Natural product extraction process intelligent monitoring and data analysis system

Abstract

The invention discloses an intelligent monitoring and data analysis system for a natural product extraction process. The intelligent monitoring and data analysis system comprises an extraction device, a sensor network, a data acquisition and processing unit, a central processing unit, an intelligent data storage unit and a user interface display unit. A multi-sensor network is deployed in the extraction process, real-time monitoring of extraction parameters in the extraction process is achieved, the accuracy and the real-time performance of monitoring are improved, meanwhile, a creatively-constructed extraction state display model can display a current extraction state display value in real time, and the parameter influence degree in an extractor is displayed; after the central processing unit obtains the digital signal, the extraction process is adjusted according to a preset extraction strategy and algorithm, the extraction process is intelligently optimized, energy conservation and consumption reduction of the extraction process are achieved, and economic benefits are improved; the method has a self-adaptive adjustment function, can perform equipment adjustment according to real-time data in the extraction process, and improves the extraction quality.

Description

Technical Field

[0001] The present invention relates to the technical field of natural product extraction, and in particular to an intelligent monitoring and data analysis system for a natural product extraction process. Background Art

[0002] In the field of natural product extraction, there are many parameters involved in the extraction process, including temperature, pressure, solvent ratio, extraction time, etc. Slight changes in these parameters may have a significant impact on the extraction efficiency and product purity.

[0003] Traditional extraction processes often rely on experienced operators to monitor and adjust the parameters of the extraction process. This manual monitoring method is limited by the operator's experience and attention, making it difficult to capture subtle changes in real time, and it is even more difficult to effectively analyze and utilize these parameter data to guide the optimization of the extraction process. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above problems existing in the existing natural product extraction process, the present invention is proposed.

[0006] Therefore, the technical problem solved by the present invention is to solve the problem that the existing natural product extraction process is limited by the experience and attention of the operator, making it difficult to capture subtle changes in real time, and it is even more impossible to effectively analyze and utilize these parameter data.

[0007] To solve the above technical problems, the present invention provides the following technical solutions: a natural product extraction process intelligent monitoring and data analysis system, comprising the following components: an extraction device, used to realize the extraction of natural products; a sensor network, a multi-sensor network is deployed during the extraction process to monitor and record the extraction parameters in real time; a data acquisition and processing unit, which converts the analog signals collected by the sensor network into digital signals and sends them to the central processing unit through a high-speed data transmission line; the central processing unit adjusts the extraction process according to a preset extraction strategy and algorithm after obtaining the digital signal; an intelligent data storage unit, which is wirelessly connected to the central processing unit, obtains the correlation between the extraction parameters and the extraction efficiency during the adjusted extraction process, and synchronously completes the storage; a user interface display unit, which is wirelessly connected to the intelligent data storage unit, and displays the correlation between the stored extraction parameters and the extraction efficiency.

[0008] As a preferred solution of the intelligent monitoring and data analysis system for the natural product extraction process described in the present invention, the extraction parameters monitored and recorded in real time by the sensor network specifically include: the temperature in the extraction device, the pressure in the extraction device, the pH value in the extraction device, the concentration of the extraction solvent configured in the extraction device, and the flow rate of the extraction solvent configured in the extraction device.

[0009] As a preferred solution of the natural product extraction process intelligent monitoring and data analysis system of the present invention, wherein: after the central processing unit obtains the digital signal collected by the sensor network, it constructs an extraction state display model, inputs the currently monitored and recorded extraction parameters, and outputs the current extraction state display value in real time;

[0010] Wherein, the extraction status display model specifically includes:

[0011]

[0012] Among them, δ is the extraction status display value; α is the temperature in the extraction device, ℃; β is the pressure in the extraction device, Pa; γ is the pH value in the extraction device; ω is the concentration of the extraction solvent configured in the extraction device, mol / L; v is the flow rate of the extraction solvent configured in the extraction device, cm / s; 1.33, 1.065, 2.40 and 2.55 are all adjustment constants; dx is an integral operation.

