Method and device for measuring chloride ion peak area based on ion chromatography

Abstract

The invention aims to provide a method and a device for determining the peak area of chloride ions based on ion chromatography. The method for determining the peak area of chloride ions based on ion chromatography comprises the following steps: step 1, identifying a chromatographic peak: peak separation, peak qualitation, baseline correction, peak trailing treatment and peak overlapping treatment; and step 2, calculating the chromatographic peak area: peak definition, integration algorithm, calibration curve application, repeatability verification, impurity peak deduction and main peak area calculation. According to the method, a chromatographic peak identification and chromatographic peak area calculation mode is designed, so that the technical problem that other impurity ions may be introduced to influence chloride ion chromatographic peak identification and accurate area calculation in an existing mode of determining organic chlorine through ion chromatography is solved.

Description

Technical Field

[0001] The present application belongs to the technical field of ion chromatography detection, and specifically relates to a method and device for measuring chloride ion peak area based on ion chromatography. Background Art

[0002] Industrial hydrochloric acid is used as a regeneration agent for cationic resins in the desalted water system and condensate purification system of nuclear power plants. Its quality will affect the purification effect of the resin bed. Due to different hydrochloric acid production processes or storage methods, hydrochloric acid contains a large amount of organic chlorine. After the cationic bed is regenerated with this hydrochloric acid, the flushing process cannot completely flush out the residual regeneration liquid. After commissioning, the hydrochloric acid chloride ions in the regeneration residual liquid are adsorbed by the mixed bed, and the organic chlorine is adsorbed by the mixed bed and then quickly desorbed, entering the condensate and feed water, and then degraded at high temperature in the steam generator, releasing chloride ions, resulting in deviation of the steam generator wastewater quality. Chloride ions exceeding the control requirements will increase the risk of stress corrosion cracking of the steam generator heat transfer tubes.

[0003] Ion chromatography (IC) is an efficient, rapid and highly automated separation and detection technology that has been widely used in the analysis of inorganic anions and cations. However, it is not common to directly use ion chromatography to determine organochlorine in hydrochloric acid, because most organochlorine compounds are not easily ionized and need to be converted into a detectable form through derivatization or other conversion methods.

[0004] A Chinese patent (application number CN202311224870.2) discloses a method for detecting organic chlorine in industrial hydrochloric acid, which includes: step 1: removing inorganic chlorine contained in an industrial hydrochloric acid sample by an electrodialysis method to obtain an industrial hydrochloric acid sample from which inorganic chlorine is removed; then using an ion chromatography detection method to detect the inorganic chlorine content of the industrial hydrochloric acid sample from which inorganic chlorine is removed, to obtain a first chloride ion content value; step 2: using an ultraviolet photolysis method to degrade the organic chlorine components in the industrial hydrochloric acid into inorganic chloride ions to obtain a degraded industrial hydrochloric acid sample; step 3: using an ion chromatography detection method to detect the inorganic chlorine content of the degraded industrial hydrochloric acid sample to obtain a second chloride ion content value; converting the difference between the second chloride ion content value and the first chloride ion content value to obtain the content of organic chlorine components in industrial hydrochloric acid. Since the determination of organic chlorine by ion chromatography requires pretreatment of an electrodialysis device and an ultraviolet photolysis device, other impurity ions may be introduced during the detection process to affect the identification of the chloride ion chromatographic peak and the correct calculation of the area. Therefore, it is urgent to develop an algorithm for determining the chloride ion peak area with good accuracy and repeatability and excellent tolerance to the chromatographic column. Summary of the invention

[0005] In view of this, the present application is committed to providing a method and device for determining the area of ​​chloride ion peaks based on ion chromatography. By designing the identification of chromatographic peaks and the calculation method of chromatographic peak areas, the technical problem that the existing method of ion chromatography for determining organic chlorine may introduce other impurity ions that affect the identification of chloride ion chromatographic peaks and the correct calculation of the area is solved.

