A fresh air control method and device for purifying operating rooms

Abstract

This invention discloses a method and device for controlling fresh air in a purified operating room, relating to the field of fresh air control technology. Before surgery begins, each local negative pressure control zone in the operating room is defined as a target zone, and air parameters in the target zones are collected in real time. Based on the subsequent surgical type and the air parameters of the target zones, the overall negative pressure control is used to simulate and regulate each target zone, generating a real-time air distribution map. The overall controllable value of the target zones is calculated based on the real-time map and compared with a preset threshold. Based on the comparison results, it is determined whether the negative pressure control method for subsequent surgeries should be overall negative pressure control or local negative pressure control. In this way, the negative pressure control method is determined before surgery, ensuring optimal negative pressure adjustment during surgery, guaranteeing the safety and efficiency of the operating room, and reducing medical costs.

Description

Technical Field

[0001] This invention relates to the field of fresh air control technology, specifically to a fresh air control method and device for purifying operating rooms. Background Technology

[0002] Air quality management in clean operating rooms has always been a crucial measure to ensure surgical safety and a hygienic medical environment. Existing fresh air control systems for clean operating rooms typically rely on two methods: overall negative pressure control and local negative pressure control. These methods achieve a negative pressure state by adjusting the airflow within the operating room, thereby preventing external air pollutants from entering. Overall negative pressure control usually focuses on regulating the airflow within the operating room to ensure continuous air circulation and removes pollutants through a high-efficiency filtration system. Overall negative pressure control has a simple control logic, is easy to operate, has relatively low cost, and effectively maintains the air pressure difference between the operating room and the outside, thus preventing pollutants from entering. In contrast, local negative pressure control focuses more on establishing independent or enhanced negative pressure environments in specific critical areas (such as around the operating table or areas with high concentrations of contaminants). This is typically achieved by configuring independent exhaust ducts, negative pressure ventilation devices, or variable air volume (VAV) terminal controllers in local areas, allowing these areas to maintain a negative pressure state even when the overall airflow remains constant. The advantages of local control are its high precision and fast response speed, which can cope with the situation of increased pollution risk in local areas and improve the flexibility and safety of environmental control. However, the logic of local control is more complex and the cost is relatively high. In most cases, overall negative pressure control is chosen to adjust the negative pressure state of the operating room.

[0003] However, in reality, various factors such as the layout of different operating rooms and the type of surgery mean that not all operating rooms are suitable for adjusting the negative pressure state through overall negative pressure control. If it is not reasonable to determine whether the operating room should adjust the negative pressure state during surgery through overall negative pressure control or local negative pressure control, it may affect the safety and efficiency of the operating room, and even prolong the operation time and increase medical costs. Summary of the Invention

[0004] The purpose of this invention is to solve the problems mentioned above and to provide a fresh air control method and device for purifying operating rooms.

[0005] In a first aspect of this invention, a method for controlling fresh air in a purified operating room is first proposed, the method comprising:

[0006] Before the surgery begins, the areas corresponding to the local negative pressure control in the operating room are marked as target areas, and the air parameters of the target areas are collected in real time.

[0007] Based on the type of surgery to be performed in the operating room and the air parameters of the target area, the overall negative pressure control is used to simulate and regulate each target area of ​​the operating room and generate a real-time air distribution map.

[0008] Calculate the overall controllable value of the target area based on the real-time air distribution map;

[0009] The overall controllable value of each target area is compared with the preset threshold, and the negative pressure control method for subsequent surgeries is determined based on the comparison results: whether it is overall negative pressure control or local negative pressure control.

[0010] Optionally, the steps for calculating the overall controllable value of the target area based on the real-time air distribution map are as follows:

[0011] The spatial pressure gradient equilibrium value and airflow path structure complexity value of each target area are calculated based on the real-time air distribution map. The overall controllable value of each target area is obtained by subtracting the airflow path structure complexity value from the spatial pressure gradient equilibrium value of each target area.

[0012] Optionally, the calculation steps for the spatial pressure gradient equilibrium value are as follows:

[0013] For each target area, extract the two-dimensional pressure difference distribution matrix of the target area from the real-time air distribution map. , Indicates the target region number Line number Column grid points Pressure difference at the location;

[0014] For each grid point Calculate its local pressure difference coupling gradient The calculation formula is: ;

[0015] Each grid point The gradient change is mapped to an angle, thus obtaining the local gradient direction angle at each point. The formula for mapping is: In the formula, Indicates the first The local gradient direction angle at a point;

[0016] Calculate each grid point The gradient phase difference in different directions yields the grid points. gradient direction difference The calculation formula is: ; express The difference in gradient direction at a point in different directions;

[0017] By using the gradient direction difference and local pressure coupling gradient of each grid point through maximum-min normalization, the gradient direction difference and local pressure coupling gradient of each grid point are mapped to the range of values ​​0-1. The local pressure equilibrium response value of each grid point is obtained by subtracting the normalized local pressure coupling gradient from the normalized gradient direction difference.

