants, dispersants, detergents, antiwear agents, viscosity improvers, preservatives, etc. The specific concentration and mass proportion of each additive are marked. The classified data is verified for consistency to ensure that the type and content of the additives are consistent with the original analysis results. Check whether the data meets the expected range of industry standards or experimental design. The classified additive component data is presented in a visual form to generate multi-dimensional charts and reports, including: Bar chart: showing the concentration distribution of various additives. Pie chart: reflecting the relative proportion of each additive in the total component. Line chart: showing the trend of component content with sample batches. Heat map: analyzing the correlation or spatial distribution characteristics between multiple components. Based on the visual chart and classified data, a lubricant additive component analysis report is automatically generated. The report content includes: a detailed list of additive types. Quantitative data of each component and its proportion analysis. Interpret charts and mark abnormal components or components that need attention. Review analysis reports to ensure data accuracy and report readability. Add necessary experimental notes or analysis conclusions to provide suggestions for subsequent optimization.

[0035] Preferably, step S1 comprises the following steps: Step S11: acquiring base oil data and lubricant additive data; Step S12: performing base oil concentration detection on the base oil data to generate base oil concentration detection data; Step S13: pre-processing the lubricating oil additive data based on the base oil concentration detection data to generate standard lubricating oil additive data, wherein the pre-processing includes filtering and solid phase extraction; performing mixed oil processing based on the standard lubricating oil additive data and the base oil concentration detection data to generate mixed lubricating oil additive data; Step S14: performing mixed oil concentration detection on the mixed lubricating oil additive data to generate mixed oil concentration detection data.

[0036] In an embodiment of the present invention, the raw data of base oil and lubricant additives are extracted from a designated supplier or laboratory database. Ensure that the base oil data and lubricant additive data are stored in a unified format, including physical and chemical properties (such as viscosity, density, chemical composition) and batch information. Check the raw data for missing values ​​and outliers to ensure data integrity and accuracy. Take an appropriate amount of base oil sample to ensure sample uniformity. Use a spectrophotometer or mass spectrometer to perform concentration detection and calibrate the instrument according to standard operating procedures. Use national standard or industry specification detection methods (such as ASTMD7042) to analyze base oil concentration. Store the test results as base oil concentration detection data, including concentration values, detection environment parameters (such as temperature, pressure) and detection equipment identification. Use a high-precision filter (such as a 0.45 µm filter membrane) to remove suspended particles and impurities in lubricant additives. Further purify the lubricant additive sample through a solid phase extraction column to remove inorganic salts or excess chemical components. Record the purity, component concentration and treatment conditions of the lubricant additive after pretreatment. Calculate the mixing ratio of base oil and lubricant additive according to the base oil concentration test data and the target concentration of lubricant additive. Mix the base oil and standard lubricant additive accurately according to the calculated ratio, and use a high-speed stirrer or ultrasonic mixer to ensure uniformity. Record the parameters during the mixing process (such as mixing time, temperature) and the physical and chemical properties of the generated mixed oil. Use a detection method similar to step S12 (such as spectrophotometer or mass spectrometry) combined with multidimensional data analysis to ensure accurate results. Perform data correction for detection deviations to ensure that the results are consistent with the actual situation. Includes final concentration value, detection process records and correction parameters.

[0037] As an example of the present invention, refer to Figure 2 As shown, in this example, step S2 includes: Step S21: performing chemical property analysis on the mixed lubricant additive data based on the mixed oil concentration detection data to generate mixed oil chemical property data; performing chromatographic column selection based on the mixed oil chemical property data to generate chromatographic column selection data, wherein the chromatographic column selection includes a polar chromatographic column and a neutral non-polar chromatographic column; Step S22: performing temperature program setting on the chromatographic column selection data to generate chromatographic column temperature program setting data; performing boiling point heating on the mixed lubricating oil additive data using the chromatographic column temperature program setting data to obtain mixed oil boiling point heating data; Step S23: performing mobile phase adjustment on the chromatographic column selection data according to the mixed oil boiling point heating data to generate chromatographic column mobile phase adjustment data; performing gas chromatography separation on the mixed lubricating oil additive data based on the chromatographic column mobile phase adjustment data to generate mixed oil gas chromatography separation data; Step S24: preprocessing the mixed oil and gas chromatography separation data to generate standard mixed oil and gas chromatography separation data, wherein the data preprocessing includes data cleaning, data denoising, data missing value filling and data standardization.

