Precise quantitative intelligent control method and system for pneumatic plastic regulating valve

Abstract

The invention relates to the field of quantitative control, in particular to an accurate quantitative intelligent control method and system for a pneumatic plastic regulating valve, and the method comprises the steps: collecting an upstream pressure sequence and a downstream pressure sequence; constructing a time window for the upstream pressure sequence, clustering the time window to obtain sub-segments, calculating a drug content accumulated value of all the sub-segments, and taking the last sub-segment as a quantitative ending segment in response to the fact that the drug content accumulated value is not less than a preset required drug content; calculating a first quantitative mark value, similarly obtaining a second quantitative mark value, and calculating the similarity between the first quantitative mark value and any second quantitative mark value to obtain a matching moment; and according to the calculated actual flow velocity, correcting the medicine-containing amount accumulated value to obtain a medicine-containing amount accumulated corrected value, and according to the medicine-containing amount accumulated corrected value, completing quantitative control. According to the technical scheme, the precision and efficiency of the quantitative control result can be improved.

Description

Technical Field

[0001] This invention relates to the field of quantitative control. In particular, it relates to a precise quantitative intelligent control method and system for a pneumatic plastic regulating valve. Background Technology

[0002] In industries such as plastics processing, chemical reactions, food manufacturing, and pharmaceutical production, precise material handling and flow control have a crucial impact on production efficiency, product quality, and safety. Among these, pneumatic plastic control valves have become commonly used actuators in various automated production systems due to their simple structure, rapid response, and convenient maintenance.

[0003] In large-volume solution transport scenarios, especially for solutes that are difficult to dissolve, fluid viscosity can cause deviations between the actual flow rate and the standard preset flow rate, further altering the flow characteristics. In existing technologies, relying solely on empirical parameters and fixed control strategies leads to inaccurate control results. Summary of the Invention

[0004] To address the aforementioned technical problems, the present invention provides solutions in the following aspects.

[0005] In the first aspect, a precise quantitative intelligent control method for a pneumatic plastic regulating valve includes: collecting an upstream pressure sequence at the inlet of the flow channel and a downstream pressure sequence at the outlet of the flow channel; constructing a time window for the upstream pressure sequence, clustering the pressure values ​​within the time window to obtain sub-segments, calculating the drug content of any sub-segment, and calculating the cumulative drug content of all sub-segments; in response to the cumulative drug content not being less than a preset required drug content, taking the last sub-segment as the quantitative termination segment; taking the center point of the quantitative termination segment as the upstream center time, calculating the average pressure value of all sampling times in the quantitative termination segment, obtaining the upper and lower rails of the quantitative termination segment, and based on the average pressure value, the pressure value at the upstream center time, and the upper and lower rails of the quantitative termination segment, and... The first quantitative marker value is calculated for the upper and lower rails; the downstream center time is obtained based on the upstream center time, and a downstream window is constructed with the downstream center time as the midpoint. The second quantitative marker value is obtained for any sampling time in the downstream window according to the calculation method of the first quantitative marker value. The size of the downstream window is equal to the length of the quantitative end segment; the similarity between the first quantitative marker value and any second quantitative marker value is calculated, and the maximum similarity is taken as the matching time of the upstream center time; the actual flow rate is calculated based on the matching time, the upstream center time, and the obtained flow channel length. The cumulative drug content value is corrected according to the actual flow rate to obtain the cumulative drug content correction value. The quantitative control is completed based on the cumulative drug content correction value.

[0006] Preferably, the construction of the time window for the upstream pressure sequence includes: using the time length required to obtain the preset required drug amount in history as the marker length, and constructing a time window with the first sampling time of the upstream pressure sequence as the starting point and the marker length as the size.

