Podophyllotoxin extraction process monitoring system based on data analysis

Abstract

The invention discloses a podophyllotoxin extraction process monitoring system based on data analysis, and particularly relates to the field of medicine. Comprising a podophyllotoxin extraction data acquisition module, a podophyllotoxin extraction parameter monitoring module, an acquired data preprocessing module, an influence data analysis module, an abnormality diagnosis module, a process optimization module and a historical data storage module. The invention discloses a podophyllotoxin extraction process monitoring system based on data analysis. A podophyllotoxin extraction data acquisition module is used for completing acquisition and transmission tasks of first basic data in a podophyllotoxin extraction process, and a solid data basis is provided; a second extraction effect is obtained through an influence data analysis module, the influence degree of each parameter on the final extraction effect in the extraction process is accurately grasped, and a quantitative basis is provided for the extraction effect; the process optimization parameters are obtained through the process optimization module, and the process parameters are rapidly and accurately adjusted according to the actual production condition so as to achieve the optimal production effect.

Description

Technical Field

[0001] The present invention relates to the field of medical technology, and more specifically, to a podophyllotoxin extraction process monitoring system based on data analysis. Background Art

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

[0003] The traditional extraction process has been continuously optimized, which has increased the extraction rate of podophyllotoxin and provided more sufficient medicinal raw materials for the treatment of diseases such as genital warts in men and women; the combination of ultrasound-assisted extraction and traditional extraction technology has improved the extraction efficiency and purity; and the development of extraction technology has gradually improved the safety of the production process.

[0004] However, there are still some shortcomings in its actual use. For example, most of the parameters in the extraction process rely on manual regular monitoring and recording, which makes it impossible to accurately grasp the real-time state changes in the extraction process, thus affecting the stability of product quality; it is difficult to discover and make effective adjustments in time for abnormal situations 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, and it is difficult to quickly and accurately adjust the process parameters according to actual production conditions to achieve the best production effect. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, the present invention provides a podophyllotoxin extraction process monitoring system based on data analysis, and solves the problems raised in the above-mentioned background technology through the following scheme.

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

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

[0008] Podophyllotoxin extraction data acquisition module: used to respond to the high-precision sensor installed in the podophyllotoxin extraction process monitoring system, obtain the first basic data in the podophyllotoxin extraction process in real time, and transmit it to the podophyllotoxin extraction parameter monitoring module;

[0009] Podophyllotoxin extraction parameter monitoring module: used to monitor the first basic data in the podophyllotoxin extraction process in real time through a visualization method, and 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 abnormal conditions to the acquisition data preprocessing module;

[0010] The acquisition data preprocessing module is used to perform a preprocessing operation on the first extraction effect corresponding to the podophyllotoxin extraction parameter monitoring module, and 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 a podophyllotoxin impact analysis model, obtain a second extraction effect corresponding to the second basic data through the second basic data according to the podophyllotoxin impact analysis model, and transmit the second extraction effect without abnormal conditions to the process optimization module;

[0012] Abnormal diagnosis module: used to obtain an abnormal diagnosis model, and obtain a third extraction effect through the abnormal diagnosis model 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;

[0013] Process optimization module: used to obtain the intelligent optimization model and obtain the process optimization parameters according to the intelligent optimization model;

[0014] The historical data storage module is used to establish a podophyllotoxin extraction data warehouse to store the monitoring data of the podophyllotoxin extraction process in real time. The data warehouse includes the start and end time of each podophyllotoxin extraction stage, the setting values ​​of key parameters of the extraction process, the initial quality of the 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 operation database includes all data texts of the podophyllotoxin extraction process monitoring system and collects information texts output by each module in real time. The system central processing module is used for information text instructions output by each module in the central control system. The user information terminal is an information output device for receiving the podophyllotoxin extraction process monitoring system.

[0016] Preferably, the podophyllotoxin extraction data acquisition module, 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 ​​of each closed 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 collection temperature include the extraction start stage, the heating process, the reflux stage, and the cooling stage; the closed space corresponding to the collection pressure includes the reactor, the distillation device, and the connecting pipeline.