[0013] As a preferred solution of the natural product extraction process intelligent monitoring and data analysis system described in the present invention, the central processing unit adjusts the extraction process according to the preset extraction strategy and algorithm after obtaining the digital signal, which specifically includes the following steps: S1: after obtaining the digital signal collected by the sensor network, construct the extraction state display model, input the currently monitored and recorded extraction parameters, and output the current extraction state display value in real time; S2: within the rated time, use the current extraction parameters to extract, and measure the extraction rate corresponding to the current extraction state display value; S3: correct the extraction parameters in different extraction time periods, and obtain the corrected extraction state display value; S4: correct the extraction parameters multiple times in different extraction time periods, and obtain multiple extraction state display values ​​after multiple corrections in each extraction time period; S5: construct a difference detection model, arbitrarily select an extraction state display value in different extraction time periods as input, and output a difference difference value; S6: obtain the corrected extraction parameters corresponding to different extraction time periods whose difference difference values ​​meet the requirements.

[0014] As a preferred solution of the natural product extraction process intelligent monitoring and data analysis system of the present invention, the difference detection model constructed is specifically:

[0015]

[0016] Wherein, η is the difference difference value; δ1 is the extraction status display value selected in the first extraction time period; δ2 is the extraction status display value selected in the second extraction time period; δ n is the extraction status display value selected in the nth extraction time period; n is the number of divisions of the extraction time period; δ max The maximum value among the values ​​displayed for the selected extraction state; min is the minimum value among the selected extraction status display values; 1.033 is the adjustment constant; dx is the integral operation.

[0017] As a preferred solution of the natural product extraction process intelligent monitoring and data analysis system described in the present invention, when the difference difference value is less than or equal to 3.457, it is determined that the replaced current group of extraction parameters meets the requirements.

[0018] As a preferred solution of the natural product extraction process intelligent monitoring and data analysis system of the present invention, the rated time is defined as 5 to 10 minutes.

[0019] As a preferred solution of the natural product extraction process intelligent monitoring and data analysis system described in the present invention, different extraction time periods are evenly divided in chronological order, and the division time of each extraction time period is not less than the rated time.

[0020] The present invention provides a natural product extraction process intelligent monitoring and data analysis system, which has the following beneficial effects:

[0021] 1. The present invention deploys a multi-sensor network during the extraction process to achieve real-time monitoring of the extraction parameters of the extraction process, thereby improving the accuracy and real-time performance of the monitoring. At the same time, the extraction status display model creatively constructed by the present invention can display the current extraction status display value in real time, showing the degree of influence of the parameters inside the extractor;

[0022] 2. After acquiring the digital signal, the central processing unit of the present invention adjusts the extraction process according to the preset extraction strategy and algorithm, and intelligently optimizes the extraction process, thereby achieving energy saving and consumption reduction in the extraction process and improving economic benefits;

[0023] 3. The present invention has an adaptive adjustment function and can adjust the equipment according to the real-time data of the extraction process, thereby improving the extraction quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0025] Figure 1 This is an overall system module diagram of the natural product extraction process intelligent monitoring and data analysis system provided by the present invention.

[0026] Figure 2 A flow chart of a method for adjusting the extraction process according to a preset extraction strategy and algorithm after the central processing unit of the present invention acquires a digital signal. DETAILED DESCRIPTION

[0027] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0028] In the field of natural product extraction, traditional manually monitored extraction processes are limited by the operator's experience and attention, making it difficult to capture subtle changes in real time, let alone effectively analyze and utilize these parameter data to guide the optimization of the extraction process.

