An Adaptive Gradient Correction Method and System for Ion Chromatography Based on Real-Time Feedback of Detection Signal

Abstract

This invention discloses an adaptive gradient correction method and system for ion chromatography based on real-time feedback of detection signals. The method extracts the actual retention time and peak width of the chromatographic peak from the key detection signals of the acquired chromatographic peak. Based on the actual retention time and a preset standard retention time, the retention time drift is calculated. The retention time drift and peak width are used to determine if the chromatographic separation is abnormal. When abnormality occurs, the key detection signals, retention time drift, and peak width of the acquired chromatographic peak are input into a chromatographic separation state prediction model to predict the gradient adjustment amount to achieve optimal separation. This method and system can sense the chromatographic analysis state in real time and automatically adaptively correct the gradient program, solving problems such as retention time drift and decreased resolution, improving the accuracy, stability, and efficiency of chromatographic analysis, and extending the lifespan of the chromatographic column.

Description

Technical Field

[0001] This invention belongs to the field of chromatographic analysis technology and relates to an adaptive gradient correction method and system for ion chromatography based on real-time feedback of detection signals. Background Technology

[0002] In chromatographic analysis, gradient elution is a commonly used elution technique that achieves effective separation of different components in complex samples by continuously changing the composition ratio of the mobile phase (such as polarity and concentration). It is widely used in many fields such as chemical engineering, pharmaceuticals, environmental monitoring, and food testing.

[0003] Currently, traditional gradient elution techniques generally employ open-loop control, meaning a fixed gradient program (including gradient slope, plateau concentration, duration, etc.) is pre-set and strictly executed throughout the analysis, without considering the influence of various interfering factors. However, in actual chromatographic analysis, multiple factors can lead to deterioration of chromatographic separation, such as column aging during long-term use, sample matrix fluctuations, column temperature fluctuations, mobile phase ratio deviations, and instrument delay volume differences. These factors can cause peak retention time drift and peak width increase, resulting in decreased component resolution and, in severe cases, peak overlap, affecting the accuracy and reliability of the analytical results.

[0004] In existing technologies, solutions to retention time drift mostly rely on manual intervention. Operators periodically observe chromatograms, and when retention time drift exceeds acceptable limits, they manually adjust gradient program parameters or replace the column. This approach is not only time-consuming and labor-intensive, but also inefficient. Furthermore, the accuracy of adjustments depends on the operator's experience, making real-time correction impossible and ill-suited for high-volume, continuous analysis. Additionally, some technologies attempt to fine-tune retention time by adjusting the gradient initiation point, but this only addresses drift caused by simple factors such as instrument delay volume differences. It cannot handle complex situations involving multiple factors, such as column aging and sample matrix fluctuations, resulting in limited correction effectiveness and an inability to adaptively respond to different anomaly modes. For example, Waters' ACQUITY Arc system uses Gradient SmartStart technology to adjust the gradient initiation point, which simplifies retention time fine-tuning during method transfer, but still requires manual judgment of the adjustment direction and magnitude. It also cannot dynamically correct the gradient slope or plateau concentration, failing to fundamentally solve the problem of retention time drift and resolution degradation caused by multiple factors.

[0005] Therefore, developing a method that can sense the chromatographic analysis status in real time and automatically perform adaptive correction of the gradient program to accurately control retention time drift and ensure stable separation results has become an urgent technical problem to be solved in the field of current chromatographic analysis technology. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide an adaptive gradient correction method and system for ion chromatography based on real-time feedback of detection signals. This method and system can sense the chromatographic analysis status in real time, automatically perform adaptive correction of the gradient program, solve problems such as retention time drift and resolution reduction, improve the accuracy, stability and efficiency of chromatographic analysis, and extend the service life of the chromatographic column.

[0007] To achieve the above objectives, this invention discloses an adaptive gradient correction method for ion chromatography based on real-time feedback of detection signals, comprising: During the chromatographic gradient elution process, key detection signals of chromatographic peaks are acquired in real time; The actual retention time and peak width of the chromatographic peak are extracted from the key detection signal of the collected chromatographic peak. Based on the actual retention time and the preset standard retention time, the retention time drift is calculated. Based on the retention time drift and the actual peak width, it is determined whether the chromatographic separation is abnormal. When the chromatographic separation is abnormal, the key detection signal, retention time drift and actual peak width of the collected chromatographic peak are input into the chromatographic separation state prediction model to predict the gradient adjustment amount to achieve the optimal separation effect. Adaptive gradient correction for ion chromatography is performed based on the gradient adjustment amount used to achieve optimal separation.

