Plateau environment cerebrovascular disease risk prediction system and method based on digital twinning

Abstract

The invention provides an altitude environment cerebrovascular disease risk prediction system and method based on digital twinning, and belongs to the technical field of cerebrovascular disease risk simulation prediction. The system comprises an equipment regulation and control module, an oxygen control module and an oxygen pressure coupling regulation and control module. Firstly, an oxygen concentration monitoring strategy of oxygen adjusting equipment is dynamically optimized based on a concentration accuracy parameter and an environment influence parameter; monitoring a gas regulation and control dynamic factor in real time, and dynamically regulating an equipment control strategy of the oxygen regulation equipment based on the gas regulation and control dynamic factor and the concentration accuracy evaluation value; finally, the wind speed is dynamically adjusted according to monitored gas injection state parameters, oxygen adjustment is triggered based on oxygen balance time and air pressure balance time, cerebrovascular disease risk prediction is conducted based on adjusted oxygen adjusting equipment and a hypobaric chamber, and high-fidelity plateau environment simulation is conducted based on digital twinning. And the accuracy of the cerebrovascular disease risk prediction model is obviously improved.

Description

Technical Field

[0001] The present invention relates to the technical field of cerebrovascular disease risk simulation prediction, and in particular to a system and method for predicting cerebrovascular disease risk in a plateau environment based on digital twins. Background Art

[0002] Digital twin technology builds a virtual model to simulate an individual's physiological responses in a high-altitude environment. It then combines environmental factors such as climate, air pressure, and oxygen concentration to dynamically predict cerebrovascular health. The digital twin-based plateau cerebrovascular disease risk prediction system integrates digital twin technology with plateau environmental characteristics. It aims to predict and assess the risk of cerebrovascular disease in plateau residents or those adapted to the plateau by real-time monitoring and analysis of individual health data and environmental changes.

[0003] The existing cerebrovascular disease risk prediction system mainly integrates plateau environmental characteristics with individual health data, uses sensors and monitoring equipment to collect environmental parameters and individual physiological data in real time, processes them through data analysis models, and combines the impact of the plateau environment on the human body to evaluate the individual's cerebrovascular health risk under different environmental conditions.

[0004] For example, the cardiovascular disease risk prediction method and system, patented under invention publication number CN118711822B, includes: identifying cardiovascular disease risk factors based on existing clinical research and medical guidelines through text mining and key information extraction, constructing a relationship mapping table, and obtaining a risk factor database. This invention uses recursive feature elimination and adaptive reinforcement learning to perform weighted calculations on risk factors within a weight adjustment model, and then uses a gradient boosting tree to classify risk levels.

[0005] For example, the patent application with publication number CN118969297A discloses a cardiovascular disease risk prediction method, system and related equipment based on multimodal data, which includes: for each sample data, performing a 5th-order tensor product operation on the characteristic matrices corresponding to each modality to obtain a high-order tensor; processing the high-order tensor through a low-rank tensor network operation to obtain a reconstructed low-rank tensor; labeling the low-rank tensor corresponding to each sample data with a risk label; using the constructed data set to train a classifier to obtain a target model; and predicting the cardiovascular disease risk of the patient to be tested through the target model.

[0006] However, the above technology still has at least the following problems:

[0007] In the existing technology, when using digital twins to simulate the risk of cerebrovascular diseases in plateau environments, it is necessary to use a low-pressure chamber and oxygen regulation equipment to synchronously control the air pressure and oxygen content to simulate the high-altitude environment. However, during the control process, since it takes a certain amount of time for the gas to mix and evenly distribute, the adjustment of oxygen concentration may lag behind the change in air pressure, resulting in the two being out of sync and the instantaneous state deviating from the real plateau environment. There is a problem of low reliability of the plateau environment simulation built based on digital twins. Summary of the Invention

[0008] In response to the above problems, the present invention provides a system and method for predicting the risk of cerebrovascular diseases in a plateau environment based on digital twins, so as to solve the problem in the prior art that when using digital twins to simulate the risk of cerebrovascular diseases in a plateau environment, it is necessary to use a low-pressure chamber and oxygen regulating equipment to synchronously control the air pressure and oxygen content to simulate the high-altitude environment. However, during the control process, since it takes a certain amount of time for the gas to mix and evenly distribute, the adjustment of the oxygen concentration may lag behind the change in air pressure, resulting in the two being out of sync, the instantaneous state deviating from the real plateau environment, and the low reliability of the plateau environment simulation constructed based on digital twins. The simulation is closer to the real plateau environment, and the reliability of the simulation results is improved.

[0009] In order to solve the above-mentioned purpose of the invention, the technical solution provided by the present invention is as follows:

[0010] On the one hand, a risk prediction system for cerebrovascular diseases in a plateau environment based on digital twins is provided, comprising: an equipment control module, an oxygen control module, an oxygen pressure coupling control module and a risk prediction database; wherein the equipment control module is used to monitor concentration accuracy parameters and environmental impact parameters in real time to obtain a concentration accuracy evaluation value, and dynamically optimize the oxygen concentration monitoring strategy of the oxygen regulating equipment based on the concentration accuracy evaluation value, and the concentration accuracy evaluation value is used to quantify the accuracy of the oxygen regulating equipment when measuring oxygen concentration; the oxygen control module is used to monitor the gas control dynamic factor in real time, and dynamically adjust the equipment control strategy of the oxygen regulating equipment based on the gas control dynamic factor and the concentration accuracy evaluation value; the oxygen pressure coupling control module is used to dynamically adjust the wind speed according to the monitored gas injection state parameters, trigger oxygen regulation based on the oxygen balance time and the air pressure balance time, and predict the risk of cerebrovascular diseases based on the adjusted oxygen regulating equipment and the low-pressure cabin.

[0011] On the other hand, a method for predicting the risk of cerebrovascular diseases in a plateau environment based on digital twins is also provided, including the following steps: real-time monitoring of concentration accuracy parameters and environmental impact parameters to obtain concentration accuracy evaluation values, and dynamically optimizing the oxygen concentration monitoring strategy of the oxygen regulating equipment based on the concentration accuracy evaluation values, and the concentration accuracy evaluation values are used to quantify the accuracy of the oxygen regulating equipment when measuring oxygen concentration; real-time monitoring of gas regulation dynamic factors, and dynamic adjustment of the equipment control strategy of the oxygen regulating equipment based on the gas regulation dynamic factors and the concentration accuracy evaluation values; dynamic adjustment of the wind speed according to the monitored gas injection state parameters, triggering oxygen regulation based on the oxygen balance time and the air pressure balance time, and predicting the risk of cerebrovascular diseases based on the adjusted oxygen regulation equipment and the low-pressure chamber.

[0012] One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages:

[0013] 1. The present invention provides a plateau environment cerebrovascular disease risk prediction system based on digital twins, thereby realizing the precise monitoring and control of oxygen concentration and air pressure changes in the plateau environment, and then realizing the strategy of dynamically optimizing oxygen regulation equipment to ensure the accuracy and stability of oxygen concentration. It can adjust gas regulation and equipment control strategies in real time to ensure the reliability of the plateau environment constructed based on digital twins, and at the same time accurately adjust the wind speed and oxygen balance through the oxygen pressure coupling control module.