[0029] Therefore, please refer to Figure 1 The present invention provides a natural product extraction process intelligent monitoring and data analysis system, comprising the following components:

[0030] An extraction device for extracting natural products;

[0031] Sensor network, deploying a multi-sensor network during the extraction process to monitor and record extraction parameters in real time;

[0032] The data acquisition and processing unit converts the analog signals collected by the sensor network into digital signals and sends them to the central processing unit through high-speed data transmission lines;

[0033] The central processing unit, after acquiring the digital signal, adjusts the extraction process according to the preset extraction strategy and algorithm;

[0034] The intelligent data storage unit is wirelessly connected to the central processing unit to obtain the correlation between the extraction parameters and the extraction efficiency during the adjusted extraction process and complete the storage synchronously;

[0035] The user interface display unit is wirelessly connected to the intelligent data storage unit to display the correlation between the stored extraction parameters and the extraction efficiency.

[0036] It should be noted that:

[0037] ① The extraction device specifically includes:

[0038] 1. Extraction tank: The extraction tank is the core part of the natural product extraction device, usually made of stainless steel or other corrosion-resistant materials. It is used to hold the extraction solvent and raw materials, and is heated by a heater to promote the dissolution of the active ingredients. The design of the extraction tank should take into account thermal efficiency and material selection to ensure the stability of the extraction process and product quality.

[0039] 2. Agitator: The agitator is used to continuously stir the raw materials and extraction solvent during the extraction process to increase the contact area between the solvent and the raw materials and improve the extraction efficiency. The agitator is usually driven by a motor, and its speed can be adjusted to meet different extraction requirements.

[0040] 3. Heater: The heater is used to provide the heat required for the extraction process, usually an electric heater or a steam heater. The control of the heater should be precise to ensure the temperature of the extraction solvent is stable and avoid overheating or underheating.

[0041] 4. Cooling system: The cooling system is used to adjust the temperature of the extraction solvent during the extraction process to maintain the extraction efficiency and prevent excessive evaporation of the extraction solvent. The cooling system can include a cooling water circulation or an air cooling system.

[0042] 5. Extraction valves and pipelines: Extraction valves and pipelines are used to control the flow and discharge of extraction solvents. They should have good sealing performance to prevent leakage of extraction solvents.

[0043] 6. Sensors (i.e., sensor networks in the present invention): Sensors are used to monitor key parameters in the extraction process, such as temperature, pressure, etc. These data are used to control the extraction process and ensure the stability and safety of the extraction process.

[0044] 7. Data acquisition and processing system (i.e., the data acquisition and processing unit, the central processing unit, and the intelligent data storage unit in the present invention): The data acquisition and processing system is used to collect sensor data and perform real-time processing and storage. The system may include a computer control system for monitoring and analyzing the extraction process and providing corresponding control instructions.

[0045] 8. Extraction auxiliary equipment: Extraction auxiliary equipment may include filters, centrifuges and evaporators, etc., which are used to assist the extraction process, such as separating the extract and the residue, concentrating the extract, etc.

[0046] ② The extraction parameters monitored and recorded in real time by the sensor network specifically include: the temperature in the extraction device, the pressure in the extraction device, the pH value in the extraction device, the concentration of the extraction solvent configured in the extraction device, and the flow rate of the extraction solvent configured in the extraction device.

[0047] The sensor network specifically includes:

[0048] 1. Temperature sensor:

[0049] Type: Temperature is usually measured using a thermocouple or thermistor such as a platinum temperature sensor Pt100 or Pt1000.

[0050] Location: Temperature sensors should be deployed at key locations in the extraction device, such as inside the extraction tank or close to the heating element of the extraction tank.

[0051] Technical details: The sensor should have high precision and fast response characteristics to ensure accurate capture of temperature changes during the extraction process. The heat transfer medium between the sensor and the extraction tank should have good thermal conductivity to reduce heat loss.

[0052] 2. Pressure sensor:

[0053] Type: Use a pressure transmitter to measure the pressure inside the extraction unit.

[0054] Location: Pressure sensors are typically mounted on the top or side of extraction tanks, as well as near pumps and valves.

[0055] Technical details: The sensor should have sufficient strength and corrosion resistance to withstand pressure fluctuations during the extraction process. The output signal of the sensor should be compatible with the data acquisition system to accurately record pressure data.

