A podophyllotoxin extraction process monitoring system based on data analysis

Abstract

This invention discloses a data analysis-based monitoring system for the podophyllotoxin extraction process, specifically relating to the pharmaceutical field. The system includes a podophyllotoxin extraction data acquisition module, a podophyllotoxin extraction parameter monitoring module, a data preprocessing module, an impact data analysis module, an anomaly diagnosis module, a process optimization module, and a historical data storage module. The data analysis-based podophyllotoxin extraction process monitoring system completes the task of collecting and transmitting the first basic data during the podophyllotoxin extraction process through the podophyllotoxin extraction data acquisition module, providing a solid data foundation. Through the impact data analysis module, it obtains the second extraction effect, accurately grasping the degree of influence of each parameter during the extraction process on the final extraction effect, providing a quantitative basis for the extraction effect. Through the process optimization module, it obtains process optimization parameters, allowing for rapid and accurate adjustment of process parameters based on actual production conditions to achieve the best production results.

Description

Technical Field

[0001] This invention relates to the field of pharmaceutical technology, and more specifically, to a data analysis-based monitoring system for the podophyllotoxin extraction process. Background Technology

[0002] With the rapid development of biotechnology and pharmaceutical technology, podophyllotoxin, as a natural product with broad-spectrum anti-tumor activity, is of vital importance for ensuring product quality, improving production efficiency, and ensuring production safety by monitoring changes in various parameters during the extraction process.

[0003] Traditional extraction processes have been continuously optimized, resulting in an increased extraction rate of podophyllotoxin, providing more abundant medicinal raw materials for the treatment of diseases such as condyloma acuminata on the male and female external genitalia; the combination of ultrasound-assisted extraction and traditional extraction techniques has improved extraction efficiency and purity; and the development of extraction technology has gradually enhanced the safety of the production process.

[0004] However, in actual use, it still has some shortcomings. For example, most of the parameters in the extraction process rely on manual monitoring and recording at regular intervals, which makes it impossible to accurately grasp the real-time status changes in the extraction process, thus affecting the stability of product quality. It is difficult to detect and make effective adjustments in time for abnormal situations that occur in the extraction process, resulting in waste of raw materials. There is a lack of sufficient data support for the optimization of the extraction process, making it difficult to quickly and accurately adjust the process parameters according to the actual production situation to achieve the best production effect. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art, the present invention provides a data analysis-based monitoring system for the podophyllotoxin extraction process, which addresses the problems mentioned in the background art through the following solutions.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A data analysis-based monitoring system for the podophyllotoxin extraction process, characterized in that it includes a system operation database, a system central processing module, and a user information terminal, and further includes:

[0008] Podophyllotoxin Extraction Data Acquisition Module: This module responds to the high-precision sensors installed in the podophyllotoxin extraction process monitoring system, acquires the first basic data during the podophyllotoxin extraction process in real time, and transmits it to the podophyllotoxin extraction parameter monitoring module.

[0009] The podophyllotoxin extraction parameter monitoring module is used to monitor the first basic data in the podophyllotoxin extraction process in real time through visualization methods, and to perform monitoring and judgment operations. The monitoring and judgment operations are used to obtain the first extraction effect corresponding to the first basic data, and transmit the first extraction effect without abnormalities to the data acquisition preprocessing module.

[0010] Data acquisition preprocessing module: used to preprocess the first extraction effect in the podophyllotoxin extraction parameter monitoring module. The preprocessing operation is used to obtain the second basic data corresponding to the first extraction effect and transmit it to the impact data analysis module.

[0011] Impact Data Analysis Module: Used to obtain the impact analysis model of podophyllotoxin, obtain the second extraction effect corresponding to the second basic data based on the second basic data through the second basic data, and transmit the second extraction effect without abnormalities to the process optimization module;

[0012] Anomaly Diagnosis Module: Used to acquire anomaly diagnosis model, and based on the first extraction effect transmitted by the podophyllotoxin extraction parameter monitoring module and the second extraction effect transmitted by the impact data analysis module, obtain the third extraction effect through the anomaly diagnosis model;

[0013] Process optimization module: used to obtain intelligent optimization models and obtain process optimization parameters based on the intelligent optimization models;

[0014] The historical data storage module is used to establish a data warehouse for podophyllotoxin extraction, which stores monitoring data during the podophyllotoxin extraction process in real time. The data warehouse includes the start and end times of each extraction stage of podophyllotoxin, the setting values ​​of key parameters in the extraction process, the initial quality of raw materials, the extraction effect indicators of each extraction stage, and the analysis reports generated by each module during the extraction process.

[0015] The system's operating database includes all data text from the podophyllotoxin extraction process monitoring system, and collects information text output from each module in real time. The system's central processing module is used to control the information text instructions output by each module in the central control system. The user information terminal is a device for receiving information output from the podophyllotoxin extraction process monitoring system.

[0016] Preferably, the podophyllotoxin extraction data acquisition module includes the following basic data: the initial mass of podophyllotoxin in the raw material, the real-time temperature values ​​at each stage in the extraction container, the real-time pressure values ​​of each enclosed space in the extraction equipment, the real-time flow rate of the solvent inflow, the real-time flow rate of the extract outflow, the real-time concentration of podophyllotoxin in the extract, the real-time concentration of each impurity in the extract, the real-time concentration of the solvent, and the pH data of the extraction environment.