[0006] The first aspect of the present application provides a method for determining the peak area of ​​chloride ions based on ion chromatography, the method for determining the peak area of ​​chloride ions based on ion chromatography comprising:

[0007] Step 1: Identify chromatographic peaks: peak separation, peak characterization, baseline correction, peak tailing and peak overlap. The peak separation is to ensure that the ions in the sample have sufficient separation so that each peak can be identified independently; the peak characterization is to use a known standard for comparative analysis, and to identify the peaks by retention time t R The target ions are determined by comparison; the baseline correction is performed by digital signal processing; the peak tailing processing and peak overlap processing are performed by data analysis algorithm processing.

[0008] Step 2, calculate the chromatographic peak area: peak definition, integration algorithm, calibration curve application, verification of repeatability, impurity peak subtraction and calculation of main peak area. The peak definition is to clearly set the peak front and peak back; the integration algorithm is to use the built-in integration function of the chromatographic workstation software to calculate the peak area; the calibration curve application is to convert the peak area of ​​the sample to be tested into the corresponding concentration value according to the pre-drawn standard curve; the verification of repeatability is to measure the same component multiple times and evaluate its precision and accuracy; the impurity peak subtraction is to calculate the main peak area after subtracting the impurity peak.

[0009] In a specific embodiment of the present application, in step 1, the specific steps of the baseline correction are as follows:

[0010] Define the window size: select a suitable window size that is large enough to smooth noise but not so large as to blur out valid peaks; average each continuous data segment in the window, slide the window along the time axis, and replace the original baseline data points point by point with the average value of the data points in the window;

[0011] The Savitzky-Golay filter sliding window least squares fitting was used.

[0012] In a specific embodiment of the present application, the specific steps of using Savitzky-Golay filtering sliding window least squares fitting are: first, set the parameters to determine the filter order and window size; second, locally fit, apply the least squares method to fit the smooth curve in the sliding window to obtain the smooth baseline estimate at each position in the window.

[0013] In a specific implementation of the present application, in step 1, the specific steps of the peak tailing process are as follows:

[0014] (1) Model building: Assume that the cause of tailing can be described by a certain function form; select one or more appropriate basis functions to build a hybrid model based on the actual peak shape characteristics;

[0015] (2) Data preparation: Collect chromatographic signal data containing tailing peaks and preprocess the chromatographic signal data, including removing noise and smoothing the baseline; determine the starting point and end point of each tailing peak, and intercept the target peak segment for deconvolution processing;

[0016] (3) Parameter estimation: Use numerical optimization methods to iteratively optimize the parameters of the selected basis functions; the goal is to minimize the residual sum of squares or other error measures between the model prediction signal and the actual observed signal;

[0017] (4) Deconvolution calculation: Substitute the optimal parameters into the basis function, implement the deconvolution operation by mathematical means, and obtain the approximate shape of each peak without tailing;

[0018] (5) The separated ideal peak is directly used for area integration.

[0019] In a specific implementation of the present application, the function form is a Gaussian function, and the form of the Gaussian function is as follows:

[0020]

[0021] Where: A represents the peak area, corresponding to the concentration of the component; μ refers to the center position of the peak, that is, the retention time; σ is the standard deviation, which is related to the degree of diffusion and affects the width of the peak.

[0022] In a specific implementation of the present application, the function form is a Lorentz function, and the form of the Lorentz function is as follows:

[0023]

[0024] Where: A represents the peak area, corresponding to the concentration of the component; μ refers to the center position of the peak, that is, the retention time; γ is the Lorentz half-peak width parameter, which is related to the asymmetry and tailing degree of the peak.

[0025] In a specific implementation of the present application, in step 1, the specific steps of the peak overlap processing are as follows:

[0026] (1) Model building: Select appropriate basis functions to describe the shape of individual peaks; assume that overlapping peaks are formed by the superposition of different parameterized versions of these basis functions;

[0027] (2) Data preprocessing: Preprocess the raw chromatographic signal, including removing noise and smoothing the baseline to ensure data quality; determine the number and approximate location of possible peaks based on visual observation or preliminary analysis;

[0028] (3) Parameter estimation: Using optimization algorithms such as nonlinear least squares, the actual observed mixed signal is fitted according to the selected basis functions. The parameters of the basis functions are regarded as unknowns, and a set of parameter values ​​is found through iterative optimization so that the difference between the sum of the basis functions and the actual signal is minimized.

