Plant essence extractive distillation method, device and system

Abstract

The invention relates to the technical field of extractive distillation, in particular to a plant essence extractive distillation method, device and system, and the method comprises the following steps: acquiring temperature data, pressure data and flow data; acquiring average temperature data at each moment, respectively recording the average temperature data, the pressure data and the flow data as related data, and acquiring oscillation degree values of various related data in the monitoring time period; respectively acquiring a first influence coefficient and a second influence coefficient of the monitoring time period; acquiring a coupling disturbance index in the current monitoring time period; acquiring an unbalance coefficient of temperature distribution in the current monitoring time period according to the temperature data at each moment; and the rectification abnormal coefficient of the current monitoring time period is obtained by combining the coupling disturbance index in the current monitoring time period, so that the prediction range parameter in the model prediction control technology in the next monitoring time period is obtained, and the reflux quantity of the next monitoring time period is adjusted. According to the method, the extractive distillation purity of the plant extract is improved by optimizing the prediction range parameters.

Description

Technical Field

[0001] This application relates to the technical field of extractive distillation, and specifically relates to a method, equipment and system for extractive distillation of plant essence extract. Background Art

[0002] Plant essence extract is a concentrated solution of active ingredients extracted from plant tissues, retaining the original natural active substances in plants, such as volatile oils, polyphenols, alkaloids, etc., and having the characteristics of high purity and biological activity. Since the boiling points of these active ingredients are close to each other, high-purity separation can be achieved at a lower temperature through extractive distillation, avoiding the destruction of heat-sensitive substances at high temperatures, and effectively removing impurities at the same time, so as to obtain a plant essence extract with high concentration and high activity.

[0003] The extractive distillation process is a multi-variable, strongly coupled non-linear system. In practical applications, the greater the disturbance received by the system, the more difficult it is to maintain stable operation of the production process, and the more difficult it is to guarantee the product quality. For example, in the invention patent "CN119236439A Extractive Distillation System, Control Method and Extractive Distillation Process", cascade control loops and fixed ratio control strategies are used to adjust the stability of liquid level and temperature respectively, without considering the influence of the complex coupling effect between system multi-variables on the reflux flow rate. The concentration of the product obtained by extractive distillation still needs to be improved. At the same time, the temperature and pressure in the distillation column may also fluctuate due to equipment failures or abnormal operating parameters, thereby affecting the volatility of components. When the existing methods perform extractive distillation, the separation efficiency of the distillation column is improved by controlling the reflux flow rate in the distillation column. When using model predictive control (MPC) technology to adjust the reflux flow rate, fixed prediction range parameters are usually used, without fully considering the influence of the coupling fluctuation interference between multiple parameters on the volatility of solvent components and the separation efficiency, resulting in insufficient purity of the extractive distillation of the essence extract. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a method, equipment and system for extractive distillation of plant essence extract, and the specific technical solutions adopted are as follows: In the first aspect, an embodiment of this application provides a method for extractive distillation of plant essence extract, and the method includes the following steps: Obtain temperature data at different heights in the tower, tower pressure data and flow rate data of the condenser; Obtain the average temperature data at each moment in the tower, and denote the average temperature data, pressure data, and flow data as relevant data respectively. Obtain the periodic sequence and trend sequence of various types of relevant data during the monitoring period; obtain the oscillation degree value of various types of relevant data during the monitoring period according to the discreteness of the time intervals between the peaks in the periodic sequence of various types of relevant data during the monitoring period; obtain the first influence coefficient of the monitoring period according to the correlation coefficient between the trend sequences of the average temperature data and the flow data during the monitoring period; obtain the second influence coefficient of the monitoring period according to the correlation coefficient between the trend sequences of the average temperature data and the pressure data during the monitoring period; obtain the coupling disturbance index during the current monitoring period according to the oscillation degree value, the first influence coefficient, and the second influence coefficient of each relevant data during the current monitoring period; Obtain the imbalance coefficient of the temperature distribution during the current monitoring period according to the average level of the shortest distances from all temperature data at each moment during the current monitoring period to its fitting line; and combine the coupling disturbance index during the current monitoring period to obtain the rectification anomaly coefficient during the current monitoring period, and then obtain the prediction range parameter in the model predictive control technology for the next monitoring period, and adjust the reflux flow rate of the rectification process for the next monitoring period.

