Liquid chromatography mobile phase liquid level real-time monitoring and early warning method based on optical sensing

Abstract

The application discloses a liquid level real-time monitoring and early warning method for liquid chromatography mobile phase based on optical sensing, which comprises the following steps: obtaining optical detection data containing reflected light intensity and monitoring time; inputting the reflected light intensity into a preset liquid level and reflected light intensity mapping model, calculating the detection liquid level of the solution in the container, and drawing a detection height change curve; when the detection liquid level of the solution is lower than a preset liquid level threshold, generating a liquid level early warning signal and sending it to a preset terminal; obtaining an experimental control instruction, performing a simulation experiment, judging whether there is a detection error, and determining abnormal detection data; when there is abnormal detection data, the mapping relationship between the liquid level and the reflected light intensity is corrected. According to the mapping relationship between the liquid level and the reflected light intensity, the liquid level in the container is calculated, and the mapping relationship between the liquid level and the reflected light intensity is dynamically corrected through the experimental control instruction combined with the detection liquid level, so that the monitoring error is reduced, and the accuracy of the mobile phase liquid level monitoring is improved.

Description

Technical Field

[0001] This application relates to the field of liquid level monitoring technology, and more specifically, to a method for real-time monitoring and early warning of liquid level in liquid chromatography mobile phase based on optical sensing. Background Technology

[0002] In liquid chromatography, a stable supply of mobile phase is fundamental to ensuring the accuracy and reproducibility of analytical results. Depletion of mobile phase not only leads to interruptions in the analytical sequence and sample loss, but can also damage expensive columns and instrument components due to pump idling. Therefore, real-time and accurate monitoring of the mobile phase level is crucial.

[0003] In existing technologies, optical sensing technology has replaced traditional non-optical monitoring technologies such as weighing, barometric pressure, and capacitive sensing. However, due to differences in the absorption and refraction characteristics of different solutions to infrared and other light sources, the intensity of the received reflected light varies. Therefore, a specific mapping relationship between liquid level and reflected light intensity needs to be set for each solution to achieve real-time monitoring of the mobile phase level. However, even for the same solution, differences in the environment of the container's placement (light, temperature, humidity, etc.) may cause the set mapping relationship between liquid level and reflected light intensity to not be perfectly matched, potentially leading to false alarms.

[0004] Therefore, the existing technology has defects and urgently needs improvement. Summary of the Invention

[0005] In view of the above problems, the purpose of this invention is to provide a real-time monitoring and early warning method for mobile phase liquid level in liquid chromatography based on optical sensing. According to the mapping relationship between liquid level and reflected light intensity, the liquid level in the container is calculated by receiving the reflected light intensity. The mapping relationship between liquid level and reflected light intensity is dynamically corrected by combining experimental control commands with the detected liquid level, thereby reducing monitoring errors and improving the accuracy of mobile phase liquid level monitoring.

[0006] The first aspect of this invention provides a method for real-time monitoring and early warning of mobile phase level in liquid chromatography based on optical sensing, comprising:

[0007] Acquire optical detection data including reflected light intensity and monitoring time;

[0008] The reflected light intensity is input into a preset liquid level and reflected light intensity mapping model. The detection liquid level of the solution in each container is calculated according to the mapping relationship between liquid level and reflected light intensity, and the corresponding detection height change curve is plotted.

[0009] When the detected liquid level of any solution is lower than the corresponding preset liquid level threshold, a liquid level warning signal is generated and sent to a preset terminal.

[0010] Obtain experimental control commands and conduct simulation experiments based on the experimental control commands to determine the simulated liquid level of each solution and plot the corresponding simulated height change curves.

[0011] By analyzing the measured height change curve and the simulated height change curve of the same solution, we can determine whether there is a detection error and identify the corresponding abnormal detection data.

[0012] When abnormal detection data is present, the liquid level of the solution is divided into multiple preset height intervals, and a second adjustment priority score for each preset height interval is calculated based on the abnormal detection data.

[0013] The corresponding correction coefficient is calculated based on the second adjustment priority score of each preset height range to correct the mapping relationship between liquid level and reflected light intensity.

[0014] In this solution, acquiring optical detection data including reflected light intensity and monitoring time includes:

[0015] The location of the optical monitoring device is determined based on the geometric parameters of each container; the optical monitoring device includes a light source and an optical sensor.

[0016] The intensity of the reflected light is determined by receiving the reflected light emitted by the light source through the optical sensor.

[0017] The timestamp of the light emitted by the light source is linked to the intensity of the reflected light to determine the optical detection data.

