Full-automatic perfusion control method and system based on Internet of Things

Abstract

The invention discloses a full-automatic perfusion control method and system based on the Internet of Things, and relates to the technical field of perfusion control. The full-automatic perfusion control method based on the Internet of Things comprises the following steps of fluid attribute detection, perfusion control analysis and perfusion stability analysis. The relevant data of the monitored perfusion fluid attribute change are input into the perfusion control algorithm to be processed, the perfusion control quantity is output, then the change condition of the perfusion fluid attribute is monitored in real time in the perfusion control algorithm processing process, and perfusion control analysis is conducted according to the change condition of the perfusion fluid attribute. And finally, after perfusion control analysis, amplitude adjustment stability analysis is performed on the perfusion control quantity to perform perfusion control adjustment, so that the effect of improving the response timeliness of full-automatic perfusion control is achieved, and the problem of low response timeliness of full-automatic perfusion control in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of perfusion control technology, and in particular to a full-automatic perfusion control method and system based on the Internet of Things. Background Art

[0002] With the rapid development of the Internet of Things (IoT), the application of intelligence and automation is becoming increasingly widespread across industries. As a key application of IoT technology, fully automatic perfusion control systems are designed to precisely control the liquid perfusion process and are widely used in fields such as medicine, agriculture, and the chemical industry. Through sensors, data collection, and remote monitoring, the IoT enables real-time monitoring of the perfusion process, ensuring operational efficiency, stability, and safety. This system not only improves work efficiency but also reduces human error and resource waste.

[0003] Existing fully automated perfusion control technologies primarily rely on traditional sensors and control algorithms, using localized automation to monitor and regulate the perfusion process. However, these systems often lack flexibility and remote control capabilities, making it difficult to acquire large-scale environmental data in real time. With the introduction of the Internet of Things (IoT), sensor networks and cloud platforms enable real-time data collection, remote monitoring, and intelligent decision-making, significantly improving the system's automation and adaptability. Despite this, existing technologies still face challenges in data processing capabilities and system stability.

[0004] For example, the invention patent announcement with announcement number: CN112000155B discloses a liquid perfusion control method, device, and system, which include: at least one infrared camera, which is used to collect a liquid level image in a liquid barrel through the infrared camera, and send the collected liquid level image to an industrial computer, so that the industrial computer can identify the liquid level of the liquid level image and send a control signal to a perfusion control module according to the identified liquid level; the perfusion control module is located on the connecting pipeline between the liquid storage tank and the liquid barrel, and is used to control the liquid transportation on the connecting pipeline according to the control signal received from the industrial computer.

[0005] For example, the microcomputer fully automatic perfusion system disclosed in the invention patent announcement with announcement number CN104991576B includes: an operating table and a perfusion box, the perfusion box includes an upper box body and a lower box body with independent inner cavities, a water inlet pipe and a drug inlet pipe communicating with the inner cavity of the lower box body, a plurality of perfusion pumps whose liquid inlet ends communicate with the inner cavity of the lower box body, and a perfusion pipe connected to the liquid outlet end of the perfusion pump. The perfusion system also includes a microcomputer controller and several module units arranged in the inner cavity of the upper box body, and a display surface arranged on the surface of the upper box body and electrically connected to the output end of the microcomputer controller.

[0006] However, in the process of implementing the technical solutions of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems: In existing technologies, inaccurate control algorithms can lead to excessive or insufficient perfusion (overshoot) or under-perfusion (under-perfusion). Control algorithms must strike a balance between adjustment speed and system stability. Excessively fast adjustment speeds can lead to overshoot, while too slow adjustment speeds can cause delayed system response and under-perfusion. If the control system fails to find the right balance, the system may respond too quickly or too slowly, resulting in poor response timeliness in fully automatic perfusion control. Summary of the Invention

[0007] The embodiments of the present application solve the problem of low response timeliness of fully automatic perfusion control in the prior art by providing a fully automatic perfusion control method and system based on the Internet of Things, and achieve an improvement in the response timeliness of fully automatic perfusion control based on the Internet of Things.

[0008] An embodiment of the present application provides a fully automatic perfusion control method based on the Internet of Things, comprising the following steps: inputting data related to monitored changes in perfusion fluid properties into a perfusion control algorithm for processing, and outputting a perfusion control amount; monitoring changes in the perfusion fluid properties in real time during the processing of the perfusion control algorithm, and performing corresponding perfusion control analysis based on the changes in the perfusion fluid properties, wherein the perfusion control analysis is used to analyze the real-time changes in the perfusion fluid properties and adopt corresponding control and adjustment measures; after the perfusion control analysis, performing an amplitude adjustment stability analysis on the perfusion control amount, and performing corresponding perfusion control adjustment based on the analysis results, wherein the amplitude adjustment stability analysis is used to quantify the degree of influence of the adjustment of the perfusion control amount on the stability of the perfusion system, and the perfusion control adjustment is used to reduce the degree of influence of the adjustment of the perfusion control amount on the stability of the perfusion system.

[0009] Furthermore, the data related to the monitored changes in the properties of the perfusion fluid are input into the perfusion control algorithm for processing, and the perfusion control amount is output. The specific process is as follows: if the perfusion sensor detects a change in the properties of the perfusion fluid, the corresponding perfusion fluid property data is obtained and the corresponding property is marked as a qualitatively changed perfusion fluid property. A first target perfusion rate is obtained based on the qualitatively changed perfusion fluid property. The first target perfusion rate and a first actual perfusion rate obtained by real-time monitoring are input into the perfusion control algorithm to output the perfusion control amount; the first actual perfusion rate represents the perfusion rate of the perfusion fluid with the qualitatively changed perfusion fluid property, and the fluid property data includes viscosity, temperature, and density; the first target perfusion rate represents the target perfusion rate that meets the qualitatively changed perfusion fluid property; the perfusion sensor includes a densitometer, a rotational viscosity sensor, and a temperature sensor.