[0029] (4) Deconvolution calculation: Use the best fitting parameters to reconstruct each independent basis function and add them together to obtain the peak shape of each component after decomposition; the separated single peaks can be further used for quantitative analysis.

[0030] In a specific embodiment of the present application, the basis function is any one or a combination of a Gaussian function and a Lorentz function.

[0031] In a specific embodiment of the present application, in step 2, the basic steps of the impurity peak subtraction are:

[0032] (1) Setting a threshold to distinguish target peaks from impurity peaks in the signal;

[0033] (2) For impurity peaks with less interference, choose to avoid the impurity peak area when integrating the target peak or automatically exclude small impurity peaks when performing peak integration calculations by setting appropriate peak width and minimum peak area parameters;

[0034] (3) When the impurity peak is significant and affects the quantification of the target peak, partial least squares regression (PLS) is used to establish a model to eliminate the impact of the impurity peak.

[0035] In a specific embodiment of the present application, the specific steps of using partial least squares regression (PLS) to establish a model to remove impurity peaks are as follows:

[0036] ① Data preparation: Collect ion chromatographic signal data containing target components and impurity peaks. Ion chromatographic signal data includes the intensity of all components in the sample at different time points or detector responses. The independent variable X is the time series data of the entire chromatographic signal; the dependent variable Y is the actual concentration of the target ion.

[0037] ② Preprocessing and impurity peak identification: First, the raw data needs to be preprocessed, including removing baseline drift and noise filtering; marking and separating the peaks of the target ions and the impurity peak areas that may interfere.

[0038] ③Construct a PLS model: Use the partial least squares regression algorithm, taking all chromatographic signals as the independent variable X, and only the actual concentration of the target ion or the known standard value as the dependent variable Y.

[0039] ④ Background subtraction: After the PLS model training is completed, the PLS model is used to predict new samples. The predicted value obtained includes the estimated concentration of the target ion after deducting the influence of the impurity peak. For experimental data where the true concentration cannot be directly obtained, the impurity peak is indirectly subtracted by comparing the difference between the model prediction value and the actual measured value (that is, the ideal signal after deducting the impurity).

[0040] The second aspect of the present application provides a device for determining the peak area of ​​chloride ions based on ion chromatography, and the device for determining the peak area of ​​chloride ions based on ion chromatography includes a processor and a memory. The processor is used to execute a method for determining the peak area of ​​chloride ions based on ion chromatography according to the first aspect of the present application. The memory is used to store executable instructions of the processor.

[0041] The third aspect of the present application provides a computer-readable storage medium on which computer executable instructions are stored. When the executable instructions are executed by a processor, a method for determining the chloride ion peak area based on ion chromatography according to the first aspect of the present application is implemented.

[0042] The fourth aspect of the present application provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements a method for determining chloride ion peak area based on ion chromatography according to the first aspect of the present application.

[0043] The beneficial effects of the technical solution of the present application are: through peak separation, peak qualitative, baseline correction, peak tailing processing and peak overlap processing, the identification of chromatographic peaks is realized, and through peak definition, integration algorithm, calibration curve application, verification of repeatability, impurity peak deduction and calculation of main peak area, the correct calculation of chromatographic peak area is realized, and the correct calculation of chromatographic peak area is conducive to quantitative accuracy, data reliability and repeatability. The method has good accuracy and repeatability, and has excellent tolerance for chromatographic columns, ensuring the quality of subsequent data interpretation, analysis results and the accuracy of scientific decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 Shown is a schematic flow chart of a method for determining chloride ion peak area based on ion chromatography provided in one embodiment of the present application. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0046] At least one embodiment of the present application provides a method for measuring the peak area of ​​chloride ions based on ion chromatography. The method for measuring the peak area of ​​chloride ions based on ion chromatography includes the following steps.

[0047] Step 1: Identify chromatographic peaks: peak separation, peak characterization, baseline correction, peak tailing and peak overlap. The peak separation is to ensure that the ions in the sample have sufficient separation so that each peak can be identified independently; the peak characterization is to use a known standard for comparative analysis, and to identify the peaks by retention time t R The target ions are determined by comparison; the baseline correction is performed by digital signal processing; the peak tailing processing and peak overlap processing are performed by data analysis algorithm processing.