[0018] In this scheme, the step of analyzing the detection height change curve and the simulated height change curve of the same solution to determine whether there is a detection error includes:

[0019] The first solution I is calculated based on the first preset time interval t1. a Simulated height change curve L 1(a-t) And the detection height change curve L 2(a-t) The area M of the enclosed region (a-t) ;

[0020] When the area of ​​the region is M (a-t) When the area exceeds a preset threshold, the first solution I within the first preset time interval t1... a Mark the exception;

[0021] The number of abnormal solution markers within the first preset time interval t1 is counted. When the number of abnormal solution markers is greater than the preset marker number threshold, the liquid level deviation rate of each marked solution is calculated. The deviation rate difference between the maximum liquid level deviation rate and the minimum liquid level deviation rate is calculated. When the deviation rate difference is less than the preset deviation rate difference threshold, it is determined that there is an error in the simulation experiment.

[0022] When the number of abnormal labels in the solution is less than or equal to a preset label number threshold, or the deviation rate difference is greater than or equal to a preset deviation rate difference threshold, it is determined that there is an error in the optical detection data.

[0023] In this solution, the step of determining the corresponding anomaly detection data includes:

[0024] Based on the simulated height change curve L 1(a-t) And the detection height change curve L 2(a-t) Calculate the liquid level error value for each optical acquisition data point in sequence, and plot the liquid level error value variation curve;

[0025] When the liquid level error value change curve meets the preset monotonic change condition, it is determined that there is an abnormality in the optical monitoring device;

[0026] Conversely, the first solution I is calculated over the first preset time interval t1. a The optical detection data was identified as undetermined abnormal data;

[0027] The undetermined abnormal data is verified for abnormality. If the verification is successful, the undetermined abnormal data is determined as abnormal detection data.

[0028] This plan also includes:

[0029] After each monitoring data collection, the corresponding simulated liquid level is updated based on the detected liquid level, and the subsequent simulated liquid level is predicted based on the updated simulated liquid level.

[0030] In this scheme, dividing the solution level into multiple preset height intervals and calculating a second adjustment priority score for each preset height interval based on the anomaly detection data includes:

[0031] The total number of anomaly detection data points;

[0032] When the total number of data exceeds a preset data quantity threshold, the abnormal detection data are classified according to the solution type, and the first influence coefficient of each solution type is determined based on the number of abnormal detection data for each solution type.

[0033] According to the preset height interval, the second solution I containing abnormal detection data will be... b The liquid level is divided into multiple preset height ranges;

[0034] The second solution I b Each anomaly detection data is matched with the multiple preset height intervals, and the cumulative value of each preset height interval is calculated.

[0035] Filter out preset height ranges where the cumulative value is less than a preset cumulative value threshold;

[0036] The cumulative values ​​of the remaining preset height range are normalized to determine the first adjustment priority score for the remaining preset height range;

[0037] For all third solutions I in containers of the same specifications c The first influence coefficient and the first adjustment priority score of each preset height range are weighted and calculated to determine the third solution I. c The second adjustment priority score for each preset height range.

[0038] In this scheme, the step of calculating the corresponding correction coefficient based on the second adjustment priority score of each preset height range to correct the mapping relationship between liquid level and reflected light intensity includes:

[0039] The preset height range with the highest score in the second adjustment priority is determined as the first height range;

[0040] Calculate the third solution I in the first height range c The first error value of the anomaly detection data;

[0041] ;

[0042] Where P is the first error value, k1 is the influence coefficient of solution type, h1 and h2 are the simulated liquid level and detected liquid level corresponding to the abnormal detection data, respectively, T1 is the time interval between the data acquisition time of the abnormal detection data and the previous data acquisition time, and n is the preset height interval.

[0043] Cluster analysis was performed on all first error values ​​to identify multiple clusters;

[0044] The first cluster is obtained by selecting the first x clusters in descending order of the number of error values.

[0045] Calculate the average error value of each first cluster, and perform a weighted calculation based on the corresponding second influence coefficient to determine the correction coefficient for the first height interval;

[0046] The mapping relationship of the middle height of the first height range is corrected according to the correction coefficient.

[0047] This plan also includes:

[0048] Step 1: Filter multiple preset height intervals adjacent to the first height interval based on a preset quantity threshold;

[0049] Step 2: Select the preset height interval with the highest second adjustment priority score from the remaining preset height intervals and determine it as the first height interval for mapping relationship correction;

[0050] Repeat steps 1-2 until the preset height range no longer exists;

[0051] Linear fitting is performed on the correction coefficients for all first height intervals to determine the correction coefficients for other preset height intervals.

[0052] This plan also includes:

[0053] Randomly select y abnormal detection data to verify the correction coefficients of the other preset height ranges, recalculate the corresponding corrected detection liquid level through the corrected mapping relationship, and calculate the corrected height error value between the corrected detection liquid level and the simulated liquid level.

[0054] Calculate the average corrected height error value of the y anomaly detection data. If the average corrected height error value is less than the preset error threshold, the verification is successful.

[0055] Conversely, the correction coefficients for the other preset height intervals are recalculated based on the mapping relationship correction method of the first height interval.