[0038] In the embodiment of the present invention, a suitable amount of sample is extracted from the mixed oil to ensure representativeness and uniformity. The mixed oil is analyzed by Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), mass spectrometry (MS) and other technologies to obtain data such as its chemical composition, molecular structure, and reactivity. Based on the detection data, the components of the mixed oil are quantitatively analyzed using chemometric methods (such as principal component analysis PCA) to generate chemical property data of the mixed oil, including the concentration and structural information of different components. According to the chemical property data of the mixed oil, such as polarity, molecular weight, solubility, etc., a suitable chromatographic column is selected. For polar substances, a polar chromatographic column is selected; for non-polar or neutral substances, a neutral non-polar chromatographic column is selected. In combination with the oil product analysis requirements, the separation efficiency, pressure resistance and applicable range of the chromatographic column are considered to generate chromatographic column selection data. Based on the chromatographic column selection data, combined with the volatility characteristics of the components in the mixed oil, a suitable temperature program is set. The temperature program includes initial temperature, heating rate, final temperature, etc., with the purpose of maintaining good resolution and efficiency during the separation process. According to the standard experimental method or known experimental data, set a suitable temperature gradient, such as starting at 50°C, heating to 300°C at 10°C / min, and maintaining for a certain time. Record the specific temperature setting parameters and experimental conditions to ensure the repeatability and accuracy of the experiment. Heat the mixed oil additives through the set temperature program to make it volatilize during the gas chromatography process, which is convenient for separation and analysis. The boiling point heating process increases the temperature of the sample, causing its components to evaporate and enter the chromatographic column according to the difference in boiling points. Record data such as temperature changes during heating, sample volatility changes, and sample volatilization points. According to the properties of the mixed oil and the chromatographic column selection data, adjust the chromatographic mobile phase (gas carrier gas such as helium, nitrogen, or the composition of the liquid mobile phase). The adjustment of the mobile phase should ensure that the sample components can be fully separated and do not interfere with the detection of other components. Optimize the effect of the mobile phase by adjusting parameters such as flow rate, gas pressure and temperature. Record the specific parameters of the adjustment, such as carrier gas flow rate, pressure, and mobile phase ratio. Separate the mixed oil by gas chromatography through the set mobile phase and temperature program. Different components are assigned to different retention times in the chromatographic column according to their molecular weight, polarity and other characteristics, thereby achieving separation. The data in the separation process is collected by a chromatographic instrument (such as GC-MS), and the chromatographic peaks of different components are recorded, and their retention time, peak area, molecular characteristics, etc. are analyzed. The separation peak, retention time, peak concentration and other data of each component are recorded as the basis for subsequent analysis. Remove redundant data, outliers or instrument noise. Common methods include using data filters and statistical analysis methods to eliminate erroneous data. Ensure that each chromatographic peak represents a real chemical component and remove non-real signals. Use denoising techniques such as wavelet transform and Fourier transform to eliminate background noise and improve the signal-to-noise ratio of the data. Improve the availability of data and ensure the accuracy of chromatographic analysis.If missing values ​​appear during data collection, they can be supplemented by interpolation methods (such as linear interpolation, KNN filling, etc.) to ensure the integrity of the data and generate complete standard mixed oil gas chromatography separation data. Use Z-Score standardization or Min-Max standardization to normalize the data to ensure that the data between different components can be compared. The processed data can be used for subsequent analysis and reporting to ensure that the concentration, retention time and other information of each component meet the standardization requirements.

[0039] Preferably, using the chromatographic column temperature program setting data to perform boiling point heating on the mixed lubricating oil additive data comprises: Using the chromatographic column temperature program setting data to collect sample separation data of the mixed lubricating oil additive data, to obtain initial chromatographic data, wherein the initial chromatographic data includes retention time and basic peak information data; The basic peak information data and the chromatographic column temperature program setting data are subjected to temperature program linear mapping according to the retention time to generate temperature program linear mapping data; wherein the temperature program linear mapping formula is as follows: In the formula, Linearly map data for the temperature program, is the initial temperature, Expressed as the heating rate, It is expressed as the residence time; Based on the preset chromatographic column calibration data, the boiling point interpolation estimation is performed on the temperature program linear mapping data to obtain the component boiling point data; the initial chromatographic data is used to calculate the mixed oil heating behavior using the component boiling point data through the cumulative weighted method to generate the mixed oil boiling point heating data; the formula of the cumulative weighted method is as follows: In the formula, The boiling point heating data of the mixed oil is Expressed as The mass percentage of each component, Expressed as The boiling points of the components, Expressed as the number of components.

[0040] In an embodiment of the present invention, a sample is taken from the mixed oil to ensure the uniformity and representativeness of the sample and prepare for gas chromatography analysis. According to the chromatographic column temperature program setting data, the mixed oil sample is introduced into the chromatograph for gas chromatography separation. This process heats the sample to different temperatures through the set temperature program and analyzes the components therein. The preliminary separation results are collected by the chromatograph to obtain initial chromatographic data, including the retention time and basic peak information of each component. The retention time is the retention time of each component in the chromatographic column, which reflects the volatility and relative molecular size of the component. The basic peak information includes the height of the peak (concentration information) and the shape of the peak (separation efficiency). Using the retention time and temperature program setting data, the initial chromatographic data is linearly mapped to the temperature program. Through this mapping, the temperature values ​​corresponding to different retention times can be calculated, and then the boiling point of the component can be deduced. Temperature program linear mapping formula: In the formula, Linearly map data for the temperature program, is the initial temperature, Expressed as the heating rate, Expressed as retention time. Based on the retention time of each component , combined with the heating rate and initial temperature , use a linear formula to calculate the temperature change of each component during the gas chromatography process, and generate temperature program linear mapping data. Use preset chromatographic column calibration data, which includes the behavior of known components at different temperatures. Calibration data is usually provided by laboratories or equipment manufacturers. Calibration data can provide a reference for the relationship between temperature and boiling point, and help estimate the boiling point of each component in the mixed oil. Based on the temperature program linear mapping data, combined with the calibration data of the chromatographic column, the boiling point data of each component in the mixed oil is estimated through interpolation methods (such as linear interpolation or polynomial interpolation). The cumulative weighted method is used to integrate the boiling point data of each component, and the weighted sum of the mass percentage of the components is used to obtain the boiling point heating behavior of the mixed oil as a whole. Cumulative weighted method formula: In the formula, The boiling point heating data of the mixed oil is Expressed as The mass percentage of each component, Expressed as The boiling points of the components, For each component in the mixed oil, according to its boiling point data and mass percentage , using the cumulative weighted method to calculate the total boiling point heating behavior data The result obtained by cumulative weighting method It reflects the overall boiling point change of the mixed oil during the heating process and can provide key data for the heating behavior of the lubricant. The boiling point heating data can be used for further lubricant optimization to ensure heating efficiency and stability in actual use. The data can also be used to adjust the formulation of lubricant additives to improve the performance of the lubricant and extend its service life.

