Composite analysis method and device for chromatographic peak

Abstract

The invention discloses a compound analysis method and device for chromatographic peaks, which define an optimal chromatographic peak region according to a plurality of chromatographic peak regions, corresponding detection precision weights and core parameter types corresponding to fluid to be detected, ensure the precision of the optimal chromatographic peak region and further process the optimal chromatographic peak region. Further, defining an analytic route map according to the region matching coefficient, the type of the fluid to be detected and the peak value range of the optimal chromatographic peak region; defining a plurality of analysis nodes according to the analysis route map and the to-be-detected fluid, and triggering the composite analysis of the chromatographic peak based on the plurality of analysis nodes, the corresponding analysis content, the flow state of the to-be-detected fluid and the optimal chromatographic peak area, multiple interaction is performed on the multiple analysis nodes, the corresponding analysis content, the flowing state of the to-be-detected fluid and the optimal chromatographic peak area, and the composite analysis of the chromatographic peak is triggered, so that the accurate control of the composite analysis of the chromatographic peak is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of chromatographic peaks, and in particular to a composite analysis method and device for chromatographic peaks. Background Art

[0002] With the development of science and technology, chromatographic peaks are part of chromatograms. Chromatograms are formed based on online detection of the fluid to be detected. Chromatograms contain chromatographic peaks and present them to the outside. In the existing technology, chromatographic peaks are defined based on the recognition of chromatograms, without considering the detection accuracy weight and the types of core parameters corresponding to the fluid to be detected, which affects the accuracy of the best chromatographic peak area and makes it impossible to achieve accurate control of the composite analysis of chromatographic peaks. Summary of the invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art. The present invention provides a composite analysis method and device for chromatographic peaks.

[0004] The embodiment of the present invention provides a composite analysis method of chromatographic peaks, which is applied to the composite analysis scenario of chromatographic peaks; The composite analysis method of the chromatographic peak comprises: Acquiring a chromatogram matched with the fluid to be detected; Defining multiple chromatographic peak regions based on the chromatogram matched by the fluid to be detected and the autonomous detection model; Defining a corresponding detection accuracy weight based on the fluid to be detected and the corresponding detection position; Defining an optimal chromatographic peak region according to a plurality of chromatographic peak regions, corresponding detection accuracy weights, and core parameter types corresponding to the fluid to be detected; Based on the optimal chromatographic peak region and the corresponding regional matching coefficient of the previous chromatographic peak region definition of the fluid to be detected, a parsing roadmap is defined according to the regional matching coefficient, the type of the fluid to be detected and the peak range of the optimal chromatographic peak region; According to the analysis route map and the fluid to be detected, a plurality of analysis nodes are defined, and based on the plurality of analysis nodes, the corresponding analysis contents, the flow state of the fluid to be detected and the optimal chromatographic peak area, a composite analysis of the chromatographic peak is triggered.

[0005] In an embodiment of the present invention, through the method in the embodiment of the present invention, a chromatogram matched by the fluid to be detected is collected; multiple chromatographic peak areas are defined based on the chromatogram matched by the fluid to be detected and an autonomous detection model; corresponding detection accuracy weights are defined based on the fluid to be detected and the corresponding detection positions; an optimal chromatographic peak area is defined based on multiple chromatographic peak areas, corresponding detection accuracy weights, and core parameter types corresponding to the fluid to be detected, which is compatible with the overall consideration of multiple chromatographic peak areas, corresponding detection accuracy weights, and core parameter types corresponding to the fluid to be detected, and realizes multi-dimensional control of multiple chromatographic peak areas, corresponding detection accuracy weights, and core parameter types corresponding to the fluid to be detected, thereby ensuring the accuracy of the optimal chromatographic peak area and further processing the optimal chromatographic peak area.

[0006] Furthermore, a corresponding regional matching coefficient is defined based on the best chromatographic peak area and the previous chromatographic peak area of ​​the fluid to be detected, and a parsing roadmap is defined according to the regional matching coefficient, the type of fluid to be detected and the peak range of the best chromatographic peak area; a plurality of parsing nodes are defined according to the parsing roadmap and the fluid to be detected, and a composite analysis of the chromatographic peak is triggered based on the plurality of parsing nodes, the corresponding parsing contents, the flow state of the fluid to be detected and the best chromatographic peak area, multiple interactions are performed on the plurality of parsing nodes, the corresponding parsing contents, the flow state of the fluid to be detected and the best chromatographic peak area, and the composite analysis of the chromatographic peak is triggered, thereby achieving precise control of the composite analysis of the chromatographic peak. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 Schematic diagram of the process of the composite analysis method of chromatographic peaks in an embodiment of the present invention; Figure 2 is a schematic flow chart of S11 in the composite analysis method of chromatographic peaks in an embodiment of the present invention; Figure 3 is a schematic flow chart of S12 in the composite analysis method of chromatographic peaks in an embodiment of the present invention; Figure 4 is a schematic flow chart of S13 in the composite analysis method of chromatographic peaks in an embodiment of the present invention; Figure 5 is a schematic flow chart of S14 in the composite analysis method of chromatographic peaks in an embodiment of the present invention; Figure 6 is a schematic flow chart of S15 in the composite analysis method of chromatographic peaks in an embodiment of the present invention; Figure 7 is a schematic flow chart of S16 in the composite analysis method of chromatographic peaks in an embodiment of the present invention; Figure 8 It is a schematic diagram of the structural composition of the composite analysis device of the chromatographic peak in an embodiment of the present invention. DETAILED DESCRIPTION

[0008] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0009] See also Figures 1 to 8 , a composite analysis method of chromatographic peaks, applied to composite analysis scenarios of chromatographic peaks; the composite analysis method of chromatographic peaks includes: Step S11: collecting a chromatogram matched by the fluid to be detected; Step S12: defining a plurality of chromatographic peak regions based on the chromatogram matched by the fluid to be detected and the autonomous detection model; Step S13: defining a corresponding detection accuracy weight based on the fluid to be detected and the corresponding detection position; Step S14: defining an optimal chromatographic peak region according to the multiple chromatographic peak regions, the corresponding detection accuracy weights, and the core parameter types corresponding to the fluid to be detected; Step S15: defining a corresponding regional matching coefficient based on the best chromatographic peak region and the previous chromatographic peak region of the fluid to be detected, and defining an analytical roadmap according to the regional matching coefficient, the type of the fluid to be detected and the peak range of the best chromatographic peak region; Step S16: define multiple analysis nodes according to the analysis route map and the fluid to be detected, and trigger the composite analysis of the chromatographic peak based on the multiple analysis nodes, the corresponding analysis contents, the flow state of the fluid to be detected and the optimal chromatographic peak area.

[0010] refer to Figure 2 , in step S11, a chromatogram matched by the fluid to be detected is collected; In the specific implementation process of the present invention, the specific steps may be: S111: collecting the position of the fluid to be detected; S112: determining information of the detected fluid and a flow state of the detected fluid according to the detection of the position of the detected fluid; S113: matching a corresponding detection instrument according to the information of the detection fluid, the flow state of the detection fluid, and the detection scene; S114: defining a chromatogram matched by the fluid to be detected based on the follow-up detection of the fluid to be detected by the detection instrument, and collecting the chromatogram matched by the fluid to be detected.