[0056] This plan also includes:

[0057] When multiple optical detection devices are set up to monitor the liquid level of the same container at the same time, the average value of the detected liquid level corresponding to the reflected light intensity obtained by all optical detection devices is calculated to determine the final detected liquid level.

[0058] This invention discloses a real-time monitoring and early warning method for mobile phase liquid level in liquid chromatography based on optical sensing. The method includes: acquiring optical detection data including reflected light intensity and monitoring time; inputting the reflected light intensity into a preset liquid level-reflected light intensity mapping model to calculate the detection liquid level in the container and plotting a detection height change curve; generating a liquid level early warning signal and sending it to a preset terminal when the detection liquid level is lower than a preset liquid level threshold; acquiring experimental control commands, conducting a simulation experiment, determining whether there is a detection error, and identifying abnormal detection data; and correcting the mapping relationship between liquid level and reflected light intensity when abnormal detection data exists. This invention calculates the liquid level in the container based on the mapping relationship between liquid level and reflected light intensity, and dynamically corrects the mapping relationship between liquid level and reflected light intensity through experimental control commands combined with the detected liquid level, thereby reducing monitoring errors and improving the accuracy of mobile phase liquid level monitoring. Attached Figure Description

[0059] Figure 1 A flowchart of the real-time monitoring and early warning method for mobile phase level in liquid chromatography based on optical sensing provided by the present invention is shown.

[0060] Figure 2 A flowchart of the optical detection data acquisition method provided by the present invention is shown;

[0061] Figure 3 A flowchart of the anomaly detection data acquisition method provided by the present invention is shown. Detailed Implementation

[0062] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0063] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0064] Figure 1 A flowchart of the real-time monitoring and early warning method for mobile phase level in liquid chromatography based on optical sensing provided by the present invention is shown.

[0065] like Figure 1 As shown, this invention discloses a method for real-time monitoring and early warning of mobile phase level in liquid chromatography based on optical sensing, comprising:

[0066] S101, acquire optical detection data including reflected light intensity and monitoring time;

[0067] S102, input the reflected light intensity into the preset liquid level and reflected light intensity mapping model, calculate the detection liquid level of the solution in each container according to the mapping relationship between liquid level and reflected light intensity, and draw the corresponding detection height change curve;

[0068] S103, when the detected liquid level of any solution is lower than the corresponding preset liquid level threshold, a liquid level warning signal is generated and sent to a preset terminal;

[0069] S104: Obtain experimental control commands, conduct simulation experiments based on experimental control commands, determine the simulated liquid level of each solution, and plot the corresponding simulated height change curves.

[0070] S105. Analyze the detection height change curve and simulated height change curve of the same solution to determine whether there is a detection error and identify the corresponding abnormal detection data.

[0071] S106, When abnormal detection data exists, the liquid level of the solution is divided into multiple preset height intervals, and the second adjustment priority score of each preset height interval is calculated based on the abnormal detection data;

[0072] S107, calculate the corresponding correction coefficient based on the second adjustment priority score of each preset height range, and correct the mapping relationship between liquid level and reflected light intensity.

[0073] According to an embodiment of the present invention, a container containing a solution is first placed on a monitoring device containing an optical monitoring device. The illumination angle of the light source and the position of the optical sensor are adjusted according to the position of the container so that the optical sensor can receive the reflected light generated by the light source through the surface of the solution and determine the intensity of the reflected light.

[0074] The preset liquid level and reflected light intensity mapping model is obtained by training and analyzing the correspondence between reflected light intensity and liquid level in historical monitoring data. For each light source setting position (height from the plane of the container and horizontal distance from the container), illumination angle and received reflected light intensity, there is a corresponding detection liquid level.

[0075] When the detected liquid level of any solution falls below the corresponding preset liquid level threshold, it is determined that the liquid level is low and there is a risk of mobile phase runoff. A corresponding liquid level warning signal is generated based on the container location coordinates corresponding to this liquid level and sent to the management personnel's computer or mobile device, etc., to remind relevant management personnel to replenish the liquid in a timely manner. The preset liquid level threshold is set by those skilled in the art according to actual needs.

[0076] During the monitoring of the mobile phase level, due to differences in the absorption and refraction characteristics of light by various solutions, a difference may exist between the detected level and the actual level. To avoid a large discrepancy between the detected and actual levels, which could lead to the risk of the mobile phase running dry, a simulation experiment is conducted based on experimental control commands. The simulated level is then used to determine whether there is a detection error in the detected level. The experimental control commands include the type of mobile phase used, the usage time, and the mobile phase flow rate. By analyzing the experimental control commands and considering the container specifications, the container level change corresponding to each experimental control command can be calculated. Based on these commands, a simulation experiment is conducted to determine the simulated level corresponding to the detected solution level. The detected height change curve and the simulated height change curve are plotted with the light beam emission time as the x-axis and the liquid level as the y-axis, respectively.