[0056] 3. pH sensor:

[0057] Type: Use electrode type pH sensor to measure the pH value of the extraction solution.

[0058] Location: The pH sensor should be placed inside the extraction tank so that it is in direct contact with the extraction solution.

[0059] Technical details: The sensor should have good stability and repeatability, as well as resistance to chemicals that may be present in the extraction solution. The calibration and maintenance of the sensor should be easy to operate to ensure accurate pH measurement.

[0060] 4. Extraction solvent concentration sensor:

[0061] Type: Use a spectrometer, turbidity meter, or chemical sensor to measure the concentration of the extraction solvent.

[0062] Location: The concentration sensor can be installed at or near the outlet of the extraction tank.

[0063] Technical details: The sensor should be able to respond quickly and accurately measure changes in the concentration of the extraction solvent. For the spectrum analyzer, a wavelength range suitable for measuring the solvent concentration should be selected.

[0064] 5. Extraction solvent flow rate sensor:

[0065] Type: Use a flow meter (such as an electromagnetic flow meter, ultrasonic flow meter, or impeller flow meter) to measure the flow rate of the extraction solvent.

[0066] Location: The flow sensor should be installed in the flow path of the extraction solvent, such as on the inlet and outlet pipes of the extraction tank.

[0067] Technical details: The sensor should have high accuracy and stability and be able to adapt to the flow rate changes that may occur during the extraction process. The sensor should be installed to ensure minimal disturbance to the fluid.

[0068] The real-time monitoring and recorded extracted parameters of the sensor network are integrated and managed by the data acquisition and processing unit (DAS). The data acquisition system should have the following technical details:

[0069] Compatibility: Ensure that the interface between the sensor and the data acquisition system is compatible so that data can be transferred smoothly.

[0070] Communication interface: The acquisition system should have an interface for communicating with the superior control system or remote monitoring center, such as Ethernet, wireless network or serial communication port.

[0071] Storage and Reporting: The system should be able to store large amounts of data and generate reports.

[0072] ③The data acquisition and processing unit is a key component in the natural product extraction process. It is responsible for converting the analog signals collected by the sensor network into digital signals and sending them to the central processing unit through high-speed data transmission lines. The following is a description of the data acquisition and processing unit and its technical details:

[0073] 1. Analog signal conversion:

[0074] Type: Use Analog-to-Digital Converters (ADCs) to convert the analog signal output by the sensor into a digital signal.

[0075] Technical details: ADCs should have high resolution and high sampling rate to ensure the accuracy and real-time performance of signal conversion. For different sensor output ranges and accuracy requirements, choose appropriate ADC chips and circuit designs.

[0076] 2. Signal conditioning and preprocessing:

[0077] Type: Before signal conversion, the sensor signal may need to be conditioned by filtering, amplifying, zeroing, etc. to remove noise and drift.

[0078] Technical details: Use filtering circuits (such as low-pass, high-pass, and band-pass filters) to reduce high-frequency noise in the signal. The amplifier circuit should have sufficient gain and linear range to adapt to the strength of different sensor signals. The zero adjustment circuit is used to calibrate near the zero point of the sensor output signal.

[0079] 3. Data transmission:

[0080] Type: Uses high-speed data transmission lines to send processed digital signals to a central processing unit.

[0081] Technical details: The transmission line can be a standard digital interface such as SPI (Serial Peripheral Interface), I2C (Interconnection Protocol for Integrated Circuits), USB (Universal Serial Bus) or Ethernet. For long-distance transmission, optical fiber or wireless transmission technology may be required.

[0082] 4. Data Acquisition Card (DAC):

[0083] Type: If additional more complex processing of the sensor signals is required, a data acquisition card can be used, which usually plugs into a PCI or PCIe slot in the computer.

[0084] Technical details: The DAC should support multi-channel input / output, with high data acquisition rate and low latency. It should be able to handle large amounts of data and support various popular operating systems.