[0011] In an embodiment of the present application, the position of the fluid to be detected is collected and introduced, and the position of the fluid to be detected is controlled, so as to determine the information of the detection fluid and the flow state of the detection fluid based on the detection of the position of the fluid to be detected, thereby realizing the detection of the position of the fluid to be detected, ensuring the accuracy of the information of the detection fluid and the flow state of the detection fluid, and then performing subsequent processing on the information of the detection fluid and the flow state of the detection fluid.

[0012] Specifically, according to the characteristics of the fluid to be tested and the testing requirements, select appropriate positioning technology, such as GPS positioning, ultrasonic positioning, laser ranging, etc. Ensure that the selected technology can accurately and real-time obtain the location information of the fluid to be tested. Use the selected positioning technology to continuously or intermittently collect the location data of the fluid to be tested. Ensure the accuracy, completeness and timeliness of the data.

[0013] Verify the collected position data to ensure its authenticity. Use redundant data, historical data or other auxiliary information for cross-verification. Monitor the position changes of the fluid to be tested in real time to detect abnormalities or deviations from the expected path in a timely manner. Set up an early warning mechanism to automatically trigger an alarm when the position changes exceed the preset range.

[0014] According to the location of the fluid to be tested, select appropriate testing instruments and methods, such as flow meters, chemical analyzers, etc. Test key information such as the composition, concentration, temperature, and pressure of the fluid. Combine the location data and fluid information to analyze the flow speed, direction, stability, and other states of the fluid. Use fluid mechanics principles and mathematical models to quantitatively describe and predict the flow state.

[0015] Calibrate and correct the collected fluid information and flow state data to eliminate errors and interference. Use standard samples, calibration curves or mathematical models for calibration. Establish a data quality control system to ensure the accuracy, integrity and traceability of the data. Regularly calibrate and maintain the testing instruments to ensure the stability and reliability of the instruments.

[0016] Conduct in-depth analysis and mining of the detected fluid information and flow state data to discover potential patterns and trends. Use data mining algorithms and machine learning techniques to extract valuable information and knowledge. Based on the analysis results, provide decision support for fluid management, process optimization, fault prediction, etc. Adjust the detection plan, optimize the detection process, and improve detection efficiency according to actual needs.

[0017] Therefore, the corresponding detection instrument is matched according to the information of the detection fluid, the flow state of the detection fluid and the detection scene, which is compatible with the overall consideration of the information of the detection fluid, the flow state of the detection fluid and the detection scene, and realizes multi-dimensional control of the information of the detection fluid, the flow state of the detection fluid and the detection scene, thereby ensuring the accuracy of the detection instrument.

[0018] Specifically, understand in detail the key parameters of the fluid to be tested, such as the type (e.g., gas, liquid), composition, temperature, pressure, viscosity, etc. Analyze possible contamination, impurities, or chemical reactions in the fluid. Evaluate the flow velocity, direction, stability, and whether there are flow characteristics such as turbulence and laminar flow. Consider the flow of the fluid in the pipe, container, or equipment, as well as possible boundary conditions. Clarify the specific environment of the test, such as indoor laboratories, outdoor sites, industrial production lines, etc. Analyze the impact of the test scene on the test instrument, such as temperature, humidity, electromagnetic interference, etc.

[0019] According to the fluid information and flow state, select the appropriate type of testing instrument, such as flow meter, chemical analyzer, physical property tester, etc. Ensure that the instrument can accurately measure the required fluid parameters and meet the flow state requirements. Ensure that the selected instrument is compatible with the detection scenario and can adapt to environmental conditions and operating requirements. Consider the convenience of instrument installation, maintenance, calibration and data processing. Compare the performance indicators of different instruments such as accuracy, stability, repeatability, response time, etc. Select instruments with excellent performance and high reliability to ensure the accuracy of the test results.

[0020] Regularly calibrate and verify the selected instruments to ensure the accuracy and reliability of their measurement results. Use standard samples or fluids of known concentration for calibration to ensure that the instrument's measurement range, precision, and accuracy meet the requirements. Develop detailed operating specifications to clarify the instrument's use procedures, precautions, and troubleshooting methods. Train operators to ensure that they are familiar with the instrument's operating methods and performance characteristics and can use the instrument correctly and skillfully for testing. Establish a data quality control system to monitor and analyze test data in real time. Use statistical methods to process and evaluate data, promptly discover and correct abnormal data, and ensure data accuracy and reliability. Continuously improve the test plan and optimize the test process based on test results and feedback. Pay attention to the development of new technologies and new instruments, and promptly update and improve test instruments and methods to improve test efficiency and accuracy.

[0021] At the same time, based on the follow-up detection of the fluid to be detected by the detection instrument, the chromatogram matching the fluid to be detected is defined, and the chromatogram matching the fluid to be detected is collected, the follow-up detection of the fluid to be detected by the detection instrument is introduced, the follow-up detection of the fluid to be detected by the detection instrument is realized, and the accuracy of the chromatogram matching the fluid to be detected is ensured, so that the chromatogram matching the fluid to be detected is further processed, and the chromatogram matching the fluid to be detected is collected.

[0022] Specifically, according to the characteristics and analysis requirements of the fluid to be tested, select appropriate chromatographic testing instruments, such as gas chromatograph (GC), liquid chromatograph (LC) or ion chromatograph (IC). Ensure that the instrument has high precision, high sensitivity and good stability. Configure the follow-up detection mode of the detection instrument to ensure that the instrument can monitor the changes of the fluid to be tested in real time and continuously. Set appropriate detection parameters, such as column temperature, flow rate, detection wavelength, etc., to adapt to the characteristics and analysis requirements of the fluid. According to the follow-up detection results of the detection instrument, define the chromatogram that matches the fluid to be tested. The chromatogram should be able to clearly and accurately reflect the composition, concentration, distribution and other information of the fluid.

[0023] Start the detection instrument and start the follow-up detection of the fluid to be detected. Collect and record the chromatogram data in real time to ensure the integrity and accuracy of the data. During the collection process, pay close attention to the operating status and test results of the instrument, and promptly discover and deal with abnormal situations. Preprocess the collected chromatogram data, such as baseline correction, noise filtering, etc., to improve the signal-to-noise ratio and readability of the data. Use chromatographic analysis software to further analyze the processed data to identify and quantify the components in the fluid. According to the analysis results, draw graphs such as the fluid's component distribution map and concentration curve to more intuitively understand the characteristics and change trends of the fluid. Use standard samples or fluids of known concentration to verify and check the analysis results. Compare the verification results with the expected values ​​to ensure the accuracy and reliability of the analysis results. If abnormalities or deviations are found, make adjustments and optimizations in a timely manner to improve the accuracy of the analysis.

[0024] Use chromatograms to control the quality of fluids and ensure that the fluids meet the established standards and requirements. Timely discover abnormal components or contaminants in the fluids and take appropriate treatment measures. According to the analysis results of the chromatograms, optimize and improve the production process. Adjust the raw material ratio, process parameters, etc. to improve the quality and output of the product. Use chromatograms for scientific research and technological development to explore new characteristics and new applications of fluids. Provide strong technical support and theoretical basis for the development and promotion of new products.