[0077] The types of detection errors include simulation experiment errors and optical detection data errors, which are determined by comparing the detected height change curve with the simulated height change curve. When optical detection data errors are present, it is determined whether there is an abnormality in the optical monitoring device. If an abnormality is found, corresponding device abnormality information is generated to remind relevant personnel to carry out maintenance; otherwise, the detection data is identified as abnormal detection data. When the total number of abnormal detection data exceeds the system's preset data quantity threshold, the mapping relationship corresponding to different preset height intervals is corrected to ensure the accuracy of liquid level monitoring.

[0078] Figure 2 A flowchart of the optical detection data acquisition method provided by the present invention is shown.

[0079] like Figure 2 As shown, according to an embodiment of the present invention, acquiring optical detection data including reflected light intensity and monitoring time includes:

[0080] S201, Determine the installation location of the optical monitoring device based on the geometric parameters of each container; the optical monitoring device includes a light source and an optical sensor;

[0081] S202, uses an optical sensor to receive reflected light from the light emitted by the light source and determines the intensity of the reflected light;

[0082] S203, bind the timestamp of the light emitted by the light source with the intensity of the reflected light to determine the optical detection data.

[0083] It should be noted that the container's geometric parameters include its shape, capacity, outer diameter, inner diameter, and wall thickness, while the optical monitoring device includes a light source and an optical (range) sensor. The positions of the light source and optical sensor are set based on the container's geometric parameters, allowing the light beam emitted by the light source (usually infrared or laser) to pass through the container surface and be reflected off the liquid surface. The optical sensor then receives the reflected light and determines its intensity.

[0084] According to an embodiment of the present invention, it further includes:

[0085] When multiple optical detection devices are set up to monitor the liquid level of the same container at the same time, the average value of the detected liquid level corresponding to the reflected light intensity obtained by all optical detection devices is calculated to determine the final detected liquid level.

[0086] It should be noted that by setting up multiple sets of corresponding light sources and optical sensors to monitor the solution in the same container and calculating the average value of the detected liquid level, the accuracy of the monitoring data can be guaranteed and the detection error can be reduced.

[0087] According to an embodiment of the present invention, analysis is performed based on the detected height change curve and the simulated height change curve of the same solution to determine whether a detection error exists, including:

[0088] The first solution I is calculated based on the first preset time interval t1 (e.g., 30s). a Simulated height change curve L 1(a-t) And the detection height change curve L 2(a-t) The area M of the enclosed region (a-t) ;

[0089] When the area of ​​the region is M (a-t)When the area exceeds a preset threshold (e.g., 5), the first solution I within the first preset time interval t1... a Mark the exception;

[0090] The number of abnormal solution markers within the first preset time interval t1 is counted (e.g., 2). When the number of abnormal solution markers is greater than the preset marker number threshold, the liquid level deviation rate of each marked solution is calculated. The difference between the maximum liquid level deviation rate and the minimum liquid level deviation rate is calculated. When the difference between the deviation rates is less than the preset deviation rate difference threshold (e.g., 10%), it is determined that there is an error in the simulation experiment.

[0091] If the number of abnormal labels in the solution is less than or equal to the preset label number threshold, or the deviation rate difference is greater than or equal to the preset deviation rate difference threshold, then the optical detection data is determined to have an error.

[0092] It should be noted that the first solution I a The solution 'a' used in the liquid chromatograph can be, in addition to the mobile phase, a washing solution and other auxiliary liquids (such as sample diluent, standard solution, etc.). The area M is the region. (a-t) The start and end times of the first preset time interval t1, and the simulated height change curve L within the first preset time interval t1. 1(a-t) And the detection height change curve L 2(a-t) The area of ​​the enclosed region can be calculated using definite integrals, etc. When the area of ​​the region is M... (a-t) If the difference between the detected liquid level and the simulated liquid level is large within the first preset time interval t1, the solution is marked as abnormal. The number of abnormally marked solutions in the same liquid chromatograph within the first preset time interval t1 is counted. When the number of abnormally marked solutions exceeds the preset mark number threshold, the simulation experiment is verified to have an error.

[0093] The liquid level deviation rate is determined by calculating the ratio of the absolute value of the difference between the detected liquid level and the simulated liquid level to the simulated liquid level.

[0094] Once an error is identified in the simulation experiment, the simulation parameters are corrected based on the acquired detected liquid level, and the correspondence between each experimental control command and the liquid level change height is updated. If an error is identified in the optical detection data, the detected liquid level and simulated liquid level within the first preset time interval t1 are re-verified to determine if a detection error exists, thereby identifying abnormal detection data.

[0095] The first preset time interval t1, the preset area threshold, the preset marker quantity threshold, and the preset deviation rate difference threshold are all set by those skilled in the art according to actual needs.