[0014] 2. The present invention dynamically optimizes the oxygen concentration monitoring strategy of the oxygen regulating equipment through the concentration accuracy evaluation value, thereby dynamically adjusting the calibration and measurement frequency of the oxygen regulating equipment based on the air pressure change rate and the oxygen concentration change rate, thereby realizing automatic optimization of the working state of the equipment within different concentration accuracy evaluation value ranges, further ensuring that the equipment accurately controls the oxygen concentration in a stable state, improving the accuracy of the equipment measurement, and thus improving the accuracy of the digital twin simulation of the plateau environment.

[0015] 3. The present invention obtains a control accuracy evaluation value by quantitatively analyzing the gas regulation dynamic factor and the concentration accuracy evaluation value, and dynamically adjusts and precisely controls the oxygen regulation equipment according to the control accuracy evaluation value, so that appropriate adjustment measures can be taken in different situations to ensure the stability of oxygen supply and the safety of subjects during digital twin simulation, thereby achieving precise control of oxygen flow and optimizing the performance and reliability of the equipment.

[0016] 4. The present invention dynamically adjusts the wind speed according to the gas injection state parameters and triggers oxygen adjustment in advance based on the difference between the oxygen balance time and the air pressure balance time, thereby ensuring the balance of gas concentration, volume and air pressure in the low-pressure cabin, optimizing the gas stability during the gas injection process, and thus ensuring the stability of oxygen concentration and the balance of air pressure, maintaining the synchronization of oxygen and air pressure during the process of cerebrovascular disease risk prediction and regulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 A schematic diagram of the structure of a high-altitude cerebrovascular disease risk prediction system based on digital twins provided in an embodiment of the present invention;

[0019] Figure 2 This is a graph showing changes in the control accuracy assessment value of a plateau environment-based cerebrovascular disease risk prediction system provided by an embodiment of the present invention.

[0020] Figure 3 A flowchart of a method for predicting the risk of cerebrovascular disease in a plateau environment based on digital twins provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0021] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the described embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Unless otherwise defined, the technical or scientific terms used in the present invention shall have the usual meaning understood by persons of ordinary skill in the field to which the present invention belongs. The words "first", "second" and similar terms used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. Similarly, words such as "one", "an" or "the" do not indicate a quantity limitation, but rather indicate the presence of at least one. Words such as "include" or "comprise" mean that the elements or objects preceding the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Words such as "connect" or "connected" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect.

[0023] It should be noted that the terms "up", "down", "left", "right", "front" and "back" used in the present invention are only used to indicate relative position relationships. When the absolute position of the object being described changes, the relative position relationship may also change accordingly.

[0024] The present invention provides a cerebrovascular disease risk prediction system in a plateau environment based on digital twins, which triggers oxygen adjustment based on oxygen balance time and air pressure balance time, thereby achieving synchronous regulation of oxygen content and air pressure.

[0025] like Figure 1As shown, an embodiment of the present invention provides a structural schematic diagram of a cerebrovascular disease risk prediction system in a plateau environment based on digital twins, including an equipment control module, an oxygen control module, an oxygen pressure coupling control module and a risk prediction database; wherein the equipment control module is used to monitor concentration accuracy parameters and environmental impact parameters in real time to obtain a concentration accuracy evaluation value, and dynamically optimize the oxygen concentration monitoring strategy of the oxygen regulating equipment based on the concentration accuracy evaluation value, and the concentration accuracy evaluation value is used to quantify the accuracy of the oxygen regulating equipment when measuring oxygen concentration; the oxygen control module is used to monitor the gas control dynamic factor in real time, and dynamically adjust the equipment control strategy of the oxygen regulating equipment based on the gas control dynamic factor and the concentration accuracy evaluation value; the oxygen pressure coupling control module is used to monitor the gas control dynamic factor in real time, and dynamically adjust the equipment control strategy of the oxygen regulating equipment based on the gas control dynamic factor and the concentration accuracy evaluation value; The block is used to dynamically adjust the wind speed according to the monitoring gas injection status parameters, trigger oxygen adjustment based on the oxygen balance time and the air pressure balance time, and simulate the plateau environment based on the adjusted oxygen adjustment equipment and the low-pressure chamber. By monitoring the multi-dimensional physiological data of the subjects (such as cerebral blood flow, blood oxygen saturation, metabolic level, etc.) and combining the basic health information of the subjects (past medical history, gender, weight, etc.), a multi-dimensional feature vector is formed. The multi-dimensional feature vector is used as the input of the cerebrovascular disease risk prediction model (including logistic regression model, neural network model, etc.) for model training. The model outputs a risk score representing the probability of the subject suffering a cerebrovascular event in this environment, and provides health management recommendations based on the risk assessment results to achieve individualized cerebrovascular disease risk prediction.

[0026] In this embodiment, the present invention regulates the oxygen concentration within the hypobaric chamber by injecting oxygen and nitrogen through an oxygen conditioning device to match the hypoxic conditions of the external plateau environment. The oxygen conditioning device monitors the oxygen concentration in real time using an internal oxygen concentration sensor and automatically adjusts the oxygen concentration based on predictions provided by a digital twin model. Based on the effects of oxygen regulation, the digital twin model simulates the impact of different oxygen concentrations on cerebrovascular health. Combined with cerebrovascular responses, it predicts the risk of cerebrovascular disease in the plateau environment and helps determine whether further intervention is necessary. By dynamically adjusting the monitoring strategy, the present invention reduces errors caused by the device's inherent precision limitations, making oxygen concentration regulation more precise and avoiding hysteresis that can affect the accuracy of prediction results. The oxygen control module, through real-time monitoring and dynamic adjustment of the device's control strategy, can promptly respond to changes in gas concentration, avoiding oxygen regulation lags and ensuring more synchronized regulation of air pressure and oxygen. By real-time monitoring and adjustment of wind speed and oxygen regulation time, the problem of asynchronous regulation of air pressure and oxygen concentration is avoided, resulting in more accurate predictions of cerebrovascular disease risk and ensuring real-time synchronization of air pressure and oxygen concentration, making the transient conditions during the simulation more closely resemble the actual plateau environment.

[0027] In addition, the preset risk prediction database is used to store relevant data of the plateau environment cerebrovascular disease risk prediction system based on digital twins, including: reference equipment calibration frequency, allowable deviation equipment calibration frequency, critical measurement frequency, critical zero drift value, equipment calibration frequency influencing factor, concentration accuracy assessment first threshold and concentration accuracy assessment second threshold, etc. The data in the risk prediction database can be directly queried through public databases such as the Plateau Climate Monitoring Data Platform and the China Health Information Platform, and can also be obtained through cooperation with research institutions such as medical hospitals.