[0018] The mean value of the local differential pressure equilibrium response of all grid points in the target area is calculated and used as the spatial differential pressure gradient equilibrium value of the target area.

[0019] Optionally, the calculation steps for the airflow path structure complexity value are as follows:

[0020] For each target area, airflow path data is extracted from the real-time air distribution map. The airflow path data contains multiple airflow path points within the target area, and the path data of each path point includes the corresponding airflow direction angle.

[0021] For each airflow path point, calculate the absolute difference of the flow direction angle between the corresponding airflow path point and the next adjacent airflow path point, and use the absolute difference as the curvature of each corresponding airflow path point;

[0022] For each airflow path point, subtract the curvature of the corresponding airflow path point from the curvature of the next adjacent airflow path point, divide the difference by the distance between the corresponding airflow path point and its next adjacent airflow path point, and take the absolute value of the division result as the curvature change value of the corresponding airflow path point.

[0023] Multiply the curvature and curvature change values ​​of each airflow path point, and use the result of the multiplication as the complexity value of the corresponding airflow path point;

[0024] The maximum-minimum normalization method is used to map the complexity values ​​of all airflow path points to the range of 0-1, and the mean of the normalized complexity values ​​of all airflow path points is used as the airflow path structure complexity value of the target area.

[0025] Optionally, the steps for determining whether the negative pressure control method for subsequent surgeries is overall negative pressure control or local negative pressure control based on the comparison results are as follows:

[0026] Compare the overall controllable value of each target area with the preset threshold, and count the percentage of target areas with an overall controllable value not less than the preset threshold and the percentage of target areas with an overall controllable value less than the preset threshold.

[0027] If the proportion of target areas with an overall controllable value not less than the preset threshold is greater than the proportion of target areas with an overall controllable value less than the preset threshold, then the negative pressure control method for subsequent surgeries will be overall negative pressure control.

[0028] If the proportion of target areas with overall controllable values ​​less than the preset threshold is greater than the proportion of target areas with overall controllable values ​​less than the preset threshold, then the negative pressure control method for subsequent surgeries will be local negative pressure control.

[0029] In a second aspect of the invention, a fresh air control device for purifying operating rooms is provided, the device comprising:

[0030] Data Acquisition Module: Before the operation begins, the areas corresponding to the local negative pressure control in the operating room are marked as target areas, and the air parameters of the target areas are collected in real time;

[0031] Simulation module: Based on the type of surgery to be performed in the operating room and the air parameters of the target area, the module simulates and regulates the target areas of the operating room through overall negative pressure control, and generates a real-time air distribution map.

[0032] Calculation module: Calculates the overall controllable values ​​of the target area based on the real-time air distribution map;

[0033] Control module: Compares the overall controllable value of each target area with the preset threshold, and determines whether the negative pressure control method for subsequent surgery is overall negative pressure control or local negative pressure control based on the comparison result.

[0034] Optionally, the computing module includes:

[0035] Overall controllable value calculation module: Calculates the spatial pressure gradient equilibrium value and airflow path structure complexity value of each target area based on the real-time air distribution map, and subtracts the airflow path structure complexity value from the spatial pressure gradient equilibrium value of each target area to obtain the overall controllable value of each target area.

[0036] Optionally, the overall controllable value calculation module further includes:

[0037] Differential Pressure Module: For each target area, extract the two-dimensional differential pressure distribution matrix of the target area from the real-time air distribution map. , Indicates the target region number Line number Column grid points Pressure difference at the location;

[0038] Local pressure difference coupled gradient module: for each grid point Calculate its local pressure difference coupling gradient The calculation formula is: ;

[0039] Local gradient direction angle module: for each grid point The gradient change is mapped to an angle, thus obtaining the local gradient direction angle at each point. The formula for mapping is: In the formula, Indicates the first The local gradient direction angle at a point;

[0040] Gradient Direction Interpolation Module: Calculates the gradient direction difference for each grid point. The gradient phase difference in different directions yields the grid points. gradient direction difference The calculation formula is: ; express The difference in gradient direction at a point in different directions;

[0041] Local pressure difference equalization response value module: By using the maximum-minimum normalized gradient direction difference and local pressure difference coupling gradient of each grid point, the gradient direction difference and local pressure difference coupling gradient of each grid point are mapped to the range of values ​​0-1. The normalized gradient direction difference is subtracted from the normalized local pressure difference coupling gradient to obtain the local pressure difference equalization response value of each grid point.