[0025] refer to Figure 3 , in step S12, a plurality of chromatographic peak regions are defined based on the chromatogram matched by the fluid to be detected and the autonomous detection model; In the specific implementation process of the present invention, the specific steps may be: S121: Freeze the chromatogram matched by the fluid to be detected; S122: Associating the detection instrument and the fluid to be detected; S123: Correlation coefficient corresponding to the matching of the detection instrument and the fluid to be detected; S124: Associating the correlation coefficient, the information of the fluid to be detected, and the corresponding detection database, and defining an autonomous detection model according to the correlation coefficient, the information of the fluid to be detected, and the corresponding detection database; S125: multiple interactions between the chromatogram matched to the fluid to be detected and the autonomous detection model; S126: Defining multiple chromatographic peak regions based on the chromatogram matched by the fluid to be detected and multiple interactions of the autonomous detection model.

[0026] In the embodiment of the present application, the chromatogram matched by the fluid to be detected is frozen, the chromatogram matched by the fluid to be detected is introduced, and the chromatogram matched by the fluid to be detected is controlled. At the same time, the detection instrument and the fluid to be detected are associated; the matching of the detection instrument and the fluid to be detected is achieved according to the corresponding correlation coefficient based on the matching of the detection instrument and the fluid to be detected, and the accuracy of the correlation coefficient is ensured.

[0027] Specifically, the fluid to be tested is sampled and analyzed on the testing instrument to obtain its chromatogram. According to the characteristics of the fluid and the analysis requirements, the acquisition parameters of the chromatogram, such as sampling time, resolution, detection sensitivity, etc., are determined. The clarity and accuracy of the chromatogram are ensured for subsequent analysis and processing. A chromatogram database is established to store and manage the collected chromatograms. The chromatograms are quality checked and controlled to ensure that they meet the analysis standards and requirements. The chromatograms are reviewed and updated regularly to reflect the latest status and change trends of the fluid.

[0028] Select the appropriate testing instrument according to the characteristics of the fluid to be tested and the analysis requirements. Ensure that the instrument has high precision, high sensitivity and good stability to meet the analysis requirements. Calibrate and verify the testing instrument to ensure the accuracy and reliability of its measurement results. Determine the corresponding correlation coefficient based on the calibration results of the instrument and the characteristics of the fluid to be tested. The correlation coefficient is used to describe the correspondence between the instrument measurement results and the actual state of the fluid to ensure the accuracy of the analysis results. Establish a correlation coefficient database to store and manage the determined correlation coefficients. Review and update the correlation coefficient regularly to reflect the latest status of the instrument and the latest characteristics of the fluid. Perform quality control on the correlation coefficient to ensure its accuracy and reliability.

[0029] Calibrate and verify the testing instruments regularly to ensure the accuracy and stability of their measurement results. Use standard samples or fluids of known concentration to calibrate the instruments to determine the measuring range and accuracy of the instruments. Conduct in-depth analysis and evaluation of the collected chromatogram data to check the integrity and accuracy of the data. Use statistical methods to process and evaluate the data to promptly identify and correct abnormal data. Based on the analysis results and feedback, continuously optimize and improve the testing methods and processes. Pay attention to the development of new technologies and new instruments, and update and improve the testing instruments and methods in a timely manner.

[0030] Therefore, the correlation coefficient, the information of the fluid to be detected and the corresponding detection database are associated, and an autonomous detection model is defined based on the correlation coefficient, the information of the fluid to be detected and the corresponding detection database, which is compatible with the overall consideration of the correlation coefficient, the information of the fluid to be detected and the corresponding detection database, realizes multi-dimensional control of the correlation coefficient, the information of the fluid to be detected and the corresponding detection database, and ensures the accuracy of the autonomous detection model.

[0031] Specifically, the correlation coefficient, detailed information of the fluid to be tested (such as composition, concentration, physical properties, etc.), and historical data in the test database are integrated into a unified platform. Ensure the integrity, consistency, and accuracy of the data. Establish the corresponding relationship between the correlation coefficient and the fluid information according to the characteristics of the fluid and the analysis requirements. Map the correlation coefficient and fluid information to the corresponding entries in the test database to ensure the traceability and relevance of the data. Verify the integrated data to check the integrity and accuracy of the data. Use standard samples or fluids of known concentration for verification to ensure the reliability of the data.

[0032] Design an autonomous detection model based on the integrated and correlated data. The model should be able to automatically retrieve relevant historical data from the detection database and perform comparative analysis based on the input fluid information and correlation coefficient. Select appropriate algorithms and mathematical models, such as machine learning, deep learning, or statistical models, to process and analyze the data. Ensure that the algorithm can adapt to changes in fluid characteristics and analysis requirements and has the ability to self-learn and self-optimize. Use historical data from the detection database to train the autonomous detection model. Improve the accuracy and reliability of the model by continuously adjusting and optimizing model parameters.

[0033] Monitor the autonomous detection model in real time to ensure the stability and accuracy of its operating status. Promptly detect and handle anomalies and deviations in the model operation. Establish a data quality control system to monitor and analyze input data and output results in real time. Use statistical methods and quality control charts to evaluate data to ensure data accuracy and reliability. Regularly verify and optimize the autonomous detection model and test it with new fluid samples and detection data. Adjust and improve the model based on verification results and feedback to improve its accuracy and adaptability. Pay attention to the development of new technologies and methods, and update and optimize the autonomous detection model in a timely manner. Introduce new algorithms and data processing technologies to improve the performance and accuracy of the model.

[0034] Furthermore, multiple interactions are performed on the chromatogram matching the fluid to be detected and the autonomous detection model; multiple chromatographic peak regions are defined based on the multiple interactions of the chromatogram matching the fluid to be detected and the autonomous detection model, thereby achieving multiple interactions of the chromatogram matching the fluid to be detected and the autonomous detection model, and ensuring the accuracy of multiple chromatographic peak regions.

[0035] Specifically, the chromatograms that match the fluid to be tested are integrated with the data required by the autonomous detection model to ensure data integrity and consistency. Preprocess the data, such as smoothing, baseline correction, noise removal, etc., to improve data quality. Create an interactive analysis platform that can simultaneously display the chromatogram and the output results of the autonomous detection model. Allow users to interact with the chromatogram and model output through the platform, such as zooming, panning, and annotating. Establish interaction rules to clarify how users can affect the analysis results of the chromatogram and the autonomous detection model through interactive operations. Ensure that these rules can both meet the analysis needs and ensure the accuracy and reliability of the results.

[0036] Use the autonomous detection model to perform preliminary analysis on the preprocessed chromatogram to identify potential chromatographic peaks. Based on the output of the model, mark the possible chromatographic peak positions. Through the interactive platform, users can intuitively see the initially identified chromatographic peaks and allow users to make further confirmations and adjustments. Users can verify and correct the initially identified chromatographic peaks based on their professional knowledge and experience. After confirming multiple chromatographic peaks, define multiple chromatographic peak regions based on their characteristics such as position, shape, and intensity. Ensure that each region accurately reflects the characteristics of one or more chromatographic peaks. Use standard samples or fluids of known concentration to verify the defined chromatographic peak regions to ensure their accuracy and reliability. Based on the verification results, optimize and adjust the chromatographic peak regions to improve the accuracy of the analysis.