[0007] Preferably, the step of clustering the pressure values ​​within the time window to obtain sub-segments includes: obtaining the viscosity of the drug solution and calculating the pressure standard deviation of the time window; mapping the viscosity using the hyperbolic tangent function to obtain a mapped value, calculating the sum of 1 and the mapped value, and using the product of the sum and the pressure standard deviation as the neighborhood radius; calculating the reciprocal of the sum of 1 and the pressure standard deviation, and rounding up the product of the reciprocal, the label length, and the sampling frequency of the upstream pressure sequence as the minimum quantity; clustering the pressure values ​​within the time window based on the neighborhood radius and the minimum quantity to obtain several effective clusters, each effective cluster corresponding to one sub-segment, and the number of sampling times in each effective cluster not less than the minimum quantity; wherein, the difference between the pressure values ​​at any two sampling times in a cluster is not greater than If the neighborhood radius and the number of sampling times within a cluster are less than the minimum number, add the next sampling time adjacent to the cluster to obtain a new cluster. If the difference in pressure values ​​between any two sampling times in the new cluster is greater than the neighborhood radius and the number of sampling times within the new cluster is less than the minimum number, add sampling times in chronological order until the number of sampling times within the new cluster equals the minimum number to obtain a valid cluster. If the difference in pressure values ​​between any two sampling times in the new cluster is not greater than the neighborhood radius and the number of sampling times within the new cluster is not less than the minimum number, continue adding sampling times in chronological order until the difference in pressure values ​​between any two sampling times in the new cluster is greater than the neighborhood radius, then stop adding sampling times and obtain a valid cluster.

[0008] Preferably, the calculation of the drug content of any sub-segment includes: obtaining the cross-sectional area and standard flow rate of the channel; calculating the density of the drug solution at each sampling time in any sub-segment, and calculating the average density of the drug solution at all sampling times in any sub-segment; and taking the product of the average density, cross-sectional area, standard flow rate and length of any sub-segment as the drug content.

[0009] Preferably, obtaining the upper and lower rails of the quantitative termination segment includes: obtaining the viscosity of the drug solution, calculating the standard deviation of all pressures within the quantitative termination segment as the quantitative standard deviation; mapping the viscosity using the hyperbolic tangent function to obtain a mapping value, and using the sum of 1.5 and the mapping value as the viscosity coefficient; calculating the first product of the viscosity coefficient and the quantitative standard deviation; using the sum of the average pressure and the first product as the upper rail, and the difference between the average pressure and the first product as the lower rail.

[0010] Preferably, the first quantitative marker value includes: taking the average of the upper and lower rails as the middle rail, taking the difference between the pressure value at the upstream center moment and the middle rail as the first term, taking the reciprocal of the difference between the upper and lower rails as the second term, and taking the product of the first term and the second term as the first quantitative marker value.

[0011] Preferably, obtaining the downstream center time based on the upstream center time includes: obtaining the distance between the channel inlet and the channel outlet, using the ratio of the distance to the standard flow velocity as the time interval, and using the sum of the upstream center time and the time interval as the downstream center time.

[0012] Preferably, the actual flow velocity includes: calculating the difference between the matching time and the upstream center time as a first difference, and using the ratio of the distance to the first difference as the actual flow velocity.

[0013] Preferably, the step of correcting the cumulative drug content value based on the actual flow rate to obtain the cumulative drug content correction value includes: obtaining the cross-sectional area of ​​the flow channel; calculating the density of the drug solution at each sampling time in any sub-segment, and calculating the average density of the drug solution at all sampling times in any sub-segment; using the product of the average density, cross-sectional area, actual flow rate, and length of any sub-segment as the drug content correction value, iterating through each sub-segment to obtain the drug content correction value, and summing the drug content correction values ​​of all sub-segments as the cumulative drug content correction value.

[0014] In a second aspect, a precise quantitative intelligent control system for a pneumatic plastic regulating valve includes: a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, a precise quantitative intelligent control method for a pneumatic plastic regulating valve as described in any one of the claims is implemented.

[0015] The present invention has the following effects: This invention provides a method for dynamic, real-time quantitative control of liquid medicine by precisely monitoring the flow and distribution of the liquid medicine within a flow channel, and combining factors such as pressure data, viscosity, and flow rate. This is achieved using the opening and closing status of a pneumatic plastic regulating valve. Analysis of upstream and downstream pressure sequences identifies issues such as pressure loss and flow non-uniformity within the flow channel, allowing for precise calculation and correction of the liquid medicine content. Particularly when considering the influence of fluid viscosity on pressure changes, an adjustable viscosity coefficient is introduced to accommodate different liquid medicine characteristics. By establishing time windows, cluster analysis, and quantitative labeling, the opening and closing times of the pneumatic plastic regulating valve can be accurately determined to achieve precise quantitative control. Furthermore, the liquid medicine content can be corrected based on the actual flow rate, ensuring accurate dosage. Attached Figure Description

[0016] Figure 1 This is a flowchart of a precise quantitative intelligent control method for a pneumatic plastic regulating valve according to an embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments.