[0085] 5. Central Processing Unit (CPU):

[0086] Type: The central processing unit can be an embedded controller, an industrial control computer, or a general-purpose computer.

[0087] Technical details: The CPU should have sufficient processing power to process and analyze data from multiple sensors. It should be equipped with corresponding software libraries and algorithms to perform data analysis and control logic.

[0088] 6. Intelligent data storage unit:

[0089] Type: In the central processing unit, data can be temporarily stored in memory and stored by data processing software.

[0090] Technical details: Data processing software should be able to perform tasks such as data cleaning, filtering, statistics, etc. For data that needs to be stored for a long time, hard disks or solid-state drives should be used as data storage media.

[0091] 7. User interface display unit:

[0092] Type: User interface allows operators to view real-time data, historical trends and generate reports.

[0093] Technical details: The user interface should be simple and intuitive, supporting graphic display and interactive operation. The report generation tool should be able to customize the report format and content according to user needs.

[0094] Furthermore, after the central processing unit acquires the digital signals collected by the sensor network, it constructs an extraction status display model, inputs the currently monitored and recorded extraction parameters, and outputs the current extraction status display value in real time;

[0095] The extraction status display model specifically includes:

[0096]

[0097] Among them, δ is the extraction status display value; α is the temperature in the extraction device, ℃; β is the pressure in the extraction device, Pa; γ is the pH value in the extraction device; ω is the concentration of the extraction solvent configured in the extraction device, mol / L; v is the flow rate of the extraction solvent configured in the extraction device, cm / s; 1.33, 1.065, 2.40 and 2.55 are all adjustment constants; dx is the integral operation.

[0098] For further information, see Figure 2 After the central processing unit obtains the digital signal, the extraction process is adjusted according to the preset extraction strategy and algorithm, which specifically includes the following steps:

[0099] S1: After acquiring the digital signals collected by the sensor network, an extraction status display model is constructed, the currently monitored and recorded extraction parameters are input, and the current extraction status display value is output in real time;

[0100] S2: Within the rated time, the current extraction parameters are used to perform extraction and the extraction rate corresponding to the current extraction status display value is measured;

[0101] Specifically, the rated time is defined as 5 to 10 minutes.

[0102] It should be noted that the extraction rate of natural products measured within a rated time specifically includes:

[0103] 1. Extraction rate definition:

[0104] The extraction rate is defined as the amount of active ingredient extracted from the raw material per unit time, usually expressed as mass / time (mg / min or g / h).

[0105] 2. Determination method:

[0106] Gravimetric method: The extraction rate is calculated by weighing the mass difference between the raw material and the extract before and after extraction.

[0107] Spectroscopic analysis method: Use spectral analysis equipment (such as ultraviolet-visible spectroscopy, Fourier transform infrared spectroscopy, nuclear magnetic resonance spectroscopy, etc.) to quantitatively analyze the concentration of active ingredients in the extract and calculate the extraction rate.

[0108] Chromatographic analysis: Use high performance liquid chromatography (HPLC) or other chromatographic techniques to separate and quantitatively analyze the active ingredients in the extract and calculate the extraction rate.

[0109] 3. Sample preparation:

[0110] Before extraction, accurately weigh a certain amount of raw materials and record their original mass.

[0111] During the extraction process, the extract is collected according to the predetermined extraction conditions and time.

[0112] 4. Extract analysis:

[0113] The collected extract is appropriately treated, such as filtration, centrifugation, concentration, etc., to remove insoluble substances and impurities.

[0114] Select appropriate analytical methods according to the characteristics of the extract for quantitative analysis of the active ingredients.

[0115] 5. Data processing:

[0116] The concentration data of the active ingredient in the extract should be calibrated using a standard curve or a control sample of known concentration.

[0117] The extraction rate was calculated based on the concentration of the active ingredient and the volume of the extract.