[0042] Spatial pressure gradient equilibrium value module: Calculates the mean of the local pressure gradient equilibrium response values ​​of all grid points in the target area, which is used as the spatial pressure gradient equilibrium value of the target area.

[0043] Optionally, the overall controllable value calculation module further includes:

[0044] Data acquisition module: For each target area, extract airflow path data from the real-time air distribution map. The airflow path data contains multiple airflow path points within the target area, and the path data of each path point includes the corresponding airflow direction angle.

[0045] Curvature module: For each airflow path point, calculate the absolute difference of the flow direction angle between the corresponding airflow path point and the next adjacent airflow path point, and use the absolute difference as the curvature of each airflow path point;

[0046] Curvature change value module: For each airflow path point, subtract the curvature of the corresponding airflow path point from the curvature of the next adjacent airflow path point, divide the difference by the distance between the corresponding airflow path point and its next adjacent airflow path point, and take the absolute value of the division result as the curvature change value of the corresponding airflow path point.

[0047] Complexity Value Module: Multiplies the curvature and curvature change values ​​of each airflow path point, and uses the result of the multiplication as the complexity value of the corresponding airflow path point;

[0048] Airflow path structure complexity value module: The maximum-minimum normalization method is used to map the complexity values ​​of all airflow path points to the range of 0-1, and the mean of the normalized complexity values ​​of all airflow path points is used as the airflow path structure complexity value of the target area.

[0049] Optionally, the control module includes:

[0050] Percentage Calculation Module: Compares the overall controllable value of each target area with the preset threshold, and calculates the percentage of target areas with an overall controllable value not less than the preset threshold and the percentage of target areas with an overall controllable value less than the preset threshold.

[0051] First control module: If the proportion of target areas with overall controllable values ​​not less than the preset threshold is greater than the proportion of target areas with overall controllable values ​​less than the preset threshold, then the negative pressure control method for subsequent surgeries will be overall negative pressure control.

[0052] Second control module: If the proportion of target areas with overall controllable values ​​less than the preset threshold is greater than the proportion of target areas with overall controllable values ​​less than the preset threshold, then the negative pressure control method for subsequent surgeries will be local negative pressure control.

[0053] The beneficial effects of this invention are:

[0054] This invention proposes a method and device for controlling fresh air in a purified operating room. Before surgery begins, the areas corresponding to local negative pressure control within the operating room are designated as target areas, and air parameters in these areas are collected in real time. Based on the subsequent surgical type and the air parameters of the target areas, overall negative pressure control is used to simulate and regulate each target area, generating a real-time air distribution map. The overall controllable value of each target area is calculated based on the real-time air distribution map. This overall controllable value is then compared with a preset threshold. The comparison result determines whether the negative pressure control method for subsequent surgeries should be overall negative pressure control or local negative pressure control. In this way, by simulating the operation before surgery, considering the specific operating room and surgical type, the method of negative pressure control during the subsequent surgery can be determined beforehand. This ensures optimal negative pressure regulation during surgery, guaranteeing the safety and efficiency of the operating room while minimizing medical costs. Attached Figure Description

[0055] The invention will now be further described with reference to the accompanying drawings.

[0056] Figure 1 A flowchart of a fresh air control method for purifying operating rooms;

[0057] Figure 2 This is a schematic diagram of a fresh air control device for purifying operating rooms. Detailed Implementation

[0058] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0059] This invention provides a method for controlling fresh air in a purified operating room. See also... Figure 1 , Figure 1 A flowchart illustrating a fresh air control method for purifying an operating room, provided as an embodiment of the present invention. The method includes the following steps:

[0060] S1: Before the operation begins, the areas corresponding to the local negative pressure control in the operating room are marked as target areas, and the air parameters of the target areas are collected in real time; the air parameters include: temperature and humidity, particulate matter concentration, and CO2 concentration;

[0061] S2: Based on the type of surgery to be performed in the operating room and the air parameters of the target area, the overall negative pressure control is used to simulate and regulate each target area of ​​the operating room and generate a real-time air distribution map.

[0062] S3: Calculate the overall controllable value of the target area based on the real-time air distribution map;

[0063] S4: Compare the overall controllable value of each target area with the preset threshold, and determine whether the negative pressure control method for subsequent surgeries is overall negative pressure control or local negative pressure control based on the comparison results.

[0064] Based on the fresh air control method for purifying operating rooms provided by the embodiments of the present invention, the above method is used to simulate the operation before the operation, combined with the specific operating room and operation type, to determine whether the negative pressure control method during the subsequent operation is overall negative pressure control or local negative pressure control. In this way, the negative pressure control method is determined before the operation, so that the negative pressure adjustment effect during the operation is optimal, ensuring the safety and efficiency of the operating room, while minimizing medical costs as much as possible.