[0037] Continuously monitor the defined chromatographic peak regions to ensure that they accurately reflect the changes in the fluid to be tested. If anomalies or deviations are found, make timely adjustments and optimizations. Establish a strict data quality control system to monitor and analyze the chromatograms and output results of the autonomous detection model in real time. Use statistical methods and quality control charts to evaluate the data to ensure the accuracy and reliability of the data. Encourage users to provide feedback and iteratively optimize the autonomous detection model and chromatographic peak region definitions based on their actual needs and analysis results. Continuously update and improve analysis methods and processes to improve the accuracy and efficiency of analysis.

[0038] refer to Figure 4 , in step S13, a corresponding detection accuracy weight is defined based on the fluid to be detected and the corresponding detection position; In the specific implementation process of the present invention, the specific steps may be: S131: freeze the fluid to be tested; S132: defining corresponding detection positions based on the division of the fluid to be detected; S133: defining corresponding detection accuracy data according to the detection position and the accuracy distribution diagram of the fluid to be detected; S134: Define a corresponding detection accuracy weight based on the detection accuracy data and the fluid to be detected.

[0039] In the embodiments of the present application, the fluid to be detected is frozen, the fluid to be detected is introduced, and the fluid to be detected is controlled. At the same time, the corresponding detection positions are defined based on the division of the fluid to be detected, thereby achieving a reasonable division of the fluid to be detected and specifically limiting the detection positions.

[0040] Specifically, determine the type, source, and quantity of the fluid to be tested to ensure the representativeness and detectability of the fluid. Mark and record the fluid so that it can be accurately identified in subsequent analysis and testing. Establish a fluid control system, including regulations for storage, transportation, handling, and protection. Ensure that the storage conditions of the fluid before testing meet the analysis requirements and avoid adverse factors such as contamination, evaporation, or degradation. Regularly inspect and monitor the fluid to ensure that its state is stable and meets the test standards.

[0041] Divide the fluid into different categories or batches according to its properties, composition or use. Ensure the rationality of the division so that the overall characteristics and differences of the fluid can be accurately reflected during the detection process. Define the corresponding detection location for each divided fluid category or batch. The detection location can be a specific location in the fluid, such as upstream, midstream or downstream; or it can be a certain stage in the fluid processing process, such as pretreatment, analysis or post-processing. Ensure that the selection of the detection location can fully reflect the key characteristics and potential problems of the fluid. Specific definition of the detection location, including parameters such as location, range, quantity, etc. Use appropriate marks or labels to identify the detection location so that it can be accurately found and identified during the detection process. Ensure that the selection and definition of the detection location meet the analysis requirements and standard operating procedures (SOP).

[0042] Use appropriate testing instruments and methods to analyze fluids according to the defined testing locations and specific limitations. Ensure the accuracy and reliability of the testing process and follow standard operating procedures (SOPs) and quality control requirements. Monitor and analyze test results in real time to ensure data accuracy and reliability. If anomalies or deviations are found, make timely adjustments and optimizations to ensure the accuracy and efficiency of the analysis. Continuously improve and optimize fluid division, test location definition, and implementation processes based on test results and feedback. Update and improve analysis methods and processes to improve the accuracy and efficiency of analysis.

[0043] In summary, by fixing and controlling the fluid to be tested, defining the test location based on fluid division, and implementing and monitoring measures, we can ensure the accuracy and efficiency of fluid analysis. This will provide strong support and guarantee for scientific research, quality control and technology development.

[0044] Therefore, corresponding detection accuracy data is defined according to the detection position and the accuracy distribution map of the fluid to be detected; corresponding detection accuracy weights are defined based on the detection accuracy data and the fluid to be detected, the detection accuracy data and the fluid to be detected are introduced, and multiple interactions are performed on the detection accuracy data and the fluid to be detected. Based on the multiple interactions of the detection accuracy data and the fluid to be detected, corresponding detection accuracy weights are defined, and corresponding detection accuracy weights are introduced, thereby achieving further control of the corresponding detection accuracy weights, so as to facilitate precise control of multiple fluids to be detected.

[0045] Specifically, collect the accuracy data of the fluid to be tested at different test positions, including repeatability, reproducibility, resolution and other indicators. Use statistical charts or maps to draw the accuracy distribution map of the fluid to be tested, and intuitively show the accuracy differences of the fluid at different positions. According to the accuracy distribution map, assign one or more test accuracy data to each test position, which should be able to accurately reflect the accuracy characteristics of the fluid at that position. Ensure the accuracy and reliability of the test accuracy data, and maintain the stability of the data through regular verification and calibration.

[0046] Conduct in-depth analysis of the collected detection accuracy data to identify key factors that affect fluid accuracy, such as location, environment, equipment, methods, etc. Based on the analysis results, determine the relative importance of fluid accuracy at different detection locations. Based on the analysis results of the accuracy data, define the corresponding detection accuracy weight for the fluid at each detection location. The weight should be able to reflect the difference in fluid accuracy at different locations and the degree of impact on the overall accuracy. Ensure the rationality and scientificity of the weight, and ensure its accuracy and reliability through expert review and verification.

[0047] Introduce detection accuracy data and fluids to be detected, and perform multiple interactions during the detection process. Through real-time monitoring and data analysis, timely adjust the detection position and weight to optimize detection accuracy and efficiency. Allow users to interact with detection accuracy data and weights according to actual needs and analysis results, such as zooming, panning, and annotation. According to the results of multiple interactions, further control the detection accuracy weights. Monitor the stability and accuracy of the weights, and promptly discover and handle anomalies or deviations. Regularly verify and calibrate the detection positions and weights to ensure that they meet the analysis requirements and standard operating procedures (SOPs). Use the defined detection accuracy weights and multiple interaction mechanisms to accurately control the fluids to be detected. Develop personalized detection strategies and processes based on different fluid characteristics and needs. Improve the accuracy and efficiency of detection through continuous monitoring and optimization, and provide strong support for scientific research, quality control, and technology development.

[0048] refer to Figure 5 , S14: defining an optimal chromatographic peak region according to the multiple chromatographic peak regions, the corresponding detection accuracy weights, and the core parameter types corresponding to the fluid to be detected; In the specific implementation process of the present invention, the specific steps may be: S141: detection accuracy weight corresponding to freeze frame; S142: defining the core parameter type corresponding to the fluid to be detected based on the fluid to be detected and the corresponding usage scenario; S143: Associating multiple chromatographic peak regions, corresponding detection accuracy weights, and core parameter types corresponding to the fluid to be detected; S144: defining a first region parameter based on the multiple chromatographic peak regions and the corresponding detection accuracy weights, and defining a second region parameter based on the multiple chromatographic peak regions and the core parameter types corresponding to the fluid to be detected; S145: defining an optimal chromatographic peak region according to the first region parameter, the second region parameter and the fluid to be detected.