[0018] Preferably, in the impact data analysis module, the second extraction effect includes an extraction rate, a purity estimate, and a quantitative value of 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 flow rate IQ of the solvent inflow and the real-time flow rate OQ of the extract outflow, the total volume EV of the extract is calculated, which is specifically expressed as:

[0021] ,

[0022] Wherein, t1 represents the effective time for starting extraction, t2 represents the end time of the planned extraction, t represents the index of the extraction time, IQ(t) represents the real-time flow rate of the solvent flowing in at time t, and OQ(t) represents the real-time flow rate of the extract flowing out 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, which is specifically expressed as:

[0024] ,

[0025] Among them, t1 represents the effective time to start extraction, t2 represents the end time of the planned extraction, t represents the index of the extraction time, CG t It is expressed as the real-time concentration of podophyllotoxin in the extract at time t, EV t Expressed as the total volume of the extract at time t.

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

[0027] Based on the real-time concentration of podophyllotoxin in the extract CG and the real-time concentration of each impurity in the extract C i , calculate the estimated value PG of podophyllotoxin purity, specifically expressed as:

[0028] ,

[0029] Among them, CG trepresents the real-time concentration of podophyllotoxin in the extract at time t, t1 represents the effective time for starting extraction, t2 represents the end time of the planned extraction, t represents the index of the extraction time, i represents the index of each impurity in the extract, n represents the total number of impurities in the extract, C it It is expressed as the real-time concentration of impurity i in the extract at time t.

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

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

[0032] Match the abnormal parameter situation with the historical cases involving the parameters in the historical data storage module through the abnormal diagnosis model, and calculate the similarity value between the abnormal parameter situation and the historical cases to determine the type of abnormal situation;

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

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

[0035] Constructing a database for storing the relationship between parameters corresponding to the podophyllotoxin extraction process, wherein the key parameter database stores the relationship between key parameters and the intelligent optimization model;

[0036] Based on the different extraction stages of podophyllotoxin extraction process, key parameters are classified and sorted out respectively, and combinations of key parameters and extraction stages are generated, including the optimal value range of key parameters and corresponding stages, the impact of different parameter values ​​on extraction rate and purity, and various abnormal situations and corresponding solutions;

[0037] The extraction rate, purity estimation, and contribution of each parameter to the extraction effect included in the second extraction effect, and the abnormal situation type, abnormal severity quantification value, and abnormal cause included in the third extraction effect are classified and extracted 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;

[0038] The second extraction effect sub-dataset and the third extraction effect sub-dataset corresponding to the key parameters are taken as a whole set and optimized with the corresponding calculation method of the intelligent optimization model in the key parameter database to obtain the target process parameter combination, which is a storage method for process optimization parameters.

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

[0040] Taking temperature as the key parameter, the following is explained based on the extraction rate ER of podophyllotoxin, the estimated value of podophyllotoxin purity PG, and the quantitative value CT of the contribution of temperature to the extraction effect. EE , calculate the temperature parameter adjustment value EY T , specifically expressed as:

[0041] ,

[0042] Among them, EY Tt It is represented as the temperature parameter adjustment value at time t, t1 represents the effective time for starting extraction, t2 represents the end time of the planned extraction, t represents the index of extraction time, and R(t) represents the rate of change of podophyllotoxin extraction efficiency over time caused by the temperature parameters stored in the key parameter database.

[0043] To achieve the above object, the present invention provides the following technical solution: a method for monitoring the podophyllotoxin extraction process based on data analysis, and implementing the above-mentioned system for monitoring the podophyllotoxin extraction process based on data analysis, comprising:

[0044] S1: Collecting podophyllotoxin extraction data: Responding to the high-precision sensor installed in the podophyllotoxin extraction process monitoring system, the first basic data of the podophyllotoxin extraction process is obtained in real time;

[0045] S2: Monitoring podophyllotoxin extraction parameters: monitoring the first basic data in the podophyllotoxin extraction process in real time through a visualization method, and performing a monitoring and judgment operation, wherein the monitoring and judgment operation is used to obtain a first extraction effect corresponding to the first basic data;

[0046] S3: preprocessing collected data: performing a preprocessing operation on the first extraction effect, the preprocessing operation is used to obtain second basic data corresponding to the first extraction effect;

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

[0048] S5: diagnose abnormality: obtain an abnormality diagnosis model, and obtain a third extraction effect through the abnormality diagnosis model based on the first extraction effect and the second extraction effect;