[0048] It should be noted that the identification of chromatographic peaks can be used for qualitative analysis, and the retention time tR of the chromatographic peak is a characteristic parameter of the measured ion; the identification of chromatographic peaks can be used for quantitative analysis, and the peak area of ​​the chromatographic peak is proportional to the concentration of the corresponding component, so by accurately measuring and calculating the peak area, accurate quantitative analysis of the target component in the sample can be achieved. The identification of chromatographic peaks is one of the core links of chromatography technology, which directly affects the subsequent data interpretation, the quality of analysis results and the accuracy of scientific decision-making.

[0049] Step 2, calculate the chromatographic peak area: peak definition, integration algorithm, calibration curve application, verification of repeatability, impurity peak subtraction and calculation of main peak area. The peak definition is to clearly set the peak front and peak back; the integration algorithm is to use the built-in integration function of the chromatographic workstation software to calculate the peak area; the calibration curve application is to convert the peak area of ​​the sample to be tested into the corresponding concentration value according to the pre-drawn standard curve; the verification of repeatability is to measure the same component multiple times and evaluate its precision and accuracy; the impurity peak subtraction is to calculate the main peak area after subtracting the impurity peak.

[0050] It should be noted that good peak shape and sufficient peak separation can help improve the reliability of the analysis results.

[0051] According to the technical solution provided in the embodiment of the present application, the identification of chromatographic peaks is achieved through peak separation, peak qualitative analysis, baseline correction, peak tailing processing and peak overlap processing, and the correct calculation of chromatographic peak area is achieved through peak definition, integration algorithm, calibration curve application, verification of repeatability, impurity peak deduction and calculation of main peak area, and the correct calculation of chromatographic peak area is conducive to quantitative accuracy, data reliability and repeatability. The method has good accuracy and repeatability, and has excellent tolerance for chromatographic columns, ensuring the quality of subsequent data interpretation, analysis results and the accuracy of scientific decision-making.

[0052] In at least one embodiment of the present application, in step 1, the specific steps of the baseline correction are as follows:

[0053] (1) Define the window size: select an appropriate window size that is large enough to smooth noise but not large enough to blur out valid peaks; average each continuous data segment in the window, slide the window along the time axis, and replace the original baseline data points with the average value of the data points in the window point by point;

[0054] (2) Use Savitzky-Golay filter sliding window least squares fitting.

[0055] In the above embodiment, the Savitzky-Golay filtering method can effectively remove or reduce noise, and correct irregular baseline fluctuations, so as to obtain a more accurate and smooth baseline. Compared with simple moving average or other smoothing filters, the Savitzky-Golay filtering can better retain the true shape and characteristics of the chromatographic peak, because it not only considers the data of the current point, but also considers other data points in the window, so that the peak shape after filtering is closer to the response corresponding to the actual physical and chemical process. After the chromatographic peak is subjected to the Savitzky-Golay filtering, the calculation accuracy of the peak area can be significantly improved. By reducing noise and stabilizing the baseline, the ratio of signal to noise (signal-to-noise ratio) can be improved. The Savitzky-Golay filtering can select different window sizes and polynomial orders according to actual conditions, so as to be flexibly applied to chromatographic signals of various complexities, and good processing effects can be obtained for both single clear peaks and overlapping complex peak groups. In summary, the use of the Savitzky-Golay filtering sliding window least squares fitting can effectively eliminate noise and correct the baseline under the premise of ensuring the integrity of the peak shape, and provide more accurate peak area calculation results, thereby greatly improving the reliability and accuracy of ion chromatography data analysis.

[0056] In at least one embodiment of the present application, the specific steps of using Savitzky-Golay filtering sliding window least squares fitting are: first, setting parameters to determine the filter order and window size; second, local fitting, applying the least squares method to fit a smooth curve within the sliding window to obtain a smooth baseline estimate at each position within the window.