[0010] Furthermore, during the perfusion control algorithm processing, the changes in the perfusion fluid properties are monitored in real time, and corresponding perfusion control analysis is performed according to the changes in the perfusion fluid properties. The specific steps are as follows: A1, when it is monitored that the perfusion fluid properties have not changed, the fluid property change trend analysis is performed, otherwise A2 and A3 are executed simultaneously. The fluid property change trend analysis is used to analyze the change trend of the perfusion fluid properties after the perfusion control algorithm processing time period; A2, according to the second target perfusion rate and the second actual perfusion rate, the target-actual perfusion error is obtained, and the target-actual perfusion error and the preset short-term correction factor are constructed. A correction mapping set is configured to input the real-time target-actual perfusion error into the correction mapping set to obtain a corresponding short-term correction factor. The perfusion control amount is corrected based on the short-term correction factor. The second target perfusion rate represents the perfusion rate corresponding to the perfusion fluid properties that change during the perfusion control algorithm processing time period. The second actual perfusion rate represents the real-time perfusion rate of the perfusion fluid properties that change during the perfusion control algorithm processing time period. The short-term correction factor is used to pre-adjust the control direction of the perfusion control amount. A3 inputs the second target perfusion rate and the second actual perfusion rate into the perfusion control algorithm to obtain the perfusion control amount to be updated.

[0011] Furthermore, the specific process of fluid property change trend analysis is as follows: the change trend of the fluid properties within the perfusion control algorithm processing time period is analyzed to obtain a fluid property trend change index, and the change trend analysis is used to quantify the probability of changes in the perfusion fluid properties after the perfusion control algorithm processing time period; the fluid property trend change index is compared with the fluid property change trend threshold obtained from the preset database: if the fluid property trend change index is less than the fluid property change trend threshold, no additional processing is performed; if the fluid property trend change index is not less than the fluid property change trend threshold, the fluid property trend change index and the fluid property change trend threshold are differenced to obtain a fluid property change trend difference value, and the perfusion control amount is adjusted by obtaining a perfusion pre-adjustment factor according to the fluid property change trend difference value mapping, and the perfusion pre-adjustment factor represents the data for pre-adjusting the perfusion control amount according to the change trend of the fluid properties.

[0012] Furthermore, a change trend analysis of the fluid properties within the perfusion control algorithm processing time period is performed to obtain a fluid property trend change index. The specific process is as follows: obtaining the fluid property change rate data within the perfusion control algorithm processing time period, the fluid property change rate data including the fluid density change rate, the fluid viscosity change rate and the fluid temperature change rate; obtaining the fluid property change compensation value from the preset database, the fluid property change compensation value including the density compensation value, the viscosity compensation value and the temperature compensation value; performing a weighted operation based on the fluid property change rate data and the corresponding fluid property change compensation value, and then coupling to obtain the fluid property trend change index, which is used to quantify the trend of changes in fluid properties.

[0013] Furthermore, after the perfusion control analysis, the perfusion control amount is subjected to an amplitude adjustment stability analysis, and corresponding perfusion control adjustments are performed based on the analysis results. The specific steps are as follows: S1, performing a difference operation between the perfusion control amount to be updated and the corrected perfusion control amount to obtain the perfusion control adjustment amount, where the corrected perfusion control amount represents the perfusion control amount adjusted by the short-term correction factor; S2, if the perfusion control adjustment amount is not less than the maximum adjustment amplitude value, adjusting the corrected perfusion control amount to the maximum amplitude perfusion control amount and executing S3, otherwise no additional processing is performed, where the maximum amplitude perfusion control amount represents the perfusion control amount obtained by mapping the maximum adjustment amplitude value; S3, in the process of adjusting the corrected perfusion control amount to the maximum amplitude perfusion control amount, obtaining system stability evaluation data in real time, and performing system stability evaluation based on the system stability evaluation data.

[0014] Furthermore, the specific process of performing system stability evaluation based on the system stability evaluation data is as follows: a system stability evaluation index is obtained by performing stability analysis on the system stability evaluation data, and the stability analysis is used to evaluate the stability of the perfusion system during the process of adjusting the corrected perfusion control amount to the maximum amplitude perfusion control amount; a difference operation is performed on the perfusion control amount to be updated and the maximum amplitude perfusion control amount to obtain the perfusion control amount to be compensated; if the system stability evaluation index is less than the stability threshold, the perfusion control amount to be compensated is adjusted based on the maximum amplitude perfusion control amount until the perfusion control amount to be updated is reached; if the system stability evaluation index is not less than the stability threshold, the maximum amplitude perfusion control amount is adjusted based on the system stability evaluation index.

[0015] Furthermore, the specific contents of adjusting the maximum amplitude perfusion control amount based on the system stability evaluation index are as follows: performing a difference operation on the system stability evaluation index and the stability threshold to obtain a perfusion adjustment stability difference; constructing a stability mapping set between the perfusion adjustment stability difference and a preset stability adjustment ratio; inputting the real-time perfusion adjustment stability difference into the stability mapping set to output the stability adjustment ratio; based on the maximum amplitude perfusion control amount, adjusting the perfusion control amount to be compensated according to the stability adjustment ratio until the perfusion control amount to be updated is reached.

[0016] Furthermore, the system stability evaluation index is obtained as follows: system stability evaluation data is obtained and normalized, the system stability evaluation data including flow rate change rate, damping ratio, phase margin, gain margin and steady-state error; stability compensation values ​​are obtained from a preset database, the stability compensation values ​​including flow rate change rate compensation value, damping ratio compensation value, phase margin compensation value, gain margin compensation value and steady-state error compensation value; after performing correlation conversion operation on the damping ratio, phase margin and gain margin and performing weighted operation with the flow rate change rate, steady-state error and corresponding stability compensation value, the system stability evaluation index is obtained after coupling. The system stability evaluation index is used to evaluate the degree of influence on system stability during the adjustment of the perfusion control quantity.