[0005] Preferably, the method for obtaining the oscillation degree value of various types of relevant data during the monitoring period is: obtain the fitting curve of the periodic sequence of various types of relevant data during the monitoring period, and extract the peaks from each fitting curve. Arrange the moment values corresponding to all peak points in each fitting curve in ascending order and denote it as the peak moment sequence of each fitting curve. Calculate the standard deviation of the first-order difference sequence of each peak moment sequence, and take the reciprocal of each standard deviation as the oscillation degree value of various types of relevant data during the monitoring period.

[0006] Preferably, the first influence coefficient of the monitoring period is the absolute value of the Spearman correlation coefficient between the trend sequences of the average temperature data and the flow data during the monitoring period.

[0007] Preferably, the second influence coefficient of the monitoring period is the absolute value of the Spearman correlation coefficient between the trend sequences of the average temperature data and the pressure data during the monitoring period.

[0008] Preferably, the calculation formula for the coupling disturbance index during the current monitoring period is: ; where is the coupling disturbance index during the current monitoring period, is the oscillation degree value of the average temperature data during the current monitoring period, is the oscillation degree value of the flow data during the current monitoring period, is the oscillation degree value of the pressure data during the current monitoring period, is the first influence coefficient of the current monitoring period, is the second influence coefficient for the current monitoring period.

[0009] Preferably, the method for obtaining the imbalance coefficient of the temperature distribution within the current monitoring period is as follows: Arrange the temperature data in the tower at each moment in ascending order of position to obtain the temperature distribution sequence at each moment, and obtain the fitting line of each temperature distribution sequence. Then, calculate the mean value of the shortest distances between all data in each temperature distribution sequence and the corresponding fitting line, and take the cumulative sum of the mean values at all moments within the current monitoring period as the imbalance coefficient of the temperature distribution within the current monitoring period.

[0010] Preferably, the rectification anomaly coefficient for the current monitoring period is the positive fusion result of the coupling disturbance index and the imbalance coefficient within the current monitoring period.

[0011] Preferably, the calculation formula for the prediction range parameter in the model predictive control technology for the next monitoring period is: ; where E is the prediction range parameter in the MPC technology for the next monitoring period, c is the first preset parameter, d is the second preset parameter, and c < d, and F is the normalized result of the rectification anomaly coefficient for the current monitoring period.

[0012] In a second aspect, an embodiment of the present application provides a plant essence extraction and rectification device, and the extraction and rectification device includes: a data acquisition module, an anomaly analysis module, and a parameter adjustment module.

[0013] The data acquisition module is used to obtain temperature data, pressure data, and flow data during the rectification process; The anomaly analysis module is used to obtain the coupling disturbance index within the current monitoring period based on the vibration degree of various relevant data and the correlation relationship between various relevant data; obtain the imbalance coefficient based on the temperature data distribution state at different heights at each moment; and further obtain the rectification anomaly coefficient for the current monitoring period; The parameter adjustment module is used to obtain the prediction range parameter in the model predictive control technology for the next monitoring period according to the rectification anomaly coefficient for the current monitoring period, and adjust the reflux flow rate during the rectification process for the next monitoring period.

[0014] In a third aspect, an embodiment of the present application further provides a plant essence extraction and rectification system, and the system includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of the method for extracting and rectifying a plant essence as described in any one of the above.

[0015] As can be seen from the above embodiments, a method, device, and system for extracting and rectifying a plant essence provided by an embodiment of the present application have at least the following beneficial effects: The present application provides a method, equipment and system for extractive distillation of plant essence extract. By deeply analyzing the vibration degree of average temperature data, pressure data and flow rate data during the distillation process, as well as the mutual influence characteristics between the average temperature data and the pressure data and flow rate data, a coupling disturbance index is calculated. Its advantage is that, compared with the single-parameter state monitoring, it can more accurately reflect the interference of the coupling effect of each parameter in the distillation system on the separation effect; further combined with the equilibrium state of the temperature distribution at each moment, an abnormal distillation coefficient is obtained, and based on this value, the prediction range parameter in the MPC technology in the next monitoring period is optimized, which helps to improve the extractive distillation purity of the plant essence extract. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 It is a flowchart of the steps of a method for extractive distillation of plant essence extract provided by an embodiment of the present application; Figure 2 It is a schematic diagram of the extractive distillation equipment provided by an embodiment of the present application. In Figure 2 1 is an extractive distillation column, 2 is a solvent recovery column, 3 is an extractant supplement stream, 4 is a plant raw material liquid, 5 is a condenser, 6 is the condensed liquid volatile oil, and 7 is the condensed liquid ginsenoside; Figure 3 It is a schematic structural diagram of a plant essence extract extractive distillation equipment provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] In order to further elaborate on the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following, in combination with the accompanying drawings and preferred embodiments, details the specific embodiments, structures, features and their effects of a method, equipment and system for extractive distillation of plant essence extract proposed according to the present application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0019] Unless otherwise specified or defined, terms such as "including", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the presence of additional identical elements in the article or device including said element. Additionally, the term "and / or" as used herein includes any and all combinations of one or more of the associated listed items. All technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this application belongs.