[0017] The stages corresponding to the temperature acquisition include the extraction initiation stage, heating process, reflux stage, and cooling stage; the enclosed spaces corresponding to the pressure acquisition include the reaction vessel, distillation apparatus, and connecting pipelines.

[0018] Preferably, in the data analysis module, the second extraction effect includes the extraction rate, the purity estimate, and the quantitative value of the contribution of each parameter to the extraction effect.

[0019] Preferably, the impact data analysis module obtains the second extraction effect corresponding to the second basic data, specifically including:

[0020] Based on the real-time inflow rate IQ of the solvent and the real-time outflow rate OQ of the extract, the total volume EV of the extract is calculated, specifically expressed as:

[0021] ,

[0022] Where t1 represents the effective time to start extraction, t2 represents the planned end time of extraction, t represents the index of extraction time, IQ(t) represents the real-time flow rate of solvent inflow at time t, and OQ(t) represents the real-time flow rate of extract outflow at time t.

[0023] Based on the real-time concentration CG of podophyllotoxin in the extract, the total volume EV of the extract, and the initial mass CM0 of podophyllotoxin in the raw material, the extraction rate ER of podophyllotoxin is calculated, specifically expressed as follows:

[0024] ,

[0025] Where t1 represents the effective start time of extraction, t2 represents the planned end time of extraction, t represents the index of the extraction time, and CG t The concentration of podophyllotoxin in the extract at time t is expressed as EV. t This represents the total volume of the extract at time t.

[0026] Preferably, the second extraction effect corresponding to the second basic data specifically includes:

[0027] Based on the real-time concentration CG of podophyllotoxin in the extract and the real-time concentration C of each impurity in the extract. i The estimated purity (PG) of podophyllotoxin was calculated and expressed as follows:

[0028] ,

[0029] Among them, CG tLet t represent the real-time concentration of podophyllotoxin in the extract at time t, t1 represent the effective time to start extraction, t2 represent the planned end time of extraction, t represent the index of the extraction time, i represent the index of each impurity in the extract, n represent the total number of impurities in the extract, and C represent the total number of impurities in the extract. it This represents the real-time concentration of impurity i in the extract at time t.

[0030] Preferably, the anomaly diagnosis module obtains the third extraction effect, specifically including:

[0031] The first extraction result transmitted by the podophyllotoxin extraction parameter monitoring module is passed through the anomaly diagnosis model, and the abnormal parameters stored in the historical data storage module are passed through the anomaly diagnosis model. The results of the two are compared according to the preset anomaly judgment rules. The preset anomaly judgment rules are the relationship logic between each parameter and the podophyllotoxin extraction anomaly established within the anomaly diagnosis model.

[0032] The abnormal parameter cases are matched with historical cases involving parameters in the historical data storage module using an anomaly diagnosis model. The similarity value between the abnormal parameter cases and the historical cases is calculated to determine the type of anomaly.

[0033] Once the type of abnormal situation is determined, the absolute difference of the parameter deviating from the normal range is calculated, and the product of the abnormal parameter's deviation from the normal range and its weight is calculated to obtain the impact value of the abnormal parameter.

[0034] Preferably, the process optimization module acquires process optimization parameters, specifically including:

[0035] A database is constructed to store the relationship between parameters corresponding to the podophyllotoxin extraction process. The key parameter database stores the correspondence between key parameters and intelligent optimization models.

[0036] Based on the different extraction stages of the podophyllotoxin extraction process, key parameters are classified and organized to generate combinations of key parameters and extraction stages, including the optimal value range of key parameters and corresponding stages, the impact data of different parameter values ​​on extraction rate and purity, and various abnormal situations and corresponding solutions.

[0037] The extraction rate, purity estimate, and contribution of each parameter to the extraction effect included in the second extraction effect, and the abnormality type, abnormality severity quantification value, and abnormality cause included in the third extraction effect, are classified and extracted according to key parameters, namely temperature, pressure, flow rate, concentration, and pH value, forming a second extraction effect subset and a third extraction effect subset corresponding to each key parameter.

[0038] The second and third extraction effect subsets corresponding to the key parameters are used as a whole set and optimized using the corresponding calculation method of the intelligent optimization model in the key parameter database to obtain the target process parameter combination. The target process parameter combination is the storage method for process optimization parameters.

[0039] Preferably, the process optimization module acquires process optimization parameters, specifically including:

[0040] Using temperature as a key parameter, this study explains the extraction efficiency (ER) of podophyllotoxin, the estimated purity (PG) of podophyllotoxin, and the quantitative value (CT) of the contribution of temperature to the extraction effect. EE Calculate the temperature parameter adjustment value EY T Specifically, it is expressed as:

[0041] ,

[0042] Among them, EY Tt Let t represent the temperature parameter adjustment value at time t, t1 represent the effective time to start extraction, t2 represent the planned end time of extraction, t represent the index of the extraction time, and R(t) represent the rate of change of podophyllotoxin extraction efficiency over time caused by the temperature parameter stored in the key parameter database.