[0017] Furthermore, the fully automatic perfusion control system based on the Internet of Things includes a fluid property detection module, a perfusion control analysis module and a perfusion stability analysis module; wherein the fluid property detection module is used to input the monitored perfusion fluid property change related data into the perfusion control algorithm for processing and output the perfusion control amount; the perfusion control analysis module is used to monitor the changes in the perfusion fluid properties in real time during the processing of the perfusion control algorithm, and perform corresponding perfusion control analysis according to the changes in the perfusion fluid properties. The perfusion control analysis is used to analyze the real-time changes in the perfusion fluid properties in order to take corresponding control and adjustment measures; the perfusion stability analysis module is used to perform amplitude adjustment stability analysis on the perfusion control amount after the perfusion control analysis, and perform corresponding perfusion control adjustment according to the analysis results. The amplitude adjustment stability analysis is used to quantify the degree of influence of the adjustment of the perfusion control amount on the stability of the perfusion system, and the perfusion control adjustment is used to reduce the degree of influence of the adjustment of the perfusion control amount on the stability of the perfusion system.

[0018] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. By inputting the relevant data of the monitored perfusion fluid property changes into the perfusion control algorithm for processing and outputting the perfusion control amount, the changes in the perfusion fluid properties are monitored in real time during the perfusion control algorithm processing, and perfusion control analysis is performed based on the changes in the perfusion fluid properties. Finally, after the perfusion control analysis, the amplitude adjustment stability analysis of the perfusion control amount is performed to perform perfusion control adjustment, thereby more fully analyzing the impact of fluid property changes on the perfusion speed, thereby improving the timeliness of the fully automatic perfusion control response, and effectively solving the problem of low response timeliness of the fully automatic perfusion control algorithm based on the Internet of Things in the existing technology.

[0019] 2. By obtaining the fluid property change rate data within the perfusion control algorithm processing time period and obtaining the fluid property change compensation value from the preset database, a fluid property trend change index is obtained after weighted calculation based on the fluid property change rate data and the fluid property change compensation value. This more accurately quantifies the trend of fluid property changes and thereby improves the adaptability of the perfusion speed to fluid property changes.

[0020] 3. By obtaining system stability evaluation data and obtaining stability compensation values ​​from a preset database, and then performing correlation conversion operations on the damping ratio, phase margin, and gain margin, and then performing weighted operations with the flow rate change rate, steady-state error, and stability compensation value, the system stability evaluation index is obtained. This more accurately evaluates the degree of influence of the perfusion control quantity adjustment process on the system stability, thereby ensuring the stability of the system during the perfusion control quantity adjustment process. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 Flowchart of the fully automatic perfusion control method based on the Internet of Things provided in an embodiment of the present application. DETAILED DESCRIPTION

[0022] The embodiments of the present application provide an Internet of Things-based fully automatic perfusion control method and system, which solves the problem of low response timeliness of the fully automatic perfusion control algorithm based on the Internet of Things in the prior art. The method inputs the monitored data related to the change of the perfusion fluid properties into the perfusion control algorithm for processing and outputs the perfusion control amount. Then, during the processing of the perfusion control algorithm, the changes in the perfusion fluid properties are monitored in real time, and perfusion control analysis is performed based on the changes in the perfusion fluid properties. Finally, the perfusion control amount to be updated and the corrected perfusion control amount are calculated to obtain the perfusion control adjustment amount. If the perfusion control adjustment amount is not less than the maximum adjustment amplitude value, the corrected perfusion control amount is adjusted to the maximum amplitude perfusion control amount and a system stability assessment is performed. Otherwise, no additional processing is performed. At the same time, during the process of adjusting the corrected perfusion control amount to the maximum amplitude perfusion control amount, system stability assessment data is obtained in real time, and a system stability assessment is performed based on the system stability assessment data, thereby improving the timeliness of the fully automatic perfusion control response.

[0023] The technical solution in the embodiment of the present application is to solve the problem of low response timeliness of the above-mentioned fully automatic perfusion control. The overall idea is as follows: By inputting the data related to the monitored changes in the perfusion fluid properties into the perfusion control algorithm for processing and outputting the perfusion control amount, the changes in the perfusion fluid properties are then monitored in real time during the processing of the perfusion control algorithm, and perfusion control analysis is performed based on the changes in the perfusion fluid properties. Finally, after the perfusion control analysis, the amplitude adjustment stability analysis of the perfusion control amount is performed to perform perfusion control adjustment, thereby achieving the effect of improving the response timeliness of the fully automatic perfusion control.

[0024] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0025] like Figure 1FIG. 1 is a flow chart of a fully automatic perfusion control method based on the Internet of Things (IoT) according to an embodiment of the present application. The method includes the following steps: inputting data related to changes in monitored perfusion fluid properties into a perfusion control algorithm (e.g., a PID control algorithm, a fuzzy control algorithm, a model predictive control algorithm, and an adaptive control algorithm) for processing, and outputting a perfusion control variable. Examples of perfusion control algorithms include a Proportional-Integral-Derivative (PID) control algorithm, a fuzzy control algorithm, a model predictive control algorithm, and an adaptive control algorithm. The present application uses the PID control algorithm as an example. During the perfusion control algorithm processing, changes in perfusion fluid properties are monitored in real time, and a corresponding perfusion control analysis is performed based on the changes in the perfusion fluid properties. The perfusion control analysis is used to analyze the real-time changes in the perfusion fluid properties and to take corresponding control and adjustment measures. Following the perfusion control analysis, an amplitude adjustment stability analysis is performed on the perfusion control variable, and corresponding perfusion control adjustments are performed based on the analysis results. The amplitude adjustment stability analysis is used to quantify the impact of the adjustment of the perfusion control variable on the stability of the perfusion system. The perfusion control adjustment is used to reduce the impact of the adjustment of the perfusion control variable on the stability of the perfusion system.

[0026] In this embodiment, the real-time target perfusion rate is input into the PID control algorithm, which outputs a perfusion control variable. This perfusion control variable is used to regulate a component (e.g., a pump or valve). The perfusion rate, and thus the perfusion flow rate, is adjusted based on the magnitude of the control output signal of the perfusion control variable. During the perfusion process, the properties of the perfusion fluid (e.g., viscosity, temperature, density, etc.) may change, resulting in the perfusion flow control system being unable to accurately determine the flow of the perfusion fluid. For example, an increase in the viscosity of the perfusion fluid may slow the perfusion flow rate, potentially leading to insufficient perfusion. Conversely, a decrease in the viscosity of the perfusion fluid may lead to excessive perfusion. Therefore, by monitoring changes in perfusion fluid properties in real time during the perfusion control algorithm, and taking timely perfusion adjustment measures based on these changes, the perfusion system can be improved in terms of its response time to changes in fluid properties, reducing the probability of overshoot or underfilling of the perfusion fluid. This improves the accuracy of the perfusion system's perfusion volume control and enhances the timeliness of the response of the fully automated perfusion control algorithm based on the Internet of Things.