[0041] Preferably, performing mobile phase adjustment on the chromatographic column selection data according to the mixed oil boiling point heating data comprises: Perform boiling point distribution characteristic analysis on key components of mixed oil boiling point heating data to generate boiling point distribution characteristic data of key components; perform chromatographic column performance matching analysis on chromatographic column selection data based on boiling point distribution characteristic data of key components to generate chromatographic column performance matching data; The preliminary mobile phase parameters are set through the chromatographic column performance matching data to generate preliminary mobile phase setting data, wherein the preliminary mobile phase parameter setting includes the mobile phase type setting and the initial flow rate range setting; the preliminary mobile phase setting data is dynamically adjusted using the boiling point distribution characteristic data of the key components to generate chromatographic column mobile phase adjustment data.

[0042] In the embodiment of the present invention, by using the mixed oil boiling point heating data obtained from the previous step, the data reflects the boiling point changes of each component of the mixed oil. Determine the key components in the mixed oil, which are usually components with lower or higher boiling points, and have a greater impact on the separation process. Perform statistical analysis on the boiling point data of each key component and analyze its distribution characteristics. Focus on its boiling point range, peak position and distribution morphology, determine whether there are obvious boiling point groups or extreme values, and generate key component boiling point distribution characteristic data, which include: boiling point range of key components, distribution characteristics of boiling points (for example: single peak or multi-peak), boiling point mean and standard deviation of each component. According to the boiling point distribution characteristic data of key components, select a suitable chromatographic column type. Common chromatographic columns include polar and non-polar columns, which are matched according to the polarity, volatility and other characteristics of the components. Analyze the selectivity, separation efficiency and temperature range of the chromatographic column to ensure that the target component can be effectively separated. According to the boiling point distribution of the mixed oil, the selection of the chromatographic column is optimized using the chromatographic column performance data. For example, a polar column is selected for the separation of polar components, and a non-polar column is selected for the separation of relatively non-polar components. The column performance matching data is generated, which includes the adaptability analysis results of different types of columns to help select the most suitable column for the mixed oil. Select the appropriate mobile phase type (for example, polar or non-polar solvent) according to the solubility and separation requirements of the target component. Set the appropriate mobile phase type according to the selectivity and performance of the column. For example, a polar solvent is selected to match a polar column, or a non-polar solvent is selected to match a non-polar column. Set the initial flow rate range according to the characteristics of the column and the viscosity of the mobile phase. The flow rate setting will affect the separation efficiency and analysis time of the components. Too fast a flow rate will result in incomplete separation, and too slow a flow rate will increase the analysis time. Set the initial flow rate range according to the standard operating procedures of the column and the results of previous experiments. For example, the flow rate range is set to 1-2 mL / min to adapt to the optimal separation conditions of the mixed oil components, and the preliminary mobile phase setting data is generated: including the type, proportion and initial flow rate range of the mobile phase, etc. These preliminary parameters will serve as the basis for mobile phase adjustment. According to the boiling point distribution characteristic data of the key components, the preliminary mobile phase setting data is adjusted. Components with higher boiling points require lower flow rates or higher temperatures for separation, and vice versa. During the experiment, the concentration, proportion or flow rate of the mobile phase is dynamically adjusted by monitoring the separation effect and retention time of the components. The flow rate is adjusted according to the separation effect of the key components. Generally, the flow rate of components with lower boiling points is set higher, while the flow rate of components with higher boiling points is set lower. For polar chromatographic columns, the proportion of polar solvents needs to be increased to speed up the outflow of polar components; while for non-polar chromatographic columns, the proportion of polar solvents needs to be reduced, and a more non-polar solvent is used for separation.Finally, after dynamic adjustment, a set of optimized chromatographic column mobile phase adjustment data is generated, including the adjusted mobile phase type, solvent ratio, flow rate and other data. These adjustment parameters can more accurately control the separation effect and improve the separation efficiency.

[0043] As an example of the present invention, refer to Figure 3 As shown, in this example, step S3 includes: Step S31: Performing mass spectrometry scanning on the gas chromatography separation data of the standard mixed oil through the GC-MS system to generate a mass spectrum signal of the mixed oil component; performing mass spectrum conversion on the mass spectrum signal of the mixed oil component to generate a mass spectrum of the mixed oil component; Step S32: performing ion peak feature extraction on the mass spectrum of the mixed oil component to obtain ion peak feature data of the mixed oil component, wherein the ion peak feature extraction includes molecular ion peak feature extraction and fragment ion peak feature extraction; performing lubricant oil additive type analysis on the standard mixed oil gas chromatography separation data through the ion peak feature data of the mixed oil component to generate lubricant oil additive type data; Step S33: Calibrate the parameter standard curve based on the preset standard lubricant additive to generate the standard lubricant additive calibration curve; perform quantitative analysis on the additive component content of the lubricant additive type data according to the standard lubricant additive calibration curve to generate the mixed oil additive component content data.