[0043] To achieve the above objectives, the present invention provides the following technical solution: a data analysis-based method for monitoring the podophyllotoxin extraction process, comprising:

[0044] S1: Collect podophyllotoxin extraction data: In response to the high-precision sensors installed in the podophyllotoxin extraction process monitoring system, acquire the first basic data in the podophyllotoxin extraction process in real time;

[0045] S2: Monitoring Podophyllotoxin Extraction Parameters: The first basic data during the podophyllotoxin extraction process is monitored in real time using visualization methods, and monitoring and judgment operations are performed. The monitoring and judgment operations are used to obtain the first extraction effect corresponding to the first basic data.

[0046] S3: Preprocessing the collected data: Performing preprocessing operations on the first extraction result to obtain the second basic data corresponding to the first extraction result;

[0047] S4: Analyze the impact of data: Obtain the podophyllotoxin impact analysis model, and based on the podophyllotoxin impact analysis model, obtain the second extraction effect corresponding to the second basic data through the second basic data;

[0048] S5: Diagnose anomalies: Obtain an anomaly diagnosis model, and based on the first and second extraction results, obtain a third extraction result through the anomaly diagnosis model;

[0049] S6: Optimize extraction process parameters: Obtain intelligent optimization model, and obtain process optimization parameters based on intelligent optimization model;

[0050] S7: Integrate historical data: Establish a data warehouse for podophyllotoxin extraction, and store monitoring data during the podophyllotoxin extraction process in real time. The data warehouse includes the start and end times of each extraction stage of podophyllotoxin, the setting values ​​of key parameters in the extraction process, the initial quality of raw materials, the extraction effect indicators of each extraction stage, and the analysis reports generated by each module during the extraction process.

[0051] The technical effects and advantages of this invention are as follows:

[0052] 1. This invention efficiently and accurately completes the task of collecting and transmitting the first basic data during the podophyllotoxin extraction process through the podophyllotoxin extraction data acquisition module, providing a solid data foundation for the normal operation of the podophyllotoxin extraction process monitoring system;

[0053] 2. This invention obtains the second extraction effect through the influence data analysis module, accurately grasps the degree of influence of each parameter on the final extraction effect during the extraction process, and provides a quantitative basis for the extraction effect;

[0054] 3. This invention obtains process optimization parameters through a process optimization module, providing data support for extracting process optimizations, and quickly and accurately adjusts process parameters according to actual production conditions to achieve the best production results. Attached Figure Description

[0055] Figure 1 This is a system flowchart of the present invention.

[0056] Figure 2 This is a system step diagram of the present invention.

[0057] Figure 3 This is a schematic diagram of the system structure of the present invention. Detailed Implementation

[0058] 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 embodiments of the present invention, and not all embodiments. 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.

[0059] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to and includes any or all possible combinations of one or more of the listed items.

[0060] Hereinafter, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first," "second," and "third" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0061] As attached Figure 1 The system shown is a data analysis-based monitoring system for the podophyllotoxin extraction process, which includes a system operation database, a system central processing module and a user information terminal. It also includes a podophyllotoxin extraction data acquisition module, a podophyllotoxin extraction parameter monitoring module, an acquisition data preprocessing module, an impact data analysis module, an anomaly diagnosis module, a process optimization module and a historical data storage module.

[0062] The system's operating database includes all data text from the podophyllotoxin extraction process monitoring system, and collects information text output from each module in real time. The system's central processing module is used to control the information text instructions output by each module in the central control system. The user information terminal is a device for receiving information output from the podophyllotoxin extraction process monitoring system.

[0063] The podophyllotoxin extraction data acquisition module is used to respond to the high-precision sensors installed in the podophyllotoxin extraction process monitoring system, acquire the first basic data in the podophyllotoxin extraction process in real time, and transmit it to the podophyllotoxin extraction parameter monitoring module.

[0064] In one possible implementation, obtaining the first basic data during the podophyllotoxin extraction process includes: selecting high-precision sensors based on the podophyllotoxin extraction process, including installing high-sensitivity temperature sensors in the heating and solution mixing areas of the extraction container, installing stable pressure sensors at the inlet and outlet of the extraction equipment and inside the reaction vessel, using a flow meter to measure the solvent flow rate, detecting the concentration of the active ingredient in the mixed solution using a concentration sensor, and measuring the pH value of the solution using a pH sensor.

[0065] Specifically, each sensor establishes a connection with the podophyllotoxin extraction data acquisition module through a compatible data cable. For sensors connected by wires, a data cable with good shielding performance is used to reduce the impact of external electromagnetic interference on data transmission. For sensors connected wirelessly, the wireless communication link between the sensor and the podophyllotoxin extraction data acquisition module is configured according to the wireless communication protocol to meet the requirements of the extraction environment for equipment wiring flexibility.

[0066] In one possible implementation, acquiring the first basic data during the podophyllotoxin extraction process also includes: based on the start of the podophyllotoxin extraction process, i.e., when any change occurs in the sensor monitoring parameters, high-precision sensors installed at each extraction location begin to monitor the corresponding physical and chemical quantities in real time; during the extraction process, a transmission frequency of 2 times per second is specifically set for the monitored temperature and flow rate data.