[0027] Furthermore, the data related to the monitored changes in the properties of the perfusion fluid are input into the perfusion control algorithm for processing, and the perfusion control amount is output. The specific process is as follows: if the perfusion sensor detects a change in the properties of the perfusion fluid, the corresponding perfusion fluid property data is obtained and the corresponding property is marked as a qualitative change perfusion fluid property. A first target perfusion rate is obtained based on the qualitative change perfusion fluid property. The first target perfusion rate and the first actual perfusion rate obtained by real-time monitoring are input into the perfusion control algorithm to output the perfusion control amount; the first actual perfusion rate represents the perfusion rate of the perfusion fluid with the qualitative change perfusion fluid property, and the fluid property data includes viscosity, temperature and density; the perfusion sensor includes a densitometer, a rotational viscosity sensor and a temperature sensor, and the viscosity is measured by using a rotational viscosity sensor deployed in the fluid pipeline of the fully automatic perfusion control system; the temperature is measured by a temperature sensor deployed at the inlet and outlet of the perfusion pipeline or the liquid storage tank of the fully automatic perfusion control system; the density is measured by a densitometer deployed in the fluid pipeline of the fully automatic perfusion control system; the first target perfusion rate represents the target perfusion rate that meets the qualitative change perfusion fluid property.

[0028] In this embodiment, the data related to changes in the properties of the perfusion fluid specifically includes a target perfusion rate, an actual perfusion rate, a flow error (i.e., the difference between the target flow rate and the actual flow rate), the rate of change of the flow error over time, and the integral value of the flow error. A mapping set is constructed between the fluid property data and the corresponding first target perfusion rate, and the real-time fluid property data is input into the mapping set to obtain the corresponding first target perfusion rate. The mapping set is pre-constructed by preset professionals and stored in a preset database. By monitoring changes in fluid viscosity, temperature, and density in real time, the system can accurately identify changes in perfusion fluid properties and adjust the perfusion rate in a timely manner. This approach ensures that the perfusion system can be adaptively adjusted according to actual fluid conditions, helps avoid inaccuracies in perfusion rate and perfusion volume caused by changes in perfusion fluid properties, and thereby improves the accuracy of the perfusion process.

[0029] Furthermore, during the perfusion control algorithm processing, the changes in the perfusion fluid properties are monitored in real time, and corresponding perfusion control analysis is performed according to the changes in the perfusion fluid properties. The specific steps are as follows: A1, when it is monitored that the perfusion fluid properties have not changed, the fluid property change trend analysis is performed, otherwise A2 and A3 are executed simultaneously. The fluid property change trend analysis is used to analyze the change trend of the perfusion fluid properties after the perfusion control algorithm processing time period; A2, according to the second target perfusion rate and the second actual perfusion rate, the target-actual perfusion error is obtained, and the target-actual perfusion error and the preset short-term correction factor are constructed. A correction mapping set is configured to input the real-time target-actual perfusion error into the correction mapping set to obtain a corresponding short-term correction factor. The perfusion control amount is corrected based on the short-term correction factor. The second target perfusion rate represents the perfusion rate corresponding to the perfusion fluid properties that change during the perfusion control algorithm processing time period. The second actual perfusion rate represents the real-time perfusion rate of the perfusion fluid properties that change during the perfusion control algorithm processing time period. The short-term correction factor is used to pre-adjust the control direction of the perfusion control amount. A3 inputs the second target perfusion rate and the second actual perfusion rate into the perfusion control algorithm to obtain the perfusion control amount to be updated.

[0030] In this embodiment, a target-actual perfusion error is obtained by performing a difference operation on the second target perfusion rate and the second actual perfusion rate; the perfusion control amount is corrected using the result obtained by multiplying the short-term correction factor by the perfusion control amount; a correction mapping set is pre-constructed by preset professionals and stored in a preset database; and by real-time monitoring of changes in perfusion fluid properties and performing corresponding trend analysis, timely response to changes in perfusion fluid properties is facilitated, thereby enhancing the system's adaptability to fluctuations in perfusion fluid properties and helping to avoid operational delays caused by changes in perfusion fluid properties, thereby improving the accuracy of the perfusion process.

[0031] Furthermore, the specific process of fluid property change trend analysis is as follows: the change trend of the fluid properties within the perfusion control algorithm processing time period is analyzed to obtain a fluid property trend change index, and the change trend analysis is used to quantify the probability of changes in the perfusion fluid properties after the perfusion control algorithm processing time period; the fluid property trend change index is compared with the fluid property change trend threshold obtained from the preset database: if the fluid property trend change index is less than the fluid property change trend threshold, no additional processing is performed; if the fluid property trend change index is not less than the fluid property change trend threshold, the fluid property trend change index and the fluid property change trend threshold are differenced to obtain a fluid property change trend difference value, and the perfusion control amount is adjusted by obtaining a perfusion pre-adjustment factor according to the fluid property change trend difference value mapping, and the perfusion pre-adjustment factor represents the data for pre-adjusting the perfusion control amount according to the change trend of the fluid properties.

[0032] In this embodiment, a mapping set of fluid property change trend difference values ​​and perfusion pre-adjustment factors is constructed, and the real-time fluid property change trend difference values ​​are input into the mapping set to obtain the corresponding perfusion pre-adjustment factors. At the same time, the mapping set is pre-constructed by preset professionals and stored in a preset database. This embodiment helps to detect possible changes in perfusion fluid properties in advance, reduces the control lag caused by sudden changes in perfusion fluid properties, and enhances the stability of the fully automatic perfusion control system.