[0028] The deviation compliance calculation and processing methods involved in the present invention are the same, both of which are methods for evaluating the degree of deviation between the measured value and the preset reference value, and combining the error allowable range to determine whether the current state meets the requirements.

[0029] Preferably, the environmental impact parameters include the temperature change amplitude at each time monitoring point, the humidity value and the vibration frequency at each time monitoring point; the concentration accuracy parameters include the equipment calibration frequency, the measurement frequency and the zero drift value; the step of real-time monitoring the concentration accuracy parameters and the environmental impact parameters to obtain the concentration accuracy evaluation value includes: obtaining environmental impact parameter reference data and concentration accuracy parameter reference data from a preset risk prediction database, the environmental impact parameter reference data specifically includes: critical temperature change amplitude, reference humidity value, allowable deviation humidity value and critical vibration frequency, the concentration accuracy parameter reference data specifically includes: reference equipment calibration frequency, allowable deviation equipment calibration frequency, critical measurement frequency and critical zero drift value; performing a proportion approximation operation on the temperature change amplitude at each time monitoring point and the critical temperature change amplitude to obtain the temperature change amplitude influencing parameter; performing a deviation conformity operation on the humidity value at each time monitoring point and the reference humidity value and the allowable deviation humidity value to obtain the humidity value influencing parameter; respectively performing a temperature change amplitude influencing factor and a humidity value influencing factor on the temperature The amplitude influencing parameter and the humidity value influencing parameter are weighted and coupled, and the coupling results are homogenized to obtain the environmental dynamic coupling parameter; the vibration frequency and the critical vibration frequency are subjected to proportion approach calculation, and then weighted by the vibration frequency influencing factor to obtain the vibration frequency influencing parameter; the environmental dynamic coupling parameter and the vibration frequency influencing parameter are coupled to obtain the environmental influencing parameter; the allowable deviation equipment calibration frequency is subjected to deviation compliance calculation with the equipment calibration frequency and the reference equipment calibration frequency to obtain the equipment calibration frequency influencing parameter; the measurement frequency and the zero drift value are subjected to proportion approach calculation with the critical measurement frequency and the critical zero drift value respectively to obtain the proportion approach calculation result; the equipment calibration frequency influencing parameter, the proportion approach calculation result and the environmental influencing parameter after the inverse proportional calculation are weighted and coupled by the concentration accuracy parameter influencing factor to obtain the concentration accuracy evaluation value. The concentration accuracy parameter influencing factor includes the equipment calibration frequency influencing factor, the measurement frequency influencing factor, the zero drift value influencing factor and the environmental influencing parameter influencing factor.

[0030] The concentration accuracy evaluation value is obtained as follows:

[0031]

[0032] Where CA1 represents the concentration accuracy assessment value, α1 represents the equipment calibration frequency influencing factor, α2 represents the measurement frequency influencing factor, α3 represents the zero drift value influencing factor, α4 represents the environmental influencing parameter influencing factor, CF1 represents the equipment calibration frequency, CF0 represents the reference equipment calibration frequency, CF2 represents the allowable deviation equipment calibration frequency, MF1 represents the measurement frequency, MF0 represents the critical measurement frequency, ZD1 represents the zero drift value, ZD0 represents the critical zero drift value, and EI represents the environmental influencing parameter.

[0033] The environmental impact parameters are obtained as follows:

[0034]

[0035] Where, EI represents the environmental influencing parameter, α5 represents the temperature change amplitude influencing factor, α6 represents the humidity value influencing factor, α7 represents the vibration frequency influencing factor, and TA 1i Indicates the temperature change amplitude of the i-th time monitoring point relative to the previous time monitoring point, where when i is 1, TA 1i 0, TA0 represents the critical temperature change range, HV 1i Represents the humidity value at the i-th time monitoring point, HV0 represents the reference humidity value, HV2 represents the allowable deviation humidity value, VG1 represents the vibration frequency, and VG0 represents the critical vibration frequency, where i is the number of each time monitoring point, i = 1, 2, 3, ..., N, N is the total number of time monitoring points

[0036] In this embodiment, the temperature variation amplitude, humidity value and vibration frequency can be obtained by directly measuring the center point of the low-pressure cabin using a temperature sensor, a humidity sensor and a vibration sensor. The three are interrelated. For example, changes in temperature can cause thermal expansion or contraction of materials such as metal and plastic in the device or sensor, which may cause slight changes in the internal structure of the device, affecting the stability of the device, and thus may increase vibration or sensitivity to vibration; high humidity may cause condensation on the metal surface, or certain non-metallic materials to absorb water and expand, thereby affecting the physical properties of the device. Humidity may also affect the electronic components of the sensor, thereby causing changes in vibration sensitivity. The environmental impact parameters obtained through comprehensive analysis can quantitatively evaluate the impact of the internal environment of the low-pressure cabin on the measurement accuracy of the oxygen regulation equipment. At the same time, the measurement accuracy of the oxygen regulation equipment can also be optimized based on the environmental impact parameters.

[0037] The device calibration frequency can be directly viewed through the device update log. The measurement frequency is provided directly within the device's functions. The zero drift value can be determined by placing the device in an oxygen environment of known concentration and observing the deviation from that known concentration. These three factors are interrelated: for example, a higher device calibration frequency results in less sensor error, potentially leading to lower zero drift. Furthermore, zero drift can be affected by environmental factors, such as temperature changes, which can cause sensor zero drift. The concentration accuracy assessment reflects the measurement stability and precision of the oxygen conditioning device, helping to optimize device performance and reduce errors, thereby improving the reliability and accuracy of cerebrovascular disease risk assessments in simulated high-altitude environments.

[0038] Preferably, the step of dynamically optimizing the oxygen concentration monitoring strategy of the oxygen regulating equipment based on the concentration accuracy evaluation value includes: obtaining the first concentration accuracy evaluation threshold and the second concentration accuracy evaluation threshold from a preset risk prediction database; comparing the concentration accuracy evaluation value with the first concentration accuracy evaluation threshold and the second concentration accuracy evaluation threshold respectively; if the concentration accuracy evaluation value is less than the first concentration accuracy evaluation threshold, forcibly shutting down and entering maintenance mode, and reporting the abnormality to the management personnel at the same time; if the concentration accuracy evaluation value is greater than or equal to the first concentration accuracy evaluation threshold and less than the second concentration accuracy evaluation threshold, performing zero point calibration in real time, starting multi-channel redundant measurement and correcting the oxygen concentration according to environmental influencing parameters, and dynamically adjusting the equipment calibration frequency and measurement frequency according to the concentration accuracy evaluation value, the air pressure change rate and the oxygen concentration change rate; if the concentration accuracy evaluation value is greater than or equal to the second concentration accuracy evaluation threshold, performing zero point calibration within the preset calibration interval to maintain the current calibration frequency and measurement frequency.