[0057] In at least one embodiment of the present application, in step 1, the specific steps of the peak tailing process are as follows:

[0058] (1) Model building: Assume that the cause of tailing can be described by a certain function form; select one or more appropriate basis functions to build a hybrid model based on the actual peak shape characteristics;

[0059] (2) Data preparation: Collect chromatographic signal data containing tailing peaks and preprocess the chromatographic signal data, including removing noise and smoothing the baseline; determine the starting point and end point of each tailing peak, and intercept the target peak segment for deconvolution processing;

[0060] (3) Parameter estimation: Use numerical optimization methods to iteratively optimize the parameters of the selected basis functions; the goal is to minimize the residual sum of squares or other error measures between the model prediction signal and the actual observed signal;

[0061] (4) Deconvolution calculation: Substitute the optimal parameters into the basis function, implement the deconvolution operation by mathematical means, and obtain the approximate shape of each peak without tailing;

[0062] (5) The separated ideal peak is directly used for area integration.

[0063] In the above embodiments, the peak tailing is processed by separating the ideal peak through modeling, data preprocessing, parameter estimation and deconvolution calculation, and the ideal peak is directly used for area integration, so as to more accurately quantify the content of each component. By effectively reducing the peak tailing, the resolution between the components can be improved, ensuring the accurate determination of each ion, and improving the separation and resolution. Appropriate peak tailing processing can improve the accuracy of peak area integration and enhance quantitative accuracy.

[0064] It should be noted that the mathematical means may be inverse Fourier transform or other appropriate mathematical methods.

[0065] In at least one embodiment of the present application, the function form is a Gaussian function, and the form of the Gaussian function is as follows:

[0066]

[0067] Where: A represents the peak area, corresponding to the concentration of the component; μ refers to the center position of the peak, that is, the retention time; σ is the standard deviation, which is related to the degree of diffusion and affects the width of the peak.

[0068] In the above embodiments, the Gaussian function is used to approximately describe the symmetrical peak tailing caused by physical processes such as molecular diffusion. Due to its good mathematical properties, such as normal distribution and integrability, it can better simulate the shape of the real chromatographic peak and help improve the qualitative and quantitative performance of chromatographic analysis.

[0069] In at least one embodiment of the present application, the function form is a Lorentz function, and the form of the Lorentz function is as follows:

[0070]

[0071] Where: A represents the peak area, corresponding to the concentration of the component; μ refers to the center position of the peak, that is, the retention time; γ is the Lorentz half-peak width parameter, which is related to the asymmetry and tailing degree of the peak.

[0072] In the above embodiments, the Lorentz function is used to simulate the asymmetric peak shape caused by the interaction between molecules and the stationary phase (such as the adsorption-desorption effect), which can accurately describe the asymmetric tailing caused by these non-uniform processes, effectively improve the peak recognition ability, and optimize the quantitative results.

[0073] In at least one embodiment of the present application, in step 1, the specific steps of the peak overlap processing are as follows:

[0074] (1) Model building: Select appropriate basis functions to describe the shape of individual peaks; assume that overlapping peaks are formed by the superposition of different parameterized versions of these basis functions;

[0075] (2) Data preprocessing: Preprocess the raw chromatographic signal, including removing noise and smoothing the baseline to ensure data quality; determine the number and approximate location of possible peaks based on visual observation or preliminary analysis;

[0076] (3) Parameter estimation: Using optimization algorithms such as nonlinear least squares, the actual observed mixed signal is fitted according to the selected basis functions. The parameters of the basis functions are regarded as unknowns, and a set of parameter values ​​is found through iterative optimization so that the difference between the sum of the basis functions and the actual signal is minimized.

[0077] (4) Deconvolution calculation: Use the best fitting parameters to reconstruct each independent basis function and add them together to obtain the peak shape of each component after decomposition; the separated single peaks can be further used for quantitative analysis.

[0078] Peak overlap may result in the inability to accurately identify and distinguish ions, affecting the qualitative analysis of the components in the sample. At the same time, due to errors in peak area calculation, the accuracy of the quantitative results may be directly affected, which may lead to concentration or content determination deviations. In the above embodiments, effective peak overlap processing can reduce background noise and interference, thereby improving the sensitivity of the method and reducing the detection limit.