[0020] The following specifically describes the specific solutions of a method, equipment and system for extractive distillation of plant essence provided by this application in conjunction with the accompanying drawings.

[0021] Please refer to Figure 1 , which shows a step flowchart of a method for extractive distillation of plant essence provided by an embodiment of this application. The method includes the following steps: Step 1: Obtain temperature data at different heights inside the tower, pressure data inside the tower, and flow rate data of the condenser.

[0022] Before performing the extractive distillation of the plant essence, the plant tissue is first pretreated. The plant tissue is ground to increase the surface area, thereby improving the extraction efficiency, and then a plant raw material liquid is obtained. In this embodiment, ginseng is taken as an example, ginsenosides and volatile oils are extracted from ginseng, ethanol is used as the extractant, and the extractant is mixed and stirred with the plant raw material liquid. Since the relative volatility between different components in the plant raw material liquid is small, adding the extractant can greatly increase the volatility between components, which helps to efficiently separate different components. Finally, the stirred mixed solution is added to the extractive distillation equipment. The schematic diagram of the extractive distillation equipment is as Figure 2 shown.

[0023] The extractive distillation equipment includes an extractive distillation column and a solvent recovery column. The obtained mixed solution is first added into the extractive distillation column. The function of the extractive distillation column is to separate the light components and heavy components. The volatile oil in the plant raw material liquid has a lower boiling point, so it will first distill out from the top of the extractive distillation column and be condensed by a condenser to obtain liquid volatile oil. The remaining mixed solution in the extractive distillation column flows out from the bottom and enters the solvent recovery column. The function of the solvent recovery column is to further separate the heavy components and the extractant. The ginsenosides in the plant raw material liquid distill out from the top of the solvent recovery column and are condensed by a condenser to obtain liquid ginsenosides. After the extractant generated at the bottom is cooled and recycled, it enters the extractant circulation pipeline and then flows into the extractive distillation column. During the distillation process, part of the extractant is lost, and an extractant makeup stream is needed for supplementation, and thus the plant essence liquid is obtained through cyclic production.

[0024] During the extractive distillation process, the temperature, pressure, and condenser load in the distillation column will all have an important impact on the efficiency of distillation separation. Therefore, in this application, temperature sensors are installed at equal intervals at different tower heights in the distillation column to monitor the temperature distribution state in the distillation column. The pressure data of the distillation column is collected through a pressure sensor.

[0025] The load of the condenser is monitored by the flow rate of the condensate. A flow sensor is installed inside the condenser to collect the flow rate data of the condensate. In this embodiment, the above-mentioned sensors collect data synchronously and in real time, and the time interval for collecting data is 1 second. Thus, the temperature data at different heights in the distillation column, the pressure data inside the column, and the flow rate data of the condenser at each moment are obtained.

[0026] Step 2: Obtain the average temperature data at each moment in the column. Denote the average temperature data, pressure data, and flow rate data as relevant data respectively, and obtain the periodic sequence and trend sequence of various types of relevant data during the monitoring period; obtain the oscillation degree value of various types of relevant data during the monitoring period according to the dispersion degree of the time intervals between the peaks in the periodic sequence of various types of relevant data during the monitoring period; obtain the first influence coefficient of the monitoring period according to the correlation coefficient between the trend sequences of the average temperature data and the flow rate data during the monitoring period; obtain the second influence coefficient of the monitoring period according to the correlation coefficient between the trend sequences of the average temperature data and the pressure data during the monitoring period; obtain the coupling disturbance index of the current monitoring period according to the oscillation degree value, the first influence coefficient, and the second influence coefficient of each relevant data in the current monitoring period.