[0033] Specifically, the fluid property change trend threshold is obtained from a preset database. In one specific embodiment, the fluid property change rate data corresponding to changes in fluid properties during the perfusion control algorithm processing in the historical database is substituted into the specific restriction expression of the fluid property trend change index to obtain a corresponding data set, and a mean operation is performed on the data set to obtain the fluid property change trend threshold.

[0034] It should be added that the fluid property trend change index is obtained by analyzing the change trend of the fluid properties within the processing time period of the perfusion control algorithm. The specific process is as follows: the fluid property change rate data within the processing time period of the perfusion control algorithm is obtained, and the fluid property change rate data includes the fluid density change rate, the fluid viscosity change rate, and the fluid temperature change rate; the fluid property change compensation value is obtained from the preset database, and the fluid property change compensation value includes the density compensation value, the viscosity compensation value, and the temperature compensation value; based on the fluid property change rate data and the corresponding fluid property change compensation value, a weighted operation is performed and coupled to obtain the fluid property trend change index, which is used to quantify the trend of fluid property changes. The specific restricted expression is as follows: ; Where, represents the rate of change of fluid density, represents the rate of change of fluid viscosity, represents the rate of change of fluid temperature, Indicates the density compensation value, Indicates the viscosity compensation value, Indicates the temperature compensation value, Indicates the fluid property trend change index.

[0035] This algorithm combines the fluid property change rate data with the fluid property compensation value for comprehensive analysis to obtain the fluid property trend change index. In the formula, as the fluid density change rate, fluid viscosity change rate, and fluid temperature change rate increase, the corresponding fluid property trend change index becomes larger, indicating a more drastic change trend in the perfusion fluid properties. Therefore, the possibility of a change in the perfusion fluid properties is higher. In addition, the fluid property trend change index can be used to more accurately quantify the corresponding fluid change trend direction, thereby enabling timely implementation of corresponding pre-adjustment measures and improving the real-time response of the perfusion system to the fluid property change trend.

[0036] It should be supplemented that the fluid density is measured in real time by a densitometer, and the difference between the fluid density at the start and end times of the perfusion control algorithm processing time period is compared with the duration between the start and end times to obtain the fluid density change rate; the fluid viscosity is measured in real time by a rotational viscometer, and the difference between the fluid viscosity at the start and end times of the perfusion control algorithm processing time period is compared with the duration between the start and end times to obtain the fluid viscosity change rate; the fluid temperature is measured in real time by a temperature sensor, and the difference between the fluid temperature at the start and end times of the perfusion control algorithm processing time period is compared with the duration between the start and end times to obtain the fluid temperature change rate.

[0037] Specifically, the fluid property compensation value is obtained from a preset database, and the fluid property compensation value represents the degree of influence of the fluid property change rate data on the fluid property trend change index. Each fluid property change rate data and the fluid property compensation value have a unique mapping relationship, and the value range is between 0 and 1; for example, a mapping set of fluid property change rate data and preset fluid property compensation values ​​is constructed, and the real-time fluid density change rate, fluid viscosity change rate, and fluid temperature change rate are input into the mapping set to obtain the corresponding density compensation value, viscosity compensation value, and temperature compensation value, which respectively represent the degree of influence of the fluid density change rate, fluid viscosity change rate, and fluid temperature change rate on the fluid property trend change index, and the sum of the three is 1.

[0038] Furthermore, after the perfusion control analysis, the perfusion control amount is subjected to an amplitude adjustment stability analysis, and corresponding perfusion control adjustments are performed based on the analysis results. The specific steps are as follows: S1, performing a difference operation between the perfusion control amount to be updated and the corrected perfusion control amount to obtain the perfusion control adjustment amount, and the corrected perfusion control amount represents the perfusion control amount adjusted by the short-term correction factor; S2, judging the perfusion control adjustment amount with the maximum adjustment amplitude value obtained from the preset database, if the perfusion control adjustment amount is not less than the maximum adjustment amplitude value, adjusting the corrected perfusion control amount to the maximum amplitude perfusion control amount and executing S3, otherwise no additional processing is performed, and the maximum amplitude perfusion control amount represents the perfusion control amount obtained by mapping the maximum adjustment amplitude value; S3, in the process of adjusting the corrected perfusion control amount to the maximum amplitude perfusion control amount, obtaining system stability evaluation data in real time, and performing system stability evaluation based on the system stability evaluation data.

[0039] In this embodiment, the maximum adjustment amplitude value is set by the preset staff according to the maximum adjustment degree that the perfusion system performance can withstand; a mapping set between the maximum adjustment amplitude value and the maximum amplitude perfusion control amount is constructed, and the real-time maximum adjustment amplitude value is input into the mapping set to output the maximum amplitude perfusion control amount, and the mapping set is pre-constructed by the preset professional and stored in the preset database; the above-mentioned adjustment mechanism helps to prevent the adjustment of the perfusion control from exceeding the maximum adjustment amplitude value, ensures the accuracy and stability of the perfusion process, and reduces the fluctuation of the perfusion quality caused by the larger fluctuation of the adjustment amplitude.

[0040] Furthermore, the specific process of performing system stability evaluation based on the system stability evaluation data is as follows: a system stability evaluation index is obtained by performing stability analysis on the system stability evaluation data, and the stability analysis is used to evaluate the stability of the perfusion system during the process of adjusting the corrected perfusion control amount to the maximum amplitude perfusion control amount; a difference operation is performed on the perfusion control amount to be updated and the maximum amplitude perfusion control amount to obtain the perfusion control amount to be compensated; the system stability evaluation index is compared with the stability threshold obtained from a preset database: if the system stability evaluation index is less than the stability threshold, the perfusion control amount to be compensated is adjusted based on the maximum amplitude perfusion control amount until the perfusion control amount to be updated is reached; if the system stability evaluation index is not less than the stability threshold, the maximum amplitude perfusion control amount is adjusted based on the system stability evaluation index.