[0079] In at least one embodiment of the present application, the basis function is any one or a combination of a Gaussian function and a Lorentz function.

[0080] In at least one embodiment of the present application, in step 2, the basic steps of the impurity peak subtraction are:

[0081] (1) Setting a threshold to distinguish target peaks from impurity peaks in the signal;

[0082] (2) For impurity peaks with less interference, choose to avoid the impurity peak area when integrating the target peak or automatically exclude small impurity peaks when performing peak integration calculations by setting appropriate peak width and minimum peak area parameters;

[0083] (3) When the impurity peak is significant and affects the quantification of the target peak, partial least squares regression (PLS) is used to establish a model to eliminate the impact of the impurity peak.

[0084] If effective impurity peak deduction is not performed, the calculated target ion concentration may include the contribution of impurities, resulting in result deviation. Therefore, impurity peak deduction is crucial to improving the accuracy and precision of quantitative analysis of target ions in samples. Correct deduction of impurity peaks helps ensure that characteristic parameters such as the shape and retention time of the target ion peak are not disturbed, thereby improving the reliability of qualitative analysis. In the above embodiment, by setting a correct way to deduct impurity peaks, it helps to ensure that characteristic parameters such as the shape and retention time of the target chloride ion peak are not disturbed, thereby improving the reliability of qualitative analysis.

[0085] In at least one embodiment of the present application, the specific steps of using partial least squares regression (PLS) to establish a model to remove impurity peaks are as follows:

[0086] ① Data preparation: Collect ion chromatographic signal data containing target components and impurity peaks. Ion chromatographic signal data includes the intensity of all components in the sample at different time points or detector responses. The independent variable X is the time series data of the entire chromatographic signal; the dependent variable Y is the actual concentration of the target ion.

[0087] ② Preprocessing and impurity peak identification: First, the raw data needs to be preprocessed, including removing baseline drift and noise filtering; marking and separating the peaks of the target ions and the impurity peak areas that may interfere.

[0088] ③Construct a PLS model: Use the partial least squares regression algorithm, taking all chromatographic signals as the independent variable X, and only the actual concentration of the target ion or the known standard value as the dependent variable Y.

[0089] ④ Background subtraction: After the PLS model training is completed, the PLS model is used to predict new samples. The predicted value obtained includes the estimated concentration of the target ion after deducting the influence of the impurity peak. For experimental data where the true concentration cannot be directly obtained, the impurity peak is indirectly subtracted by comparing the difference between the model prediction value and the actual measured value (that is, the ideal signal after deducting the impurity).

[0090] In ion chromatography data, the signals of various components may be highly correlated, resulting in multicollinearity problems. PLS can solve this problem to a certain extent by finding the best linear combination of the original variables (i.e., PLS factors), and more accurately distinguish and deduct the impact of impurity peaks. Moreover, compared with traditional methods such as multivariate linear regression, PLS reduces the risk of model overfitting while ensuring predictive ability by reducing the dimensionality of the independent variables, thereby improving the generalization ability and robustness of the model.

[0091] The basic principles and main features of the present application are shown and described above. For those skilled in the art, it is obvious that the present application is not limited to the details of the above exemplary embodiments. Therefore, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present application is limited by the attached claims rather than the above description. Therefore, it is intended to include all changes within the meaning and scope of the equivalent elements of the claims in the present application.

[0092] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

[0093] At least one embodiment of the present application also provides a device for measuring chloride ion peak area based on ion chromatography, and the device for measuring chloride ion peak area based on ion chromatography includes a processor and a memory. The processor is used to execute a method for measuring chloride ion peak area based on ion chromatography provided in any of the above embodiments of the present application. The memory is used to store executable instructions of the processor, such as application programs. The number of processors can be one or more. The application program stored in the memory may include one or more modules, each corresponding to a set of instructions. In addition, the processor is configured to execute instructions to execute the above-mentioned method for measuring chloride ion peak area based on ion chromatography.