[0008] Furthermore, the key detection signals include conductivity signals, chromatographic peak retention time signals, and chromatographic peak width signals.

[0009] Furthermore, if the retention time drift exceeds the threshold or the actual peak width exceeds the preset peak width range, it is determined to be an abnormal chromatographic separation.

[0010] Furthermore, based on the predicted optimal gradient adjustment amount and combined with a pre-defined gradient adjustment strategy library, subsequent gradient segments are subjected to online adaptive correction.

[0011] Furthermore, the gradient adjustment strategy library contains correction strategies corresponding to different anomaly modes.

[0012] Furthermore, the gradient adjustment strategy library pre-sets correction strategies for a variety of typical abnormal modes, including: slow drift in retention time caused by column aging, abrupt change in retention time caused by sample matrix fluctuation, increased peak width caused by temperature fluctuation, and abnormal conductivity caused by mobile phase ratio deviation. Each abnormal mode corresponds to at least two gradient adjustment schemes.

[0013] Furthermore, the conductivity signal is acquired using a conductivity detector, while the retention time signal and peak width signal are acquired using an ultraviolet detector or a fluorescence detector.

[0014] This invention discloses an adaptive gradient correction system for ion chromatography based on real-time feedback of detection signals, comprising: The acquisition module is used to acquire key detection signals of chromatographic peaks in real time during the chromatographic gradient elution process; The preprocessing module is used to extract the actual retention time and actual peak width of the chromatographic peak from the key detection signals of the collected chromatographic peak, calculate the retention time drift based on the actual retention time and the preset standard retention time, and determine whether the chromatographic separation is abnormal based on the retention time drift and the actual peak width. When the chromatographic separation is abnormal, the key detection signals, retention time drift and actual peak width of the collected chromatographic peak are input into the chromatographic separation state prediction model to predict the gradient adjustment amount to achieve the optimal separation effect. The control module is used to perform adaptive gradient correction for ion chromatography based on the gradient adjustment amount to achieve the optimal separation effect.

[0015] The present invention discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the ion chromatography adaptive gradient correction method based on real-time feedback of detection signals.

[0016] The present invention discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the ion chromatography adaptive gradient correction method based on real-time feedback of detection signals.

[0017] The present invention has the following beneficial effects: In practical operation, the ion chromatography adaptive gradient correction method and system based on real-time feedback of detection signals described in this invention, when chromatographic separation becomes abnormal, inputs the key detection signals of the collected chromatographic peaks, retention time drift, and actual peak width values ​​into the chromatographic separation state prediction model to predict the gradient adjustment amount to achieve the optimal separation effect. Based on the gradient adjustment amount to achieve the optimal separation effect, ion chromatography adaptive gradient correction is performed, thereby automatically and adaptively correcting the gradient program, solving problems such as retention time drift and decreased resolution, improving the accuracy, stability, and efficiency of chromatographic analysis, and extending the service life of the chromatographic column, making it highly practical. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of Example 1; Figure 2 This is a flowchart of Example 2; Figure 3 This is a flowchart of Example 3. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] In the description of this invention, it should be understood that the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0022] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0023] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this invention generally indicates that the preceding and following objects have an "or" relationship.

[0024] It should be understood that although terms such as first, second, third, etc., may be used in the embodiments of the present invention to describe the preset range, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from one another. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0025] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0027] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0028] Example 1 refer to Figure 1 The adaptive gradient correction method for ion chromatography based on real-time feedback of detection signals described in this invention includes the following steps: 1) Real-time acquisition of key detection signals of chromatographic peaks.

[0029] During the chromatographic gradient elution process, key detection signals of the chromatographic peaks are acquired in real time. These key detection signals include conductivity signals, chromatographic peak retention time signals, and chromatographic peak width signals. The conductivity signal reflects the real-time changes in the composition of the mobile phase, while the retention time and peak width signals reflect the real-time status of the chromatographic separation effect. The key detection signals of the chromatographic peaks are acquired synchronously by a detector and transmitted to the control module at a frequency of not less than 1 Hz to ensure the real-time performance and continuity of the signals.