[0027] The temperature inside the extractive distillation column is an important factor affecting the distillation separation efficiency. An excessively high temperature inside the distillation column may cause other components in the plant raw material liquid to enter the distillate and contaminate the product, while a too low temperature will make it difficult for the components to evaporate sufficiently and remain in the distillation column, resulting in incomplete separation and reduced separation efficiency. Under the combined influence of factors such as feed component disturbance, heater load change, and other multiple factors, the temperature inside the distillation column, the pressure inside the column, and the condenser load are not constant. Specifically, the condensate flow rate reflects the load state of the condenser. Adjusting the condensate flow rate too low will cause the distillate components and other substances to not be well separated. And the change in the condenser flow rate will affect the temperature distribution inside the distillation column. If the condensate flow rate is too large, it may cause the temperature at the top of the column to be too low, affecting the vaporization of the components; while too small a condensate flow rate will cause the temperature at the top of the column to rise, reducing the purity of the components. The change in pressure inside the distillation column will also directly affect the temperature state inside the column. When the pressure increases, the temperature inside the column increases; when the pressure decreases, the temperature inside the column decreases.

[0028] From the above analysis, it can be seen that under good distillation conditions, the temperature data inside the column and the condensate flow rate data show a negative correlation, and the temperature data inside the column and the pressure data inside the column show a positive correlation. And the fluctuation stability of each data item will affect the final separation purity. To achieve real-time monitoring and rapid adjustment of the components, the length of the monitoring period is set to 2 minutes in this embodiment, that is, monitoring is carried out every 2 minutes.

[0029] Under the influence of raw material component disturbances and changes in heater load, the overall temperature of the distillation column will change. In order to achieve stability regulation, the control system makes the overall temperature change show certain periodic characteristics. If the existing periodic fluctuations are more significant, it means that the temperature oscillation in the column is more obvious and is more likely to affect the separation and extraction effect. Therefore, first, calculate the mean value of the temperature data at all positions in the column at each moment, and then obtain the average temperature data at each moment in the column. In this application, the STL (Seasonal and Trend decomposition using Loess) sequence decomposition algorithm is used to decompose the average temperature data, pressure data, and flow data during the current monitoring period, and output the periodic sequence and trend sequence of the average temperature data, pressure data, and flow data. The obtained periodic sequence can better reflect the periodic characteristics of the average temperature data itself. When the periodic characteristics are more significant, the distances between the fluctuation peaks in the obtained periodic sequence are more regular. Therefore, the polynomial fitting technology is used to obtain the fitting curve of the periodic sequence, and the peak value is extracted from the fitting curve by the derivative calculation method. The purpose of the fitting process is to avoid identifying local jitters in the sequence as peak values. Arrange the moment values corresponding to all peak points in ascending order as the peak moment sequence, and calculate the standard deviation of the first-order difference sequence of the obtained peak moment sequence. The smaller the standard deviation, the more regular the distribution of the distances between the peaks, and the more significant the periodic fluctuation of the temperature data in the corresponding period. Take the reciprocal of the obtained standard deviation as the oscillation degree value of the average temperature data during the current monitoring period, denoted as . The larger the oscillation degree value, the greater the impact of the temperature fluctuation during the current monitoring period on the separation and purification effect. Since the temperature change of the distillation column will affect the flow rate of the condensate and the pressure change in the distillation column, the condensate flow rate data and the pressure data in the column also have similar periodic fluctuation characteristics, which will further affect the separation purity. Similarly, calculate the oscillation degree values of the flow rate data and pressure data during the monitoring period according to the same steps, denoted as , .