[0094] The device for determining the peak area of ​​chloride ions based on ion chromatography may further include a power supply component configured to manage the power supply of the device for determining the peak area of ​​chloride ions based on ion chromatography, a wired or wireless network interface configured to connect the device for determining the peak area of ​​chloride ions based on ion chromatography to a network, and an input / output (I / O) interface. The device for determining the peak area of ​​chloride ions based on ion chromatography may operate based on an operating system stored in a memory, such as Windows Server 2003. TM , Mac OSX TM , Unix TM , Linux TM , FreeBSDTM or similar.

[0095] At least one embodiment of the present application further provides a computer-readable storage medium on which computer executable instructions are stored. When the executable instructions are executed by a processor, a method for determining the peak area of ​​chloride ions based on ion chromatography provided in any of the above embodiments of the present application is implemented.

[0096] A non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by the processor of the above-mentioned device for measuring the peak area of ​​chloride ions based on ion chromatography, enables the above-mentioned device for measuring the peak area of ​​chloride ions based on ion chromatography to perform the above-mentioned method for measuring the peak area of ​​chloride ions based on ion chromatography. The method for measuring the peak area of ​​chloride ions based on ion chromatography is executed by an agent program.

[0097] Those of ordinary skill in the art will appreciate that the algorithmic steps of each example described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0098] At least one embodiment of the present application further provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements a method for determining chloride ion peak area based on ion chromatography provided in any of the above embodiments of the present application.

[0099] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a computer program product, which is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method for determining the peak area of ​​chloride ions based on ion chromatography of each embodiment of the present application. And the aforementioned storage medium includes: various media that can store program check codes such as USB flash drive, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk.

[0100] It should be noted that the combination of the various technical features in the embodiments of the present application is not limited to the combination described in the embodiments of the present application or the combination described in the specific embodiments, and all technical features described in the present application can be freely combined or combined in any way unless there is a contradiction between them.

[0101] As shown in this application and claims, unless the context clearly indicates an exception, the words "a", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the term "comprising" only indicates that the steps and elements that have been clearly identified are included, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0102] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for determining chloride ion peak area based on ion chromatography, characterized in that: include: Step 1: Identify chromatographic peaks: peak separation, peak characterization, baseline correction, peak tailing processing and peak overlap processing. The peak separation is to ensure that the ions in the sample have sufficient separation so that each peak can be identified independently; the peak characterization is to use known standards for comparative analysis, and the retention time t R The target ions are determined by comparison; the baseline correction is performed by digital signal processing; the peak tailing processing and peak overlap processing are performed by data analysis algorithm processing; Step 2, calculate the chromatographic peak area: peak definition, integration algorithm, calibration curve application, verification repeatability, impurity peak subtraction and calculation of main peak area, the peak definition is to clearly set the peak front and peak back; the integration algorithm is to use the built-in integration function of the chromatography workstation software to calculate the peak area; the calibration curve application is to convert the peak area of ​​the sample to be tested into the corresponding concentration value according to the pre-drawn standard curve; the verification repeatability is to perform multiple injection measurements on the same component and evaluate its precision and accuracy; the impurity peak subtraction is to calculate the main peak area after subtracting the impurity peak.

2. The method for measuring chloride ion peak area based on ion chromatography according to claim 1, characterized in that: In step 1, the specific steps of the baseline correction are as follows: Define the window size: select a suitable window size that is large enough to smooth noise but not so large as to blur out valid peaks; average each continuous data segment in the window, slide the window along the time axis, and replace the original baseline data points point by point with the average value of the data points in the window; The Savitzky-Golay filter sliding window least squares fitting was used.

3. The method for measuring chloride ion peak area based on ion chromatography according to claim 1, characterized in that: In step 1, the specific steps of the peak tailing process are as follows: Establish a model: Assume that the cause of tailing can be described by a certain function form; according to the actual peak shape characteristics, select one or more appropriate basis functions to construct a mixed model; Data preparation: Collect chromatographic signal data containing tailing peaks and preprocess the chromatographic signal data, including noise removal and baseline smoothing; Determine the starting and ending points of each tailing peak, and intercept the target peak segment for deconvolution processing; Parameter estimation: Iteratively optimize the parameters of the selected basis functions using numerical optimization methods; the goal is to minimize the residual sum of squares or other error measures between the model predicted signal and the actual observed signal; Deconvolution calculation: Substitute the optimal parameters into the basis function, implement the deconvolution operation by mathematical means, and obtain the approximate shape of each peak without tailing; The separated ideal peaks were directly used for area integration.