[0044] In an embodiment of the present invention, a standard mixed oil sample is separated by using GC (gas chromatography) to obtain gas chromatography separation data of the standard mixed oil. The chromatographic data contains the retention time and peak area information of each component. A GC-MS (gas chromatography-mass spectrometry system) is used to perform mass spectrometry scanning on the separated mixed oil sample. During the mass spectrometry scanning process, each separated component will be ionized and generate an ion signal. The GC-MS system records the mass spectrometry information of each component based on the molecular weight and fragment ion characteristics. The mass spectrometry signal is obtained from the GC-MS system to generate a mass spectrometry signal of the mixed oil component. The signal provides the mass and intensity information of each component as the basic data for subsequent analysis. The obtained mass spectrometry signal is converted to generate a standard mixed oil component mass spectrum. The mass spectrum contains the ion intensity (y-axis) and mass-to-charge ratio (m / z, x-axis) information of each component, showing the ion characteristics of each component. The ion peak characteristics are extracted from the generated mixed oil component mass spectrum, and the ion peaks represent the ionization characteristics of different components in the sample. The extraction of ion peaks can be divided into two categories: molecular ion peaks represent the parent ions of the components, which usually correspond to the maximum intensity peaks in the mass spectrum and reflect the mass of the original compound. Fragment ion peaks represent the fragment ions after the molecular ion is broken down, which are usually used to determine the structural characteristics of the molecule. According to the intensity, mass-to-charge ratio (m / z value) and corresponding retention time of the ion peaks, the ion peak characteristic data of the mixed oil components are generated, which help to identify the chemical properties and structural characteristics of each component. Using the ion peak characteristic data of the mixed oil components, the type of lubricant additives is analyzed by comparing the characteristic information of known additives. The types of different additives are determined using mass spectrometry databases, standard mass spectra or data from existing literature. Qualitative analysis of lubricant additives is performed based on ion peak characteristics to generate lubricant additive type data. This data contains the presence and type of each additive in the sample. According to known standard lubricant additives (for example, certain antioxidants, preservatives or friction modifiers), standard solutions with a certain concentration range are selected for calibration. For each standard lubricant additive, a GC-MS system is used for quantitative analysis, and the mass spectrometry signal intensity of each additive at different concentrations is recorded. A standard curve is drawn based on the concentration of standard lubricating oil additives and the corresponding mass spectrometry signal intensity data. The horizontal axis of the standard curve is the concentration of the additive, and the vertical axis is the intensity of the mass spectrometry signal. Through the standard curve, a quantitative relationship between the concentration of the additive and the intensity of the mass spectrometry signal can be established. Using the standard lubricating oil additive calibration curve, the lubricating oil additive type data in the mixed oil sample is compared with the corresponding mass spectrometry signal intensity. According to the standard curve, the content of the mixed oil additive is quantitatively analyzed to obtain the specific content of each additive, and the mixed oil additive component content data is generated, which includes the concentration or mass fraction of each additive in the sample.

[0045] Preferably, extracting ion peak features from the mass spectrum of the mixed oil components includes: The mass-to-charge ratio of the ion peak is calculated for the mass spectrum of the mixed oil component to obtain the ion peak mass-to-charge ratio; based on the molecular ion peak screening rule, the candidate peaks of the mass spectrum of the mixed oil component are screened by the molecular ion peak mass-to-charge ratio to generate the molecular ion peak screening data of the mixed oil component; wherein the molecular ion peak screening rule is as follows: in, Expressed as the molecular peak intensity, It is expressed as the minimum range of mass-to-charge ratio of the molecular ion peak, Expressed as the maximum range of the mass-to-charge ratio of the molecular ion peak, Expressed as mass spectrum intensity, It is expressed as the response intensity of the relative abundance of the ion signal to the mass-to-charge ratio signal. Expressed as the mass of the ion, It is expressed as the charge number of the ion; Perform isotope peak comparison on the molecular ion peak screening data of the mixed oil components to generate molecular ion peak verification data; perform molecular ion peak shape feature extraction on the mass spectrum of the mixed oil components through the molecular ion peak verification data to obtain molecular ion peak feature extraction data; Based on the fragment ion peak screening rules, the candidate peaks of the mass spectrum of the mixed oil components are screened by the mass-to-charge ratio of the molecular ion peak to generate the fragment ion peak screening data of the mixed oil components; the fragment ion peak screening rules are as follows: in, Expressed as ion peak intensity, Expressed as the molecular peak intensity, is represented as the intensity threshold, Expressed as mass spectrum intensity, It is expressed as the response intensity of the relative abundance of the ion signal to the mass-to-charge ratio signal. Expressed as the mass of the ion, It is expressed as the charge number of the ion; The fragment ion peak feature extraction is performed on the fragment ion peak screening data of the mixed oil components to obtain the fragment ion peak feature extraction data; the molecular ion peak feature extraction data and the fragment ion peak feature extraction data are integrated to generate the mixed oil component ion peak feature data.