[0018] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0019] Reference Figure 1 A method for precise quantitative intelligent control of a pneumatic plastic regulating valve includes steps S1-S4, as detailed below: S1: Collect the upstream pressure sequence at the inlet of the flow channel and the downstream pressure sequence at the outlet of the flow channel.

[0020] In one embodiment, a pressure sensor is placed at the inlet of the flow channel to collect the upstream pressure sequence, and a pressure sensor is placed at the outlet of the flow channel to collect the downstream pressure sequence. The upstream pressure typically reflects the state of the liquid before it enters the flow channel, while the downstream pressure reflects the changes in the liquid after it passes through the flow channel. By comparing the inlet and outlet pressure data, information such as pressure loss within the flow channel, fluid flow resistance, and potential flow non-uniformity can be obtained.

[0021] S2: Construct a time window for the upstream pressure sequence, cluster the pressure values ​​within the time window to obtain sub-segments, calculate the drug content of any sub-segment, and calculate the cumulative drug content of all sub-segments. In response to the cumulative drug content not being less than the preset required drug content, the last sub-segment is taken as the quantitative termination segment.

[0022] In one embodiment, the time required to obtain the preset required drug dosage in history is used as the marker length, and a time window is constructed with the first sampling moment of the upstream pressure sequence as the starting point and the marker length as the size.

[0023] Obtain the viscosity of the drug solution and calculate the pressure standard deviation over the time window. Map the viscosity using the hyperbolic tangent function to obtain the mapped value. Calculate the sum of 1 and the mapped value, and use the product of this sum and the pressure standard deviation as the neighborhood radius. The hyperbolic tangent function can map viscosity to the range of 0-1 and eliminate dimensions. The neighborhood radius satisfies the following relationship: , Represents the neighborhood radius. Indicates viscosity. Represents the hyperbolic tangent function. This represents the standard deviation of pressure within the time window. The standard deviation of pressure reflects the fluctuation of pressure values ​​within the time window, that is, the degree of deviation of the pressure value at each sampling moment from the mean of all pressure values ​​within the time window.

[0024] Calculate the reciprocal of the sum of 1 and the pressure standard deviation, and round up the product of the reciprocal, the tag length, and the sampling frequency of the upstream pressure sequence to obtain the minimum quantity. The minimum quantity satisfies the following relationship: , Indicates the minimum quantity. This indicates the sampling frequency of the upstream pressure sequence. Indicates the length of the marker. The standard deviation of stress within the time window. This indicates rounding up to the nearest integer.

[0025] The pressure values ​​within the time window are clustered based on the neighborhood radius and the minimum number of samples to obtain several effective clusters. Each effective cluster corresponds to a sub-segment, and the number of sampling times in each effective cluster is not less than the minimum number of samples.

[0026] Specifically, in response to the condition that the difference in pressure values ​​between any two sampling moments in a cluster is not greater than the neighborhood radius and the number of sampling moments in the cluster is less than the minimum number, a new cluster is obtained by adding the next sampling moment adjacent to the cluster. In response to the condition that the difference in pressure values ​​between any two sampling moments in the new cluster is greater than the neighborhood radius and the number of sampling moments in the new cluster is less than the minimum number, sampling moments are added in chronological order until the number of sampling moments in the new cluster equals the minimum number, thus obtaining a valid cluster. In response to the condition that the difference in pressure values ​​between any two sampling moments in the new cluster is not greater than the neighborhood radius and the number of sampling moments in the new cluster is not less than the minimum number, sampling moments are added in chronological order until the difference in pressure values ​​between any two sampling moments in the new cluster is greater than the neighborhood radius, at which point the addition stops, and a valid cluster is obtained.

[0027] It should be noted that the clustering process involves constructing a second valid cluster only after the first valid cluster has been completed. Therefore, clustering is performed sequentially for each sampling time. A valid cluster must satisfy the condition that the number of sampling times within the cluster is not less than a minimum number.

[0028] If the difference in pressure values ​​between any two sampling times in a cluster is not greater than the neighborhood radius and the number of sampling times in the cluster is less than the minimum number, it means that the clustering is not yet complete. The next time that is adjacent to the last sampling time in the cluster needs to be added to the cluster in chronological order to obtain a new cluster. At this time, there will be two situations in the new cluster.

[0029] Scenario 1: The difference in pressure values ​​between any two sampling moments in the new cluster is greater than the neighborhood radius, and the number of sampling moments in the new cluster is less than the minimum number. In this case, the difference in pressure values ​​between any two sampling moments is greater than the neighborhood radius, indicating that the newly added sampling moment does not belong to the new cluster. However, since the number of sampling moments in the new cluster is less than the minimum number, the consecutive sampling moments are directly added to the new cluster according to the minimum number, which can avoid data gaps.