[0049] S6: Optimizing extraction process parameters: obtaining an intelligent optimization model, and obtaining process optimization parameters according to the intelligent optimization model;

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

[0051] Technical effects and advantages of the present invention:

[0052] 1. The present invention efficiently and accurately completes the collection and transmission of the first basic data in 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. The present invention obtains the second extraction effect by influencing the data analysis module, accurately grasps the influence of each parameter on the final extraction effect during the extraction process, and provides a quantitative basis for the extraction effect;

[0054] 3. The present invention obtains process optimization parameters through a process optimization module, provides data support for extraction process optimization, and adjusts process parameters quickly and accurately according to actual production conditions to achieve the best production effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a system flow chart of the present invention.

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

[0057] Figure 3 It is a schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0058] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to and includes any or all possible combinations of one or more listed items.

[0060] In the following, the terms "first", "second", and "third" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first", "second", and "third" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0061] As attached Figure 1 The podophyllotoxin extraction process monitoring system shown in the figure, which is based on data analysis, includes a system operation database, a system central processing module and a user information terminal, and 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 abnormality diagnosis module, a process optimization module, and a historical data storage module.

[0062] The system operation database includes all data texts of the podophyllotoxin extraction process monitoring system and collects information texts output by each module in real time. The system central processing module is used for information text instructions output by each module in the central control system. The user information terminal is an information output device for receiving the podophyllotoxin extraction process monitoring system.

[0063] The podophyllotoxin extraction data acquisition module is used to respond to the high-precision sensor installed in the podophyllotoxin extraction process monitoring system, obtain 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 embodiment, obtaining the first basic data in the podophyllotoxin extraction process includes: selecting high-precision sensors according to the podophyllotoxin extraction process, including installing high-sensitivity temperature sensors in the heating area and solution mixing area of ​​the extraction container, installing pressure sensors with good stability at the inlet and outlet of the extraction equipment and inside the reactor, selecting a flow meter to measure the solvent flow rate, detecting the concentration of the active ingredient in the mixed solution through a concentration sensor, and measuring the pH value of the solution through a pH sensor.

[0065] Specifically, each sensor is connected to the podophyllotoxin extraction data acquisition module through an adapted data cable. For sensors connected via wires, data cables with good shielding performance are used to reduce the impact of external electromagnetic interference on data transmission; for sensors connected via wireless networks, 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 a possible embodiment, obtaining the first basic data during the podophyllotoxin extraction process further includes: based on the start of the podophyllotoxin extraction process, that is, when any change occurs in the sensor monitoring parameter, the high-precision sensors installed at each extraction position begin to monitor the corresponding physical and chemical quantities in real time; during the extraction process, for the monitored temperature and flow data, a transmission frequency of 2 times per second is specially set;

[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 ​​of each closed 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 corresponding stages when the first basic data is collected at temperature include the extraction start stage, the heating process, the reflux stage, and the cooling stage; the corresponding closed space when collecting pressure includes the reactor, the distillation device, and the connecting pipeline.

[0069] Podophyllotoxin extraction parameter monitoring module: used to monitor the first basic data in the podophyllotoxin extraction process in real time through a visualization method, and 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 abnormal conditions to the acquisition data preprocessing module.

[0070] In a 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 with a line graph, comparing the real-time pressure values ​​of each closed space with a bar graph, displaying the real-time flow rate of solvent inflow and extract outflow with a real-time updated flow value table, presenting the real-time concentration of podophyllotoxin in the extract and the real-time concentration change of the solvent through a concentration change curve, and displaying the pH data of the extraction environment in the form of a digital dashboard;

[0072] In a possible implementation, obtaining the first extraction effect corresponding to the first basic data further includes: setting a standard parameter range, performing a monitoring and judgment operation on the first basic data displayed visually, the monitoring and judgment operation is based on comparing and judging the set standard parameter range with the actually collected data, the standard parameter range is set based on a large amount of historical data stored in the historical data storage module and adjustments by professionals;

[0073] Compare the real-time temperature value with the set appropriate temperature range. If the real-time temperature is within the range, the temperature parameter is considered normal. If it is out of the range, whether it is too high or too low, it is considered to be an abnormal temperature condition.