[0065] In one embodiment, S1: Before the operation begins, the areas corresponding to the local negative pressure control in the operating room are recorded as target areas, and the air parameters of the target areas are collected in real time; the air parameters include: temperature and humidity, particulate matter concentration, CO2 concentration, etc.

[0066] Specifically: Before surgery begins, the installed local negative pressure controls are first divided into zones. Each local negative pressure control has a corresponding negative pressure control area, which is called the "target area." For example, the area around the operating table, the anesthesia area, the instrument placement area, etc., are each managed by an independent local negative pressure control system, and these are all designated as target areas. Within each target area, multiple air quality sensors are deployed to collect key air parameters in real time, including temperature, humidity, particulate matter concentration, and CO2 concentration. These air parameters help monitor changes in air quality in the area in real time and provide data support for subsequent control decisions. The data collected by these sensors is sent to the central control system, which analyzes the real-time data of each target area to understand the air quality status of each local negative pressure control zone. This data will be used for simulation control and judgment in subsequent steps to ensure that the air quality in each area meets the surgical requirements. In addition, key air parameters include, but are not limited to, temperature, relative humidity, particulate matter concentration (such as PM2.5, PM10), carbon dioxide (CO2) concentration, volatile organic compound (VOCs) concentration, and microbial concentration such as air exchange rate (ACH), etc. Among these parameters, temperature and humidity primarily affect the survival conditions of pathogens and comfort control; particulate matter concentration directly reflects the level of suspended pollutants in the air and is an important indicator for measuring air cleanliness; CO2 concentration is often used as an indirect indicator of personnel density and ventilation conditions; parameters such as VOCs and airborne bacteria are suitable for assessing the higher air quality requirements in certain special types of surgeries (such as organ transplantation and infectious surgery). Through real-time acquisition and analysis of these key air parameters, the system can comprehensively grasp the air environment status of each target area, providing high-resolution data support for subsequent control simulation and negative pressure control strategies, ensuring that each high-risk area operates within a controllable and predictable air quality range.

[0067] In one embodiment, S2: Based on the type of subsequent surgery in the operating room and the air parameters of the target area, simulate and regulate each target area of ​​the operating room through overall negative pressure control, and generate a real-time air distribution map.

[0068] Specifically, the pre-set simulation system will acquire the type of surgery to be performed and select the appropriate air quality standard based on the air quality requirements of different surgical types. For example, organ transplant surgery may have higher air quality requirements, especially in the area around the operating table. The simulation system will automatically load the corresponding air quality control standard according to the type of surgery and combine it with real-time air parameters of the target area (such as temperature, humidity, particulate matter concentration, CO2 concentration, etc.) as simulation input data.

[0069] Based on the air quality requirements of the surgical procedure and the air parameters of each target area, the system sets preliminary negative pressure control parameters. The goal of negative pressure control is to ensure that the air pressure inside the operating room is lower than that of the external environment, preventing the spread of pollutants. The simulation system calculates the required exhaust and fresh air volumes for each target area based on the size and layout of the operating room, the air quality requirements of the target areas (such as CO2 concentration, PM2.5 concentration, etc.), and air quality standards. Exhaust volume refers to the amount of air exhausted from the operating room, while fresh air volume is the amount of fresh air introduced into the operating room. The simulation system also calculates the required airflow direction and velocity for each area to ensure that air flows in the expected direction, avoiding dead zones and cross-contamination.

[0070] By inputting the above data, the simulation system initiates an overall negative pressure control mode to simulate airflow, which is the core process of simulation control. The simulation system simulates the airflow in the operating room based on fluid mechanics principles (such as Bernoulli's principle and airflow dynamics) and numerical simulation techniques (such as CFD computational fluid dynamics). The specific process is as follows: Establishing an airflow model: The simulation system constructs a three-dimensional model of the operating room in a virtual environment and subdivides each target area. Information such as airflow, wind speed, and pressure difference in these areas is quantified and converted into digital data for subsequent analysis. Simulating airflow paths and distribution: Using CFD technology, the airflow path and distribution in each target area are simulated. For example, the airflow in the operating table area should be from the ceiling to the floor, forming a vertical airflow direction, while other areas may require horizontal airflow to ensure that pollutants do not diffuse into the operating table area. The system simulates the pressure difference changes in each target area. For example, the negative pressure intensity in the operating table area may be stronger than in other areas to avoid the diffusion of pollutants. The system ensures that air within the negative pressure range does not flow back to the external area by simulating the airflow path. After the simulation is complete, the system calculates the air quality distribution map for each target area, including airflow direction, wind speed, negative pressure intensity, and particulate matter concentration. Using this data, the system can comprehensively assess whether the air quality in each target area meets preset standards and generate a real-time air distribution map, displaying wind speed, negative pressure intensity, and pollutant concentration for each target area. The air distribution map clearly shows the airflow and distribution patterns in each area of ​​the operating room under overall negative pressure control, detailing parameters such as air quality, airflow distribution, airflow adjustment, and negative pressure intensity in each target area. This data not only provides a basis for decision-making during surgery but also serves as a reference for the subsequent implementation of negative pressure control strategies.