[0030] Scenario 2: If the difference in pressure values ​​between any two sampling moments in the new cluster is not greater than the neighborhood radius, and the number of sampling moments in the new cluster is not less than the minimum number, then not only does the newly added sampling moment belong to the new cluster, but the addition of the new sampling moment also causes the new cluster to meet the minimum number. In this case, continue adding the next sampling moment in chronological order, and calculate the difference in pressure values ​​between any two sampling moments, until the difference in pressure values ​​between any two sampling moments in the cluster is greater than the neighborhood radius. Stop adding sampling moments, and a valid cluster is obtained. This method clusters sampling moments of the same cluster together as much as possible, preventing sampling moments of the same cluster from being divided into two or more clusters, thus avoiding redundancy in the calculation process.

[0031] Calculating the drug content of any segment includes: obtaining the cross-sectional area and standard flow rate of the channel; calculating the density of the drug solution at each sampling time in any segment, and calculating the average density of the drug solution at all sampling times in any segment; and taking the product of the average density, cross-sectional area, standard flow rate and length of any segment as the drug content.

[0032] Calculate the cumulative drug content of all sub-segments. If the cumulative drug content is not less than the preset required drug content, the last sub-segment is taken as the quantitative termination segment.

[0033] S3: Using the center point of the quantitative termination segment as the upstream center time, calculate the average pressure value of all sampling times in the quantitative termination segment, obtain the upper and lower rails of the quantitative termination segment, and calculate the first quantitative marker value based on the average pressure value, the pressure value of the upstream center time, the upper rail, and the lower rail; obtain the downstream center time based on the upstream center time, construct the downstream window with the downstream center time as the midpoint, and obtain the second quantitative marker value of any sampling time in the downstream window according to the calculation method of the first quantitative marker value, wherein the size of the downstream window is the same as the quantitative termination segment; calculate the similarity between the first quantitative marker value and any second quantitative marker value, and take the maximum similarity value as the matching time of the upstream center time.

[0034] In one embodiment, the center point of the quantitative termination segment is taken as the upstream center time. The average pressure at all sampling times within the quantitative termination segment is calculated to obtain the upper and lower rails of the quantitative termination segment. Existing technology obtains this using Bollinger Bands, typically calculated as twice the standard deviation. In this embodiment, the viscosity coefficient is used instead of the fixed twice. Specifically, the viscosity of the drug solution is obtained, and the standard deviation of all pressures within the quantitative termination segment is calculated as the quantitative standard deviation. The viscosity is mapped using a hyperbolic tangent function to obtain a mapped value, and the sum of 1.5 and the mapped value is taken as the viscosity coefficient. The first product of the viscosity coefficient and the quantitative standard deviation is calculated. The sum of the average pressure and the first product is taken as the upper rail, and the difference between the average pressure and the first product is taken as the lower rail.

[0035] The viscosity coefficient plays a moderating role in this calculation, specifically determined by the sum of 1.5 and the mapped viscosity. When the viscosity of the liquid is high, the viscosity coefficient increases, thus amplifying the impact on the calculation of the upper and lower rails.

[0036] The upper rail satisfies the following relation: , Indicates the upper rail. This represents the average pressure across all pressures within the final quantitative segment. Indicates the viscosity coefficient. It represents the standard deviation of all pressures within the quantitative endpoint.

[0037] The lower rail satisfies the following relation: , Indicates the lower rail. This represents the average pressure across all pressures within the final quantitative segment. Indicates the viscosity coefficient. It represents the standard deviation of all pressures within the quantitative endpoint.

[0038] Next, based on the average pressure, the pressure value at the upstream center time, and the upper and lower rails, the first quantitative marker value is calculated, including: The average of the upper and lower rails is taken as the middle rail. The difference between the pressure value at the upstream center moment and the middle rail is taken as the first term. The reciprocal of the difference between the upper and lower rails is taken as the second term. The product of the first and second terms is taken as the first quantitative marker value.

[0039] The first quantitative marker value satisfies the following relationship: , Indicates the upstream center time The first quantitative marker value, Indicates the upstream center time Pressure value, Indicates the upper rail. Indicates the lower rail.