[0030] Furthermore, analyze the cooperative balance characteristics among the parameters. The STL algorithm in the above steps obtains the trend sequences of various data. The data in the trend sequences reflect the overall changes over a long period of time. There is a certain time delay in the mutual influence between the temperature in the distillation column and the condensate flow rate and pressure respectively. Therefore, by comparing the correlation characteristics between the trend sequences, the coupling influence relevance of the current period can be better evaluated. Thus, the better the separation effect during distillation, the better the negative correlation between the temperature data and the condensate flow rate data. Calculate the Spearman correlation coefficient between the trend sequences of the average temperature data and the flow rate data during the current monitoring period, and take the absolute value of the Spearman correlation coefficient as the first influence coefficient of the current monitoring period, denoted as , the closer the value of the first influence coefficient is to zero, the worse the coordination degree between the temperature inside the tower and the condenser state during this monitoring period, and the less conducive to separation and purification. The better the separation effect during rectification, the better the positive correlation between the temperature data and the pressure data. Therefore, similar to the above steps, the absolute value of the Spearman correlation coefficient between the trend sequences of the average temperature data and the pressure data is used as the second influence coefficient, denoted as , the smaller the second influence coefficient, the worse the coordination degree between the temperature inside the tower and the pressure inside the tower during this monitoring period, and the less conducive to separation and purification.

[0031] The oscillation degree value reflects the change characteristics of each variable parameter. The different degrees of oscillation of each parameter will affect the separation effect of rectification. Furthermore, the coupling disturbance characteristics during the current monitoring period are obtained by integrating the oscillation degree value, the first influence coefficient, and the second influence coefficient. Since the separation effect of extractive distillation is more significantly affected by temperature changes compared to pressure and condenser flow rate, and there is a certain mutual disturbance between the temperature inside the distillation tower and the condenser flow rate and pressure respectively, which further affects the temperature change. Therefore, according to the first and second influence coefficients, the oscillation degree values of the condenser flow rate and pressure are adjusted respectively, and combined with the oscillation degree corresponding to the temperature, the coupling disturbance index during the current monitoring period is obtained. Its specific expression is: ; where, is the coupling disturbance index during the current monitoring period, is the oscillation degree value of the average temperature data during the current monitoring period, is the oscillation degree value of the flow rate data during the current monitoring period, is the oscillation degree value of the pressure data during the current monitoring period, is the first influence coefficient during the current monitoring period, is the second influence coefficient during the current monitoring period. The larger the obtained coupling disturbance index, the greater the degree of coupling fluctuation interference of multiple variables during the rectification process.

[0032] Step 3: Obtain the imbalance coefficient of the temperature distribution during the current monitoring period according to the average level of the shortest distance from all temperature data at each moment during the current monitoring period to its fitting line; and combine the coupling disturbance index during the current monitoring period to obtain the rectification anomaly coefficient during the current monitoring period, and then obtain the prediction range parameter in the model predictive control technology for the next monitoring period, and adjust the reflux flow rate during the rectification process of the next monitoring period.

[0033] Furthermore, the temperature states at different heights inside the distillation column are directly related to the mass transfer and heat transfer processes of the materials inside the column. The bottom of the column is usually a high-temperature zone because sufficient heat is required to maintain the evaporation of the liquid and ensure that the heavier components can be effectively retained at the bottom of the column. While the top of the column is a low-temperature zone, enabling the light components to be discharged in a liquid state. Therefore, a good distillation state is that the temperature distribution inside the column gradually decreases from the bottom to the top and changes smoothly. The imbalance of the temperature distribution will seriously affect the separation efficiency, and the degree of coupled disturbance of the distillation column also affects the temperature distribution. Therefore, evaluate the dynamic characteristics of the distillation process based on the temperature distribution state inside the distillation column and the degree of coupled disturbance it receives.

[0034] Arrange the temperature data inside the column at each moment in ascending order of position to obtain the temperature distribution sequence at each moment, and obtain the fitting straight line of each temperature distribution sequence. Then, calculate the mean value of the shortest distances between all the data in each temperature distribution sequence and the corresponding fitting straight line respectively, and take the cumulative sum of the mean values at all moments within the current monitoring period as the imbalance coefficient of the temperature distribution within the current monitoring period. This value reflects the imbalance state of the temperature distribution at different heights inside the distillation column. The coupled disturbance index reflects the mutual influence between the overall temperature state inside the column and other factors, and the imbalance coefficient reflects the state change of the heat transfer process inside the column. The two reflect the abnormal dynamic change characteristics of the distillation process from different perspectives. Therefore, take the product of the coupled disturbance index and the imbalance coefficient under the current monitoring period as the distillation anomaly coefficient of the current monitoring period. The larger this value is, the more obvious the abnormal dynamic change in the distillation process is.