[0071] In one embodiment, S3: The step of calculating the overall controllable value of the target area based on the real-time air distribution map is as follows:

[0072] The spatial pressure gradient equilibrium value and airflow path structure complexity value of each target area are calculated based on the real-time air distribution map. The overall controllable value of each target area is obtained by subtracting the airflow path structure complexity value from the spatial pressure gradient equilibrium value of each target area.

[0073] In one embodiment, the calculation steps for the spatial pressure gradient equilibrium value are as follows:

[0074] For each target area, extract the two-dimensional pressure difference distribution matrix of the target area from the real-time air distribution map. , Indicates the target region number Line number Column grid points Pressure difference at the location;

[0075] For each grid point Calculate the product of its gradient deviation with its four adjacent points, and use it as the corresponding grid point. Local pressure difference coupling gradient This represents the interaction strength of the gradient at that point in the horizontal and vertical directions; a larger value indicates a point where the gradient changes drastically, making it more likely to form a perturbation boundary or a point difficult to control. The formula for calculation is: In the formula, Indicates the first Local pressure difference coupled gradient at a point; The first term indicates the change in pressure difference in the vertical direction; The second term indicates the change in pressure difference in the horizontal direction;

[0076] Each grid point The gradient change is mapped to an angle, thus obtaining the local gradient direction angle at each point. The formula for mapping is: In the formula, Indicates the first The local gradient direction angle at a point; the more similar they are, the more consistent the flow direction of the regional pressure difference field in space.

[0077] Calculate each grid point The gradient phase difference in different directions yields the grid points. gradient direction difference The calculation formula is: ; express The difference in gradient direction at a point in different directions reflects the presence of a "vortex" or abrupt change; if the entire region The generally small values ​​indicate good consistency in the direction of the pressure difference;

[0078] By using the gradient direction difference and local pressure coupling gradient of each grid point through maximum-min normalization, the gradient direction difference and local pressure coupling gradient of each grid point are mapped to the range of values ​​0-1. The local pressure equilibrium response value of each grid point is obtained by subtracting the normalized local pressure coupling gradient from the normalized gradient direction difference.

[0079] The mean value of the local differential pressure equilibrium response of all grid points in the target area is calculated and used as the spatial differential pressure gradient equilibrium value of the target area.

[0080] It should be noted that in calculating the equilibrium value of the spatial pressure gradient, the first step is to extract the two-dimensional pressure gradient distribution matrix M=Pi,j of the target area from the real-time air distribution map of the operating room, where Pi,j represents the pressure gradient value of the grid point in the i-th row and j-th column of the target area. This two-dimensional pressure gradient matrix is ​​derived from CFD (Computational Fluid Dynamics) simulation results. Based on the real-time airflow conditions in the operating room, the system calculates the pressure gradient value at each grid point using airflow dynamics models and numerical simulation techniques. These values ​​are typically measured in real-time by the negative pressure control system of the operating room. Next, the local pressure gradient coupling gradient at each grid point is calculated by examining the pressure gradient values ​​of each grid point and its four adjacent points. This value represents the intensity of gradient changes at that point in the horizontal and vertical directions. This data is obtained through the airflow field in the computational fluid dynamics simulation system, ensuring that the pressure gradient of each region is correctly reflected. Then, the system maps the gradient change of each grid point to an angle using the arctangent function. This step helps determine the directionality of the pressure gradient field; the angle value is calculated from the airflow direction in the simulation results, ensuring that the airflow trend within each region is reflected. Subsequently, the system calculates the gradient phase difference of each grid point in different directions. This value reflects local airflow disturbances or inconsistencies. The data is derived from the comparison of gradient direction angles between points within the region, and the results are based on the relative changes between points in the simulation diagram. Based on this, the system normalizes the gradient direction difference and the local pressure difference coupled gradient, obtaining a value between 0 and 1. This process ensures that calculations across all regions can be compared consistently and avoids data bias or imbalance. Finally, by averaging the local pressure difference equilibrium response values ​​of all grid points, the spatial pressure difference gradient equilibrium value of the target region is obtained. This value comprehensively reflects the pressure difference distribution equilibrium of the target region under overall negative pressure control. The final data is provided by the simulation system, and the accuracy and validity of the values ​​are ensured through real-time feedback and dynamic calculation.