[0039] In this embodiment, in maintenance mode, the oxygen conditioning equipment automatically performs comprehensive inspections and repairs, and any software or hardware errors detected are immediately reported to management. Unlike "real-time zero calibration," periodic zero calibration does not rely on immediate deviations in measured values. Instead, it is adjusted based on regular inspection and maintenance of the equipment. Periodic calibration can be performed daily, hourly, or half-hourly, for example. When correcting oxygen concentration based on environmental impact parameters, the environmental impact parameters can be mapped to the corresponding oxygen concentration correction values preset in the risk prediction database to obtain the corrected oxygen concentration value. The oxygen concentration value is then summed with the oxygen concentration correction value to obtain the corrected oxygen concentration value. In the risk prediction database, environmental impact parameters and oxygen concentration correction values are mapped one-to-one to form a mapping table. The table records each environmental impact parameter and its corresponding oxygen concentration correction value. These relationships can be one-to-one or many-to-one. To obtain the oxygen concentration correction value, the environmental impact parameter can be entered into the mapping table, and the risk prediction database can quickly locate and return the corresponding oxygen concentration correction value. The present invention divides three risk scenarios through dual thresholds, achieving precise response from "emergency shutdown" to "optimization fine-tuning", balancing safety and efficiency, maintaining sensor accuracy through dynamic calibration, extending equipment maintenance cycle, and reducing operation and maintenance costs.

[0040] Preferably, the step of dynamically adjusting the equipment calibration frequency and measurement frequency according to the concentration accuracy evaluation value, the air pressure change rate and the oxygen concentration change rate includes: obtaining the equipment calibration frequency and measurement frequency range corresponding to each concentration accuracy evaluation value range from a preset risk prediction database; comparing the concentration accuracy evaluation value with each concentration accuracy evaluation value range to obtain the concentration accuracy evaluation value range, and then comparing the concentration accuracy evaluation value range with the equipment calibration frequency and measurement frequency range corresponding to each concentration accuracy evaluation value range to obtain the equipment calibration frequency and measurement frequency range corresponding to the concentration accuracy evaluation value; obtaining the measurement frequency adjustment value according to the comprehensive processing of the air pressure change rate and the oxygen concentration change rate, coupling and adding the current measurement frequency and the measurement frequency adjustment value to obtain the adjusted measurement frequency; judging whether the adjusted measurement frequency is within the measurement frequency range, and if so, marking the current measurement frequency as the adjusted measurement frequency; if not and the adjusted measurement frequency is less than the minimum value of the measurement frequency range, marking the minimum value of the measurement frequency range as the adjusted measurement frequency; if not and the adjusted measurement frequency is greater than the maximum value of the measurement frequency range, marking the maximum value of the measurement frequency range as the adjusted measurement frequency.

[0041] In this embodiment, the present invention can ensure that the oxygen regulating device is always in the best measurement state by dynamically adjusting the calibration frequency and measurement frequency of the device according to real-time data, thereby improving the measurement accuracy and reliability of the device; by dynamically adjusting in combination with the air pressure and oxygen concentration change rate, the system can automatically optimize the calibration frequency and measurement frequency according to environmental conditions, avoiding wasting unnecessary measurement cycles, while ensuring the real-time and accuracy of the data; by limiting the range of the calibration frequency and measurement frequency, avoiding the measurement frequency being too high or too low, thereby avoiding unnecessary damage to the equipment or producing inaccurate results, and ensuring the safety of the equipment operation.

[0042] Preferably, the step of obtaining the measurement frequency adjustment value by comprehensive processing of the air pressure change rate and the oxygen concentration change rate includes: obtaining a reference air pressure change rate, a reference oxygen concentration change rate, a unit air pressure change rate, and a unit oxygen concentration change rate from a preset risk prediction database; when the air pressure change rate is greater than the reference air pressure change rate, marking the difference between the air pressure change rate and the reference air pressure change rate as a deviation air pressure change rate, and obtaining an air pressure adjustment unit based on the deviation air pressure change rate and the unit air pressure change rate; otherwise, no additional processing is performed, and the air pressure adjustment unit represents a truncated division relationship between the deviation air pressure change rate and the unit air pressure change rate; when the oxygen concentration change rate is greater than the reference oxygen concentration change rate, marking the difference between the oxygen concentration change rate and the reference oxygen concentration change rate as a deviation oxygen concentration change rate, and obtaining an oxygen adjustment unit based on the deviation oxygen concentration change rate and the unit oxygen concentration change rate; otherwise, no additional processing is performed, and the oxygen adjustment unit represents a truncated division relationship between the deviation oxygen concentration change rate and the unit oxygen concentration change rate; and coupling the air pressure adjustment unit with the oxygen adjustment unit to obtain the measurement frequency adjustment value.

[0043] In this embodiment, the pressure adjustment unit can be obtained by dividing the deviation pressure change rate by the unit pressure change rate, and rounding it up. The oxygen adjustment unit can be obtained by dividing the deviation oxygen concentration change rate by the unit oxygen concentration change rate, and rounding it up. The unit pressure change rate and the unit oxygen concentration change rate represent the response rate to changes in pressure and oxygen concentration, i.e., the correction required per unit change. The pressure adjustment unit and the oxygen adjustment unit represent the integer multiple relationship between the difference between the pressure change and oxygen concentration change and the unit change rate, respectively, indicating the degree to which the measurement frequency needs to be adjusted. By dynamically adjusting the measurement frequency based on the pressure change rate and the oxygen concentration change rate, the present invention ensures that the device can still provide accurate measurement data even under significant environmental changes. Furthermore, through intelligent adjustment, it can adapt to changes in pressure and oxygen concentration, avoiding measurement errors caused by external environmental fluctuations. Precisely controlling the range of the measurement frequency and calibration frequency effectively prevents device malfunctions caused by improper operation. Especially in situations of significant environmental fluctuations, this prevents the device from operating at an inappropriate frequency, thereby ensuring long-term safe operation of the device.

[0044] Preferably, the step of dynamically adjusting the equipment control strategy of the oxygen regulation equipment based on the gas regulation dynamic factor and the concentration accuracy evaluation value includes: quantifying the regulation accuracy of the oxygen regulation equipment according to the gas regulation dynamic factor and the concentration accuracy evaluation value to obtain a control accuracy evaluation value; comparing the control accuracy evaluation value with the first control accuracy evaluation threshold and the second control accuracy evaluation threshold preset in the risk prediction database respectively; if the control accuracy evaluation value is less than the first control accuracy evaluation threshold, suspending the air pressure adjustment, locking the current cabin pressure, switching to a constant oxygen flow mode to ensure the safety of the subject, and identifying the faulty unit; if the control accuracy evaluation value is greater than or equal to the first control accuracy evaluation threshold and less than the second control accuracy evaluation threshold, starting the detection step signal to dynamically adjust the equipment parameters, and at the same time starting the turbulent mode at the oxygen injection point; if the control accuracy evaluation value is greater than or equal to the second control accuracy evaluation threshold, loading the preset high altitude simulation equipment parameters, and maintaining the laminar flow mode.