[0046] In the embodiment of the present invention, the mass-to-charge ratio (m / z) of each ion peak is calculated based on the mass (m) and charge number (z) of each ion peak recorded in the mass spectrum. The mass-to-charge ratio is a basic parameter used to identify ions in mass spectrometry analysis, and the calculation formula is as follows: mass-to-charge ratio = Through this calculation, the mass-to-charge ratio of each ion peak is obtained. According to the molecular ion peak screening rules, the mass spectrum of the mixed oil components is screened for candidate peaks. The molecular ion peak screening rules are based on the mass-to-charge ratio range. ,in is the minimum value of the mass-to-charge ratio of the molecular ion peak, The maximum value is set, and the peaks that meet the mass-to-charge ratio conditions are screened to generate the molecular ion peak screening data of the mixed oil components. The molecular ion peak screening data of the mixed oil components are compared with isotope peaks. This step is used to confirm whether there are isotope peaks, which usually present similar mass-to-charge ratios but have different intensities and slight mass differences. The isotope peaks are calibrated according to their mass-to-charge ratios and relative intensities to verify whether the screened molecular ion peaks meet the expected isotope pattern. According to the results of the isotope peak comparison, the peak shape characteristics and mass-to-charge ratio of each molecular ion peak are verified to generate molecular ion peak verification data, which are helpful to further confirm the accuracy of the molecular ion peak. Based on the molecular ion peak verification data, the peak shape of the molecular ion peak is feature extracted. Common peak shape features include peak width, peak height, peak area, and peak symmetry. The extracted peak shape features can provide key information for subsequent component identification and quantitative analysis. The extracted peak shape features are sorted into molecular ion peak feature extraction data, which is used to describe the detailed physical properties of each molecular ion peak. Based on the mass-to-charge ratio of the molecular ion peak, the mass spectrum of the mixed oil components is screened for fragment ion peaks. The screening rules are: Through this screening rule, all fragment ion peaks with intensities greater than the threshold and mass-to-charge ratios lower than the molecular ion peak are selected. The fragment ion peak screening data of mixed oil components are generated for the screened fragment ion peaks, which contain the mass-to-charge ratio and intensity information of the fragment ion peaks. Feature extraction is performed on the fragment ion peak screening data to analyze the mass-to-charge ratio, intensity, and fragmentation pattern of the fragment ion peaks, which helps to determine the specific pattern of molecular cleavage and the structural characteristics of the fragments. The extracted fragment ion peak features are organized into fragment ion peak feature extraction data to provide detailed ion feature data for subsequent component analysis. The molecular ion peak feature extraction data and the fragment ion peak feature extraction data are integrated to form the mixed oil component ion peak feature data. This data set comprehensively displays the mass spectral characteristics of each component, including the characteristics of the molecular ion peak and the fragment ion peak.

[0047] Preferably, performing a quantitative analysis of the additive component content on the lubricant additive type data according to the standard lubricant additive calibration curve comprises: Verify the effective range of the standard lubricant additive calibration curve to generate the effective range data of the calibration curve; extract regression model parameters from the effective range data of the calibration curve to generate the calibration curve model parameter data; Performing concentration regression calculation on the sample additive type peak information data to generate sample additive concentration data; performing internal standard correction on the sample additive concentration data to generate corrected sample additive concentration data; performing concentration ratio calculation on the corrected sample additive concentration data to generate sample additive relative ratio data; Based on the calibration curve model parameter data, the relative proportion data of the sample additives are quantitatively analyzed to generate the component content data of the mixed oil additives.

[0048] In an embodiment of the present invention, the effective range of the calibration curve of the standard lubricant additive is verified. The verification process includes evaluating the applicability and accuracy of the calibration curve in practical applications to ensure that the concentration range of the calibration curve is consistent with the concentration range of the sample additive. The validity of the curve is determined by analyzing the response intensity of the calibration curve at different concentration levels. According to the verification result, the effective range data of the calibration curve is generated, and the data includes the concentration range applicable to the calibration curve. Using the effective range data of the calibration curve, the regression model parameters of the calibration curve are extracted by regression analysis (such as linear regression or nonlinear regression), and these parameters include slope, intercept and other regression coefficients, which can accurately describe the relationship between the concentration of the additive and the mass spectrometry signal, and generate calibration curve model parameter data, which includes all key parameters calculated in the regression model. Based on the extracted calibration curve model parameter data, the concentration regression calculation is performed on the peak information of the sample additive type. The process compares the mass spectrometry signal of the sample with the calibration curve model, calculates the concentration value of each additive in the sample, and generates sample additive concentration data, which includes the estimated concentration value of each additive in the sample. The sample additive concentration data is corrected by selecting an internal standard substance with a known concentration. The concentration of the internal standard substance should be similar to that of the additive to be tested, and can compensate for errors caused by instrument fluctuations, sample processing or other factors. The internal standard correction formula is used to correct the sample additive concentration data according to the response intensity of the internal standard to generate the corrected sample additive concentration data. According to the corrected sample additive concentration data, the concentration ratio of each additive in the sample is calculated. The concentration ratio reflects the relative content of each additive in the mixed oil. The relative ratio is calculated through the concentration data of all additives in the sample to generate the sample additive relative ratio data. Based on the calibration curve model parameter data and the sample additive relative ratio data, the component content of the sample additive is quantitatively analyzed. This process uses the regression model and sample concentration data, combined with the relative ratio of each component, to calculate the exact content of each additive in the mixed oil and generate the mixed oil additive component content data, which is the specific content of each additive in the mixed oil (unit: mg / L or other appropriate units).