[0041] In this embodiment, the difference operation means obtaining the difference between the corresponding two quantities; the stability of the fully automatic perfusion control system is analyzed and the system stability evaluation index is calculated by the method of this embodiment, thereby ensuring real-time evaluation of system instability that may occur during the adjustment process; and in the process of correcting the perfusion control quantity, if the system stability evaluation index is lower than the corresponding stability threshold, the perfusion control quantity to be compensated is gradually adjusted to ensure the smooth progress of the perfusion process.

[0042] Specifically, the stability threshold is obtained from a preset database. In one specific embodiment, system stability assessment data from a historical database that indicates system oscillations due to changes in perfusion rate is substituted into a specific restricted expression for the system stability assessment index to obtain a corresponding data set, and a mean operation is performed on the data set to obtain the stability threshold.

[0043] Furthermore, the specific contents of adjusting the maximum amplitude perfusion control amount based on the system stability evaluation index are as follows: performing a difference operation on the system stability evaluation index and the stability threshold to obtain a perfusion adjustment stability difference; constructing a stability mapping set between the perfusion adjustment stability difference and a preset stability adjustment ratio; inputting the real-time perfusion adjustment stability difference into the stability mapping set to output the stability adjustment ratio; based on the maximum amplitude perfusion control amount, adjusting the perfusion control amount to be compensated according to the stability adjustment ratio until the perfusion control amount to be updated is reached.

[0044] In this embodiment, the stability mapping set is pre-constructed by preset professionals and stored in the corresponding preset database; the difference between the above-mentioned real-time calculation system stability evaluation index and the stability threshold value helps the system to more accurately evaluate the current perfusion control amount adjustment requirements; at the same time, the accuracy of perfusion adjustment is improved, and the perfusion amount adjustment is made more in line with the real-time needs of the system, and the accuracy of perfusion control is ensured.

[0045] Furthermore, the system stability evaluation index is obtained as follows: system stability evaluation data is obtained and normalized, the system stability evaluation data including flow rate change rate, damping ratio, phase margin, gain margin and steady-state error; stability compensation values ​​are obtained from a preset database, the stability compensation values ​​including flow rate change rate compensation value, damping ratio compensation value, phase margin compensation value, gain margin compensation value and steady-state error compensation value; after performing correlation conversion operation on the damping ratio, phase margin and gain margin and performing weighted operation with the flow rate change rate, steady-state error and corresponding stability compensation value, the system stability evaluation index is obtained after coupling, which is used to evaluate the degree of influence on system stability during the perfusion control quantity adjustment process.

[0046] The specific restricted expression of the system stability evaluation index is as follows: ; Where, represents the rate of change of flow velocity, represents the damping ratio, represents the phase margin, represents the gain margin, represents the steady-state error, Indicates the flow rate change rate compensation value, Indicates the damping ratio compensation value, represents the phase margin compensation value, Indicates the gain margin compensation value, represents the steady-state error compensation value, Represents the system stability evaluation index.

[0047] In this embodiment, the algorithm combines system stability assessment data and corresponding stability compensation values ​​to perform a comprehensive calculation to obtain a system stability assessment index. Here, a greater flow rate change rate indicates greater fluctuations in the perfusion fluid flow velocity, potentially greater impact on the stability of the perfusion system, and a corresponding greater system stability assessment index. A smaller damping ratio indicates more severe vibrations in the perfusion system, and a corresponding greater system stability assessment index. A smaller phase margin indicates greater stability of the perfusion system near the gain crossover frequency, and a corresponding greater system stability assessment index. A smaller gain margin indicates that the perfusion system is approaching a critical stability state, and a slight increase in gain may cause oscillation or instability in the perfusion system. A larger steady-state error may indicate insufficient adjustment speed and poorer stability of the perfusion system, and a corresponding greater system stability assessment index. By analyzing the system stability assessment index, the stability of the perfusion system during the process of correcting the perfusion control variable to the maximum amplitude perfusion control variable is more accurately quantified, allowing timely implementation of corresponding adjustment measures and improving the stability of the perfusion system during the adjustment process.

[0048] It should be added that the fluid density is measured in real time by a flow meter, and the difference between the fluid velocities at the start and end of the process of adjusting the corrected perfusion control amount to the maximum amplitude perfusion control amount is compared with the corresponding time length to obtain the flow rate change rate; by applying a step input or pulse input to the perfusion system, the response of the perfusion system is observed, and the damping ratio is estimated by analyzing the oscillation attenuation characteristics of the perfusion system; by testing the frequency response of the perfusion system, a Bode diagram (amplitude-frequency characteristics and phase-frequency characteristics) is drawn, and the phase margin refers to the angle between the gain crossover frequency point (when the perfusion system gain is 1 or 0 dB) and the -180° phase; the gain margin is the difference between the gain amplitude at a phase of -180° and 1. The gain crossover frequency is obtained through frequency response testing (Bode diagram) and the gain margin is calculated; by applying a step input, ramp input or other standard input signal, the output of the perfusion system is measured, and the difference between the output and the target value is observed to obtain the steady-state error.

[0049] Specifically, the stability compensation value is obtained from a preset database, and the stability compensation value represents the degree of influence of the system stability evaluation data on the system stability evaluation index. Each system stability evaluation data has a unique mapping relationship with the stability compensation value, and the value range is between 0 and 1; for example, a mapping set of system stability evaluation data and preset stability compensation values ​​is constructed, and the real-time flow rate change rate, damping ratio, phase margin, gain margin and steady-state error are input into the mapping set to obtain the corresponding flow rate change rate compensation value, damping ratio compensation value, phase margin compensation value, gain margin compensation value and steady-state error compensation value, which respectively represent the degree of influence of the flow rate change rate, damping ratio, phase margin, gain margin and steady-state error on the system stability evaluation index, and the sum of the five is 1.

[0050] It should be explained that the aforementioned preset database is a database used by the fully automatic perfusion control method based on the Internet of Things in the embodiment of the present application to store various types of setting data. The preset database includes but is not limited to correction mapping sets, fluid property change trend thresholds, perfusion pre-adjustment factors, fluid property change compensation values, maximum amplitude perfusion control amounts, stability thresholds, stability mapping sets and stability compensation values, etc., wherein various numerical values ​​are directly set by preset professionals. For example, by obtaining the fluid property change rate data corresponding to the changes in fluid properties during the processing of the perfusion control algorithm in historical data, and substituting them into the specific restriction expression of the fluid property trend change index to obtain the corresponding data set, the fluid property change trend threshold is represented by the average value of the data set.