[0030] 2) Detection signal analysis and anomaly judgment.

[0031] The control module preprocesses the key detection signals of the chromatographic peaks (including filtering, noise reduction, and peak identification), extracting the actual retention time and peak width values ​​of the chromatographic peaks. It compares the actual retention time values ​​with preset standard retention times, calculates the retention time drift, and sets a retention time drift threshold (which can be adjusted according to actual analytical needs; the default threshold is 0.5%). When the retention time drift exceeds the threshold, or the actual peak width exceeds the preset peak width range, it is determined to be an abnormal chromatographic separation, and a gradient correction program is initiated. If the threshold is not exceeded, the preset gradient program continues to run.

[0032] 3) Prediction of optimal gradient adjustment amount.

[0033] A model predictive control algorithm is adopted, using real-time collected conductivity, retention time drift, and peak width change as input parameters. Combined with preset chromatographic column parameters (including column length, inner diameter, stationary phase type), mobile phase parameters (including initial ratio, viscosity, and polarity), and analytical conditions (including column temperature and flow rate), a chromatographic separation state prediction model is established to predict the gradient adjustment amount to achieve the optimal separation effect. The model predictive control algorithm is trained and optimized through historical correction data, and can quickly respond to different abnormal modes with a prediction error of no more than ±0.1%.

[0034] 4) Gradient program adaptive correction.

[0035] The control module performs online adaptive correction on subsequent gradient segments based on the predicted optimal gradient adjustment amount and a preset gradient adjustment strategy library. This library includes correction strategies for different abnormal modes (such as positive or negative retention time drift, increased peak width, and sudden changes in conductivity). Specifically, when a retention time drift exceeds a threshold, the slope or plateau concentration of subsequent gradient segments is automatically adjusted. If the retention time drifts positively (actual retention time is greater than the standard retention time), the gradient slope is increased or the plateau concentration is raised to accelerate component elution. If the retention time drifts negatively (actual retention time is less than the standard retention time), the gradient slope is decreased or the plateau concentration is lowered to slow down component elution. Simultaneously, the gradient parameters are fine-tuned based on peak width changes to ensure the separation meets analytical requirements.

[0036] 5) Verification and iterative optimization of the correction effect.

[0037] After gradient calibration is completed, the detection signal continues to be acquired in real time, and the retention time drift and resolution of the chromatographic peak after calibration are analyzed. If the retention time drift is controlled within ±1% and the resolution meets the preset requirements, the current calibrated gradient program is maintained. If the requirements are still not met, steps 3) to 4) are repeated for secondary calibration until the analytical requirements are met. At the same time, the calibration data (including abnormal modes, adjustment parameters, and calibration effects) are stored in the gradient adjustment strategy library to achieve iterative optimization of the strategy library and improve the response speed and accuracy of subsequent calibrations.

[0038] Furthermore, in step 1), the conductivity signal is acquired by a conductivity detector, and the retention time signal and peak width signal are acquired by an ultraviolet detector or a fluorescence detector. All detection signals are converted into digital signals by an A / D converter and then transmitted to the control module to ensure the accuracy of signal transmission.

[0039] Furthermore, in step 3), the model predictive control algorithm includes three modules: a predictive model, rolling optimization, and feedback correction. The predictive model is used to predict the chromatographic separation state over a future period based on the current detection signal. The rolling optimization is used to calculate the optimal gradient adjustment based on the prediction results and performance indicators (retention time drift ≤ ±1%, resolution ≥ 1.5). The feedback correction is used to correct the predictive model based on the deviation between the actual detection signal and the predicted signal, thereby improving the prediction accuracy.

[0040] Furthermore, the gradient adjustment strategy library pre-sets correction strategies for various typical abnormal modes, including: slow drift in retention time caused by column aging, abrupt change in retention time caused by sample matrix fluctuation, increased peak width caused by temperature fluctuation, and abnormal conductivity caused by mobile phase ratio deviation. Each abnormal mode corresponds to at least two gradient adjustment schemes, and the control module automatically selects the optimal correction scheme according to the actual abnormal type.