[0049] Preferably, step S4 comprises the following steps: Step S41: analyzing the mixed oil additive component content data and extracting the additive quantitative result data; classifying the additive quantitative result data by additive function and generating classified additive component data; Step S42: Repeat the analysis and verification of the classified additive component data to generate lubricant additive quantitative analysis verification data; visualize the lubricant additive quantitative analysis verification data to generate a lubricant additive component analysis report to perform the lubricant additive quantitative analysis operation.

[0050] In the embodiment of the present invention, the generated mixed oil additive component content data is analyzed in detail. The analysis process includes extracting the concentration, relative proportion, type and other aspects of each additive, and identifying the specific component content data of each additive. The additive quantitative result data is extracted, which includes the concentration value, mass percentage and other related quantitative data of each additive. The additive quantitative result data is functionally classified according to the functional characteristics of the additive (such as anti-wear, anti-oxidation, clean dispersion, etc.). This step analyzes the chemical properties and functional requirements of each additive, classifies it into different functional types, and generates classified additive component data, which lists the additive ingredients, content and functional effects under different functional categories in detail. The classified additive component data is repeatedly analyzed and verified to ensure the accuracy and reliability of the data. The verification process includes multiple measurements of the sample, consistency checks of the analysis results and comparisons with standard data to generate lubricant additive quantitative analysis verification data, which includes all deviations, error analysis and final confirmed data accuracy that occur during the verification process. Based on the lubricant additive quantitative analysis verification data, data visualization is performed using charts, graphs and other methods. This step helps analysts quickly identify the concentration, functional classification and verification results of each additive by converting the data into an easy-to-understand form, and generates a lubricant additive component analysis report, which visually displays the composition, functional category, quantitative data and verification analysis results of lubricant additives. The quantitative analysis of lubricant additives is performed through the generated lubricant additive component analysis report. The work includes further lubricant performance evaluation, optimized use of additives and application recommendations based on the data in the analysis report. This step ensures that the additive ingredients in the lubricant formula meet the performance requirements and provides decision support for lubricant production, quality control and research and development.

[0051] In the present specification, a system for quantitative analysis of lubricating oil additives is provided, which is used to perform the above-mentioned method for quantitative analysis of lubricating oil additives. The system for quantitative analysis of lubricating oil additives comprises: A mixing module is used to obtain base oil data and lubricant additive data; perform mixed oil processing based on the base oil data and the lubricant additive data to generate mixed lubricant additive data; perform mixed oil concentration detection on the mixed lubricant additive data to generate mixed oil concentration detection data; The chromatographic separation module is used to select a chromatographic column for the mixed lubricant additive data based on the mixed oil concentration detection data to generate chromatographic column selection data; perform boiling point heating on the chromatographic column selection data to obtain mixed oil boiling point heating data; perform gas chromatography separation on the chromatographic column selection data according to the mixed oil boiling point heating data to generate standard mixed oil gas chromatography separation data; The component content detection module is used to convert the standard mixed oil gas chromatography separation data into a mass spectrum to generate a mixed oil component mass spectrum; to analyze the types of lubricating oil additives on the mixed oil component mass spectrum to generate lubricating oil additive type data; to perform additive component content quantitative analysis on the lubricating oil additive type data to generate mixed oil additive component content data; The analysis module is used to analyze the results of the mixed oil additive component content data to generate classified additive component data; to visualize the classified additive component data, thereby generating a lubricant additive component analysis report to perform lubricant additive quantitative analysis operations.

[0052] The beneficial effect of the present invention is that the process covers the complete life cycle of lubricant analysis from the acquisition of base oil data and lubricant additive data to the generation of the final lubricant additive component analysis report, ensuring the systematicness of data processing and the consistency of results. Each step is closely linked, effectively avoiding the problem of step dispersion and data fragmentation in traditional analysis, and improving the analysis efficiency and consistency of results. Through the mixed oil processing and concentration detection in step S1, high-precision initial data is provided for subsequent chromatographic column selection and boiling point heating. The application of mass spectrum conversion and ion peak extraction (step S3) makes the identification of lubricant additive types and quantitative analysis of content more accurate, providing a reliable basis for functional evaluation and formulation optimization of lubricants. Based on the concentration detection and boiling point characteristics of the mixed oil (step S2), chromatographic column selection and heating parameter setting are performed to ensure the resolution and stability of gas chromatography separation and reduce the trial and error cost of the experiment. The standard gas chromatography separation data provided lays a solid foundation for the component identification and subsequent analysis of lubricant additives. By performing quantitative analysis of the component content of lubricant additive type data, combined with internal standard correction and concentration regression calculation, high-precision additive component content data is generated (step S3), which effectively improves the accuracy of the analysis and the credibility of the results. In step S4, through data analysis and classification, complex additive component information is displayed in an intuitive visual form, lowering the threshold for data understanding. Therefore, the present invention improves the accuracy of lubricant additive quantitative analysis by optimizing data acquisition, chromatographic separation, component identification and quantitative analysis, and result analysis and visualization.