[0035] This application calculates the distillation anomaly coefficient by analyzing the coupled disturbance characteristics between the temperature distribution inside the distillation column and the pressure and condenser load, as well as the temperature distribution state inside the column. This value reflects the significant degree of the abnormal dynamic change in the distillation process. The magnitude of the reflux flow directly affects the separation efficiency and energy consumption of the distillation column. To improve the distillation separation efficiency, optimize the response state of the reflux flow regulation to reduce the impact of abnormal dynamic changes. This embodiment uses the MPC technology to regulate the reflux flow, and improves the extractive distillation effect by optimizing the prediction range parameter in the MPC technology. During the distillation column separation process in the current monitoring period, the larger the obtained distillation anomaly coefficient is, the more obvious the abnormal dynamic change degree of the distillation system in the current monitoring period is. At this time, a larger prediction range parameter can be set to make the controller respond to the changes of the system faster and quickly adjust the reflux flow to a reasonable level; on the contrary, setting a smaller prediction range parameter helps to improve the control accuracy and save computing power. Specifically, set the interval of the prediction range parameter as [c, d]. In this embodiment, the interval of the prediction range parameter is set as [20, 30]. Then, the calculation formula for the prediction range parameter in the model predictive control of the next monitoring period is: ; where E is the prediction range parameter in the MPC technology for the next monitoring period, c is the first preset parameter, d is the second preset parameter, and c < d. F is the normalized result of the rectification anomaly coefficient for the current monitoring period. In this embodiment, the tanh function is used for normalization processing. Adjusting the prediction range parameter in the MPC technology for the next monitoring period through the calculated prediction range parameter helps improve the purity of extractive distillation.

[0036] Please refer to Figure 3 , Figure 3 which is a schematic structural diagram of an extractive distillation device for plant essence extraction liquid provided by an embodiment of the present application. In this embodiment, each unit included in the terminal is used to execute each step in the corresponding embodiment of a method for extractive distillation of plant essence extraction liquid. Refer to Figure 3 , the extractive distillation device includes: a data acquisition module, an anomaly analysis module, and a parameter adjustment module.

[0037] The data acquisition module is used to obtain temperature data, pressure data, and flow data during the rectification process; The anomaly analysis module is used to obtain the coupling disturbance index within the current monitoring period based on the vibration degree of various relevant data and the correlation relationship between various relevant data; obtain the imbalance coefficient based on the temperature data distribution state at different heights at each moment; and further obtain the rectification anomaly coefficient for the current monitoring period; The parameter adjustment module is used to obtain the prediction range parameter in the model predictive control technology for the next monitoring period according to the rectification anomaly coefficient for the current monitoring period, and adjust the reflux flow rate during the rectification process for the next monitoring period.

[0038] Based on the same inventive concept as the above method, an embodiment of the present application also provides a plant essence extraction liquid extractive distillation system, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-mentioned methods for extractive distillation of plant essence extraction liquid.

[0039] Each embodiment in the present application is described in a progressive manner. The same or similar parts between each embodiment can be referred to each other. The key points of each embodiment are the differences from other embodiments.

[0040] It should be noted that, unless otherwise specified and defined, terms such as "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the article or device including said element. In addition, the term "and / or" used herein includes any and all combinations of any one of the one or more related listed items.

[0041] Those skilled in the art will readily conceive of other embodiments of the present application after considering the specification and practicing the invention herein. The present application is intended to cover any variations, uses or adaptations of the present application that follow the general principles of the present application and include common general knowledge or conventional technical means in the technical field not invented by the present application.

[0042] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope.

Claims

1. A method for extractive distillation of plant essence liquid, characterized in that, The method comprises the following steps: Obtain the temperature data at different heights inside the tower, the pressure data inside the tower, and the flow rate data of the condenser; Obtain the average temperature data at each moment inside the tower, denote the average temperature data, the pressure data, and the flow rate data as relevant data respectively, and obtain the periodic sequence and the trend sequence of various types of relevant data within the monitoring period; Obtain the oscillation degree value of various types of relevant data within the monitoring period according to the dispersion degree of the time intervals between the peaks in the periodic sequence of various types of relevant data within the monitoring period; Obtain the first influence coefficient of the monitoring period according to the correlation coefficient between the trend sequences of the average temperature data and the flow rate data within the monitoring period; Obtain the second influence coefficient of the monitoring period according to the correlation coefficient between the trend sequences of the average temperature data and the pressure data within the monitoring period; Obtain the coupling disturbance index within the current monitoring period according to the oscillation degree value, the first influence coefficient, and the second influence coefficient of each relevant data within the current monitoring period; Obtain the imbalance coefficient of the temperature distribution within the current monitoring period according to the average level of the shortest distances from all the temperature data at each moment within the current monitoring period to their fitting lines; and combine the coupling disturbance index within the current monitoring period to obtain the rectification anomaly coefficient of the current monitoring period, and further obtain the prediction range parameter in the model predictive control technology for the next monitoring period, and adjust the reflux flow rate of the rectification process for the next monitoring period.