[0096] Figure 3A flowchart of the anomaly detection data acquisition method provided by the present invention is shown.

[0097] like Figure 3 As shown in the embodiment of the present invention, the step of determining the corresponding anomaly detection data includes:

[0098] S301, based on simulated height change curve L 1(a-t) And the detection height change curve L 2(a-t) Calculate the liquid level error value for each optical acquisition data point in sequence, and plot the liquid level error value variation curve;

[0099] S302, when the liquid level error value change curve meets the preset monotonic change condition, it is judged that there is an abnormality in the optical monitoring device;

[0100] S303, Conversely, the first solution I is calculated using the first preset time interval t1. a The optical detection data was identified as undetermined abnormal data;

[0101] S304, perform anomaly verification on the pending abnormal data. If the verification is successful, the pending abnormal data is identified as anomaly detection data.

[0102] It should be noted that the liquid level error value is the difference between the detected liquid level and the simulated liquid level. Curve fitting is performed on the liquid level error values ​​of adjacent monitoring points to generate a liquid level error value variation curve. By analyzing the liquid level error value variation curve, when it satisfies a monotonically increasing or monotonically decreasing function curve, an anomaly is determined in the optical monitoring device. An anomaly message is then generated and sent to a preset terminal, alerting relevant personnel to inspect and repair the optical monitoring device.

[0103] The anomaly verification method is set by those skilled in the art according to actual needs. For example, by adjusting the illumination angle of other optical monitoring devices, the auxiliary detection liquid level corresponding to the optical monitoring device is calculated, and the liquid level difference between the auxiliary detection liquid level and the detection liquid level is calculated. If the liquid level difference is within the system's preset liquid level difference fluctuation range, then it is determined that there is an error in the simulation experiment; otherwise, the pending abnormal data is determined as abnormal detection data.

[0104] According to an embodiment of the present invention, it further includes:

[0105] After each monitoring data collection, the corresponding simulated liquid level is updated based on the detected liquid level, and the subsequent simulated liquid level is predicted based on the updated simulated liquid level.

[0106] It should be noted that the simulated liquid level is only used as a basis for judging whether there are errors in the simulation experiment, whether there are errors in the optical detection data, and whether there are abnormalities in the optical monitoring device. To ensure the accuracy of the detected liquid level, after each data acquisition, the corresponding simulated liquid level is replaced and updated by the detected liquid level, and the changes in the simulated liquid level corresponding to the subsequent experimental control commands are predicted and updated based on the updated simulated liquid level, thereby avoiding larger deviations between the subsequently detected liquid level and the simulated liquid level.

[0107] According to an embodiment of the present invention, the liquid level of the solution is divided into multiple preset height intervals, and a second adjustment priority score for each preset height interval is calculated based on anomaly detection data, including:

[0108] The total number of anomaly detection data points;

[0109] When the total number of data exceeds the preset data threshold (e.g., 500), the abnormal detection data are classified according to the solution type, and the first influence coefficient of each solution type is determined based on the number of abnormal detection data for each solution type.

[0110] According to a preset height interval (e.g., 1 mm), the second solution I containing abnormal detection data will be... b The liquid level is divided into multiple preset height ranges;

[0111] The second solution I b Each anomaly detection data is matched with multiple preset height intervals, and the cumulative value of each preset height interval is calculated.

[0112] Filter out the preset height range where the cumulative value is less than the preset cumulative value threshold (e.g., 10);

[0113] The cumulative values ​​of the remaining preset height range are normalized to determine the first adjustment priority score for the remaining preset height range;

[0114] For all third solutions I in containers of the same specifications c The first influence coefficient and the first adjustment priority score of each preset height range are weighted and calculated to determine the third solution I. c The second adjustment priority score for each preset height range.

[0115] It should be noted that the intensity of light reflected from a liquid surface is affected by the type of solution. Different solutions exhibit varying absorption and refraction characteristics for infrared and other light sources. Therefore, when analyzing anomaly detection data, it is necessary to first categorize the data according to the solution type and determine the first influence coefficient for each solution type based on the ratio of the number of anomaly detection data points for that type. The sum of all first influence coefficients should be 1.

[0116] Second solution I b This indicates that for the b-th solution with abnormal detection data, its liquid level is divided into multiple preset height intervals based on the corresponding container height. This process is then applied sequentially to the second solution I. b The detection height change curve in each anomaly detection data is analyzed, and the cumulative value of the preset height interval contained in each detection height change curve is incremented by 1. After all anomaly detection data is analyzed, the preset height intervals with cumulative values ​​less than the preset cumulative value threshold (e.g., 10) are filtered out. The cumulative values ​​of the remaining preset height intervals are scaled proportionally to between 0 and 1 using normalization methods such as maximum value minus minimum value, and the first adjustment priority score of each remaining preset height interval is determined.