[0041] Furthermore, the method also includes a gradient correction permission setting function, which sets two modes: automatic correction and manual correction, according to the analysis requirements. In the automatic correction mode, no manual intervention is required, and the entire process is completed by the control module. In the manual correction mode, the control module provides gradient adjustment suggestions, which are then confirmed by the operator before correction is performed, thus improving the flexibility of the method.

[0042] Example 2 This embodiment is used for gradient correction in the analysis of drug components in high performance liquid chromatography.

[0043] refer to Figure 2 The adaptive gradient correction method for ion chromatography based on real-time feedback of detection signals, as described in this invention, comprises the following specific steps: 1) Real-time acquisition of detection signals.

[0044] During the gradient elution process, the retention time and peak width signals of the chromatographic peaks are acquired in real time using an ultraviolet detector at a frequency of 2 Hz; the conductivity signal of the mobile phase is acquired in real time using a conductivity detector at a frequency of 1 Hz. All detection signals are converted by an A / D converter and then transmitted to the control module.

[0045] 2) Detection signal analysis and anomaly judgment.

[0046] The standard retention time of each component in the antibiotic is preset (e.g., the standard retention time of component A is 8.0 min and the standard retention time of component B is 12.0 min), the retention time drift threshold is set to 0.5%, and the preset peak width range is 0.2-0.5 min. The control module performs filtering and noise reduction on the acquired signal, extracts the actual retention time of component A as 8.09 min, and calculates the retention time drift as (8.09-8.0) / 8.0×100%=1.125%, which exceeds the preset threshold of 0.5%, and is judged as a separation abnormality, and the gradient correction program is started.

[0047] 3) Prediction of optimal gradient adjustment amount.

[0048] Using a model predictive control algorithm, the current conductivity signal (120 μS / cm), retention time drift (1.125%), and actual peak width (0.55 min) were input. Combined with the column parameters (column length 250 mm, inner diameter 4.6 mm, stationary phase C18), mobile phase parameters (initial ratio of methanol:water = 30:70, flow rate 1.0 mL / min), and column temperature (30 °C), the optimal gradient adjustment was predicted to be: adjusting the slope of the subsequent gradient segment (8-15 min) from 10% / min to 12% / min, while keeping the plateau concentration unchanged.

[0049] 4) Gradient program adaptive correction.

[0050] Based on the predicted optimal adjustment amount, and combined with the correction strategy corresponding to "positive drift of retention time" in the gradient adjustment strategy library, the control module automatically adjusts the slope of the subsequent gradient segment from 10% / min to 12% / min, thereby accelerating the elution rate of component A.

[0051] 5) Verification and iterative optimization of the correction effect.

[0052] After calibration, the detection signal was collected again. The actual retention time of component A became 8.02 min, and the retention time drift was (8.02-8.0) / 8.0×100%=0.25%, which was controlled within ±1%. The peak width became 0.42 min, which was within the preset range, and the resolution was 1.8, which met the analysis requirements. The calibration data (retention time positive drift of 1.125%, slope adjusted to 12% / min, calibration effect met the standard) was stored in the gradient adjustment strategy library to complete the calibration.

[0053] Experimental comparison: Using the traditional open-loop controlled gradient elution method, after 20 consecutive analyses, the retention time drift of component A reached 3.2%, the peak width increased to 0.7 min, and the resolution dropped to 1.2, which could not meet the analytical requirements. Using the method of this invention, after 20 consecutive analyses, the retention time drift of component A was controlled within ±0.8%, the peak width was maintained between 0.3 and 0.45 min, the resolution was always ≥1.5, and the chromatographic column maintained good separation performance even after 300 uses. Compared with the traditional method, the column life was extended by 42%.

[0054] Example 3 refer to Figure 3 This embodiment is used for gradient correction application in the analysis of anions in environmental water samples by ion chromatography.

[0055] This embodiment is applied to the separation and analysis of fluoride, chloride, and sulfate ions in environmental water samples using ion chromatography. The specific steps of the method of this invention are as follows: 1) Real-time acquisition of detection signals.

[0056] Conductivity, retention time, and peak width signals are acquired in real time using a conductivity detector at a frequency of 1.5 Hz. The processed signals are then transmitted to the control module.

[0057] 2) Detection signal analysis and anomaly judgment.