[0118] S3: Correct the extraction parameters in different extraction time periods and obtain the corrected extraction status display value;

[0119] S4: Correcting the extraction parameters multiple times in different extraction time periods, and obtaining multiple extraction status display values ​​after multiple corrections in each extraction time period;

[0120] It should be noted that different extraction time periods are evenly divided in chronological order, and in order to ensure that at least one extraction rate can be calculated for each extraction time period, the division time of each extraction time period is not less than the rated time.

[0121] S5: construct a difference detection model, select any one of the extraction status display values ​​in different extraction time periods as input, and output the difference distinction value;

[0122] S6: Obtain corrected extraction parameters corresponding to different extraction time periods whose difference distinction values ​​meet the requirements.

[0123] Furthermore, the constructed difference detection model is as follows:

[0124]

[0125] Wherein, η is the difference difference value; δ1 is the extraction status display value selected in the first extraction time period; δ2 is the extraction status display value selected in the second extraction time period; δ n is the extraction status display value selected in the nth extraction time period; n is the number of divisions of the extraction time period; δ max The maximum value among the values ​​displayed for the selected extraction state; min is the minimum value among the selected extraction status display values; 1.033 is the adjustment constant; dx is the integral operation.

[0126] Specifically, when the difference difference value is less than or equal to 3.457, it is determined that the replaced current group extraction parameters meet the requirements.

[0127] It should be noted that there may be more than one set of extraction parameter groups that meet the requirements. You can select one set that meets the requirements, and the final total extraction result will not be much different.

[0128] In order to verify the technical effect of the present invention, the following experiments are performed for verification:

[0129] 1. Equipment preparation: Prepare the natural product extraction process intelligent monitoring and data analysis system described in the present invention, including extraction device, sensor network, data acquisition and processing unit, central processing unit and user interface. Ensure that all equipment is calibrated and functionally tested.

[0130] 2. Raw material preparation: Two different types of natural raw materials (raw material A and raw material B) were prepared, and a small batch pre-test was carried out for each raw material.

[0131] 3. Experimental design: Design multiple extraction experiments, including different raw materials (raw material A and raw material B), extraction solvent concentration (0.5 mol / L, 1 mol / L, 1.5 mol / L), extraction temperature (30°C, 40°C, 50°C), pH value (4, 5, 6), extraction pressure (1Mpa, 3Mpa, 5Mpa) and extraction solvent rate (3cm / s, 5cm / s, 10cm / s).

[0132] 4. Extraction experiment: The extraction experiment is carried out according to the experimental design, and the system of the present invention is started to perform real-time monitoring and data recording.

[0133] 5. Data collection: Collect data for real-time monitoring during the extraction process.

[0134] 6. Result analysis: Analyze the collected data, analyze the energy-saving effect and extraction quality, and use chemical analysis methods (such as high performance liquid chromatography, mass spectrometry) to quantitatively analyze the effective ingredients in the extract.

[0135] 7. Experimental report: Write an experimental report summarizing the experimental results, including the measured value of the extraction rate, the effect of energy saving and consumption reduction, and the improvement of extraction quality.

[0136] Among them, a group of representative data is selected, as shown in Table 1:

[0137] Table 1: Partial data collection form

[0138]

[0139]

[0140] The present invention provides a natural product extraction process intelligent monitoring and data analysis system, which has the following beneficial effects:

[0141] 1. The present invention deploys a multi-sensor network during the extraction process to achieve real-time monitoring of the extraction parameters of the extraction process, thereby improving the accuracy and real-time performance of the monitoring. At the same time, the extraction status display model creatively constructed by the present invention can display the current extraction status display value in real time, showing the degree of influence of the parameters inside the extractor;

[0142] 2. After acquiring the digital signal, the central processing unit of the present invention adjusts the extraction process according to the preset extraction strategy and algorithm, and intelligently optimizes the extraction process, thereby achieving energy saving and consumption reduction in the extraction process and improving economic benefits;

[0143] 3. The present invention has an adaptive adjustment function and can adjust the equipment according to the real-time data of the extraction process, thereby improving the extraction quality.