[0081] It should be noted that the spatial pressure gradient equilibrium value is an indicator used to measure whether the pressure field of a target area in the operating room has coordination and stability in spatial distribution under the overall negative pressure control conditions. The larger the value, the more uniform the pressure gradient distribution in the area, the more consistent the direction, and the fewer the vortex or abrupt structures. This means that the area responds more smoothly to the overall negative pressure system and is easier to be incorporated into the unified control of the system. When the equilibrium value of the spatial pressure gradient is high, it indicates that the pressure difference varies smoothly in space within the target area, and there are fewer coupled gradients of local pressure differences (i.e., areas with significant changes in both the horizontal and vertical directions). Under this distribution, it is less likely to occur phenomena such as local airflow reversal, pressure difference instability, or edge disturbance accumulation. At the same time, because the gradient direction angle tends to be consistent, the airflow in the entire area has a clear and continuous flow trend, which is easy to form an overall coordinated flow field structure under the guidance of the system's negative pressure, and will not be disturbed by local "disturbance sources" to affect the system's pressure difference balance. Conversely, if this value is too small, it indicates that there are a large number of gradient coupling anomalies and gradient direction abrupt change points in the area, and the overall pressure difference field exhibits a highly unbalanced or turbulent structure. When the system controls it, the control effect will deteriorate due to inconsistent response and feedback distortion, and may even cause continuous instability or loss of control in some areas. Therefore, this value essentially reflects the ability of the overall negative pressure control system to maintain the stability of the pressure difference in the target area through unified control means, and is an important indicator for assessing whether the operating room is suitable for relying on the overall negative pressure control mechanism to regulate the air state of each area.

[0082] It should be noted that the advantage of calculating the spatial pressure gradient equilibrium value using the above method is that it can accurately reflect the spatial distribution uniformity, gradient consistency, and flow stability of the pressure differential field in each target area of ​​the operating room under overall negative pressure control. First, using local gradient coupling calculations can reveal the degree of local variation in the pressure differential field, especially the interaction intensity between the horizontal and vertical directions, helping to identify areas of drastic pressure differential changes. These areas are often prone to airflow turbulence, boundary disturbances, or reverse flow, and therefore require special attention. Second, by mapping gradient changes to angles, the consistency of flow direction in the pressure differential field can be reflected, avoiding simple pressure value comparisons. Thus, if the consistency of the pressure differential gradient direction within a region is poor, i.e., if "vortices" or "abrupt changes" exist, it can be detected in time, preventing local contamination diffusion caused by inconsistent flow directions. Finally, by normalizing the gradient direction difference and the local pressure differential coupling gradient, not only can the dimensions be unified, but the interference caused by the magnitude of pressure differentials in different regions can also be eliminated, ensuring the standardization and comparability of the results. Overall, this method, through a progressive analysis, can systematically evaluate the air control situation in the operating room, ensuring stable airflow and balanced pressure difference under negative pressure control. This improves the effectiveness of the overall negative pressure control system, reduces the need for local negative pressure control, thereby saving resources and improving control efficiency.

[0083] In one embodiment, the steps for calculating the airflow path structure complexity are as follows:

[0084] For each target area, airflow path data is extracted from the real-time air distribution map. The airflow path data contains multiple airflow path points within the target area, and the path data for each path point includes its spatial coordinates. airflow velocity and the direction angle of airflow These data come from computational fluid dynamics (CFD) simulations, which obtain the spatial distribution of airflow paths and their flow characteristics by simulating airflow.

[0085] For each airflow path point Calculate the absolute difference in the flow direction angle between the corresponding airflow path point and the next adjacent airflow path point, and use this absolute difference as the curvature of each airflow path point; the calculation formula is: , Indicates airflow path point The degree of curvature reflects the intensity of airflow change at that point; the greater the angle difference, the more pronounced the curvature of the airflow path at that point; conversely, the smaller the angle difference, the more straight the path.

[0086] For each airflow path point The next adjacent airflow path point degree of curvature Subtract the corresponding airflow path point degree of curvature The difference between the subtraction and division are then divided by the corresponding airflow path point. At its next adjacent airflow path point Distance between The absolute value of the division result is then used to determine the corresponding airflow path point. curvature change value The calculation formula is: ;

[0087] Each airflow path point degree of curvature and curvature change value Multiply, and use the result of the multiplication as the corresponding airflow path point. The complexity value;

[0088] The maximum-min normalization method is used to map the complexity values ​​of all airflow path points to a range of 0-1, and the mean of the normalized complexity values ​​of all airflow path points is taken as the airflow path structure complexity value of the target area. The smaller the value, the simpler and more regular the airflow path, and the better the overall negative pressure control system's control effect on the area; the larger the value, the more complex the airflow path in the area, the existence of backflow or dead zones, and the greater the overall control difficulty.