[0045] In this embodiment, the device parameters include proportional gain, integral time, and differential time. The proportional gain is adjusted as follows: Where K p1 Indicates the current proportional gain, K p0 Represents the original proportional gain, α is the adjustment coefficient (controls the adjustment range of the proportional gain, which directly affects the oxygen regulation response speed of the equipment. In existing usage scenarios, the proportional gain adjustment range is 1 to 1.5 times the default value, such as α is 0.5), E2 represents the second threshold for control accuracy evaluation, E represents the current control accuracy evaluation value, and E1 represents the first threshold for control accuracy evaluation. The integral time is adjusted as follows: Where T1 represents the current integral time, T0 represents the original integral time, and β is the adjustment coefficient (which controls the strength of the integral action and eliminates steady-state errors. In existing usage scenarios, the integral time adjustment range is 0.7 to 1 times the default value. For example, β is 0.3 to avoid excessive weakening of the integral time). The differential time is adjusted as follows: Where, T d1 Indicates the current differential time, T d0Represents the original integration time, and γ is the adjustment coefficient (controls the damping effect of the differential action, suppresses overshoot, and limits the differential time to 1 to 1.2 times the default value in existing usage scenarios, such as γ is 0.2). Laminar flow mode is a state of gas flow, in which gas molecules flow along parallel paths at a steady and orderly speed, which can ensure a stable and uniform airflow, making the oxygen supply more accurate and stable, and is suitable for environments with strict requirements on oxygen concentration; turbulent flow mode is an irregular and chaotic flow state of gas flow, with large changes in flow rate, generating vortices, which helps to increase the mixing of gas flow and improve the mixing efficiency of oxygen and other gases. The present invention makes precise adjustments based on the gas regulation dynamic factor and the concentration accuracy evaluation value. When the control accuracy is insufficient, it can automatically switch to a safer mode to ensure the safety of the subject; dynamically adjust the equipment parameters according to the evaluation value, turn on the turbulent mode and other measures, and can respond more quickly under various dynamic changes to ensure the accuracy of oxygen regulation, thereby improving the overall efficiency and reliability of the equipment.

[0046] Preferably, the gas regulation dynamic factor includes the air pressure change rate, the oxygen concentration change rate and the gas mixing efficiency; the regulation accuracy of the oxygen regulation equipment is quantified according to the gas regulation dynamic factor and the concentration accuracy evaluation value, and the step of obtaining the control accuracy evaluation value includes: obtaining the gas regulation dynamic factor reference data and the critical concentration accuracy evaluation value from a preset risk prediction database, the gas regulation dynamic factor reference data specifically including: the critical air pressure change rate, the critical oxygen concentration change rate and the critical gas mixing efficiency; performing a proportion approximation operation on the air pressure change rate and the oxygen concentration change rate respectively with the critical air pressure change rate and the critical oxygen concentration change rate, and performing a proportion approximation operation on the air pressure change rate influencing factor and the oxygen concentration change rate The influencing factors are weighted and coupled to the results of the proportion approach calculation, and the processing results are inversely proportionally calculated to obtain the change rate influencing parameters; the gas mixing efficiency and concentration accuracy evaluation values are respectively subjected to proportion approach calculations with the critical gas mixing efficiency and critical concentration accuracy evaluation values, and then the calculation results are weighted by the gas mixing efficiency influence factor and the concentration accuracy influence factor to obtain the dynamic control performance index; the change rate influencing parameter and the dynamic control performance index are coupled to obtain the control accuracy evaluation value, which represents the quantitative data of the degree of influence of the pressure change rate, oxygen concentration change rate and gas mixing efficiency on the regulation accuracy when the oxygen regulation equipment is performing oxygen regulation.

[0047] The control accuracy evaluation value is obtained as follows:

[0048]

[0049] Wherein, CA represents the control accuracy assessment value, β1 represents the pressure change rate influencing factor, β2 represents the oxygen concentration change rate influencing factor, β3 represents the gas mixing efficiency influencing factor, β7 represents the concentration accuracy influencing factor, GP1 represents the pressure change rate, GP0 represents the critical pressure change rate, OC1 represents the oxygen concentration change rate, OC0 represents the critical oxygen concentration change rate, ME1 represents the gas mixing efficiency, ME0 represents the critical gas mixing efficiency, CA1 represents the concentration accuracy assessment value, and CA0 represents the critical concentration accuracy assessment value.

[0050] In this embodiment, the air pressure change rate is the ratio of the change in the low-pressure cabin air pressure during the current monitoring period to the current monitoring period, which can be monitored and calculated in real time by the air pressure sensor; the oxygen concentration change rate represents the ratio of the change in the low-pressure cabin oxygen concentration during the current monitoring period to the current monitoring period, which can be directly monitored using an oxygen regulating device; the gas mixing efficiency represents the uniformity of the gas mixing in the low-pressure cabin, which can be obtained by collecting the oxygen concentration at each position in the low-pressure cabin and calculating the standard deviation of the oxygen concentration, and using the gas mixing efficiency calculation formula. The gas mixing efficiency calculation formula is: Where, ME1 represents the gas mixing efficiency, σ represents the standard deviation of oxygen concentration, and σ max The three factors are interrelated. For example, changes in air pressure in plateau areas directly affect the dissolution and concentration of oxygen. Larger pressure changes generally increase the rate of change in oxygen concentration. The higher the gas mixing efficiency, the smoother the rate of change in oxygen concentration. The control accuracy assessment value derived from this comprehensive analysis can be used to evaluate the control status of oxygen regulation equipment, enabling precise control of the oxygen regulation system and ensuring a stable and safe oxygen supply in simulated plateau environments.

[0051] The pressure change rate influence factor was set to 0.2, the oxygen concentration change rate influence factor was set to 0.2, the gas mixing efficiency influence factor was set to 0.5, the concentration accuracy influence factor was set to 0.1, the pressure change rate was set to 10 hPa / s, the critical pressure change rate was set to 0, the oxygen concentration change rate was set to 100 ppm / s, the critical oxygen concentration change rate was set to 0, the critical gas mixing efficiency was set to 95%, the concentration accuracy evaluation value was set to 1, and the critical concentration accuracy evaluation value was set to 1. The control accuracy evaluation value was calculated under the condition of increasing gas mixing efficiency. This is shown in Table 1, a table of control accuracy evaluation values for the plateau environment cerebrovascular disease risk prediction system.

[0052] Table 1. Control accuracy evaluation value data table based on plateau environment cerebrovascular disease risk prediction system

[0053] serial number <![CDATA[ME1%]]> CA 1 90 0.619 2 92 0.630 3 94 0.640 4 96 0.651 5 98 0.661

[0054] like Figure 2 As shown in Table 1 and Figure 2 It can be seen that when the pressure change rate influencing factor, oxygen concentration change rate influencing factor, gas mixing efficiency influencing factor, concentration accuracy influencing factor, pressure change rate, critical pressure change rate, oxygen concentration change rate, critical oxygen concentration change rate, critical gas mixing efficiency, concentration accuracy evaluation value and critical concentration accuracy evaluation value remain unchanged, and the gas mixing efficiency continues to increase, the control accuracy evaluation value also continues to increase.