2. The extraction and rectification method of a plant essence extract according to claim 1, characterized in that The method for obtaining the oscillation degree value of various types of relevant data within the monitoring period is as follows: Obtain the fitting curve of the periodic sequence of various types of relevant data within the monitoring period, extract the peaks from each fitting curve, arrange the moment values corresponding to all the peak points in each fitting curve in ascending order to form the peak moment sequence of each fitting curve, calculate the standard deviation of the first-order difference sequence of each peak moment sequence, and take the reciprocal of each standard deviation as the oscillation degree value of various types of relevant data within the monitoring period.

3. The extraction and rectification method of a plant essence liquid according to claim 1, characterized in that, The first influence coefficient of the monitoring period is the absolute value of the Spearman correlation coefficient between the trend sequences of the average temperature data and the flow rate data within the monitoring period.

4. The extraction and rectification method of a plant essence liquid according to claim 1, characterized in that, The second influence coefficient of the monitoring period is the absolute value of the Spearman correlation coefficient between the trend sequences of the average temperature data and the pressure data within the monitoring period.

5. A method for extractive distillation of a plant essence liquid according to claim 1, characterized in that, The calculation formula for the coupling disturbance index within the current monitoring period is as follows: ; where is the coupling disturbance index within the current monitoring period, is the oscillation degree value of the average temperature data within the current monitoring period, is the oscillation degree value of the flow rate data within the current monitoring period, is the oscillation degree value of the pressure data within the current monitoring period, is the first influence coefficient within the current monitoring period, is the second influence coefficient within the current monitoring period.

6. The extraction and rectification method of a plant essence liquid according to claim 1, characterized in that, The method for obtaining the imbalance coefficient of the temperature distribution within the current monitoring period is as follows: Arrange the temperature data inside the tower at each moment in ascending order of position to obtain the temperature distribution sequence at each moment, and obtain the fitting line of each temperature distribution sequence, then calculate the mean value of the shortest distances between all the data in each temperature distribution sequence and the corresponding fitting line respectively, and take the sum of the mean values at all the moments within the current monitoring period as the imbalance coefficient of the temperature distribution within the current monitoring period.

7. The extraction and rectification method of a plant essence liquid according to claim 1, characterized in that, The rectification anomaly coefficient of the current monitoring period is the positive fusion result of the coupling disturbance index and the imbalance coefficient within the current monitoring period.

8. The extraction and rectification method of a plant essence liquid according to claim 1, characterized in that, The calculation formula for the prediction range parameter in the next monitoring period model predictive control technology is as follows: ; where E is the prediction range parameter in the MPC technology for the next monitoring period, c is the first preset parameter, d is the second preset parameter, and c < d, and F is the normalized result of the rectification abnormality coefficient for the current monitoring period.

9. An extraction and rectification device for plant essence liquid, characterized in that, Implement a plant essence extraction and rectification method as described in any one of claims 1-8, wherein the extraction and rectification equipment comprises: A data acquisition module for obtaining the temperature data, pressure data, and flow rate data during the rectification process; Anomaly analysis module, which is used to obtain the coupling disturbance index during the current monitoring period based on the vibration degree of various relevant data and the correlation relationship between various relevant data; obtain the imbalance coefficient based on the temperature data distribution state at different heights at each moment; and further obtain the rectification anomaly coefficient during the current monitoring period. Parameter adjustment module, which is used to obtain the prediction range parameter in the model predictive control technology for the next monitoring period according to the rectification anomaly coefficient during the current monitoring period, and adjust the reflux flow rate of the rectification process for the next monitoring period.

10. A rectification system for extracting plant essence liquid, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements a method for extractive distillation of plant essence liquid as described in any one of claims 1-8.

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