[0040] To calculate the flow time of the liquid medicine from the inlet to the outlet in a flow channel, it is first necessary to obtain the distance between the inlet and outlet of the flow channel and then calculate the time required for fluid flow using a standard flow velocity. Specifically, the ratio of the flow channel distance to the standard flow velocity is used as the time interval, which is the flow time of the liquid medicine from the inlet to the outlet. Then, the upstream center time is added to the calculated time interval to obtain the downstream center time. In this way, the propagation time of the liquid medicine in the flow channel can be calculated, thus providing accurate time information for dynamic monitoring and control.

[0041] A downstream window is constructed with the downstream center time as the midpoint, and a second quantitative marker value is obtained at any sampling time within the downstream window according to the calculation method of the first quantitative marker value. The size of the downstream window is equal to the length of the quantitative end segment. The similarity between the first quantitative marker value at the upstream center time and the second quantitative marker value at any sampling time within the downstream window is calculated, and the maximum similarity is taken as the matching time of the upstream center time. It should be noted that the similarity can be represented by the reciprocal of the Euclidean distance.

[0042] S4: Calculate the actual flow rate based on the matching time, upstream center time, and obtained channel length. Correct the cumulative drug content value according to the actual flow rate, obtain the cumulative drug content correction value, and complete the quantitative control based on the cumulative drug content correction value.

[0043] In one embodiment, the difference between the matching time and the upstream center time is calculated as a first difference, and the ratio of the distance to the first difference is used as the actual flow velocity.

[0044] Replace the standard flow rate in the drug content formula calculated in step S2 with the actual flow rate. That is, use the product of the average density, cross-sectional area, actual flow rate and the length of any segment as the drug content correction value. Iterate through each segment to obtain the drug content correction value, and sum the drug content correction values ​​of all segments as the cumulative drug content correction value.

[0045] When the cumulative correction value of the drug content is not less than the preset required drug content, it means that the drug solution meets the requirements. At this time, the pneumatic plastic regulating valve needs to be closed and no drug solution is added, so as to complete the quantitative control.

[0046] The system includes a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement a precise quantitative intelligent control method for a pneumatic plastic regulating valve according to the first aspect of the present invention.

[0047] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

[0048] It should be noted that those skilled in the art can make various modifications and improvements without departing from the inventive concept, and these all fall within the scope of protection of this invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A precise quantitative intelligent control method for a pneumatic plastic regulating valve, characterized in that, include: Upstream pressure sequences were collected at the flow channel inlet, and downstream pressure sequences were collected at the flow channel outlet. A time window is constructed for the upstream pressure sequence. The pressure values ​​within the time window are clustered to obtain sub-segments. The drug content of any sub-segment is calculated, and the cumulative drug content of all sub-segments is calculated. In response to the cumulative drug content not being less than the preset required drug content, the last sub-segment is taken as the quantitative termination segment. The center point of the quantitative termination segment is taken as the upstream center time. The average pressure value of all sampling times in the quantitative termination segment is calculated, and the upper and lower rails of the quantitative termination segment are obtained. The first quantitative marker value is calculated based on the average pressure value, the pressure value of the upstream center time, and the upper and lower rails. The downstream center time is obtained according to the upstream center time. The downstream window is constructed with the downstream center time as the midpoint, and the second quantitative marker value of any sampling time in the downstream window is obtained according to the calculation method of the first quantitative marker value. The size of the downstream window is the same as the length of the quantitative termination segment. Calculate the similarity between the first quantitative marker value and any second quantitative marker value, and take the maximum similarity as the matching time of the upstream center time; The actual flow rate is calculated based on the matching time, the upstream center time, and the obtained channel length. The cumulative drug content value is corrected according to the actual flow rate to obtain the cumulative drug content correction value. Quantitative control is then completed based on the cumulative drug content correction value.

2. The precise quantitative intelligent control method for a pneumatic plastic regulating valve according to claim 1, characterized in that, The time window for constructing the upstream pressure sequence includes: The time required to obtain the preset required amount of drug in history is used as the marker length. A time window is constructed with the first sampling moment of the upstream pressure sequence as the starting point and the marker length as the size.