[0049] At this time, the corresponding detection accuracy weight is frozen and the detection accuracy weight is introduced. The importance of detection accuracy is presented through the detection accuracy weight. At the same time, the core parameter types corresponding to the fluid to be detected are defined based on the fluid to be detected and the corresponding usage scenarios, which is compatible with the overall consideration of the fluid to be detected and the corresponding usage scenarios, realizes the multi-dimensional control of the fluid to be detected and the corresponding usage scenarios, and ensures the accuracy of the core parameter types corresponding to the fluid to be detected.

[0050] Specifically, analyze the characteristics of the fluid to be tested and identify the key factors that affect the detection accuracy, such as the sensitivity, resolution, linear range, etc. of the instrument. Consider the physical and chemical properties of the fluid itself, as well as possible interference factors. According to the key factors of detection accuracy, evaluate the impact of each factor on the overall accuracy. Use quantitative indicators (such as relative error, coefficient of variation, etc.) to measure the contribution of different factors. Based on the evaluation results, assign a weight value to each key factor to reflect its relative importance in the detection accuracy. Ensure that the weight distribution is reasonable and scientific, and can truly reflect the impact of each factor on the detection accuracy.

[0051] Have an in-depth understanding of the usage scenarios of the fluid to be tested, including its application areas, process requirements, safety standards, etc. Identify the key requirements for fluid performance in the usage scenarios, which will directly affect the selection of core parameter types. Determine the types of core parameters for the fluid to be tested based on the key requirements of the usage scenarios. Core parameters may include concentration, purity, component ratio, physical properties (such as viscosity, density, etc.) and chemical properties (such as pH value, redox potential, etc.). When determining the core parameters, the inherent characteristics and usage scenarios of the fluid to be tested should be comprehensively considered to ensure that the selected parameters can fully reflect the performance of the fluid and meet the usage requirements. Ensure the accuracy and reliability of core parameters through multi-dimensional control.

[0052] Integrate the fixed detection accuracy weights and defined core parameter types to form a complete analysis framework. Ensure that the information in the framework is coordinated and complementary to support subsequent fluid analysis. In practical applications, the fluid to be tested is tested and analyzed according to the analysis framework. Use appropriate instruments and methods to ensure the accuracy and reliability of the detection process. Continuously monitor the detection process and results to promptly detect and handle anomalies or deviations. Optimize and adjust the analysis framework based on monitoring results and analysis requirements to improve the accuracy and efficiency of detection.

[0053] Therefore, multiple chromatographic peak areas, corresponding detection accuracy weights, and core parameter types corresponding to the fluid to be detected are associated; a first area parameter is defined based on the multiple chromatographic peak areas and the corresponding detection accuracy weights, and a second area parameter is defined according to the multiple chromatographic peak areas and the core parameter types corresponding to the fluid to be detected; an optimal chromatographic peak area is defined according to the first area parameter, the second area parameter, and the fluid to be detected, which is compatible with the overall consideration of multiple chromatographic peak areas, corresponding detection accuracy weights, and core parameter types corresponding to the fluid to be detected, and realizes multi-dimensional control of multiple chromatographic peak areas, corresponding detection accuracy weights, and core parameter types corresponding to the fluid to be detected, thereby ensuring the accuracy of the optimal chromatographic peak area and further processing the optimal chromatographic peak area.

[0054] Specifically, based on the chromatogram of the fluid to be tested, multiple potential chromatographic peak regions are identified and defined. According to the detection accuracy weight corresponding to each region (these weights reflect the relative importance of different regions in detection accuracy), these regions are sorted or classified. Based on multiple chromatographic peak regions and their corresponding detection accuracy weights, the first region parameters are defined. These parameters may include peak height, peak area, resolution, etc., which can reflect the performance of different regions in detection accuracy. The first region parameters should be able to comprehensively evaluate the detection accuracy of multiple chromatographic peak regions and provide a basis for subsequent analysis. According to the types of core parameters corresponding to the fluid to be tested (these parameters are key indicators for evaluating fluid quality and performance), the second region parameters are defined. These parameters may include concentration, purity, component ratio, etc. The second region parameters should be able to reflect the core characteristics of the fluid to be tested and provide a basis for determining the optimal chromatographic peak region.

[0055] Comprehensively consider the first region parameters (reflecting detection accuracy) and the second region parameters (reflecting the core characteristics of the fluid), as well as their interactions and influences. Analyze how these factors work together to select the best chromatographic peak region to ensure that the selected region can accurately reflect the core parameters of the fluid to be detected and has high detection accuracy. Based on the results of multi-dimensional considerations, select the chromatographic peak region with the highest comprehensive score or the best match as the best region. This region should be able to accurately reflect the core parameters of the fluid to be detected and have high detection accuracy and reliability.

[0056] The best chromatographic peak area is further processed and analyzed, such as integration, correction, normalization, etc. These processing steps are designed to improve the accuracy and reliability of the data and provide strong support for subsequent quality control and scientific research. The best chromatographic peak area is verified using standard samples or reference substances of known concentrations. The accuracy and reliability of the analysis are evaluated by comparing the differences between the analytical results and the standard values. Based on the verification results and analysis requirements, the analytical methods and processes are optimized and adjusted. This may include improving chromatographic conditions, adjusting data processing methods, or updating analytical models.

[0057] refer to Figure 6 , S15: defining a corresponding regional matching coefficient based on the best chromatographic peak region and the previous chromatographic peak region of the fluid to be detected, and defining an analytical roadmap according to the regional matching coefficient, the type of the fluid to be detected and the peak range of the best chromatographic peak region; In the specific implementation process of the present invention, the specific steps may be: S151: freeze the best chromatographic peak area; S152: defining a previous chromatographic peak region of the fluid to be detected based on the source of the fluid to be detected; S153: Correlate the best chromatographic peak region and the previous chromatographic peak region of the fluid to be detected; S154: defining a corresponding region matching coefficient according to the best chromatographic peak region and the previous chromatographic peak region of the fluid to be detected; S155: defining a peak range of the best chromatographic peak region based on autonomous identification of the best chromatographic peak region; S156: Correlate the regional matching coefficient, the type of the fluid to be detected, and the peak range of the best chromatographic peak region, and define an analytical roadmap based on the regional matching coefficient, the type of the fluid to be detected, and the peak range of the best chromatographic peak region.

[0058] In an embodiment of the present application, the best chromatographic peak area is frozen, the best chromatographic peak area is introduced, and the best chromatographic peak area is controlled. At the same time, based on the traceability of the fluid to be detected, the previous chromatographic peak area of ​​the fluid to be detected is defined, the traceability of the fluid to be detected is achieved, and the previous chromatographic peak area of ​​the fluid to be detected is guaranteed, so as to introduce the previous chromatographic peak area of ​​the fluid to be detected and further control the previous chromatographic peak area of ​​the fluid to be detected.

[0059] Specifically, based on the chromatogram of the fluid to be tested, the detection accuracy weight, and the type of core parameters, through multi-dimensional considerations, the chromatographic peak area with the highest comprehensive score or the best match is selected as the best area. Ensure that the selected area can accurately reflect the core parameters of the fluid to be tested and has high detection accuracy and reliability. Record the selected best chromatographic peak area, including its key features such as position, shape, and area. Use appropriate methods and techniques (such as data labeling, storage, etc.) to freeze the best area for subsequent analysis and comparison.