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

[0075] Check the deviation between the real-time flow rate of the solvent inflow and the 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 parameter is normal. If the deviation is too large, it is judged as abnormal flow.

[0076] The real-time concentration of podophyllotoxin in the extract and the real-time concentration of the solvent are judged according to the preset target range of active ingredient concentration and the reasonable range of solvent concentration. If the podophyllotoxin concentration does not reach the expected level or the solvent concentration deviates from the standard, it is considered as an abnormal concentration.

[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 pH parameter is normal. If not, it is determined to be abnormal.

[0078] In this embodiment, the temperature range of the initial stage of extraction is set at 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 inside of the extraction equipment is maintained near the standard atmospheric pressure, i.e. 101.3 kPa; when extracting impurities by vacuum distillation, the pressure range is set to 5 kPa to 20 kPa;

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

[0081] The solvent concentration is 70% to 95%; during the extraction process, the concentration of podophyllotoxin in the extract will gradually change at different stages, with the initial concentration set at 0.1% to 1%; when the extraction is completed, the concentration of podophyllotoxin in the extract reaches 5% to 15%;

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

[0083] In a possible implementation, obtaining the first extraction effect corresponding to the first basic data also includes: when all parameters corresponding to the first basic data are in a normal state, that is, the extraction process is judged to be running normally, and the corresponding extraction effect is the first extraction effect without abnormal conditions, and is transmitted to the acquisition data preprocessing module; if one or more parameters are abnormal, it is judged that an abnormality occurs and 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, a state identifier of each parameter, that is, Y represents a normal situation, N represents an abnormal situation, and an extraction parameter evaluation table.

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

[0086] The data collection preprocessing module is used to perform preprocessing operations on 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, unified format and dimension.

[0087] Specifically, after the podophyllotoxin extraction process monitoring system obtains that the status identifiers of all parameters corresponding to the first extraction effect in the podophyllotoxin extraction parameter monitoring module are all Y, the second basic data corresponding to the first extraction effect can be obtained through preprocessing operations; the preprocessing steps are as follows: data verification: checking missing values ​​and data formats through a data verification mechanism; data cleaning: removing noise and interference factors; data encoding and conversion: normalizing each parameter to a basic form, and performing encoding and conversion operations on the first extraction effect data, the encoding and conversion operations including converting decimal data into binary data according to encoding rules or representing data in a specific vector form.

[0088] The impact data analysis module is used to obtain a podophyllotoxin impact analysis model, and obtain a second extraction effect corresponding to the second basic data through the second basic data according to the podophyllotoxin impact analysis model.

[0089] Specifically, the podophyllotoxin impact analysis model is a pre-constructed learning model. By inputting the second basic data into the podophyllotoxin impact analysis model, the podophyllotoxin impact analysis model obtains the second extraction effect based on the second basic data, and sends the second extraction effect corresponding to no abnormal situation to the process optimization module, and sends the second extraction effect corresponding to the abnormal situation to the abnormality judgment module.

[0090] It should be noted that the second extraction effect corresponding to the abnormal situation includes that the estimated extraction rate and purity obtained based on the podophyllotoxin impact analysis model are significantly different from the expected target value; the relationship between the various parameters does not conform to normal physical and chemical laws or previous empirical data.

[0091] In this embodiment, when the temperature rises, the solubility of podophyllotoxin does not increase but decreases, and the solvent concentration does not change accordingly, which means that there is an abnormal situation that the relationship between the parameters does not conform to the normal physical and chemical laws.

[0092] In a possible implementation, obtaining the second extraction effect corresponding to the second basic data includes: generating a mathematical relationship between each parameter and the podophyllotoxin extraction effect by a podophyllotoxin impact analysis model based on a large amount of podophyllotoxin extraction experimental data and historical production data; arranging and sorting each parameter data corresponding to the received second basic data, and obtaining the corresponding second extraction effect according to the relationship logic between each parameter and the podophyllotoxin extraction effect established within the model;

[0093] Specifically, the second extraction effect includes an extraction rate, a purity estimation value, and a quantitative value of contribution of each parameter to the extraction effect;

[0094] In a 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, which is specifically expressed as:

[0095] ,

[0096] Wherein, t1 represents the effective time for starting extraction, t2 represents the end time of the planned extraction, t represents the index of the extraction time, IQ(t) represents the real-time flow rate of the solvent flowing in at time t, and OQ(t) represents the real-time flow rate of the extract flowing out 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, which is specifically expressed as:

[0098] ,

[0099] Among them, t1 represents the effective time to start extraction, t2 represents the end time of the planned extraction, t represents the index of the extraction time, CG t It is expressed as the real-time concentration of podophyllotoxin in the extract at time t, EV t It is expressed as the total volume of the extract at time t;

[0100] Based on the real-time concentration of podophyllotoxin in the extract CG and the real-time concentration of each impurity in the extract C i , calculate the estimated value PG of podophyllotoxin purity, specifically expressed as:

[0101] ,

[0102] Among them, CG t represents the real-time concentration of podophyllotoxin in the extract at time t, t1 represents the effective time for starting extraction, t2 represents the end time of the planned extraction, t represents the index of the extraction time, i represents the index of each impurity in the extract, n represents the total number of impurities in the extract, C it It is expressed as 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. Based on the temperature change ΔT and the podophyllotoxin extraction rate ER during the period from the effective time of the start of extraction to the planned end time of extraction, the quantitative value of the contribution of temperature to the extraction effect CT is calculated. EE , specifically expressed as:

[0104] ,

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

[0106] The abnormal diagnosis module is used to obtain an abnormal diagnosis model, and obtain a third extraction effect through the abnormal diagnosis model 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.

[0107] Specifically, the abnormal diagnosis model is a pre-constructed learning model. By inputting the first extraction effect transmitted by the podophyllotoxin extraction parameter monitoring module or the second extraction effect transmitted by the impact data analysis module into the abnormal diagnosis model, the abnormal 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 an abnormal situation identification, where NN indicates the presence of an abnormal situation, YY indicates the absence of an abnormal situation, an abnormal situation type, a quantitative value of the abnormal severity, and an abnormal cause.

[0109] In a possible embodiment, obtaining the third extraction effect includes: passing the first extraction effect transmitted by the podophyllotoxin extraction parameter monitoring module through the abnormal diagnosis model, and passing the abnormal parameters stored in the historical data storage module through the abnormal diagnosis model, and comparing the two results according to a preset abnormal judgment rule, wherein the preset abnormal judgment rule is the relationship logic between each parameter established inside the abnormal diagnosis model and the abnormal situation of podophyllotoxin extraction; if it is determined that an abnormal situation exists, the abnormal situation is marked as NN; if the parameter is judged to be normal, the abnormal situation is marked as YY;

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

[0111] In a possible implementation, obtaining the third extraction effect further includes: for determining the abnormal situation type, 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 a possible implementation, obtaining the third extraction effect also includes: based on the historical abnormal situation types contained in the abnormal diagnosis model, the detailed investigation results of each abnormal situation and the determined causes, comparing the current abnormal situation with similar situations in historical cases to obtain the abnormal cause of the abnormal situation.

[0114] The process optimization module is used to obtain an intelligent optimization model and obtain process optimization parameters according to the intelligent optimization model.

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

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

[0117] In a possible implementation, obtaining the process optimization parameters further includes: classifying and extracting the extraction rate, purity estimation value, and contribution of each parameter to the extraction effect contained in the second extraction effect, and the abnormal situation type, abnormal severity quantification value, and abnormal cause contained 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 a possible embodiment, obtaining process optimization parameters also includes: optimizing the second extraction effect sub-dataset and the third extraction effect sub-dataset corresponding to the key parameters as a whole set and the corresponding calculation method of the intelligent optimization model in the key parameter database to obtain a target process parameter combination, and the target process parameter combination is a storage method for process optimization parameters.

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

[0120] In a possible embodiment, obtaining the process optimization parameters further includes: taking temperature as a key parameter for explanation, based on the extraction rate ER of podophyllotoxin, the estimated value PG of podophyllotoxin purity, and the quantitative value CT of the contribution of temperature to the extraction effect EE , calculate the temperature parameter adjustment value EY T , specifically expressed as:

[0121] ,

[0122] Among them, EY Tt It is represented as the temperature parameter adjustment value at time t, t1 represents the effective time for starting extraction, t2 represents the end time of the planned extraction, t represents the index of extraction time, and R(t) represents the rate of change of podophyllotoxin extraction efficiency over time caused by the temperature parameters stored in the key parameter database.