3. The precise quantitative intelligent control method for a pneumatic plastic regulating valve according to claim 2, characterized in that, The process of clustering the pressure values ​​within the time window to obtain sub-segments includes: Obtain the viscosity of the drug solution and calculate the pressure standard deviation within the time window; The viscosity is mapped using the hyperbolic tangent function to obtain the mapped value. The sum of 1 and the mapped value is calculated, and the product of the sum and the pressure standard deviation is used as the neighborhood radius. Calculate the reciprocal of the sum of 1 and the pressure standard deviation, and round up the product of the reciprocal, the tag length, and the sampling frequency of the upstream pressure sequence to obtain the minimum quantity; The pressure values ​​within the time window are clustered based on the neighborhood radius and the minimum number to obtain several effective clusters. Each effective cluster corresponds to a sub-segment, and the number of sampling times in each effective cluster is not less than the minimum number. Specifically, in response to the condition that the difference in pressure values ​​between any two sampling moments in a cluster is not greater than the neighborhood radius and the number of sampling moments in the cluster is less than the minimum number, a new cluster is obtained by adding the next sampling moment adjacent to the cluster. In response to the condition that the difference in pressure values ​​between any two sampling moments in the new cluster is greater than the neighborhood radius and the number of sampling moments in the new cluster is less than the minimum number, sampling moments are added in chronological order until the number of sampling moments in the new cluster equals the minimum number, thus obtaining a valid cluster. In response to the condition that the difference in pressure values ​​between any two sampling moments in the new cluster is not greater than the neighborhood radius and the number of sampling moments in the new cluster is not less than the minimum number, sampling moments are added in chronological order until the difference in pressure values ​​between any two sampling moments in the new cluster is greater than the neighborhood radius, at which point the addition stops, and a valid cluster is obtained.

4. The precise quantitative intelligent control method for a pneumatic plastic regulating valve according to claim 1, characterized in that, The calculation of the drug content of any sub-segment includes: Obtain the cross-sectional area and standard flow velocity of the flow channel; Calculate the density of the liquid medicine at each sampling time in any sub-segment, and calculate the average density of the liquid medicine at all sampling times in any sub-segment; The drug content is calculated as the product of the mean density, cross-sectional area, standard flow rate, and length of any segment.

5. The precise quantitative intelligent control method for a pneumatic plastic regulating valve according to claim 1, characterized in that, The acquisition of the upper and lower rails of the quantitative end segment includes: Obtain the viscosity of the drug solution and calculate the standard deviation of all pressures within the final quantitative segment as the quantitative standard deviation; The viscosity is mapped using the hyperbolic tangent function to obtain the mapped value, and the sum of 1.5 and the mapped value is taken as the viscosity coefficient. Calculate the first product of the viscosity coefficient and the standard deviation of quantitation; The sum of the average pressure and the first product is used as the upper rail, and the difference between the average pressure and the first product is used as the lower rail.

6. The precise quantitative intelligent control method for a pneumatic plastic regulating valve according to claim 1, characterized in that, The first quantitative marker value includes: The average of the upper and lower rails is taken as the middle rail. The difference between the pressure value at the upstream center moment and the middle rail is taken as the first term. The reciprocal of the difference between the upper and lower rails is taken as the second term. The product of the first and second terms is taken as the first quantitative marker value.

7. The precise quantitative intelligent control method for a pneumatic plastic regulating valve according to claim 1, characterized in that, The process of obtaining the downstream center time based on the upstream center time includes: Obtain the distance between the flow channel inlet and outlet, use the ratio of the distance to the standard flow velocity as the time interval, and use the sum of the upstream center time and the time interval as the downstream center time.

8. The precise quantitative intelligent control method for a pneumatic plastic regulating valve according to claim 7, characterized in that, The actual flow velocity includes: The difference between the matching time and the upstream center time is calculated as the first difference, and the ratio of the distance to the first difference is taken as the actual flow velocity.

9. The precise quantitative intelligent control method for a pneumatic plastic regulating valve according to claim 1, characterized in that, The step of correcting the cumulative drug content value based on the actual flow rate to obtain the corrected cumulative drug content value includes: Obtain the cross-sectional area of ​​the flow channel; Calculate the density of the liquid medicine at each sampling time in any sub-segment, and calculate the average density of the liquid medicine at all sampling times in any sub-segment; The product of the mean density, cross-sectional area, actual flow velocity, and length of any segment is used as the drug content correction value. The drug content correction value of each segment is obtained by iterating through all segments, and the cumulative value of the drug content correction values ​​of all segments is used as the cumulative drug content correction value.

10. A precise quantitative intelligent control system for a pneumatic plastic regulating valve, characterized in that, include: A processor and a memory, wherein the memory stores computer program instructions that, when executed by the processor, implement a precise quantitative intelligent control method for a pneumatic plastic regulating valve according to any one of claims 1-9.

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