[0060] Review the historical records, production batches, and origin of the fluid to be tested. Collect data and reports from previous chromatographic analyses, especially information on chromatographic peak regions related to the current fluid to be tested. Based on the traceability information, identify and define previous chromatographic peak regions of the fluid to be tested. These regions should be compared with the chromatogram of the current analysis to ensure consistency and traceability.

[0061] Establish control standards for the best chromatographic peak area and previous chromatographic peak area, including the allowable deviation range, data quality requirements, etc. Ensure that these standards comply with industry specifications, regulatory requirements, and internal quality control processes. Continuously monitor the best chromatographic peak area to ensure its stability, accuracy, and consistency. Regularly or irregularly evaluate the difference between the previous chromatographic peak area and the current analysis results to identify any potential changes or anomalies. Record all monitoring and evaluation results in detail, including any deviations, anomalies, or improvement measures. Prepare reports to provide stakeholders (such as quality control departments, R&D teams, etc.) with the latest information and analysis results on the best chromatographic peak area and previous chromatographic peak area. Make necessary adjustments and optimizations to control standards, analytical methods, or processes based on monitoring and evaluation results. Introduce new technologies, methods, or instruments to improve the accuracy and efficiency of analysis.

[0062] At this time, the best chromatographic peak area and the previous chromatographic peak area of ​​the fluid to be detected are associated; the corresponding regional matching coefficients are defined according to the best chromatographic peak area and the previous chromatographic peak area of ​​the fluid to be detected, which is compatible with the overall consideration of the best chromatographic peak area and the previous chromatographic peak area of ​​the fluid to be detected, realizes the multiple interactions of the best chromatographic peak area and the previous chromatographic peak area of ​​the fluid to be detected, and ensures the accuracy of the corresponding regional matching coefficients.

[0063] Specifically, obtain data for the best chromatographic peak region, including key features such as peak height, peak area, and peak position. Collect previous chromatographic peak region data for the fluid to be tested to ensure that these data are comparable and consistent with the current analysis. Align the data of the two regions to ensure that they are compared under the same chromatographic conditions. This may involve steps such as adjusting the time axis of the data, correcting baseline drift, or removing noise.

[0064] Select appropriate matching indicators based on analysis requirements and data characteristics. These indicators may include the degree of overlap of peak areas, the offset of peak positions, the similarity of peak shapes, etc. Ensure that the selected indicators can fully reflect the degree of match between the two regions in terms of key features. Based on the selected matching indicators, calculate the matching coefficient between the best chromatographic peak area and the previous chromatographic peak area. The matching coefficient can be a numerical value (such as similarity percentage, correlation coefficient, etc.) or a vector (containing the degree of match in multiple dimensions). Use appropriate mathematical methods or algorithms for calculations to ensure the accuracy and reliability of the results.

[0065] Consider the interaction between the best chromatographic peak area and the previous chromatographic peak area in multiple dimensions. Analyze the mutual influence and constraint relationship between different matching indicators to ensure the comprehensiveness and accuracy of the matching coefficient. Verify and check the calculated matching coefficient. Use known standard samples or reference materials for comparative analysis to evaluate the accuracy and reliability of the matching coefficient. According to the verification results and analysis requirements, make necessary adjustments and optimizations to the calculation method and process of the matching coefficient. Explain the similarities or differences between the best chromatographic peak area and the previous chromatographic peak area based on the size and distribution of the matching coefficient. Apply the matching coefficient to quality control, batch consistency assessment, product traceability and other fields to provide strong support for related decision-making.

[0066] Therefore, the peak range of the best chromatographic peak region is defined based on the autonomous identification of the best chromatographic peak region; the regional matching coefficient, the type of fluid to be detected and the peak range of the best chromatographic peak region are associated, and the analysis roadmap is defined based on the regional matching coefficient, the type of fluid to be detected and the peak range of the best chromatographic peak region, which is compatible with the overall consideration of the regional matching coefficient, the type of fluid to be detected and the peak range of the best chromatographic peak region, realizes the multiple interactions of the regional matching coefficient, the type of fluid to be detected and the peak range of the best chromatographic peak region, ensures the accuracy of the analysis roadmap, facilitates analysis control along the analysis roadmap, and performs composite analysis on the best chromatographic peak region, thereby realizing multi-dimensional analysis.

[0067] Specifically, advanced algorithms or software tools are used to automatically identify the best chromatographic peak region in the chromatogram. This may involve comprehensive consideration of multiple features such as peak height, peak area, and peak shape. Based on the results of autonomous identification, the start and end positions of the best chromatographic peak region are determined. A reasonable peak range is set that can accurately cover the main peak shape features while avoiding excessive noise interference.

[0068] Based on the previously defined matching indicators and methods, calculate the matching coefficient between the best chromatographic peak region and the previous chromatographic peak region of the fluid to be tested. Identify the type of fluid to be tested and understand its chemical and physical properties. These properties may affect the chromatographic separation effect and peak shape characteristics, so they should be considered during the analysis process. Comprehensively correlate the regional matching coefficient, the type of fluid to be tested, and the peak range of the best chromatographic peak region. Analyze the interaction and constraint relationship between these factors to lay the foundation for defining the analysis roadmap.

[0069] Define a clear analytical roadmap based on the combined factors. The roadmap should clearly define the order of the analytical steps, the required data and methods, and the expected results. Ensure that the analytical roadmap is compatible and considers multiple dimensions such as the region matching coefficient, the type of fluid to be detected, and the peak range of the optimal chromatographic peak region. Through appropriate algorithms or tools, multiple interactions and synergies between these dimensions can be achieved.

[0070] Strictly follow the analytical roadmap to perform each analytical step. Monitor and evaluate the results of each step to ensure that they meet the expected accuracy and quality requirements. Based on the preliminary analysis, conduct a more in-depth composite analysis of the best chromatographic peak area. This may involve further subdivision of peak shape features, identification of unknown components, and quantitative analysis. Verify the analytical results using standard samples or reference materials of known concentrations. Make necessary adjustments and optimizations to the analytical methods and processes based on the verification results and analytical requirements.

[0071] refer to Figure 7 , S16: defining a plurality of analysis nodes according to the analysis route map and the fluid to be detected, and triggering a composite analysis of the chromatographic peak based on the plurality of analysis nodes, the corresponding analysis contents, the flow state of the fluid to be detected, and the optimal chromatographic peak area; In the specific implementation process of the present invention, the specific steps may be: S161: Freeze-frame analysis roadmap; S162: multiple interactions are performed on the analysis route map and the fluid to be detected; S163: defining a plurality of analysis nodes according to the analysis route map and multiple interactions of the fluid to be detected; S164: Associating a plurality of analysis nodes, corresponding analysis contents, and a portion corresponding to the best chromatographic peak region; S165: constructing a composite analysis system based on the plurality of analysis nodes, the corresponding analysis contents, and the portion corresponding to the optimal chromatographic peak region; S166: Triggering composite analysis of the chromatographic peaks according to the composite analysis system, the flow state of the fluid to be detected, and the optimal chromatographic peak region.