[0089] It should be noted that the airflow path data for the target area comes from real-time air distribution maps or computational fluid dynamics (CFD) simulation results. Using the CFD model, the simulation system calculates the spatial coordinates and corresponding flow direction angles of each airflow path point based on the negative pressure environment and airflow conditions of the operating room. The airflow path point data includes the flow direction angles of each path point, which are calculated from the velocity field during the airflow simulation. Next, for each airflow path point, the absolute difference (curvature) of its flow direction angles with the next adjacent airflow path point is calculated. This value is obtained by calculating the directional differences between path points, based on the direction angle data derived from the airflow model. Then, the curvature change value of each airflow path point is calculated. This value is obtained by calculating the curvature difference between adjacent points and their physical distance (Δd), which is based on the spatial coordinate differences between airflow path points. Finally, the complexity values ​​of all airflow path points are normalized, mapping them to a range of 0 to 1 to ensure consistency and comparability of the results. The normalized complexity value is calculated by averaging the values ​​of all path points to obtain the airflow path structure complexity value for the target area. The acquisition and calculation of these data are based entirely on the airflow direction and path information output by CFD simulation, ensuring the accuracy and real-time nature of the calculation process.

[0090] It's important to note that the airflow path structure complexity value is an indicator used to measure the simplicity and regularity of the airflow path within a target area. It quantifies the flow characteristics of airflow by calculating the degree of curvature and changes in curvature of the airflow path, reflecting whether the airflow is smooth and whether it is prone to backflow, dead zones, or mixed flow. Specifically, when the airflow path complexity of the target area is low, it indicates that the airflow is relatively straight and stable, less prone to turbulence or irregular flow directions. Such areas are more easily regulated by the overall negative pressure control system. Conversely, areas with high airflow path complexity have more tortuous and unstable airflow, potentially leading to local backflow, air stagnation, and other problems. This makes precise execution of overall negative pressure control difficult, and pollutants are more likely to accumulate, resulting in poor control performance. Therefore, the lower the airflow path structure complexity value, the simpler and more regular the airflow, and the more uniform the pressure differential distribution. The overall negative pressure control system can more effectively guide the airflow and maintain a stable pressure differential in the target area, allowing the entire operating room to rely on overall negative pressure control for regulation, improving control efficiency and reducing the need for local negative pressure control. For example, if the airflow path in a certain area is complex, airflow reversal or stagnation may occur, in which case local negative pressure control becomes more important; while if the complexity of the area is small and the airflow is smooth, overall negative pressure control can play a better role in achieving uniform air distribution and ensuring air cleanliness and the safety of the surgical environment.

[0091] The advantage of calculating the airflow path structure complexity value using the above method is that it can comprehensively and accurately quantify the flow characteristics of the airflow path, especially in reflecting the curvature, curvature change, and consistency of airflow direction, providing a more detailed control analysis. First, calculating the curvature of each airflow path point directly reflects whether the airflow at that point has undergone a significant directional change, which is crucial for determining whether the airflow is prone to backflow, dead zones, or mixing. Second, calculating the curvature change further reveals the stability of the airflow path. If the airflow near a certain path point experiences a drastic directional change, it means that the airflow in that area is relatively unstable, which may lead to irregular airflow patterns and increase the overall control complexity. The complexity value obtained by multiplying these two values ​​comprehensively reflects the flow pattern at the path point. Combined with max-min normalization, the complexity values ​​of different regions can be unified to the range of 0 to 1, ensuring comparability between different regions. Finally, by calculating the average complexity of all path points within the target area, the resulting airflow path structure complexity value not only reflects the regularity of airflow within that area but also helps determine whether the area is suitable for relying on overall negative pressure control. Overall, this approach assesses airflow characteristics from multiple dimensions (bending, curvature variation, flow consistency, etc.), ensuring the comprehensiveness and accuracy of the calculations. Compared to traditional simple velocity or pressure difference analysis methods, it can more effectively capture potential unstable factors in airflow, thus providing a more scientific basis for air control in operating rooms.

[0092] In one embodiment, S4: The step of comparing the overall controllable value of each target area with a preset threshold, and determining whether the negative pressure control method for subsequent surgery is overall negative pressure control or local negative pressure control based on the comparison result is as follows:

[0093] Compare the overall controllable value of each target area with the preset threshold, and count the percentage of target areas with an overall controllable value not less than the preset threshold and the percentage of target areas with an overall controllable value less than the preset threshold.

[0094] If the proportion of target areas with an overall controllable value not less than the preset threshold is greater than the proportion of target areas with an overall controllable value less than the preset threshold, then the negative pressure control method for subsequent surgeries will be overall negative pressure control.