[0051] An embodiment of the present application provides a fully automatic perfusion control system based on the Internet of Things, including a fluid property detection module, a perfusion control analysis module, and a perfusion stability analysis module; wherein the fluid property detection module is used to input the monitored data related to the change of the perfusion fluid property into the perfusion control algorithm for processing and output the perfusion control amount; the perfusion control analysis module is used to monitor the changes in the perfusion fluid properties in real time during the processing of the perfusion control algorithm, and perform corresponding perfusion control analysis based on the changes in the perfusion fluid properties. The perfusion control analysis is used to analyze the real-time changes in the perfusion fluid properties and take corresponding control and adjustment measures; the perfusion stability analysis module is used to perform amplitude adjustment stability analysis on the perfusion control amount after the perfusion control analysis, and perform corresponding perfusion control adjustment based on the analysis results. The amplitude adjustment stability analysis is used to quantify the degree of influence of the adjustment of the perfusion control amount on the stability of the perfusion system, and the perfusion control adjustment is used to reduce the degree of influence of the adjustment of the perfusion control amount on the stability of the perfusion system.

[0052] In this embodiment, the fully automatic perfusion control system based on the Internet of Things achieves precise control of the perfusion process and system stability assurance through the close integration of fluid property detection, perfusion control analysis and stability analysis; the system not only improves the perfusion production efficiency and more accurately controls the perfusion volume, but also helps to reduce the instability caused by the adjustment of the maximum adjustment amplitude value, enhances the system's adaptability to changes in the properties of the perfusion fluid, and enables the system to maintain stability in a changing production environment and automatically adjust according to actual conditions to ensure the continuity and efficiency of the production process.

[0053] In summary, the embodiment of the present application inputs the monitored data related to the change in the perfusion fluid properties into the perfusion control algorithm for processing and outputs the perfusion control amount. Then, during the processing of the perfusion control algorithm, the changes in the perfusion fluid properties are monitored in real time, and perfusion control analysis is performed based on the changes in the perfusion fluid properties. Finally, after the perfusion control analysis, the amplitude adjustment stability analysis is performed on the perfusion control amount to perform perfusion control adjustment, thereby more fully analyzing the impact of the fluid property changes on the perfusion speed, thereby improving the timeliness of the fully automatic perfusion control response, and effectively solving the problem of low timeliness of the fully automatic perfusion control response in the prior art.

[0054] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0055] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0056] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0057] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0058] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0059] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A fully automatic perfusion control method based on the Internet of Things, characterized in that: The following steps are involved: Inputting the data related to the monitored perfusion fluid property changes into the perfusion control algorithm for processing and outputting the perfusion control amount; During the perfusion control algorithm processing, changes in the properties of the perfusion fluid are monitored in real time, and corresponding perfusion control analysis is performed based on the changes in the properties of the perfusion fluid. The perfusion control analysis is used to analyze the changes in the properties of the perfusion fluid in real time to take corresponding control and adjustment measures; After the perfusion control analysis, an amplitude adjustment stability analysis is performed on the perfusion control amount, and corresponding perfusion control adjustments are performed based on the analysis results. The amplitude adjustment stability analysis is used to quantify the degree of influence of the adjustment of the perfusion control amount on the stability of the perfusion system, and the perfusion control adjustment is used to reduce the degree of influence of the adjustment of the perfusion control amount on the stability of the perfusion system.

2. The fully automatic perfusion control method based on the Internet of Things as claimed in claim 1, characterized in that: The data related to the monitored perfusion fluid property changes are input into the perfusion control algorithm for processing, and the perfusion control amount is output. The specific process is as follows: If the perfusion sensor detects a change in the perfusion fluid property, corresponding perfusion fluid property data is acquired and the corresponding property is marked as a qualitatively changed perfusion fluid property. A first target perfusion rate is obtained based on the qualitatively changed perfusion fluid property. The first target perfusion rate and a first actual perfusion rate obtained through real-time monitoring are input into a perfusion control algorithm to output a perfusion control amount. The first actual perfusion rate represents a perfusion rate of the perfusion fluid that qualitatively changes perfusion fluid properties, and the fluid property data includes viscosity, temperature, and density; The first target perfusion rate represents a target perfusion rate that meets the properties of the qualitatively changed perfusion fluid; The perfusion sensor includes a densitometer, a rotational viscosity sensor, and a temperature sensor.

3. The fully automatic perfusion control method based on the Internet of Things as claimed in claim 1, characterized in that: During the perfusion control algorithm processing, the changes in the properties of the perfusion fluid are monitored in real time, and corresponding perfusion control analysis is performed according to the changes in the properties of the perfusion fluid. The specific steps are as follows: A1: When it is detected that the perfusion fluid properties have not changed, a fluid property change trend analysis is performed; otherwise, A2 and A3 are performed simultaneously. The fluid property change trend analysis is used to analyze the change trend of the perfusion fluid properties after the perfusion control algorithm processing time period. A2, based on the second target perfusion rate and the second actual perfusion rate, obtains a target-actual perfusion error, constructs a correction mapping set of the target-actual perfusion error and a preset short-term correction factor, inputs the real-time target-actual perfusion error into the correction mapping set to obtain a corresponding short-term correction factor, and corrects the perfusion control amount based on the short-term correction factor. The second target perfusion rate represents a perfusion rate corresponding to perfusion fluid properties that change during a processing time period of the perfusion control algorithm, and the second actual perfusion rate represents a real-time perfusion rate corresponding to perfusion fluid properties that change during a processing time period of the perfusion control algorithm. The short-term correction factor is used to pre-adjust the control direction of the perfusion control amount. A3: Input the second target perfusion rate and the second actual perfusion rate into the perfusion control algorithm to obtain the perfusion control amount to be updated.