[0058] The preset standard retention times were 3.5 min for fluoride ions, 5.2 min for chloride ions, and 8.8 min for sulfate ions. The retention time drift threshold was 0.4%, and the peak width range was 0.15-0.4 min. During the analysis, the actual retention time of chloride ions was detected to be 5.0 min, with a drift of (5.0-5.2) / 5.2×100%=-3.85%, which exceeded the threshold. Furthermore, the peak width changed to 0.45 min, indicating an abnormal separation. The correction procedure was then initiated.

[0059] 3) Prediction of optimal gradient adjustment amount.

[0060] The model predictive control algorithm takes the conductivity signal (85 μS / cm), retention time drift (-3.85%), actual peak width (0.45 min) as input, and combines the column parameters, mobile phase (sodium carbonate-sodium bicarbonate buffer solution) parameters, and column temperature to predict the optimal adjustment: adjust the slope of the subsequent gradient segment (5-8 min) from 8% / min to 6% / min, and reduce the plateau concentration by 5%.

[0061] 4) Gradient program adaptive correction.

[0062] The control module automatically adjusts the gradient slope and plateau concentration based on the correction strategy of "negative drift of retention time" in the gradient adjustment strategy library to complete the correction.

[0063] 5) Verification and iterative optimization of the correction effect.

[0064] After calibration, the chloride ion retention time became 5.18 min, the drift was -0.38%, the peak width became 0.38 min, and the resolution was 2.0, which met the analytical requirements. The calibration data were stored in the strategy library to optimize the strategy library.

[0065] Experimental results show that, using the method of this invention, the retention time drift of each anion in the environmental water sample is controlled within ±0.5%, the separation effect is stable, and it can effectively compensate for the effects of water sample matrix fluctuations and column aging. The service life of the chromatographic column is extended by 38%, which is significantly better than the traditional method.

[0066] Example 4 The ion chromatography adaptive gradient correction system based on real-time feedback of detection signals described in this invention is characterized by comprising: The acquisition module is used to acquire key detection signals of chromatographic peaks in real time during the chromatographic gradient elution process; The preprocessing module is used to extract the actual retention time and actual peak width of the chromatographic peak from the key detection signals of the collected chromatographic peak, calculate the retention time drift based on the actual retention time and the preset standard retention time, and determine whether the chromatographic separation is abnormal based on the retention time drift and the actual peak width. When the chromatographic separation is abnormal, the key detection signals, retention time drift and actual peak width of the collected chromatographic peak are input into the chromatographic separation state prediction model to predict the gradient adjustment amount to achieve the optimal separation effect. The control module is used to perform adaptive gradient correction for ion chromatography based on the gradient adjustment amount to achieve the optimal separation effect.

[0067] The module division in this embodiment is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in each embodiment of this application can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0068] Example 5 A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the ion chromatography adaptive gradient correction method based on real-time feedback of detection signals. For example, the method includes: during chromatographic gradient elution, real-time acquisition of key detection signals of chromatographic peaks; extraction of actual retention time and actual peak width values ​​of the chromatographic peaks from the acquired key detection signals; calculation of retention time drift based on the actual retention time value and a preset standard retention time; determination of chromatographic separation abnormality based on the retention time drift and actual peak width values; when chromatographic separation abnormality occurs, inputting the acquired key detection signals, retention time drift, and actual peak width values ​​of the chromatographic peaks into a chromatographic separation state prediction model to predict the gradient adjustment amount to achieve optimal separation; and performing ion chromatography adaptive gradient correction based on the gradient adjustment amount to achieve optimal separation. The memory may include main memory, such as high-speed random access memory (RAM), or non-volatile memory, such as at least one disk storage device. The processor, network interface, and memory are interconnected via an internal bus, which may be an industry-standard architecture bus, a peripheral component interconnection standard bus, or an extended industry-standard architecture bus. The bus can be categorized as an address bus, data bus, or control bus. The memory stores programs; specifically, the program may include program code, which includes computer operation instructions. The memory may include main memory and non-volatile memory, and provides instructions and data to the processor.