[0053] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0054] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for quantitative analysis of lubricating oil additives, characterized in that: The following steps are involved: Step S1: acquiring base oil data and lubricant additive data; performing mixed oil processing based on the base oil data and the lubricant additive data to generate mixed lubricant additive data; Performing mixed oil concentration detection on the mixed lubricating oil additive data to generate mixed oil concentration detection data; Step S2: performing chromatographic column selection on the mixed lubricant additive data based on the mixed oil concentration detection data to generate chromatographic column selection data; performing boiling point heating on the chromatographic column selection data to obtain mixed oil boiling point heating data; performing gas chromatography separation on the chromatographic column selection data according to the mixed oil boiling point heating data to generate standard mixed oil gas chromatography separation data; Step S3: converting the standard mixed oil gas chromatography separation data into a mass spectrum to generate a mixed oil component mass spectrum; performing a lubricant oil additive type analysis on the mixed oil component mass spectrum to generate lubricant oil additive type data; performing a quantitative analysis of the additive component content on the lubricant oil additive type data to generate mixed oil additive component content data; Step S4: Analyze the content data of the mixed oil additive components to generate classified additive component data; Data visualization of classified additive component data is performed to generate lubricant additive component analysis reports to perform lubricant additive quantitative analysis tasks.

2. The method for quantitative analysis of lubricating oil additives according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: acquiring base oil data and lubricant additive data; Step S12: performing base oil concentration detection on the base oil data to generate base oil concentration detection data; Step S13: pre-processing the lubricating oil additive data based on the base oil concentration detection data to generate standard lubricating oil additive data, wherein the pre-processing includes filtering and solid phase extraction; performing mixed oil processing based on the standard lubricating oil additive data and the base oil concentration detection data to generate mixed lubricating oil additive data; Step S14: performing mixed oil concentration detection on the mixed lubricating oil additive data to generate mixed oil concentration detection data.

3. The method for quantitative analysis of lubricating oil additives according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: performing chemical property analysis on the mixed lubricant additive data based on the mixed oil concentration detection data to generate mixed oil chemical property data; performing chromatographic column selection based on the mixed oil chemical property data to generate chromatographic column selection data, wherein the chromatographic column selection includes a polar chromatographic column and a neutral non-polar chromatographic column; Step S22: performing temperature program setting on the chromatographic column selection data to generate chromatographic column temperature program setting data; performing boiling point heating on the mixed lubricating oil additive data using the chromatographic column temperature program setting data to obtain mixed oil boiling point heating data; Step S23: performing mobile phase adjustment on the chromatographic column selection data according to the mixed oil boiling point heating data to generate chromatographic column mobile phase adjustment data; performing gas chromatography separation on the mixed lubricating oil additive data based on the chromatographic column mobile phase adjustment data to generate mixed oil gas chromatography separation data; Step S24: preprocessing the mixed oil and gas chromatography separation data to generate standard mixed oil and gas chromatography separation data, wherein the data preprocessing includes data cleaning, data denoising, data missing value filling and data standardization.

4. The method for quantitative analysis of lubricating oil additives according to claim 3, characterized in that: The boiling point heating of the mixed lubricant additive data using the column temperature program setting data includes: Using the chromatographic column temperature program setting data to collect sample separation data of the mixed lubricating oil additive data, to obtain initial chromatographic data, wherein the initial chromatographic data includes retention time and basic peak information data; The basic peak information data and the chromatographic column temperature program setting data are subjected to temperature program linear mapping according to the retention time to generate temperature program linear mapping data; wherein the temperature program linear mapping formula is as follows: In the formula, Linearly map data for the temperature program, is the initial temperature, Expressed as the heating rate, It is expressed as the residence time; Based on the preset chromatographic column calibration data, the boiling point interpolation estimation is performed on the temperature program linear mapping data to obtain the component boiling point data; the initial chromatographic data is used to calculate the mixed oil heating behavior using the component boiling point data through the cumulative weighted method to generate the mixed oil boiling point heating data; the formula of the cumulative weighted method is as follows: In the formula, The boiling point heating data of the mixed oil is Expressed as The mass percentage of each component, Expressed as The boiling points of the components, Expressed as the number of components.

5. The method for quantitative analysis of lubricating oil additives according to claim 3, characterized in that: The mobile phase adjustment of the chromatographic column selection data based on the mixed oil boiling point heating data includes: Perform boiling point distribution characteristic analysis on key components of mixed oil boiling point heating data to generate boiling point distribution characteristic data of key components; perform chromatographic column performance matching analysis on chromatographic column selection data based on boiling point distribution characteristic data of key components to generate chromatographic column performance matching data; The preliminary mobile phase parameters are set through the chromatographic column performance matching data to generate preliminary mobile phase setting data, wherein the preliminary mobile phase parameter setting includes the mobile phase type setting and the initial flow rate range setting; the preliminary mobile phase setting data is dynamically adjusted using the boiling point distribution characteristic data of the key components to generate chromatographic column mobile phase adjustment data.