[0123] The historical data storage module is used to establish a podophyllotoxin extraction data warehouse to store the monitoring data of the podophyllotoxin extraction process in real time. The data warehouse includes the start and end time of each podophyllotoxin extraction stage, the setting values ​​of key parameters of the extraction process, the initial quality of the 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 A method for monitoring the podophyllotoxin extraction process based on data analysis is shown, comprising: S1: collecting podophyllotoxin extraction data, S2: monitoring podophyllotoxin extraction parameters, S3: pre-processing collected data, S4: analyzing data impact effects, S5: diagnosing abnormalities, S6: optimizing extraction process parameters, and S7: integrating historical data.

[0125] S1: Collecting podophyllotoxin extraction data: Responding to the high-precision sensor installed in the podophyllotoxin extraction process monitoring system, the first basic data of the podophyllotoxin extraction process is obtained in real time;

[0126] S2: Monitoring podophyllotoxin extraction parameters: monitoring the first basic data in the podophyllotoxin extraction process in real time through a visualization method, and performing a monitoring and judgment operation, wherein the monitoring and judgment operation is used to obtain a first extraction effect corresponding to the first basic data;

[0127] S3: preprocessing collected data: performing a preprocessing operation on the first extraction effect, the preprocessing operation is used to obtain second basic data corresponding to the first extraction effect;

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

[0129] S5: diagnose abnormality: obtain an abnormality diagnosis model, and obtain a third extraction effect through the abnormality diagnosis model based on the first extraction effect and the second extraction effect;

[0130] S6: Optimizing extraction process parameters: obtaining an intelligent optimization model, and obtaining process optimization parameters according to the intelligent optimization model;

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

[0132] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other; 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 protection scope of the present invention.

Claims

1. A podophyllotoxin extraction process monitoring system based on data analysis, 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: used to respond to the high-precision sensor installed in the podophyllotoxin extraction process monitoring system, obtain the first basic data in the podophyllotoxin extraction process in real time, and transmit it to the podophyllotoxin extraction parameter monitoring module; Podophyllotoxin extraction parameter monitoring module: used to monitor the first basic data in the podophyllotoxin extraction process in real time through a visualization method, and 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 abnormal conditions to the acquisition data preprocessing module; The acquisition data preprocessing module is used to perform a preprocessing operation on the first extraction effect corresponding to the podophyllotoxin extraction parameter monitoring module, and 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 a podophyllotoxin impact analysis model, obtain a second extraction effect corresponding to the second basic data through the second basic data according to the podophyllotoxin impact analysis model, and transmit the second extraction effect without abnormal conditions to the process optimization module; Abnormal diagnosis module: used to obtain an abnormal diagnosis model, and obtain a third extraction effect through the abnormal diagnosis model 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; Process optimization module: used to obtain the intelligent optimization model and obtain the process optimization parameters according to the intelligent optimization model; The historical data storage module is used to establish a podophyllotoxin extraction data warehouse to store the monitoring data of the podophyllotoxin extraction process in real time. The data warehouse includes the start and end time of each podophyllotoxin extraction stage, the setting values ​​of key parameters of the extraction process, the initial quality of the raw materials, the extraction effect indicators of each extraction stage, and the analysis reports generated by each module during the extraction process; The system operation database includes all data texts of the podophyllotoxin extraction process monitoring system and collects information texts output by each module in real time. The system central processing module is used for information text instructions output by each module in the central control system. The user information terminal is an information output device for receiving the podophyllotoxin extraction process monitoring system.

2. A podophyllotoxin extraction process monitoring system based on data analysis according to claim 1, characterized in that: The podophyllotoxin extraction data acquisition module, 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 ​​of each closed 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 collection temperature include the extraction start stage, the heating process, the reflux stage, and the cooling stage; the closed space corresponding to the collection pressure includes the reactor, the distillation device, and the connecting pipeline.

3. A podophyllotoxin extraction process monitoring system based on data analysis according to claim 1, characterized in that: The impact data analysis module, the second extraction effect includes the extraction rate, the purity estimation value, and the quantitative value of the contribution of each parameter to the extraction effect.