[0117] Third solution I c This refers to the c-th container of the same type containing the same solution under the same environment (e.g., in the same room). The number of different solution types in each container is counted. Based on a preset height range, the first influence coefficient and the first adjustment priority score for each solution type are multiplied, and the results are summed to determine the third solution I in that container. c The second adjustment priority score for each preset height range, i.e., the third solution I in each container of the same specification. c The second adjustment priority score is the same.

[0118] The preset data quantity threshold, preset height interval, and preset cumulative value threshold are all set by those skilled in the art according to actual needs.

[0119] According to an embodiment of the present invention, a correction coefficient is calculated based on the second adjustment priority score of each preset height range to correct the mapping relationship between liquid level and reflected light intensity, including:

[0120] The preset height range with the highest score in the second adjustment priority is determined as the first height range;

[0121] Calculate the third solution I in the first height interval c The first error value of the anomaly detection data;

[0122] ;

[0123] Where P is the first error value, k1 is the influence coefficient of solution type, h1 and h2 are the simulated liquid level and detected liquid level corresponding to the abnormal detection data, respectively, T1 is the time interval between the data acquisition time of the abnormal detection data and the previous data acquisition time, and n is the preset height interval.

[0124] Cluster analysis was performed on all first error values ​​to identify multiple clusters;

[0125] The first cluster is obtained by selecting the first x clusters in descending order of the number of error values.

[0126] Calculate the average error value of each first cluster, and perform a weighted calculation based on the corresponding second influence coefficient to determine the correction coefficient for the first height interval;

[0127] The mapping relationship of the intermediate height of the first height range is corrected based on the correction factor.

[0128] It should be noted that the cluster analysis of all first error values ​​was performed using the K-means clustering algorithm. The K-means clustering algorithm was used to cluster the third solution I... c The first error value of the anomaly detection data is automatically divided into K clusters.

[0129] The average error value of each first cluster is determined by averaging the first error values ​​in the first cluster. The average error value of each first cluster is then multiplied by its corresponding second influence coefficient, and the results are summed to determine the correction coefficient for the first height interval. The mapping value corresponding to the midpoint of the first height interval is multiplied by this correction coefficient to correct the mapping relationship, thereby eliminating the influence of environmental factors on the mapping relationship and improving the accuracy of the monitoring results.

[0130] The second influence coefficient of a cluster is determined based on the number of first error values ​​within the cluster, and the sum of all second influence coefficients is 1.

[0131] In addition, when determining the first cluster, in order to ensure that the number of first error values ​​in each cluster is greater than the system's preset error value threshold (such as 10), the number of clusters selected can be less than x.

[0132] According to an embodiment of the present invention, it further includes:

[0133] Step 1: Filter multiple preset height intervals adjacent to the first height interval based on a preset quantity threshold;

[0134] Step 2: Select the preset height interval with the highest second adjustment priority score from the remaining preset height intervals and determine it as the first height interval for mapping relationship correction;

[0135] Repeat steps 1-2 until the preset height range no longer exists;

[0136] Linear fitting is performed on the correction coefficients for all first height intervals to determine the correction coefficients for other preset height intervals.

[0137] It should be noted that, to ensure the optimization speed during the mapping relationship correction process, a method of intermittently selecting preset height intervals for optimization is adopted. After the first height interval is corrected, adjacent preset height intervals in both directions that meet a preset threshold (e.g., 3) are filtered out. The preset height interval with the highest second adjustment priority score is then selected as the first height interval, and the corresponding correction coefficient is calculated to correct the mapping relationship between liquid level and reflected light intensity. Through multiple operations, correction coefficients for one or more first height intervals are determined. During linear fitting, the correction coefficients for preset height intervals with cumulative values ​​less than a preset cumulative value threshold are set to 0. Curves showing the change in correction coefficients for different height intervals are plotted using multi-segment linear fitting to determine the correction coefficients for other preset height intervals.

[0138] The preset quantity threshold is set by those skilled in the art according to actual needs.

[0139] According to an embodiment of the present invention, it further includes:

[0140] Randomly select y abnormal detection data to verify the correction coefficients of other preset height ranges, recalculate the corresponding corrected detection liquid level through the corrected mapping relationship, and calculate the corrected height error value between the corrected detection liquid level and the simulated liquid level.

[0141] Calculate the average corrected height error value of y anomaly detection data. If the average corrected height error value is less than the preset error threshold, the verification is successful.

[0142] Conversely, the correction coefficients for other preset height intervals are recalculated based on the mapping relationship correction method of the first height interval.

[0143] It should be noted that, for each other preset height interval, verification is performed sequentially. y abnormal detection data points are randomly selected, and the average corrected height error value is determined by calculating the average of the corrected height error values ​​between the corresponding corrected detection liquid level and the simulated liquid level. The y abnormal detection data points are determined through random sampling. When the average corrected height error value is less than a preset error threshold (e.g., 0.2 mm), it indicates that the mapping relationship is within the system's allowable error range, and the verification is successful, completing the correction of the mapping relationship for that other preset height interval. Otherwise, the correction coefficient for that other preset height interval is recalculated according to the mapping relationship correction method for the first height interval.