[0067] Specifically, the first basic data includes the initial mass of podophyllotoxin in the raw material, the real-time temperature values ​​at each stage in the extraction container, the real-time pressure values ​​in each enclosed space in the extraction equipment, the real-time flow rate of the solvent inflow, the real-time flow rate of the extract outflow, the real-time concentration of podophyllotoxin in the extract, the real-time concentration of each impurity in the extract, the real-time concentration of the solvent, and the pH data of the extraction environment.

[0068] It should be noted that the stages corresponding to the first basic data acquisition temperature include the extraction initiation stage, heating process, reflux stage, and cooling stage; the enclosed space corresponding to the acquisition pressure includes the reaction vessel, distillation device, and connecting pipelines.

[0069] The podophyllotoxin extraction parameter monitoring module is used to monitor the first basic data in the podophyllotoxin extraction process in real time through visualization methods, and to perform monitoring and judgment operations. The monitoring and judgment operations are used to obtain the first extraction effect corresponding to the first basic data, and transmit the first extraction effect without abnormalities to the data acquisition preprocessing module.

[0070] In one possible implementation, obtaining the first extraction effect corresponding to the first basic data includes: displaying the first basic data transmitted from the podophyllotoxin extraction data acquisition module through a visualization operation;

[0071] Specifically, the visualization operation includes dynamically displaying the real-time temperature changes at each stage of the extraction process using line graphs, comparing the real-time pressure values ​​of each enclosed space using bar charts, displaying the real-time flow rates of solvent inflow and extract outflow using real-time updated flow rate tables, presenting the real-time concentration changes of podophyllotoxin in the extract and the real-time concentration changes of the solvent through concentration change curves, and displaying the pH data of the extraction environment in the form of a digital dashboard.

[0072] In one possible implementation, obtaining the first extraction effect corresponding to the first basic data further includes: setting a standard parameter range, performing monitoring and judgment operations on the visualized first basic data, wherein the monitoring and judgment operations are based on comparing and judging the set standard parameter range with the actual collected data, and the standard parameter range is set based on a large amount of historical data stored in the historical data storage module and adjustments made by professionals.

[0073] Compare the real-time temperature value with the set suitable temperature range. If the real-time temperature is within the range, the temperature parameter is considered normal. If it is outside the range, whether too high or too low, it is judged as an abnormal temperature condition.

[0074] The real-time pressure values ​​of each enclosed space are compared with the corresponding standard pressure range. When the pressure value is within the specified range, the pressure parameter is judged to be normal; otherwise, it is considered to be abnormal.

[0075] Check the deviation between the real-time flow rate of solvent inflow and extract outflow and the standard value. If the deviation between the actual flow rate and the standard value is within the allowable range, the flow rate parameter is normal. If the deviation is too large, it is judged as an abnormal flow rate.

[0076] The real-time concentrations of podophyllotoxin in the extract and solvent were judged according to the pre-set target range of active ingredient concentration and reasonable range of solvent concentration. If the podophyllotoxin concentration did not reach the expected level or the solvent concentration deviated from the standard, it was considered an abnormal concentration situation.

[0077] The real-time monitored pH value is compared with the pH range suitable for podophyllotoxin extraction. If the pH value is within the range, the acid-base parameter is normal; if it is not, it is judged as an abnormal pH value.

[0078] In this embodiment, the temperature range for the initial extraction stage is set to 20°C to 30°C, the temperature during the heating process is 60°C to 80°C, the temperature during the reflux stage is 70°C to 90°C, and the temperature during the cooling stage is gradually reduced to 25°C to 35°C.

[0079] The extraction equipment is maintained at a pressure close to standard atmospheric pressure, i.e., 101.3 kPa; the pressure range is set to 5 kPa to 20 kPa when extracting impurities by vacuum distillation.

[0080] The solvent inflow rate is set to 5L to 20L per hour; the extract outflow rate is set to 3L to 18L per hour.

[0081] The solvent concentration is between 70% and 95%. During the extraction process, the concentration of podophyllotoxin in the extract gradually changes at different stages, with the initial concentration set at 0.1% to 1%. Upon completion of extraction, the concentration of podophyllotoxin in the extract reaches 5% to 15%.

[0082] The suitable pH range for podophyllotoxin extraction is 4.5–6.5;

[0083] In one possible implementation, obtaining the first extraction effect corresponding to the first basic data further includes: when all parameters corresponding to the first basic data are in a normal state, the extraction process is determined to be running normally, and the corresponding extraction effect is the first extraction effect without abnormalities, which is then transmitted to the data acquisition preprocessing module; if one or more parameters are abnormal, it is determined to be abnormal, and the data is directly transmitted to the abnormality diagnosis module.

[0084] Specifically, the first extraction effect corresponding to the first basic data includes each parameter corresponding to the first basic data, the status identifier of each parameter (Y represents the normal situation, N represents the abnormal situation), and the extraction parameter evaluation table.