4. A podophyllotoxin extraction process monitoring system based on data analysis according to claim 3, 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 flow rate IQ of the solvent inflow and the real-time flow rate OQ of the extract outflow, the total volume EV of the extract is calculated, which is specifically expressed as: ， Wherein, t1 represents the effective time for starting extraction, t2 represents the end time of the planned extraction, t represents the index of the extraction time, IQ(t) represents the real-time flow rate of the solvent flowing in at time t, and OQ(t) represents the real-time flow rate of the extract flowing out 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, which is specifically expressed as: ， Among them, t1 represents the effective time to start extraction, t2 represents the end time of the planned extraction, t represents the index of the extraction time, CG t It is expressed as the real-time concentration of podophyllotoxin in the extract at time t, EV t Expressed as the total volume of the extract at time t.

5. A podophyllotoxin extraction process monitoring system based on data analysis according to claim 3, characterized in that: The obtaining of the second extraction effect corresponding to the second basic data specifically includes: Based on the real-time concentration of podophyllotoxin in the extract CG and the real-time concentration of each impurity in the extract C i , calculate the estimated value PG of podophyllotoxin purity, specifically expressed as: ， Among them, CG t represents the real-time concentration of podophyllotoxin in the extract at time t, t1 represents the effective time for starting extraction, t2 represents the end time of the planned extraction, t represents the index of the extraction time, i represents the index of each impurity in the extract, n represents the total number of impurities in the extract, C it It is expressed as the real-time concentration of impurity i in the extract at time t.

6. A podophyllotoxin extraction process monitoring system based on data analysis according to claim 1, characterized in that: The abnormality diagnosis module obtains the third extraction effect, specifically including: The first extraction effect transmitted by the podophyllotoxin extraction parameter monitoring module is passed through the abnormal diagnosis model, and the abnormal parameters stored in the historical data storage module are passed through the abnormal diagnosis model, and the results of the two are compared according to the preset abnormal judgment rule, and the preset abnormal judgment rule is the relationship logic between each parameter established inside the abnormal diagnosis model and the abnormal situation of podophyllotoxin extraction; Match the abnormal parameter situation with the historical cases involving the parameters in the historical data storage module through the abnormal diagnosis model, and calculate the similarity value between the abnormal parameter situation and the historical cases to determine the type of abnormal situation; For the determined abnormal situation type, the absolute difference of the parameter deviation from the normal range is calculated, and the product of the value of the abnormal parameter deviation from the normal range and the weight is calculated to obtain the impact value of the abnormal parameter.

7. The podophyllotoxin extraction process monitoring system based on data analysis according to claim 1, characterized in that: The process optimization module obtains process optimization parameters, specifically including: Constructing a database for storing the relationship between parameters corresponding to the podophyllotoxin extraction process, wherein the key parameter database stores the relationship between key parameters and the intelligent optimization model; Based on the different extraction stages of podophyllotoxin extraction process, key parameters are classified and sorted out respectively, and combinations of key parameters and extraction stages are generated, including the optimal value range of key parameters and corresponding stages, the impact of different parameter values ​​on extraction rate and purity, and various abnormal situations and corresponding solutions; The extraction rate, purity estimation, and contribution of each parameter to the extraction effect included in the second extraction effect, and the abnormal situation type, abnormal severity quantification value, and abnormal cause included in the third extraction effect are classified and extracted 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; The second extraction effect sub-dataset and the third extraction effect sub-dataset corresponding to the key parameters are taken as a whole set and optimized with the corresponding calculation method of the intelligent optimization model in the key parameter database to obtain the target process parameter combination, which is a storage method for process optimization parameters.

8. The podophyllotoxin extraction process monitoring system based on data analysis according to claim 1, characterized in that: The process optimization module obtains process optimization parameters, specifically including: Taking temperature as the key parameter, the following is explained based on the extraction rate ER of podophyllotoxin, the estimated value of podophyllotoxin purity PG, and the quantitative value CT of the contribution of temperature to the extraction effect. EE , calculate the temperature parameter adjustment value EY T , specifically expressed as: ， Among them, EY Tt It is represented as the temperature parameter adjustment value at time t, t1 represents the effective time for starting extraction, t2 represents the end time of the planned extraction, t represents the index of extraction time, and R(t) represents the rate of change of podophyllotoxin extraction efficiency over time caused by the temperature parameters stored in the key parameter database.

Images