6. The method for quantitative analysis of lubricating oil additives according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: Performing mass spectrometry scanning on the gas chromatography separation data of the standard mixed oil through the GC-MS system to generate a mass spectrum signal of the mixed oil component; performing mass spectrum conversion on the mass spectrum signal of the mixed oil component to generate a mass spectrum of the mixed oil component; Step S32: performing ion peak feature extraction on the mass spectrum of the mixed oil component to obtain ion peak feature data of the mixed oil component, wherein the ion peak feature extraction includes molecular ion peak feature extraction and fragment ion peak feature extraction; performing lubricant oil additive type analysis on the standard mixed oil gas chromatography separation data through the ion peak feature data of the mixed oil component to generate lubricant oil additive type data; Step S33: Calibrate the parameter standard curve based on the preset standard lubricant additive to generate the standard lubricant additive calibration curve; perform quantitative analysis on the additive component content of the lubricant additive type data according to the standard lubricant additive calibration curve to generate the mixed oil additive component content data.

7. The method for quantitative analysis of lubricating oil additives according to claim 6, characterized in that: The ion peak feature extraction of the mass spectrum of the mixed oil components includes: The mass-to-charge ratio of the ion peak is calculated for the mass spectrum of the mixed oil component to obtain the ion peak mass-to-charge ratio; based on the molecular ion peak screening rule, the candidate peaks of the mass spectrum of the mixed oil component are screened by the molecular ion peak mass-to-charge ratio to generate the molecular ion peak screening data of the mixed oil component; wherein the molecular ion peak screening rule is as follows: in, Expressed as the molecular peak intensity, It is expressed as the minimum range of mass-to-charge ratio of the molecular ion peak, Expressed as the maximum range of the mass-to-charge ratio of the molecular ion peak, Expressed as mass spectrum intensity, It is expressed as the response intensity of the relative abundance of the ion signal to the mass-to-charge ratio signal. Expressed as the mass of the ion, It is expressed as the charge number of the ion; Perform isotope peak comparison on the molecular ion peak screening data of the mixed oil components to generate molecular ion peak verification data; perform molecular ion peak shape feature extraction on the mass spectrum of the mixed oil components through the molecular ion peak verification data to obtain molecular ion peak feature extraction data; Based on the fragment ion peak screening rules, the candidate peaks of the mass spectrum of the mixed oil components are screened by the mass-to-charge ratio of the molecular ion peak to generate the fragment ion peak screening data of the mixed oil components; the fragment ion peak screening rules are as follows: in, Expressed as ion peak intensity, Expressed as the molecular peak intensity, is represented as the intensity threshold, Expressed as mass spectrum intensity, It is expressed as the response intensity of the relative abundance of the ion signal to the mass-to-charge ratio signal. Expressed as the mass of the ion, It is expressed as the charge number of the ion; The fragment ion peak feature extraction is performed on the fragment ion peak screening data of the mixed oil components to obtain the fragment ion peak feature extraction data; the molecular ion peak feature extraction data and the fragment ion peak feature extraction data are integrated to generate the mixed oil component ion peak feature data.

8. The method for quantitative analysis of lubricating oil additives according to claim 6, characterized in that: Quantitative analysis of the content of additive components of lubricant additive types based on the standard lubricant additive calibration curve includes: Verify the effective range of the standard lubricant additive calibration curve to generate the effective range data of the calibration curve; extract regression model parameters from the effective range data of the calibration curve to generate the calibration curve model parameter data; Performing concentration regression calculation on the sample additive type peak information data to generate sample additive concentration data; performing internal standard correction on the sample additive concentration data to generate corrected sample additive concentration data; performing concentration ratio calculation on the corrected sample additive concentration data to generate sample additive relative ratio data; Based on the calibration curve model parameter data, the relative proportion data of the sample additives are quantitatively analyzed to generate the component content data of the mixed oil additives.

9. The method for quantitative analysis of lubricating oil additives according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: analyzing the mixed oil additive component content data and extracting the additive quantitative result data; classifying the additive quantitative result data by additive function and generating classified additive component data; Step S42: Repeat the analysis and verification of the classified additive component data to generate lubricant additive quantitative analysis verification data; visualize the lubricant additive quantitative analysis verification data to generate a lubricant additive component analysis report to perform the lubricant additive quantitative analysis operation.

10. A system for quantitative analysis of lubricating oil additives, characterized in that: For executing the method for quantitative analysis of lubricating oil additives as claimed in claim 1, the system for quantitative analysis of lubricating oil additives comprises: A mixing module is used to obtain base oil data and lubricant additive data; perform mixed oil processing based on the base oil data and the lubricant additive data to generate mixed lubricant additive data; perform mixed oil concentration detection on the mixed lubricant additive data to generate mixed oil concentration detection data; The chromatographic separation module is used to select a chromatographic column for the mixed lubricant additive data based on the mixed oil concentration detection data to generate chromatographic column selection data; perform boiling point heating on the chromatographic column selection data to obtain mixed oil boiling point heating data; perform gas chromatography separation on the chromatographic column selection data according to the mixed oil boiling point heating data to generate standard mixed oil gas chromatography separation data; The component content detection module is used to convert the standard mixed oil gas chromatography separation data into a mass spectrum to generate a mixed oil component mass spectrum; to analyze the types of lubricating oil additives on the mixed oil component mass spectrum to generate lubricating oil additive type data; to perform additive component content quantitative analysis on the lubricating oil additive type data to generate mixed oil additive component content data; The analysis module is used to analyze the results of the mixed oil additive component content data to generate classified additive component data; to visualize the classified additive component data, thereby generating a lubricant additive component analysis report to perform lubricant additive quantitative analysis operations.

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