[0085] In this embodiment, the status identifier of the temperature parameter is represented by temperature parameter Y, and the current temperature value is 63℃, which is within the preset range of 60℃-80℃; when there are abnormal parameters, the parameter evaluation table will list the name of the abnormal parameter and the specific abnormal situation.

[0086] The data acquisition preprocessing module is used to preprocess the first extraction effect corresponding to the podophyllotoxin extraction parameter monitoring module. The preprocessing operation is used to obtain the second basic data corresponding to the first extraction effect. The second basic data is the key information corresponding to the first extraction effect with high quality and uniform format and dimensions.

[0087] Specifically, after the status identifier of each parameter corresponding to the first extraction effect in the podophyllotoxin extraction parameter monitoring module is Y, the podophyllotoxin extraction process monitoring system can obtain the second basic data corresponding to the first extraction effect through preprocessing. The preprocessing steps are as follows: Data verification: Check missing values ​​and data format through data verification mechanism; Data cleaning: Remove noise and interference factors; Data encoding and conversion: Normalize each parameter to the basic form, and encode and convert the first extraction effect data. The encoding and conversion operations include converting decimal data into binary data or representing data in a specific vector form according to encoding rules.

[0088] The impact data analysis module is used to obtain the podophyllotoxin impact analysis model. Based on the podophyllotoxin impact analysis model, the second extraction effect corresponding to the second basic data is obtained through the second basic data.

[0089] Specifically, the podophyllotoxin impact analysis model is a pre-built learning model. By inputting the second basic data into the podophyllotoxin impact analysis model, the model obtains the second extraction effect based on the second basic data. The second extraction effect corresponding to the absence of abnormalities is sent to the process optimization module, and the second extraction effect corresponding to the presence of abnormalities is sent to the anomaly judgment module.

[0090] It should be noted that the second extraction effect corresponding to abnormal situations includes the extraction rate and purity estimates obtained from the podophyllotoxin influence analysis model differing significantly from the expected target values; and the interrelationships between various parameters not conforming to normal physicochemical laws or past experience data.

[0091] In this embodiment, the solubility of podophyllotoxin did not increase but decreased when the temperature increased, and the solvent concentration did not change accordingly. This indicates an abnormal situation where the relationship between the parameters does not conform to normal physicochemical laws.

[0092] In one possible implementation, obtaining the second extraction effect corresponding to the second basic data includes: the podophyllotoxin impact analysis model generates a mathematical relationship between each parameter and the podophyllotoxin extraction effect based on a large amount of podophyllotoxin extraction experimental data and historical production data; the parameter data corresponding to the received second basic data are arranged and organized, and the corresponding second extraction effect is obtained according to the relationship logic between each parameter and the podophyllotoxin extraction effect established within the model.

[0093] Specifically, the second extraction effect includes the extraction rate, the estimated purity, and the quantitative values ​​of the contribution of each parameter to the extraction effect;

[0094] In one possible implementation, obtaining the second extraction effect corresponding to the second basic data further includes: calculating the total volume EV of the extract based on the real-time flow rate IQ of the solvent inflow and the real-time flow rate OQ of the extract outflow, specifically expressed as:

[0095] ,

[0096] Where t1 represents the effective time to start extraction, t2 represents the planned end time of extraction, t represents the index of extraction time, IQ(t) represents the real-time flow rate of solvent inflow at time t, and OQ(t) represents the real-time flow rate of extract outflow at time t.

[0097] Based on the real-time concentration CG of podophyllotoxin in the extract, the total volume EV of the extract, and the initial mass CM0 of podophyllotoxin in the raw material, the extraction rate ER of podophyllotoxin is calculated, specifically expressed as follows:

[0098] ,

[0099] Where t1 represents the effective start time of extraction, t2 represents the planned end time of extraction, t represents the index of the extraction time, and CG t The concentration of podophyllotoxin in the extract at time t is expressed as EV. t This represents the total volume of the extract at time t;

[0100] Based on the real-time concentration CG of podophyllotoxin in the extract and the real-time concentration C of each impurity in the extract. i The estimated purity (PG) of podophyllotoxin was calculated and expressed as follows:

[0101] ,

[0102] Among them, CG t Let t represent the real-time concentration of podophyllotoxin in the extract at time t, t1 represent the effective time to start extraction, t2 represent the planned end time of extraction, t represent the index of the extraction time, i represent the index of each impurity in the extract, n represent the total number of impurities in the extract, and C represent the total number of impurities in the extract. it This represents the real-time concentration of impurity i in the extract at time t.

[0103] The contribution of temperature to the extraction effect is illustrated by the quantitative value of temperature CT, which is calculated based on the temperature change ΔT and the extraction rate ER of podophyllotoxin during the effective time from the start of extraction to the planned end time. EE Specifically, it is expressed as:

[0104] ,

[0105] Wherein, ER(T) represents the extraction rate of podophyllotoxin at temperature T.

[0106] The anomaly diagnosis module is used to obtain an anomaly diagnosis model, and based on the first extraction effect transmitted by the podophyllotoxin extraction parameter monitoring module and the second extraction effect transmitted by the impact data analysis module, a third extraction effect is obtained through the anomaly diagnosis model.