[0144] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A natural product extraction process intelligent monitoring and data analysis system, characterized in that: Includes the following components: An extraction device for extracting natural products; Sensor network, deploying a multi-sensor network during the extraction process to monitor and record extraction parameters in real time; A data acquisition and processing unit converts the analog signals collected by the sensor network into digital signals and sends them to the central processing unit through a high-speed data transmission line; The central processing unit, after acquiring the digital signal, adjusts the extraction process according to the preset extraction strategy and algorithm; An intelligent data storage unit is wirelessly connected to the central processing unit to obtain the correlation between the extraction parameters and the extraction efficiency in the adjusted extraction process and store the data synchronously; The user interface display unit is wirelessly connected to the intelligent data storage unit to display the correlation between the stored extraction parameters and the extraction efficiency.

2. The natural product extraction process intelligent monitoring and data analysis system according to claim 1, characterized in that: The extraction parameters monitored and recorded in real time by the sensor network specifically include: the temperature in the extraction device, the pressure in the extraction device, the pH value in the extraction device, the concentration of the extraction solvent configured in the extraction device, and the flow rate of the extraction solvent configured in the extraction device.

3. The natural product extraction process intelligent monitoring and data analysis system according to claim 2, characterized in that: After the central processing unit acquires the digital signal collected by the sensor network, it constructs an extraction status display model, inputs the currently monitored and recorded extraction parameters, and outputs the current extraction status display value in real time; Wherein, the extraction status display model specifically includes: Among them, δ is the extraction status display value; α is the temperature in the extraction device, ℃; β is the pressure in the extraction device, Pa; γ is the pH value in the extraction device; ω is the concentration of the extraction solvent configured in the extraction device, mol / L; v is the flow rate of the extraction solvent configured in the extraction device, cm / s; 1.33, 1.065, 2.40 and 2.55 are all adjustment constants; dx is an integral operation.

4. The natural product extraction process intelligent monitoring and data analysis system according to claim 3, characterized in that: After the central processing unit acquires the digital signal, the extraction process is adjusted according to the preset extraction strategy and algorithm, which specifically includes the following steps: S1: After acquiring the digital signal collected by the sensor network, construct the extraction status display model, input the currently monitored and recorded extraction parameters, and output the current extraction status display value in real time; S2: Within the rated time, the current extraction parameters are used to perform extraction and the extraction rate corresponding to the current extraction status display value is measured; S3: Correct the extraction parameters in different extraction time periods and obtain the corrected extraction status display value; S4: Correcting the extraction parameters multiple times in different extraction time periods, and obtaining multiple extraction status display values ​​after multiple corrections in each extraction time period; S5: construct a difference detection model, select any one of the extraction status display values ​​in different extraction time periods as input, and output the difference distinction value; S6: Obtain corrected extraction parameters corresponding to different extraction time periods in which the difference difference values ​​meet the requirements.

5. The natural product extraction process intelligent monitoring and data analysis system according to claim 4, characterized in that: The difference detection model constructed is specifically: Wherein, η is the difference difference value; δ1 is the extraction status display value selected in the first extraction time period; δ2 is the extraction status display value selected in the second extraction time period; δ n is the extraction status display value selected in the nth extraction time period; n is the number of divisions of the extraction time period; δ max The maximum value among the values ​​displayed for the selected extraction state; min is the minimum value among the selected extraction status display values; 1.033 is the adjustment constant; dx is the integral operation.

6. The natural product extraction process intelligent monitoring and data analysis system according to claim 5, characterized in that: When the difference difference value is less than or equal to 3.457, it is determined that the replaced current group extraction parameters meet the requirements.

7. The natural product extraction process intelligent monitoring and data analysis system according to claim 6, characterized in that: The rated time is defined as 5 to 10 minutes.

8. The natural product extraction process intelligent monitoring and data analysis system according to claim 7, characterized in that: Different extraction time periods are evenly divided according to the time sequence, and the division time of each extraction time period is not less than the rated time.

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