[0072] At this time, the analysis roadmap is frozen; multiple interactions are performed on the analysis roadmap and the fluid to be detected; multiple analysis nodes are defined based on the multiple interactions between the analysis roadmap and the fluid to be detected, thereby realizing multiple interactions between the analysis roadmap and the fluid to be detected and ensuring the rationality and accuracy of multiple analysis nodes.

[0073] Specifically, a preliminary analytical roadmap is designed based on the goals of the chromatographic analysis and the characteristics of the fluid to be tested. The roadmap should cover all key steps from sample pretreatment to final data analysis. Consider the impact of possible interference factors, system errors and sample characteristics on the analysis results, and refine and optimize the initial design. Make sure that each step in the roadmap is clear, specific and executable.

[0074] In-depth analysis of the chemical composition, physical state and possible interfering substances of the fluid to be tested. This information is crucial for determining the analytical steps and selecting appropriate chromatographic conditions. Dynamically adjust the analytical roadmap based on the characteristics of the fluid to be tested. For example, if the fluid contains multiple volatile components, additional pretreatment steps may be required to remove interfering substances. Establish a feedback mechanism that allows the roadmap to be fine-tuned based on real-time data during the analytical process. This ensures continuous interaction and adaptability between the roadmap and the fluid to be tested.

[0075] Based on the analytical roadmap and the multiple interaction results of the fluid to be tested, identify the key analytical steps. These steps usually include sample pretreatment, chromatographic separation, detector response, and data acquisition. Set an analytical node at each key step. Each node should have a clear analytical goal and expected results. Ensure that there is logical coherence and dependency between analytical nodes. For example, the output of the previous node should be used as the input of the next node.

[0076] During the analysis process, the execution and data quality of each node are continuously monitored. Based on the real-time feedback, necessary adjustments are made to the roadmap or analysis nodes. The analysis results are verified using standard samples of known concentration. The chromatography system is regularly calibrated to ensure the accuracy and reliability of the analysis. A comprehensive evaluation of the analysis results is performed to identify any potential sources of deviation or error. Based on the evaluation results, the analysis roadmap or analysis nodes are further optimized.

[0077] Therefore, multiple analysis nodes, corresponding analysis contents and the part corresponding to the best chromatographic peak area are associated; a composite analysis system is constructed based on the multiple analysis nodes, corresponding analysis contents and the part corresponding to the best chromatographic peak area; composite analysis of chromatographic peaks is triggered according to the composite analysis system, the flow state of the fluid to be detected and the best chromatographic peak area, multiple analysis nodes, corresponding analysis contents, the flow state of the fluid to be detected and the best chromatographic peak area are multiple interacted, and composite analysis of chromatographic peaks is triggered, thereby realizing precise control of composite analysis of chromatographic peaks.

[0078] Specifically, determine the key analytical nodes according to the goal of chromatographic analysis and the characteristics of the fluid to be tested. Each node should correspond to a specific analytical task, such as sample pretreatment, optimization of chromatographic separation conditions, data acquisition and processing, etc. For each analytical node, clarify the specific content that needs to be analyzed, such as peak shape characteristics, retention time, peak area, etc. Ensure that the analytical content matches the chemical composition and physical state of the fluid to be tested. Determine the optimal chromatographic peak area based on historical data and experimental conditions. Associate the area with the analytical node and analytical content to ensure that this area can be focused on during the composite analysis process.

[0079] Design a structured composite analytical system that can integrate multiple analytical nodes, corresponding analytical content, and information about the best chromatographic peak region. Ensure that the various parts of the system can coordinate and support each other. Define the flow path and interaction mechanism of data in the composite analytical system. Ensure that data can be smoothly transmitted between various analytical nodes, while supporting real-time feedback and adjustment. Integrate advanced algorithms and tools to support tasks such as data processing, peak identification, and quantitative analysis during the composite analytical process. Ensure that these algorithms and tools are compatible with the composite analytical system and can provide accurate and reliable analysis results.

[0080] Monitor the flow state of the fluid to be tested in real time, including key parameters such as flow rate, pressure, and temperature. Ensure that the fluid state is stable to avoid affecting the shape and position of the chromatographic peak. Identify the best chromatographic peak area in the chromatogram to ensure that the peak shape in this area is clear and free of interference. According to the identification results, adjust the chromatographic conditions to optimize the peak separation effect. When the fluid to be tested flows to the best chromatographic peak area, trigger the composite analysis process. Use the algorithms and tools in the composite analysis system to perform synchronous or sequential analysis on multiple analysis nodes.

[0081] During the composite analysis process, data is collected and analyzed in real time, and necessary adjustments are made to the analysis nodes and analysis contents based on the feedback results. Ensure that the analysis process is always consistent with the actual conditions of the fluid to be tested. Use standard samples of known concentrations to verify and calibrate the composite analysis results. Ensure the accuracy and reliability of the analysis results. Conduct a comprehensive evaluation of the composite analysis results to identify potential problems and room for improvement. Based on the evaluation results, optimize and improve the composite analysis system to improve the accuracy and efficiency of the analysis.

[0082] See also Figure 8 , Figure 8 It is a schematic diagram of the structural composition of the composite analysis device of the chromatographic peak in an embodiment of the present invention.

[0083] like Figure 8 As shown, a composite analysis device for chromatographic peaks, the composite analysis device for chromatographic peaks comprises: The acquisition module 21 is used to acquire the chromatogram matched by the fluid to be detected; A chromatographic peak region module 22, used to define a plurality of chromatographic peak regions based on the chromatogram matched by the fluid to be detected and the autonomous detection model; A detection accuracy weight module 23, used to define a corresponding detection accuracy weight based on the fluid to be detected and the corresponding detection position; The optimal chromatographic peak region module 24 is used to define the optimal chromatographic peak region according to the multiple chromatographic peak regions, the corresponding detection accuracy weights and the core parameter types corresponding to the fluid to be detected; The analytical route map module 25 is used to define a corresponding regional matching coefficient based on the best chromatographic peak region and the previous chromatographic peak region of the fluid to be detected, and define an analytical route map according to the regional matching coefficient, the type of the fluid to be detected and the peak range of the best chromatographic peak region; The composite analysis module 26 is used to define multiple analysis nodes according to the analysis route map and the fluid to be detected, and trigger the composite analysis of the chromatographic peak based on the multiple analysis nodes, the corresponding analysis contents, the flow state of the fluid to be detected and the optimal chromatographic peak area.

[0084] The above is a detailed introduction to the composite analysis method and device for chromatographic peaks provided in the embodiments of the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. For those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A composite analysis method for chromatographic peaks, characterized in that: Applied to composite analysis scenarios of chromatographic peaks; The composite analysis method of the chromatographic peak comprises: Acquiring a chromatogram matched with the fluid to be detected; Defining multiple chromatographic peak regions based on the chromatogram matched by the fluid to be detected and the autonomous detection model; Defining a corresponding detection accuracy weight based on the fluid to be detected and the corresponding detection position; Defining an optimal chromatographic peak region according to a plurality of chromatographic peak regions, corresponding detection accuracy weights, and core parameter types corresponding to the fluid to be detected; Based on the optimal chromatographic peak region and the corresponding regional matching coefficient of the previous chromatographic peak region definition of the fluid to be detected, a parsing roadmap is defined according to the regional matching coefficient, the type of the fluid to be detected and the peak range of the optimal chromatographic peak region; According to the analysis route map and the fluid to be detected, a plurality of analysis nodes are defined, and based on the plurality of analysis nodes, the corresponding analysis contents, the flow state of the fluid to be detected and the optimal chromatographic peak area, a composite analysis of the chromatographic peak is triggered.