[0107] Specifically, the anomaly diagnosis model is a pre-built learning model. It inputs the first extraction effect transmitted by the podophyllotoxin extraction parameter monitoring module or the second extraction effect transmitted by the influence data analysis module into the anomaly diagnosis model. The anomaly diagnosis model obtains the third extraction effect based on the first extraction effect or the second basic data, and sends the third extraction effect to the process optimization module.

[0108] Specifically, the third extraction effect includes anomaly identification, where NN represents the presence of anomalies and YY represents the absence of anomalies, the anomaly type, the anomaly severity quantification value, and the anomaly cause.

[0109] In one possible implementation, obtaining the third extraction effect includes: passing the first extraction effect transmitted by the podophyllotoxin extraction parameter monitoring module through an anomaly diagnosis model, and passing the abnormal parameters stored in the historical data storage module through the anomaly diagnosis model, comparing the two results according to a preset anomaly judgment rule, wherein the preset anomaly judgment rule is the relationship logic between each parameter and the podophyllotoxin extraction anomaly established within the anomaly diagnosis model; if an anomaly is determined to exist, the anomaly is identified as NN; if the parameters are determined to be normal, the anomaly is identified as YY.

[0110] In one possible implementation, obtaining the third extraction effect further includes: obtaining specific monitoring data and status identifiers of each parameter from the first extraction effect to identify parameters with abnormal conditions; analyzing the contribution of each parameter to the extraction effect from the second extraction effect to identify abnormal parameters; matching the abnormal parameter situation with historical cases involving parameters in the historical data storage module through an anomaly diagnosis model, calculating the similarity value between the abnormal parameter situation and the historical cases to determine the type of anomaly, including abnormal temperature, abnormal pressure, abnormal flow rate, abnormal concentration, abnormal pH value, and abnormal transmission process.

[0111] In one possible implementation, obtaining the third extraction effect further includes: determining the type of abnormal situation, calculating the absolute difference of the parameter deviating from the normal range, calculating the product of the value of the abnormal parameter deviating from the normal range and the weight, and obtaining the influence value of the abnormal parameter.

[0112] In this embodiment, an impact value between 0 and 2 is defined as a slight abnormality, between 2 and 5 is defined as a moderate abnormality, and greater than 5 is defined as a severe abnormality.

[0113] In one possible implementation, obtaining the third extraction effect also includes: comparing the current abnormal situation with similar situations in historical cases based on the types of historical abnormal situations contained in the abnormal diagnosis model, the detailed investigation results of each abnormal situation, and the determined causes, to obtain the abnormal causes of the abnormal situation.

[0114] The process optimization module is used to obtain intelligent optimization models and then to obtain process optimization parameters based on these models.

[0115] Specifically, the intelligent optimization model is a pre-built learning model. By inputting the second and third extraction effects transmitted by the podophyllotoxin extraction process system into the intelligent optimization model, the intelligent optimization model obtains process optimization parameters based on the second and third extraction effects and sends the process optimization parameters to the process optimization module.

[0116] In one possible implementation, obtaining process optimization parameters includes: constructing a database for storing the relationship between parameters corresponding to the podophyllotoxin extraction process, wherein the key parameter database stores the correspondence between key parameters and intelligent optimization models; classifying and organizing key parameters according to different extraction stages of the podophyllotoxin extraction process, generating a combination of key parameters and extraction stages, including the optimal value range of key parameters and corresponding stages, the impact data of different parameter values ​​on extraction rate and purity, and various abnormal situations and corresponding solutions;

[0117] In one possible implementation, obtaining process optimization parameters further includes: classifying and extracting the extraction rate, purity estimate, and contribution of each parameter to the extraction effect included in the second extraction effect, and the abnormality type, abnormality severity quantification value, and abnormality cause included in the third extraction effect, according to key parameters, namely temperature, pressure, flow rate, concentration, and pH value, to form a second extraction effect subset and a third extraction effect subset corresponding to each key parameter;

[0118] In one possible implementation, obtaining process optimization parameters further includes: taking the second extraction effect subset and the third extraction effect subset corresponding to the key parameters as a whole set and performing optimization calculations with the corresponding calculation method of the intelligent optimization model in the key parameter database to obtain the target process parameter combination, and the target process parameter combination is the storage method of process optimization parameters.

[0119] Specifically, the process optimization parameters include temperature adjustment values, pressure adjustment values, flow rate adjustment values, concentration adjustment values, and pH value adjustment values.

[0120] In one possible implementation, obtaining process optimization parameters further includes: using temperature as a key parameter, and based on the extraction rate (ER) of podophyllotoxin, the estimated purity (PG) of podophyllotoxin, and the quantified contribution (CT) of temperature to the extraction effect. EE Calculate the temperature parameter adjustment value EY T Specifically, it is expressed as:

[0121] ,

[0122] Among them, EY Tt Let t represent the temperature parameter adjustment value at time t, t1 represent the effective time to start extraction, t2 represent the planned end time of extraction, t represent the index of the extraction time, and R(t) represent the rate of change of podophyllotoxin extraction efficiency over time caused by the temperature parameter stored in the key parameter database.