[0055] Preferably, the gas includes oxygen and nitrogen; the wind speed is dynamically adjusted according to the monitored gas injection state parameters, and the step of triggering oxygen adjustment based on the oxygen balance time and the air pressure balance time includes: obtaining the gas injection state parameter according to the gas injection state parameter; comparing the gas injection state parameter with the gas injection state threshold preset in the risk prediction database; if the gas injection state parameter is greater than or equal to the gas injection state threshold and the gas type is oxygen, then the difference between the gas injection state parameter and the gas injection state threshold is marked as a deviation gas injection state parameter; the deviation gas injection state parameter is compared with the wind speed adjustment ratio corresponding to each deviation gas injection state parameter preset in the risk prediction database, and the wind speed adjustment ratio corresponding to the deviation gas injection state parameter is obtained, and the wind speed is increased according to the wind speed adjustment ratio. speed and balance the air pressure at the same time; if the gas injection state parameter is greater than or equal to the gas injection state threshold and the gas type is nitrogen, the oxygen concentration is monitored in real time and the air pressure is balanced at the same time, oxygen compensation injection is started according to the oxygen concentration, and a nitrogen over-limit alarm is triggered; if the gas injection state parameter is less than the gas injection state threshold and the gas type is oxygen, determine whether the current wind speed is the preset minimum wind speed limit, if so, no additional processing is performed, otherwise the wind speed is gradually reduced (for example, a preset wind speed is reduced by one gear per second) until the minimum wind speed limit is reached; if the gas injection state parameter is less than the gas injection state threshold and the gas type is nitrogen, close the vent; trigger oxygen adjustment in advance according to the difference between the oxygen balance time and the air pressure balance time, specifically: adjust oxygen first, and then adjust the air pressure after the difference time has passed.

[0056] In this embodiment, when the oxygen concentration needs to be increased, oxygen is injected using the oxygen regulating device; when the oxygen concentration needs to be reduced, nitrogen is injected using the oxygen regulating device. Simultaneously, the gases are rapidly mixed and the exhaust valve is opened to maintain pressure balance. By dynamically adjusting the wind speed according to changes in the gas injection state parameters, the system can ensure that while meeting oxygen and pressure balances, it avoids unnecessary energy consumption due to excessively high or low wind speeds. The system can automatically adjust the wind speed based on the gas injection state parameters monitored in real time, ensuring that the oxygen regulating device can quickly respond to changes in different states and maintain oxygen concentration and pressure balance. In particular, when the oxygen and nitrogen injections are unbalanced, oxygen can be replenished or an alarm can be triggered in a timely manner to effectively avoid gas over- or under-injection. Depending on the type of gas, the system can flexibly adjust its response strategy to improve the system's flexibility and adaptability.

[0057] Preferably, the gas injection state parameters include injection gas concentration, cabin volume and air pressure range; the step of obtaining gas injection state parameters according to the gas injection state parameters includes: obtaining gas injection state parameter reference data from a preset risk prediction database, specifically including: reference injection gas concentration, allowable deviation injection gas concentration, critical cabin volume and critical air pressure range; performing deviation conformity calculation on the allowable deviation injection gas concentration, the injection gas concentration and the reference injection gas concentration to obtain injection gas concentration influencing parameters; performing proportion approximation calculation on the cabin volume and the critical air pressure range with the critical cabin volume and the air pressure range respectively, and then weighting the injection gas concentration influencing parameters and the proportion approximation calculation results through the gas injection state parameter influencing factors and then coupling them to obtain gas injection state parameters, the gas injection state parameter influencing factors include cabin volume influencing factors, air pressure range influencing factors and injection gas concentration influencing factors, and the gas injection state parameters represent quantitative data of the degree of influence of the injection gas concentration, cabin volume and air pressure range on the gas stability in the cabin.

[0058] The gas injection state parameters are obtained as follows:

[0059]

[0060] Where GI represents the gas injection state parameter, β4 represents the injection gas concentration influencing factor, β5 represents the cabin volume influencing factor, β6 represents the pressure range influencing factor, IC1 represents the injection gas concentration, IC0 represents the reference injection gas concentration, IC2 represents the allowable deviation injection gas concentration, CV1 represents the cabin volume, CV0 represents the critical cabin volume, PR1 represents the pressure range, and PR0 represents the critical pressure range.

[0061] In this embodiment, since the oxygen regulating device controls gas concentration by injecting oxygen or nitrogen, the injected gas concentration can be directly obtained by the gas control function of the oxygen regulating device; the cabin volume can be directly obtained by the cabin's geometric dimensions (length, width, height) or by using a measuring device such as a three-dimensional scanner; the air pressure range refers to the difference between the maximum and minimum air pressure values within the cabin, and the change in air pressure within the cabin can be measured by a pressure sensor or barometer. The three are interrelated. For example, if the amount of oxygen injected is too large, the gas concentration increases, which may cause the cabin air pressure to rise and produce a large air pressure range; if the amount of gas injected is too small, the gas concentration decreases, and the air pressure may also decrease, thereby affecting the balance of the system; if the injected gas concentration is too high or too low while the cabin volume remains unchanged, the air pressure will change, resulting in an increase in the air pressure range. The gas injection state parameters obtained through comprehensive analysis can provide a basis for adjusting the oxygen regulating device, accurately adjusting the gas injection amount and regulating the wind speed to maintain the stability and safe operation of the system.

[0062] A method for predicting the risk of cerebrovascular diseases in a plateau environment based on digital twins includes the following steps: real-time monitoring of concentration accuracy parameters and environmental impact parameters to obtain concentration accuracy evaluation values, and dynamically optimizing the oxygen concentration monitoring strategy of the oxygen regulating equipment based on the concentration accuracy evaluation values, where the concentration accuracy evaluation values are used to quantify the accuracy of the oxygen regulating equipment when measuring oxygen concentration; real-time monitoring of gas regulation dynamic factors, and dynamic adjustment of the equipment control strategy of the oxygen regulating equipment based on the gas regulation dynamic factors and the concentration accuracy evaluation values; dynamic adjustment of wind speed according to the monitored gas injection state parameters, triggering oxygen regulation based on the oxygen balance time and the air pressure balance time, and predicting the risk of cerebrovascular diseases based on the adjusted oxygen regulation equipment and the low-pressure chamber.

[0063] There are a few points to note:

[0064] (1) The drawings of the embodiments of the present invention only relate to the structures related to the embodiments of the present invention. Other structures may refer to conventional designs.

[0065] (2) For the sake of clarity, the thickness of layers or regions in the drawings used to describe the embodiments of the present invention are exaggerated or reduced, that is, these drawings are not drawn to scale. It is understood that when an element such as a layer, film, region, or substrate is referred to as being "on" or "under" another element, the element may be "directly" "on" or "under" the other element or intervening elements may be present.

[0066] (3) In the absence of conflict, the embodiments of the present invention and the features therein may be combined with each other to form new embodiments.