4. The method for measuring chloride ion peak area based on ion chromatography according to claim 3, characterized in that: The function form is Gaussian and / or Lorentzian, The Gaussian function has the following form: Where: A represents the peak area, corresponding to the concentration of the component; μ refers to the center position of the peak, that is, the retention time; σ is the standard deviation, which is related to the degree of diffusion and affects the width of the peak; The Lorentz function has the following form: Where: A represents the peak area, corresponding to the concentration of the component; μ refers to the center position of the peak, that is, the retention time; γ is the Lorentz half-peak width parameter, which is related to the asymmetry and tailing degree of the peak.

5. The method for determining the chloride ion peak area based on ion chromatography according to claim 1, characterized in that: In step 1, the specific steps of the peak overlap processing are as follows: Model building: Choose appropriate basis functions to describe the shapes of individual peaks; assume that overlapping peaks are caused by the superposition of different parameterized versions of these basis functions; Data preprocessing: Preprocess the raw chromatographic signal, including removing noise and smoothing the baseline to ensure data quality; determine the number and approximate location of possible peaks based on visual observation or preliminary analysis; Parameter estimation: Use optimization algorithms such as nonlinear least squares to fit the actual observed mixed signal according to the selected basis function; take the parameters of the basis function as unknowns, and find a set of parameter values ​​through iterative optimization to minimize the difference between the sum of the basis functions and the actual signal; Deconvolution calculation: Each independent basis function is reconstructed using the best fitting parameters and added together to obtain the peak shapes of each component after decomposition; the separated individual peaks are further used for quantitative analysis.

6. A method for measuring chloride ion peak area based on ion chromatography according to any one of claims 1 to 5, characterized in that: In step 2, the basic steps of impurity peak subtraction are: Set the threshold to distinguish the target peaks and impurity peaks in the signal; For impurity peaks with less interference, choose to avoid the impurity peak area when integrating the target peak or automatically exclude small impurity peaks when performing peak integration calculations by setting appropriate peak width and minimum peak area parameters; When the impurity peak is significant and affects the quantification of the target peak, partial least squares regression is used to establish a model to eliminate the impact of the impurity peak.

7. The method for measuring chloride ion peak area based on ion chromatography according to claim 6, characterized in that: The specific steps of using partial least squares regression to establish a model to remove the impact of impurity peaks are as follows: Data preparation: Collect ion chromatographic signal data containing target components and impurity peaks. Ion chromatographic signal data includes the intensity of all components in the sample at different time points or detector responses. The independent variable X is the time series data of the entire chromatographic signal; the dependent variable Y is the actual concentration of the target ion; Preprocessing and impurity peak identification: First, the raw data needs to be preprocessed, including removing baseline drift and noise filtering; marking and separating the peak of the target ion and the impurity peak area that may interfere; Construct a partial least squares regression model: Use the partial least squares regression algorithm, taking all chromatographic signals as the independent variable X, and only the actual concentration of the target ion or the known standard value as the dependent variable Y; Background subtraction: After the partial least squares regression model is trained, the partial least squares regression model is used to predict new samples. The predicted value obtained includes the estimated concentration of the target ion after deducting the influence of the impurity peak. For experimental data where the true concentration cannot be directly obtained, the impurity peak is indirectly subtracted by comparing the difference between the model prediction value and the actual measurement value.

8. A device for measuring chloride ion peak area based on ion chromatography, characterized in that: include: A processor, for executing a method for determining a chloride ion peak area based on ion chromatography according to any one of claims 1 to 7; as well as A memory is used to store executable instructions of the processor.

9. A computer-readable storage medium having computer executable instructions stored thereon, characterized in that: When the executable instructions are executed by the processor, a method for measuring chloride ion peak area based on ion chromatography according to any one of claims 1 to 7 is implemented.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, a method for determining chloride ion peak area based on ion chromatography according to any one of claims 1 to 7 is implemented.

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