[0123] The historical data storage module is used to establish a data warehouse for podophyllotoxin extraction, which stores monitoring data during the podophyllotoxin extraction process in real time. The data warehouse includes the start and end times of each extraction stage of podophyllotoxin, the settings of key parameters in the extraction process, the initial quality of raw materials, the extraction effect indicators of each extraction stage, and the analysis reports generated by each module during the extraction process.

[0124] As attached Figure 2 The method for monitoring the podophyllotoxin extraction process based on data analysis includes: S1: collecting podophyllotoxin extraction data; S2: monitoring podophyllotoxin extraction parameters; S3: preprocessing the collected data; S4: analyzing the impact of the data; S5: diagnosing abnormalities; S6: optimizing the extraction process parameters; and S7: integrating historical data.

[0125] S1: Collect podophyllotoxin extraction data: In response to the high-precision sensors installed in the podophyllotoxin extraction process monitoring system, acquire the first basic data in the podophyllotoxin extraction process in real time;

[0126] S2: Monitoring Podophyllotoxin Extraction Parameters: The first basic data during the podophyllotoxin extraction process is monitored in real time using visualization methods, and monitoring and judgment operations are performed. The monitoring and judgment operations are used to obtain the first extraction effect corresponding to the first basic data.

[0127] S3: Preprocessing the collected data: Performing preprocessing operations on the first extraction result to obtain the second basic data corresponding to the first extraction result;

[0128] S4: Analyze the impact of data: Obtain the podophyllotoxin impact analysis model, and based on the podophyllotoxin impact analysis model, obtain the second extraction effect corresponding to the second basic data through the second basic data;

[0129] S5: Diagnose anomalies: Obtain an anomaly diagnosis model, and based on the first and second extraction results, obtain a third extraction result through the anomaly diagnosis model;

[0130] S6: Optimize extraction process parameters: Obtain intelligent optimization model, and obtain process optimization parameters based on intelligent optimization model;

[0131] S7: Integrate historical data: Establish a data warehouse for podophyllotoxin extraction, and store monitoring data during the podophyllotoxin extraction process in real time. The data warehouse includes the start and end times of each extraction stage of podophyllotoxin, the setting values ​​of key parameters in the extraction process, the initial quality of raw materials, the extraction effect indicators of each extraction stage, and the analysis reports generated by each module during the extraction process.

[0132] Secondly: The drawings of the embodiments disclosed in the present invention only involve structures related to the embodiments disclosed in the present invention. Other structures may refer to conventional designs. The same embodiment and different embodiments of the present invention may be combined with each other without conflict.

[0133] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A data analysis-based monitoring system for the podophyllotoxin extraction process, comprising a system operation database, a system central processing module, and a user information terminal, characterized in that, Also includes: Podophyllotoxin Extraction Data Acquisition Module: This module responds to the high-precision sensors installed in the podophyllotoxin extraction process monitoring system, acquires the first basic data during the podophyllotoxin extraction process in real time, and transmits it to the podophyllotoxin extraction parameter monitoring module. The podophyllotoxin extraction data acquisition module includes the following basic data: the initial mass of podophyllotoxin in the raw material, the real-time temperature values ​​at each stage in the extraction container, the real-time pressure values ​​of each enclosed space in the extraction equipment, the real-time flow rate of the solvent inflow, the real-time flow rate of the extract outflow, the real-time concentration of podophyllotoxin in the extract, the real-time concentration of each impurity in the extract, the real-time concentration of the solvent, and the pH data of the extraction environment. The stages corresponding to the temperature acquisition include the extraction initiation stage, heating process, reflux stage, and cooling stage; the enclosed spaces corresponding to the pressure acquisition include the reaction vessel, distillation apparatus, and connecting pipelines. The podophyllotoxin extraction parameter monitoring module is used to monitor the first basic data in the podophyllotoxin extraction process in real time through visualization methods, and to perform monitoring and judgment operations. The monitoring and judgment operations are used to obtain the first extraction effect corresponding to the first basic data, and transmit the first extraction effect without abnormalities to the data acquisition preprocessing module. Data acquisition preprocessing module: used to preprocess the first extraction effect in the podophyllotoxin extraction parameter monitoring module. The preprocessing operation is used to obtain the second basic data corresponding to the first extraction effect and transmit it to the impact data analysis module. Impact Data Analysis Module: Used to obtain the impact analysis model of podophyllotoxin, obtain the second extraction effect corresponding to the second basic data based on the second basic data through the second basic data, and transmit the second extraction effect without abnormalities to the process optimization module; The impact data analysis module includes the second extraction effect, which includes the extraction rate, the purity estimate, and the quantitative value of the contribution of each parameter to the extraction effect. Anomaly Diagnosis Module: Used to acquire anomaly diagnosis model, and based on the first extraction effect transmitted by the podophyllotoxin extraction parameter monitoring module and the second extraction effect transmitted by the impact data analysis module, obtain the third extraction effect through the anomaly diagnosis model; The anomaly diagnosis module obtains a third extraction result, specifically including: The first extraction result transmitted by the podophyllotoxin extraction parameter monitoring module is passed through the anomaly diagnosis model, and the abnormal parameters stored in the historical data storage module are passed through the anomaly diagnosis model. The results of the two are compared according to the preset anomaly judgment rules. The preset anomaly judgment rules are the relationship logic between each parameter and the podophyllotoxin extraction anomaly established within the anomaly diagnosis model. The abnormal parameter cases are matched with historical cases involving parameters in the historical data storage module using an anomaly diagnosis model. The similarity value between the abnormal parameter cases and the historical cases is calculated to determine the type of anomaly. Once the type of abnormal situation is determined, the absolute difference of the parameter deviating from the normal range is calculated, and the product of the abnormal parameter's deviation from the normal range and its weight is calculated to obtain the impact value of the abnormal parameter. Process optimization module: used to obtain intelligent optimization models and obtain process optimization parameters based on the intelligent optimization models; The historical data storage module is used to establish a data warehouse for podophyllotoxin extraction, which stores monitoring data during the podophyllotoxin extraction process in real time. The data warehouse includes the start and end times of each extraction stage of podophyllotoxin, the setting values ​​of key parameters in the extraction process, the initial quality of raw materials, the extraction effect indicators of each extraction stage, and the analysis reports generated by each module during the extraction process. The system's operating database includes all data text from the podophyllotoxin extraction process monitoring system, and collects information text output from each module in real time. The system's central processing module is used to control the information text instructions output by each module in the central control system. The user information terminal is a device for receiving information output from the podophyllotoxin extraction process monitoring system.