[0069] Example 6 A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the ion chromatography adaptive gradient correction method based on real-time feedback of detection signals. For example, the method includes: during chromatographic gradient elution, real-time acquisition of key detection signals of chromatographic peaks; extraction of actual retention time and peak width values ​​of the chromatographic peaks from the acquired key detection signals; calculation of retention time drift based on the actual retention time and a preset standard retention time; determination of chromatographic separation abnormality based on the retention time drift and peak width values; inputting the acquired key detection signals, retention time drift, and peak width values ​​into a chromatographic separation state prediction model when chromatographic separation abnormality occurs; predicting the gradient adjustment amount to achieve optimal separation; and performing ion chromatography adaptive gradient correction based on the gradient adjustment amount to achieve optimal separation. Specifically, the computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. The volatile memory may include random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include read-only memory (ROM), hard disk, flash memory, optical disk, magnetic disk, etc.

[0070] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0071] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0072] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0073] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0074] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and disclosure of the invention. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.

[0075] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

[0076] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the present invention. Any simple modifications, alterations, or equivalent structural changes made to the above embodiments based on the technical essence of the present invention shall still fall within the protection scope of the present invention.

Claims

1. An adaptive gradient correction method for ion chromatography based on real-time feedback of detection signals, characterized in that, include: During the chromatographic gradient elution process, key detection signals of chromatographic peaks are acquired in real time; The actual retention time and peak width of the chromatographic peak are extracted from the key detection signal of the collected chromatographic peak. Based on the actual retention time and the preset standard retention time, the retention time drift is calculated. Based on the retention time drift and the actual peak width, it is determined whether the chromatographic separation is abnormal. When the chromatographic separation is abnormal, the key detection signal, retention time drift and actual peak width of the collected chromatographic peak are input into the chromatographic separation state prediction model to predict the gradient adjustment amount to achieve the optimal separation effect. Adaptive gradient correction for ion chromatography is performed based on the gradient adjustment amount used to achieve optimal separation.

2. The adaptive gradient correction method for ion chromatography based on real-time feedback of detection signal according to claim 1, characterized in that, The key detection signals include conductivity signal, chromatographic peak retention time signal, and chromatographic peak width signal.

3. The adaptive gradient correction method for ion chromatography based on real-time feedback of detection signal according to claim 1, characterized in that, When the retention time drift exceeds the threshold or the actual peak width exceeds the preset peak width range, the chromatographic separation is determined to be abnormal.

4. The adaptive gradient correction method for ion chromatography based on real-time feedback of detection signal according to claim 1, characterized in that, Based on the predicted optimal gradient adjustment amount, and combined with a pre-set gradient adjustment strategy library, the subsequent gradient segments are adaptively corrected online.

5. The adaptive gradient correction method for ion chromatography based on real-time feedback of detection signal according to claim 1, characterized in that, The gradient adjustment strategy library contains correction strategies corresponding to different anomaly modes.

6. The adaptive gradient correction method for ion chromatography based on real-time feedback of detection signal according to claim 1, characterized in that, The gradient adjustment strategy library pre-sets correction strategies for a variety of typical abnormal modes, including: slow drift in retention time caused by column aging, abrupt change in retention time caused by sample matrix fluctuation, increased peak width caused by temperature fluctuation, and abnormal conductivity caused by mobile phase ratio deviation. Each abnormal mode corresponds to at least two gradient adjustment schemes.

7. The adaptive gradient correction method for ion chromatography based on real-time feedback of detection signal according to claim 1, characterized in that, The conductivity signal is acquired using a conductivity detector, while the retention time and peak width signals are acquired using an ultraviolet detector or a fluorescence detector.

8. An adaptive gradient correction system for ion chromatography based on real-time feedback of detection signals, characterized in that, include: The acquisition module is used to acquire key detection signals of chromatographic peaks in real time during the chromatographic gradient elution process; The preprocessing module is used to extract the actual retention time and actual peak width of the chromatographic peak from the key detection signals of the collected chromatographic peak, calculate the retention time drift based on the actual retention time and the preset standard retention time, and determine whether the chromatographic separation is abnormal based on the retention time drift and the actual peak width. When the chromatographic separation is abnormal, the key detection signals, retention time drift and actual peak width of the collected chromatographic peak are input into the chromatographic separation state prediction model to predict the gradient adjustment amount to achieve the optimal separation effect. The control module is used to perform adaptive gradient correction for ion chromatography based on the gradient adjustment amount to achieve the optimal separation effect.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the ion chromatography adaptive gradient correction method based on real-time feedback of detection signals as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the ion chromatography adaptive gradient correction method based on real-time feedback of detection signals as described in any one of claims 1-7.

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