4. The fully automatic perfusion control method based on the Internet of Things as claimed in claim 3, characterized in that: The specific process of the fluid property change trend analysis is as follows: Performing a change trend analysis on the fluid properties during the perfusion control algorithm processing period to obtain a fluid property trend change index, wherein the change trend analysis is used to quantify the probability of a change in the perfusion fluid properties after the perfusion control algorithm processing period; Compare the fluid property trend change index with the fluid property change trend threshold obtained from the preset database: If the fluid property trend change index is less than the fluid property change trend threshold, no additional processing is performed; If the fluid property trend change index is not less than the fluid property change trend threshold, a difference operation is performed on the fluid property trend change index and the fluid property change trend threshold to obtain a fluid property change trend difference value, and the perfusion control amount is adjusted by obtaining a perfusion pre-adjustment factor according to the fluid property change trend difference value mapping. The perfusion pre-adjustment factor represents data for pre-adjusting the perfusion control amount according to the change trend of the fluid property.

5. The fully automatic perfusion control method based on the Internet of Things as claimed in claim 4, characterized in that: The fluid property trend change index is obtained by analyzing the change trend of the fluid property within the time period processed by the perfusion control algorithm. The specific process is as follows: Acquiring fluid property change rate data within a perfusion control algorithm processing time period, wherein the fluid property change rate data includes a fluid density change rate, a fluid viscosity change rate, and a fluid temperature change rate; Obtaining fluid property change compensation values ​​from a preset database, wherein the fluid property change compensation values ​​include density compensation values, viscosity compensation values, and temperature compensation values; A fluid property trend change index is obtained by coupling a weighted operation based on the fluid property change rate data and the corresponding fluid property change compensation value. The fluid property trend change index is used to quantify the trend of fluid property change.

6. The fully automatic perfusion control method based on the Internet of Things as claimed in claim 3, characterized in that: After the perfusion control analysis, the amplitude adjustment stability analysis is performed on the perfusion control amount, and the corresponding perfusion control adjustment is performed according to the analysis results. The specific steps are as follows: S1, performing a difference calculation between the perfusion control amount to be updated and the corrected perfusion control amount to obtain a perfusion control adjustment amount, wherein the corrected perfusion control amount represents the perfusion control amount adjusted by the short-term correction factor; S2: If the perfusion control adjustment amount is not less than the maximum adjustment amplitude value, the modified perfusion control amount is adjusted to the maximum amplitude perfusion control amount and S3 is executed; otherwise, no additional processing is performed. The maximum amplitude perfusion control amount represents the perfusion control amount obtained by mapping the maximum adjustment amplitude value. S3, in the process of correcting the perfusion control amount and adjusting it to the maximum amplitude perfusion control amount, obtaining system stability evaluation data in real time, and performing system stability evaluation based on the system stability evaluation data.

7. The fully automatic perfusion control method based on the Internet of Things as claimed in claim 6, characterized in that: The specific process of performing system stability assessment based on system stability assessment data is as follows: Obtaining a system stability evaluation index by performing stability analysis on the system stability evaluation data, wherein the stability analysis is used to evaluate the stability of the perfusion system during the process of adjusting the corrected perfusion control amount to the maximum amplitude perfusion control amount; Performing a difference calculation on the perfusion control amount to be updated and the maximum amplitude perfusion control amount to obtain the perfusion control amount to be compensated; If the system stability evaluation index is less than the stability threshold, the perfusion control amount to be compensated is adjusted based on the maximum amplitude perfusion control amount until the perfusion control amount to be updated is reached; If the system stability evaluation index is not less than the stability threshold, the maximum amplitude perfusion control amount is adjusted based on the system stability evaluation index.

8. The fully automatic perfusion control method based on the Internet of Things as claimed in claim 7, characterized in that: The specific content of adjusting the maximum amplitude perfusion control amount based on the system stability evaluation index is as follows: Perform difference calculation on the system stability evaluation index and the stability threshold to obtain the perfusion regulation stability difference; Constructing a stability mapping set between perfusion regulation stability differences and preset stability regulation ratios; Inputting the real-time perfusion regulation stability difference into the stability map set to output a stability regulation ratio; Based on the maximum amplitude perfusion control amount, the perfusion control amount to be compensated is adjusted according to the stability adjustment ratio until the perfusion control amount to be updated is reached.

9. The fully automatic perfusion control method based on the Internet of Things according to claim 7, characterized in that: The system stability evaluation index is obtained as follows: Acquiring system stability evaluation data and performing data normalization processing, wherein the system stability evaluation data includes flow rate change rate, damping ratio, phase margin, gain margin and steady-state error; Acquiring stability compensation values ​​from a preset database, the stability compensation values ​​including a flow rate change rate compensation value, a damping ratio compensation value, a phase margin compensation value, a gain margin compensation value, and a steady-state error compensation value; After the damping ratio, phase margin and gain margin are subjected to correlation conversion operation and weighted operation coupled with the flow rate change rate, steady-state error and corresponding stability compensation value, the system stability evaluation index is obtained. The system stability evaluation index is used to evaluate the degree of influence on the system stability during the perfusion control amount adjustment process.

10. A fully automatic perfusion control system based on the Internet of Things, including a fluid property detection module, a perfusion control analysis module, and a perfusion stability analysis module; in, The fluid property detection module is used to input the monitored data related to the change of the perfusion fluid properties into the perfusion control algorithm for processing and output the perfusion control amount; The perfusion control analysis module is used to monitor the changes in the properties of the perfusion fluid in real time during the processing of the perfusion control algorithm, and perform corresponding perfusion control analysis based on the changes in the properties of the perfusion fluid. The perfusion control analysis is used to analyze the changes in the properties of the perfusion fluid in real time to take corresponding control and adjustment measures; The perfusion stability analysis module is used to perform amplitude adjustment stability analysis on the perfusion control amount after the perfusion control analysis, and to perform corresponding perfusion control adjustment based on the analysis results. The amplitude adjustment stability analysis is used to quantify the degree of influence of the adjustment of the perfusion control amount on the stability of the perfusion system, and the perfusion control adjustment is used to reduce the degree of influence of the adjustment of the perfusion control amount on the stability of the perfusion system.

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