2. The data analysis-based monitoring system for podophyllotoxin extraction process according to claim 1, characterized in that: The impact data analysis module obtains the second extraction effect corresponding to the second basic data, specifically including: Based on the real-time inflow rate IQ of the solvent and the real-time outflow rate OQ of the extract, the total volume EV of the extract is calculated, specifically expressed as: ， Where t1 represents the effective time to start extraction, t2 represents the planned end time of extraction, t represents the index of extraction time, IQ(t) represents the real-time flow rate of solvent inflow at time t, and OQ(t) represents the real-time flow rate of extract outflow at time t. Based on the real-time concentration CG of podophyllotoxin in the extract, the total volume EV of the extract, and the initial mass CM0 of podophyllotoxin in the raw material, the extraction rate ER of podophyllotoxin is calculated, specifically expressed as follows: ， Where t1 represents the effective start time of extraction, t2 represents the planned end time of extraction, t represents the index of the extraction time, and CG t The concentration of podophyllotoxin in the extract at time t is expressed as EV. t This represents the total volume of the extract at time t.

3. The data analysis-based monitoring system for podophyllotoxin extraction process according to claim 1, characterized in that: The second extraction effect corresponding to the second basic data specifically includes: Based on the real-time concentration CG of podophyllotoxin in the extract and the real-time concentration C of each impurity in the extract. i The estimated purity (PG) of podophyllotoxin was calculated and expressed as follows: ， Among them, CG t Let t represent the real-time concentration of podophyllotoxin in the extract at time t, t1 represent the effective time to start extraction, t2 represent the planned end time of extraction, t represent the index of the extraction time, i represent the index of each impurity in the extract, n represent the total number of impurities in the extract, and C represent the total number of impurities in the extract. it This represents the real-time concentration of impurity i in the extract at time t.

4. The data analysis-based monitoring system for podophyllotoxin extraction process according to claim 1, characterized in that: The process optimization module acquires process optimization parameters, specifically including: A database is constructed to store the relationship between parameters corresponding to the podophyllotoxin extraction process. The key parameter database stores the correspondence between key parameters and intelligent optimization models. Based on the different extraction stages of the podophyllotoxin extraction process, key parameters are classified and organized to generate combinations of key parameters and extraction stages, including the optimal value range of key parameters and corresponding stages, the impact data of different parameter values ​​on extraction rate and purity, and various abnormal situations and corresponding solutions. The extraction rate, purity estimate, and contribution of each parameter to the extraction effect included in the second extraction effect, and the abnormality type, abnormality severity quantification value, and abnormality cause included in the third extraction effect, are classified and extracted according to key parameters, namely temperature, pressure, flow rate, concentration, and pH value, forming a second extraction effect subset and a third extraction effect subset corresponding to each key parameter. The second and third extraction effect subsets corresponding to the key parameters are used as a whole set and optimized using the corresponding calculation method of the intelligent optimization model in the key parameter database to obtain the target process parameter combination. The target process parameter combination is the storage method for process optimization parameters.

5. The data analysis-based monitoring system for podophyllotoxin extraction process according to claim 1, characterized in that: The process optimization module acquires process optimization parameters, specifically including: Using temperature as a key parameter, this study explains the extraction efficiency (ER) of podophyllotoxin, the estimated purity (PG) of podophyllotoxin, and the quantitative value (CT) of the contribution of temperature to the extraction effect. EE Calculate the temperature parameter adjustment value EY T Specifically, it is expressed as: ， Among them, EY Tt Let t represent the temperature parameter adjustment value at time t, t1 represent the effective time to start extraction, t2 represent the planned end time of extraction, t represent the index of the extraction time, and R(t) represent the rate of change of podophyllotoxin extraction efficiency over time caused by the temperature parameter stored in the key parameter database.

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