2. The composite analysis method of chromatographic peaks according to claim 1, characterized in that: The step of acquiring a chromatogram matched with the fluid to be detected comprises: Collect the location of the fluid to be tested; Determine the information of the detected fluid and the flow state of the detected fluid according to the detection of the position of the detected fluid; Matching corresponding detection instruments according to the information of the detection fluid, the flow state of the detection fluid and the detection scene; Based on the follow-up detection of the fluid to be detected by the detection instrument, a chromatogram matched by the fluid to be detected is defined, and the chromatogram matched by the fluid to be detected is collected.

3. The composite analysis method of chromatographic peaks according to claim 2, characterized in that: The method of defining a plurality of chromatographic peak regions based on the chromatogram matched by the fluid to be detected and the autonomous detection model includes: Freeze the chromatogram matched by the fluid to be tested; Associated testing instruments and fluids to be tested; Correlation coefficient corresponding to the matching of the testing instrument and the fluid to be tested; Associating the correlation coefficient, information about the fluid to be detected, and a corresponding detection database, and defining an autonomous detection model according to the correlation coefficient, information about the fluid to be detected, and the corresponding detection database; Multiple interactions between the chromatogram matched to the fluid to be detected and the autonomous detection model; Multiple chromatographic peak regions are defined based on the chromatogram matched by the fluid to be detected and multiple interactions of the autonomous detection model.

4. The composite analysis method of chromatographic peaks according to claim 3, characterized in that: The method of defining a corresponding detection accuracy weight based on the fluid to be detected and the corresponding detection position includes: Freeze the fluid to be tested; Defining corresponding detection positions based on the division of the fluid to be detected; Defining corresponding detection accuracy data according to the detection position and the accuracy distribution diagram of the fluid to be detected; Based on the detection accuracy data, the corresponding detection accuracy weight is defined for the fluid to be detected.

5. The composite analysis method of chromatographic peaks according to claim 4, characterized in that: The method of defining the optimal chromatographic peak region according to the plurality of chromatographic peak regions, the corresponding detection accuracy weights and the core parameter types corresponding to the fluid to be detected includes: The detection accuracy weight corresponding to the freeze frame; Define the core parameter types corresponding to the fluid to be detected based on the fluid to be detected and the corresponding usage scenarios; Associating multiple chromatographic peak regions, corresponding detection accuracy weights, and core parameter types corresponding to the fluid to be detected; A first region parameter is defined based on a plurality of chromatographic peak regions and corresponding detection accuracy weights, and a second region parameter is defined based on a plurality of chromatographic peak regions and core parameter types corresponding to the fluid to be detected; The optimal chromatographic peak region is defined according to the first region parameter, the second region parameter and the fluid to be detected.

6. The composite analysis method of chromatographic peaks according to claim 5, characterized in that: The method defines a corresponding regional matching coefficient based on the optimal chromatographic peak region and the previous chromatographic peak region of the fluid to be detected, and defines an analytical roadmap according to the regional matching coefficient, the type of the fluid to be detected and the peak range of the optimal chromatographic peak region, including: Freeze the best chromatographic peak area; Defining the previous chromatographic peak region of the fluid to be detected based on the traceability of the fluid to be detected; Correlating the best chromatographic peak area with the previous chromatographic peak area of ​​the fluid to be tested; The corresponding regional matching coefficient is defined according to the best chromatographic peak region and the previous chromatographic peak region of the fluid to be detected.

7. The composite analysis method of chromatographic peaks according to claim 6, characterized in that: The method further comprises: defining a corresponding regional matching coefficient based on the optimal chromatographic peak region and the previous chromatographic peak region of the fluid to be detected, and defining an analytical roadmap according to the regional matching coefficient, the type of the fluid to be detected and the peak range of the optimal chromatographic peak region; Defining the peak range of the optimal chromatographic peak region based on autonomous identification of the optimal chromatographic peak region; The regional matching coefficient, the type of the fluid to be detected, and the peak range of the best chromatographic peak region are associated, and an analytical roadmap is defined based on the regional matching coefficient, the type of the fluid to be detected, and the peak range of the best chromatographic peak region.

8. The composite analysis method of chromatographic peaks according to claim 7, characterized in that: The method of defining a plurality of analysis nodes according to the analysis route map and the fluid to be detected, and triggering the composite analysis of the chromatographic peak based on the plurality of analysis nodes, the corresponding analysis contents, the flow state of the fluid to be detected and the optimal chromatographic peak area, includes: Freeze-frame analysis roadmap; Multiple interactions are performed on the analytical route map and the fluid to be detected; A plurality of analysis nodes are defined according to the analysis roadmap and the multiple interactions of the fluid to be detected.

9. The composite analysis method of chromatographic peaks according to claim 8, characterized in that: The method further includes: defining a plurality of analysis nodes according to the analysis route map and the fluid to be detected, triggering a composite analysis of the chromatographic peak based on the plurality of analysis nodes, the corresponding analysis contents, the flow state of the fluid to be detected and the optimal chromatographic peak area; Associating multiple analytical nodes, corresponding analytical contents, and the portion corresponding to the best chromatographic peak region; Constructing a composite analytical system based on multiple analytical nodes, corresponding analytical contents, and the portion corresponding to the optimal chromatographic peak region; The composite analysis of the chromatographic peak is triggered according to the composite analysis system, the flow state of the fluid to be detected and the optimal chromatographic peak area.

10. A composite analysis device for chromatographic peaks, characterized in that: The composite analysis device for chromatographic peaks is applied to the composite analysis method for chromatographic peaks as claimed in any one of claims 1 to 9, and the composite analysis device for chromatographic peaks comprises: An acquisition module, used for acquiring a chromatogram matched by the fluid to be detected; A chromatographic peak region module, used to define multiple chromatographic peak regions based on the chromatogram matched by the fluid to be detected and the autonomous detection model; A detection accuracy weight module, used to define a corresponding detection accuracy weight based on the fluid to be detected and the corresponding detection position; An optimal chromatographic peak region module is used to define an optimal chromatographic peak region according to multiple chromatographic peak regions, corresponding detection accuracy weights, and core parameter types corresponding to the fluid to be detected; An analytical roadmap module, for defining a corresponding regional matching coefficient based on the best chromatographic peak region and the previous chromatographic peak region of the fluid to be detected, and defining an analytical roadmap according to the regional matching coefficient, the type of the fluid to be detected and the peak range of the best chromatographic peak region; The composite analysis module is used to define multiple analysis nodes according to the analysis route map and the fluid to be detected, and trigger the composite analysis of the chromatographic peak based on the multiple analysis nodes, the corresponding analysis contents, the flow state of the fluid to be detected and the optimal chromatographic peak area.

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