[0144] The preset error threshold is set by those skilled in the art according to actual needs.

[0145] According to an embodiment of the present invention, it further includes:

[0146] Based on the analysis of the height change curve and experimental control commands, the liquid replacement time of each solution in the corresponding container is determined in combination with the preset liquid level threshold.

[0147] Based on the liquid replacement time of each solution's corresponding container, a simulated liquid replacement operation is performed using a preset liquid replacement simulation model;

[0148] When the simulated liquid replacement operation cannot be achieved, the preset liquid level threshold of one or more solutions in the corresponding containers is dynamically adjusted until the simulated liquid replacement operation is met.

[0149] It should be noted that, in order to avoid the liquid chromatography mobile phase running dry, based on the detection height change curve, the simulation is continued based on the experimental control command to determine the time when the simulated liquid level is equal to the preset liquid level threshold, and this time is determined as the liquid replacement time of the corresponding container for that solution.

[0150] All information (including but not limited to user equipment information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals (including but not limited to signals transmitted between user terminals and other devices) involved in this application have been authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the "optical detection data" and "experimental control instructions" involved in this disclosure were obtained under full authorization.

[0151] This invention discloses a real-time monitoring and early warning method for mobile phase liquid level in liquid chromatography based on optical sensing. The method includes: acquiring optical detection data including reflected light intensity and monitoring time; inputting the reflected light intensity into a preset liquid level-reflected light intensity mapping model to calculate the detection liquid level in the container and plotting a detection height change curve; generating a liquid level early warning signal and sending it to a preset terminal when the detection liquid level is lower than a preset liquid level threshold; acquiring experimental control commands, conducting a simulation experiment, determining whether there is a detection error, and identifying abnormal detection data; and correcting the mapping relationship between liquid level and reflected light intensity when abnormal detection data exists. This invention calculates the liquid level in the container based on the mapping relationship between liquid level and reflected light intensity, and dynamically corrects the mapping relationship between liquid level and reflected light intensity through experimental control commands combined with the detected liquid level, thereby reducing monitoring errors and improving the accuracy of mobile phase liquid level monitoring.

[0152] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0153] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0154] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0155] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0156] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

Claims

1. A method for real-time monitoring and early warning of mobile phase level in liquid chromatography based on optical sensing, characterized in that, include: Acquire optical detection data including reflected light intensity and monitoring time; The reflected light intensity is input into a preset liquid level and reflected light intensity mapping model. The detection liquid level of the solution in each container is calculated according to the mapping relationship between liquid level and reflected light intensity, and the corresponding detection height change curve is plotted. When the detected liquid level of any solution is lower than the corresponding preset liquid level threshold, a liquid level warning signal is generated and sent to a preset terminal. Obtain experimental control commands and conduct simulation experiments based on the experimental control commands to determine the simulated liquid level of each solution and plot the corresponding simulated height change curves. By analyzing the measured height change curve and the simulated height change curve of the same solution, we can determine whether there is a detection error and identify the corresponding abnormal detection data. When abnormal detection data is present, the liquid level of the solution is divided into multiple preset height intervals, and a second adjustment priority score for each preset height interval is calculated based on the abnormal detection data. The corresponding correction coefficient is calculated based on the second adjustment priority score of each preset height range to correct the mapping relationship between liquid level and reflected light intensity. The process of dividing the solution level into multiple preset height intervals and calculating a second adjustment priority score for each preset height interval based on the anomaly detection data includes: The total number of anomaly detection data points; When the total number of data exceeds a preset data quantity threshold, the abnormal detection data are classified according to the solution type, and the first influence coefficient of each solution type is determined based on the number of abnormal detection data for each solution type. According to the preset height interval, the second solution I containing abnormal detection data will be... b The liquid level is divided into multiple preset height ranges; The second solution I b Each anomaly detection data is matched with the multiple preset height intervals, and the cumulative value of each preset height interval is calculated. Filter out preset height ranges where the cumulative value is less than a preset cumulative value threshold; The cumulative values ​​of the remaining preset height range are normalized to determine the first adjustment priority score for the remaining preset height range; For all third solutions I in containers of the same specifications c The first influence coefficient and the first adjustment priority score of each preset height range are weighted and calculated to determine the third solution I. c The second adjustment priority score for each preset height range; The step of calculating the corresponding correction coefficient based on the second adjustment priority score of each preset height range to correct the mapping relationship between liquid level and reflected light intensity includes: The preset height range with the highest score in the second adjustment priority is determined as the first height range; Calculate the third solution I in the first height range c The first error value of the anomaly detection data; ； Where P is the first error value, k1 is the influence coefficient of solution type, h1 and h2 are the simulated liquid level and detected liquid level corresponding to the abnormal detection data, respectively, T1 is the time interval between the data acquisition time of the abnormal detection data and the previous data acquisition time, and n is the preset height interval. Cluster analysis was performed on all first error values ​​to identify multiple clusters; The first cluster is obtained by selecting the first x clusters in descending order of the number of error values. Calculate the average error value of each first cluster, and perform a weighted calculation based on the corresponding second influence coefficient to determine the correction coefficient for the first height interval; The mapping relationship of the middle height of the first height range is corrected according to the correction coefficient.