[0067] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. The protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. The plateau environment cerebrovascular disease risk prediction system based on digital twins is characterized by: include: Equipment control module, oxygen control module, oxygen pressure coupling control module and risk prediction database; The device control module is configured to monitor concentration accuracy parameters and environmental impact parameters in real time to obtain a concentration accuracy evaluation value, and dynamically optimize the oxygen concentration monitoring strategy of the oxygen regulating device based on the concentration accuracy evaluation value. The concentration accuracy evaluation value is used to quantify the accuracy of the oxygen regulating device in measuring oxygen concentration. The oxygen control module is used to monitor the gas regulation dynamic factor in real time and dynamically adjust the device control strategy of the oxygen regulation device based on the gas regulation dynamic factor and the concentration accuracy evaluation value; The oxygen-pressure coupling control module is used to dynamically adjust the wind speed according to the monitored gas injection state parameters, trigger oxygen adjustment based on the oxygen balance time and the air pressure balance time, and predict the risk of cerebrovascular disease based on the adjusted oxygen regulation equipment and low-pressure chamber.

2. The plateau environment cerebrovascular disease risk prediction system based on digital twin according to claim 1 is characterized in that: The environmental impact parameters include the temperature variation amplitude at each time monitoring point, the humidity value and the vibration frequency at each time monitoring point; The concentration accuracy parameters include equipment calibration frequency, measurement frequency and zero drift value; The step of real-time monitoring the concentration accuracy parameter and the environmental impact parameter to obtain the concentration accuracy evaluation value comprises: Obtain environmental impact parameter reference data and concentration accuracy parameter reference data from a preset risk prediction database. The environmental impact parameter reference data specifically includes: critical temperature variation range, reference humidity value, allowable deviation humidity value, and critical vibration frequency. The concentration accuracy parameter reference data specifically includes: reference equipment calibration frequency, allowable deviation equipment calibration frequency, critical measurement frequency, and critical zero drift value. The temperature variation amplitude at each time monitoring point is calculated with the critical temperature variation amplitude to obtain the temperature variation amplitude influencing parameter; Perform deviation compliance calculation on the humidity value at each time monitoring point, the reference humidity value and the allowable deviation humidity value to obtain the humidity value influencing parameter; The temperature variation amplitude influencing factor and the humidity value influencing factor are weighted and coupled respectively, and the results of the coupling processing are homogenized to obtain the environmental dynamic coupling parameters. After calculating the approximation of the vibration frequency to the critical vibration frequency, the vibration frequency influencing parameter is obtained by weighting the vibration frequency influencing factor. The environmental dynamic coupling parameter and the vibration frequency influencing parameter are coupled to obtain the environmental influencing parameter; Perform deviation compliance calculation on the allowable deviation device calibration frequency, the device calibration frequency and the reference device calibration frequency to obtain the device calibration frequency influencing parameter; Performing a proportion approximation operation on the measurement frequency and the zero drift value, the critical measurement frequency, and the critical zero drift value, respectively, to obtain a proportion approximation operation result; The concentration accuracy parameter influencing factors are used to weight the equipment calibration frequency influencing parameters, the proportion approach calculation results and the environmental influencing parameters after inverse proportional operation, and then coupled to obtain the concentration accuracy evaluation value. The concentration accuracy parameter influencing factors include the equipment calibration frequency influencing factor, the measurement frequency influencing factor, the zero drift value influencing factor and the environmental influencing parameter influencing factor.

3. The plateau environment cerebrovascular disease risk prediction system based on digital twin according to claim 1 is characterized in that: The step of dynamically optimizing the oxygen concentration monitoring strategy of the oxygen regulating device based on the concentration accuracy evaluation value includes: Obtaining a first concentration accuracy assessment threshold and a second concentration accuracy assessment threshold from a preset risk prediction database; Compare the concentration accuracy assessment value with the first concentration accuracy assessment threshold and the second concentration accuracy assessment threshold respectively. If the concentration accuracy assessment value is less than the first concentration accuracy assessment threshold, the machine is forced to shut down and enter maintenance mode, and the abnormality is reported to the management personnel at the same time; If the concentration accuracy assessment value is greater than or equal to the first concentration accuracy assessment threshold and less than the second concentration accuracy assessment threshold, zero point calibration is performed in real time, multi-channel redundant measurement is started, and the oxygen concentration is corrected according to the environmental influencing parameters. The calibration frequency and measurement frequency of the equipment are dynamically adjusted according to the concentration accuracy assessment value, the rate of change of air pressure, and the rate of change of oxygen concentration; If the concentration accuracy evaluation value is greater than or equal to the concentration accuracy evaluation second threshold value, zero point calibration is performed within a preset calibration interval.

4. The plateau cerebrovascular disease risk prediction system based on digital twin according to claim 3 is characterized in that: The step of dynamically adjusting the equipment calibration frequency and the measurement frequency according to the concentration accuracy evaluation value, the air pressure change rate, and the oxygen concentration change rate comprises: Obtaining the equipment calibration frequency and measurement frequency range corresponding to each concentration accuracy assessment value range from a preset risk prediction database; Comparing the concentration accuracy assessment value with each concentration accuracy assessment value range to obtain a concentration accuracy assessment value range, and then comparing the concentration accuracy assessment value range with the device calibration frequency and measurement frequency range corresponding to each concentration accuracy assessment value range to obtain the device calibration frequency and measurement frequency range corresponding to the concentration accuracy assessment value; The measurement frequency adjustment value is obtained by comprehensive processing of the air pressure change rate and the oxygen concentration change rate, and the current measurement frequency and the measurement frequency adjustment value are coupled to obtain the adjusted measurement frequency; Determine whether the adjusted measurement frequency is within the measurement frequency range, and if so, mark the current measurement frequency as the adjusted measurement frequency; If not and the adjusted measured frequency is less than the minimum value of the measured frequency range, the minimum value of the measured frequency range is marked as the adjusted measured frequency; If not and the adjusted measurement frequency is greater than the maximum value of the measurement frequency range, the maximum value of the measurement frequency range is marked as the adjusted measurement frequency.

5. The plateau environment cerebrovascular disease risk prediction system based on digital twin according to claim 4 is characterized in that: The step of obtaining the measurement frequency adjustment value based on the comprehensive processing of the air pressure change rate and the oxygen concentration change rate comprises: Obtaining a reference air pressure change rate, a reference oxygen concentration change rate, a unit air pressure change rate, and a unit oxygen concentration change rate from a preset risk prediction database; When the air pressure change rate is greater than the reference air pressure change rate, the difference between the air pressure change rate and the reference air pressure change rate is marked as the deviation air pressure change rate, and the air pressure adjustment unit is obtained based on the deviation air pressure change rate and the unit air pressure change rate. Otherwise, no additional processing is performed, and the air pressure adjustment unit represents the truncated division relationship between the deviation air pressure change rate and the unit air pressure change rate. When the oxygen concentration change rate is greater than the reference oxygen concentration change rate, the difference between the oxygen concentration change rate and the reference oxygen concentration change rate is marked as a deviation oxygen concentration change rate, and an oxygen adjustment unit is obtained based on the deviation oxygen concentration change rate and the unit oxygen concentration change rate; otherwise, no additional processing is performed, and the oxygen adjustment unit represents a truncated division relationship between the deviation oxygen concentration change rate and the unit oxygen concentration change rate; The air pressure adjustment unit and the oxygen adjustment unit are coupled to obtain a measurement frequency adjustment value.