2. The method for real-time monitoring and early warning of mobile phase level in liquid chromatography based on optical sensing according to claim 1, characterized in that, The acquisition of optical detection data, including reflected light intensity and monitoring time, includes: The location of the optical monitoring device is determined based on the geometric parameters of each container; the optical monitoring device includes a light source and an optical sensor. The intensity of the reflected light is determined by receiving the reflected light emitted by the light source through the optical sensor. The timestamp of the light emitted by the light source is linked to the intensity of the reflected light to determine the optical detection data.

3. The method for real-time monitoring and early warning of mobile phase level in liquid chromatography based on optical sensing according to claim 1, characterized in that, The analysis based on the detected height change curve and the simulated height change curve of the same solution to determine whether there is a detection error includes: The first solution I is calculated based on the first preset time interval t1. a Simulated height change curve L 1(a-t) And the detection height change curve L 2(a-t) The area M of the enclosed region (a-t) ; When the area of ​​the region is M (a-t) When the area exceeds a preset threshold, the first solution I within the first preset time interval t1... a Mark the exception; The number of abnormal solution markers within the first preset time interval t1 is counted. When the number of abnormal solution markers is greater than the preset marker number threshold, the liquid level deviation rate of each marked solution is calculated. The deviation rate difference between the maximum liquid level deviation rate and the minimum liquid level deviation rate is calculated. When the deviation rate difference is less than the preset deviation rate difference threshold, it is determined that there is an error in the simulation experiment. When the number of abnormal labels in the solution is less than or equal to a preset label number threshold, or the deviation rate difference is greater than or equal to a preset deviation rate difference threshold, it is determined that there is an error in the optical detection data.

4. The method for real-time monitoring and early warning of mobile phase level in liquid chromatography based on optical sensing according to claim 1, characterized in that, The step of determining the corresponding anomaly detection data includes: Based on the simulated height change curve L 1(a-t) And the detection height change curve L 2(a-t) Calculate the liquid level error value for each optical acquisition data point in sequence, and plot the liquid level error value variation curve; When the liquid level error value change curve meets the preset monotonic change condition, it is determined that there is an abnormality in the optical monitoring device; Conversely, the first solution I is calculated over the first preset time interval t1. a The optical detection data was identified as undetermined abnormal data; The undetermined abnormal data is verified for anomalies. If the verification is successful, the undetermined abnormal data is determined as anomaly detection data.

5. The method for real-time monitoring and early warning of mobile phase level in liquid chromatography based on optical sensing according to claim 1, characterized in that, Also includes: After each monitoring data collection, the corresponding simulated liquid level is updated based on the detected liquid level, and the subsequent simulated liquid level is predicted based on the updated simulated liquid level.

6. The method for real-time monitoring and early warning of mobile phase level in liquid chromatography based on optical sensing according to claim 1, characterized in that, Also includes: Step 1: Filter multiple preset height intervals adjacent to the first height interval based on a preset quantity threshold; Step 2: Select the preset height interval with the highest second adjustment priority score from the remaining preset height intervals and determine it as the first height interval for mapping relationship correction; Repeat steps 1-2 until the preset height range no longer exists; Linear fitting is performed on the correction coefficients for all first height intervals to determine the correction coefficients for other preset height intervals.

7. The method for real-time monitoring and early warning of mobile phase level in liquid chromatography based on optical sensing according to claim 6, characterized in that, Also includes: Randomly select y abnormal detection data to verify the correction coefficients of the other preset height ranges, recalculate the corresponding corrected detection liquid level through the corrected mapping relationship, and calculate the corrected height error value between the corrected detection liquid level and the simulated liquid level. Calculate the average corrected height error value of the y anomaly detection data. If the average corrected height error value is less than the preset error threshold, the verification is successful. Conversely, the correction coefficients for the other preset height intervals are recalculated based on the mapping relationship correction method of the first height interval.

8. The method for real-time monitoring and early warning of mobile phase level in liquid chromatography based on optical sensing according to claim 1, characterized in that, Also includes: When multiple optical detection devices are set up to monitor the liquid level of the same container at the same time, the average value of the detected liquid level corresponding to the reflected light intensity obtained by all optical detection devices is calculated to determine the final detected liquid level.

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