6. The plateau environment cerebrovascular disease risk prediction system based on digital twin according to claim 1 is characterized in that: The step of dynamically adjusting the device control strategy of the oxygen regulation device based on the gas regulation dynamic factor and the concentration accuracy evaluation value includes: quantifying the regulation accuracy of the oxygen regulation equipment according to the gas regulation dynamic factor and the concentration accuracy evaluation value to obtain a control accuracy evaluation value; The control accuracy assessment value is compared with the first control accuracy assessment threshold and the second control accuracy assessment threshold preset in the risk prediction database. If the control accuracy assessment value is less than the first control accuracy assessment threshold, the air pressure adjustment is suspended, the current cabin pressure is locked, the constant oxygen flow mode is switched to ensure the safety of the subject, and the faulty unit is identified; If the control accuracy evaluation value is greater than or equal to the first control accuracy evaluation threshold and less than the second control accuracy evaluation threshold, the detection step signal is activated to dynamically adjust the device parameters, and the turbulence mode is activated at the oxygen injection point; If the control accuracy evaluation value is greater than or equal to the second control accuracy evaluation threshold, the preset high altitude simulation equipment parameters are loaded while maintaining the laminar flow mode.

7. The plateau cerebrovascular disease risk prediction system based on digital twin according to claim 6 is characterized in that: The gas regulation dynamic factors include the rate of change of gas pressure, the rate of change of oxygen concentration and the gas mixing efficiency; The steps of quantifying the control accuracy of the oxygen control device according to the gas control dynamic factor and the concentration accuracy evaluation value to obtain the control accuracy evaluation value include: Obtain gas control dynamic factor reference data and critical concentration accuracy assessment values from a preset risk prediction database. The gas control dynamic factor reference data specifically includes: critical gas pressure change rate, critical oxygen concentration change rate, and critical gas mixing efficiency; The pressure change rate and the oxygen concentration change rate are respectively subjected to a proportion approach calculation with the critical pressure change rate and the critical oxygen concentration change rate. The proportion approach calculation results are weighted and coupled by the pressure change rate influencing factor and the oxygen concentration change rate influencing factor. The processed results are subjected to an inverse proportional calculation to obtain the change rate influencing parameter. The gas mixing efficiency and concentration accuracy evaluation values are respectively subjected to a proportion approach calculation with the critical gas mixing efficiency and critical concentration accuracy evaluation values, and the calculation results are weighted by the gas mixing efficiency influencing factor and the concentration accuracy influencing factor to obtain the dynamic control performance index; The change rate influencing parameter and the dynamic control performance index are coupled to obtain a control accuracy evaluation value, which represents quantitative data on the degree of influence of the air pressure change rate, the oxygen concentration change rate and the gas mixing efficiency on the regulation accuracy when the oxygen regulating device performs oxygen regulation.

8. The plateau cerebrovascular disease risk prediction system based on digital twin according to claim 1 is characterized in that: The gas includes oxygen and nitrogen; The steps of dynamically adjusting the wind speed according to the monitored gas injection state parameters and triggering oxygen adjustment based on the oxygen balance time and the air pressure balance time include: Obtaining gas injection state parameters according to gas injection state parameters; The gas injection state parameter is compared with the gas injection state threshold value preset in the risk prediction database. If the gas injection state parameter is greater than or equal to the gas injection state threshold value and the gas type is oxygen, the difference between the gas injection state parameter and the gas injection state threshold value is marked as the deviation gas injection state parameter. The deviation gas injection state parameter is compared with the wind speed adjustment ratio corresponding to each deviation gas injection state parameter preset in the risk prediction database to obtain the wind speed adjustment ratio corresponding to the deviation gas injection state parameter. The wind speed is increased according to the wind speed adjustment ratio while balancing the air pressure; If the gas injection state parameter is greater than or equal to the gas injection state threshold and the gas type is nitrogen, the oxygen concentration is monitored in real time while the gas pressure is balanced. Oxygen compensation injection is started according to the oxygen concentration and a nitrogen over-limit alarm is triggered. If the gas injection state parameter is less than the gas injection state threshold and the gas type is oxygen, determine whether the current wind speed is the preset minimum wind speed limit. If so, no additional processing is performed. If not, gradually reduce the wind speed until it reaches the minimum wind speed limit. If the gas injection state parameter is less than the gas injection state threshold and the gas type is nitrogen, the vent is closed; Oxygen regulation is triggered based on the difference between oxygen balance time and pressure balance time.

9. The plateau environment cerebrovascular disease risk prediction system based on digital twin according to claim 8 is characterized in that: The gas injection state parameters include the injected gas concentration, the cabin volume and the air pressure difference; The step of obtaining the gas injection state parameter according to the gas injection state parameter comprises: Obtain reference data of gas injection state parameters from a preset risk prediction database, specifically including: reference injection gas concentration, allowable deviation injection gas concentration, critical chamber volume, and critical gas pressure range; Perform deviation compliance calculation on the allowable deviation injected gas concentration, the injected gas concentration and the reference injected gas concentration to obtain the injected gas concentration influencing parameter; The cabin volume and critical air pressure range difference are respectively subjected to proportion approximation calculation with the critical cabin volume and air pressure range difference, and then the injection gas concentration influencing parameters and the proportion approximation calculation results are weighted and coupled through the gas injection state parameter influencing factors to obtain the gas injection state parameters. The gas injection state parameter influencing factors include the cabin volume influencing factor, the air pressure range difference influencing factor and the injection gas concentration influencing factor. The gas injection state parameters represent the quantitative data of the degree of influence of the injection gas concentration, cabin volume and air pressure range difference on the gas stability in the cabin.

10. A method for predicting the risk of cerebrovascular disease in plateau environments based on digital twins, the method being based on the system according to any one of claims 1 to 9, characterized in that: The method comprises the following steps: monitoring concentration accuracy parameters and environmental impact parameters in real time to obtain a concentration accuracy evaluation value, and dynamically optimizing the oxygen concentration monitoring strategy of the oxygen regulating device based on the concentration accuracy evaluation value, wherein the concentration accuracy evaluation value is used to quantify the accuracy of the oxygen regulating device in measuring oxygen concentration; Real-time monitoring of gas regulation dynamic factors, and dynamic adjustment of the equipment control strategy of the oxygen regulation equipment based on the gas regulation dynamic factors and concentration accuracy assessment values; The wind speed is dynamically adjusted according to the monitored gas injection status parameters, oxygen adjustment is triggered based on the oxygen balance time and air pressure balance time, and the risk of cerebrovascular disease is predicted based on the adjusted oxygen regulation equipment and low-pressure chamber.

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