[0095] If the proportion of target areas with overall controllable values ​​less than the preset threshold is greater than the proportion of target areas with overall controllable values ​​less than the preset threshold, then the negative pressure control method for subsequent surgeries will be local negative pressure control.

[0096] It's important to note that the overall controllable value of each target area is compared with a preset threshold to determine whether each area is suitable for adjustment via overall negative pressure control. This comparison clarifies which areas have higher overall controllable values ​​and which require other adjustment methods (such as local negative pressure control). Specifically, first, the number of target areas with overall controllable values ​​not less than the preset threshold and the number of target areas with overall controllable values ​​less than the preset threshold are counted. Then, the proportion of these two is calculated: the ratio of areas not less than the preset threshold to the total target areas versus the ratio of areas less than the preset threshold. If the proportion of areas not less than the threshold is greater than the proportion of areas less than the threshold, it indicates that airflow in most areas is relatively regular, and the overall negative pressure control system can effectively maintain a stable pressure differential. In this case, subsequent surgeries can rely on overall negative pressure control. Conversely, if the proportion of areas less than the threshold is greater than the proportion of areas not less than the threshold, it means that airflow in most areas is more complex or unstable, prone to backflow or air stagnation. In this case, local negative pressure control is needed to assist in adjustment, ensuring stable airflow in the operating room and preventing the spread of pollutants, thereby ensuring the safety of the surgery.

[0097] Based on the same inventive concept, this invention also provides a fresh air control device for purifying operating rooms. See also Figure 2 , Figure 2 A framework diagram of a fresh air control device for purifying an operating room, provided by an embodiment of the present invention, is shown. The device includes:

[0098] Data Acquisition Module: Before the operation begins, the areas corresponding to the local negative pressure control in the operating room are marked as target areas, and the air parameters of the target areas are collected in real time;

[0099] Simulation module: Based on the type of surgery to be performed in the operating room and the air parameters of the target area, the module simulates and regulates the target areas of the operating room through overall negative pressure control, and generates a real-time air distribution map.

[0100] Calculation module: Calculates the overall controllable values ​​of the target area based on the real-time air distribution map;

[0101] Control module: Compares the overall controllable value of each target area with the preset threshold, and determines whether the negative pressure control method for subsequent surgery is overall negative pressure control or local negative pressure control based on the comparison result.

[0102] Based on the fresh air control system for purifying operating rooms provided by the embodiments of the present invention, the above-mentioned method is used to simulate the operation before the operation, combined with the specific operating room and operation type, to determine whether the negative pressure control method during the subsequent operation is overall negative pressure control or local negative pressure control. In this way, the negative pressure control method is determined before the operation, so that the negative pressure adjustment effect during the operation is optimal, ensuring the safety and efficiency of the operating room, while minimizing medical costs as much as possible.

[0103] In one embodiment, the computing module includes:

[0104] Overall controllable value calculation module: Calculates the spatial pressure gradient equilibrium value and airflow path structure complexity value of each target area based on the real-time air distribution map, and subtracts the airflow path structure complexity value from the spatial pressure gradient equilibrium value of each target area to obtain the overall controllable value of each target area.

[0105] In one embodiment, the overall controllable value calculation module further includes:

[0106] Differential Pressure Module: For each target area, extract the two-dimensional differential pressure distribution matrix of the target area from the real-time air distribution map. , Indicates the target region number Line number Column grid points Pressure difference at the location;

[0107] Local pressure difference coupled gradient module: for each grid point Calculate its local pressure difference coupling gradient The calculation formula is: ;

[0108] Local gradient direction angle module: for each grid point The gradient change is mapped to an angle, thus obtaining the local gradient direction angle at each point. The formula for mapping is: In the formula, Indicates the first The local gradient direction angle at a point;

[0109] Gradient Direction Interpolation Module: Calculates the gradient direction difference for each grid point. The gradient phase difference in different directions yields the grid points. gradient direction difference The calculation formula is: ; express The difference in gradient direction at a point in different directions;

[0110] Local pressure difference equalization response value module: By using the maximum-minimum normalized gradient direction difference and local pressure difference coupling gradient of each grid point, the gradient direction difference and local pressure difference coupling gradient of each grid point are mapped to the range of values ​​0-1. The normalized gradient direction difference is subtracted from the normalized local pressure difference coupling gradient to obtain the local pressure difference equalization response value of each grid point.

[0111] Spatial pressure gradient equilibrium value module: Calculates the mean of the local pressure gradient equilibrium response values ​​of all grid points in the target area, which is used as the spatial pressure gradient equilibrium value of the target area.

[0112] In one embodiment, the overall controllable value calculation module further includes:

[0113] Data acquisition module: For each target area, extract airflow path data from the real-time air distribution map. The airflow path data contains multiple airflow path points within the target area, and the path data of each path point includes the corresponding airflow direction angle.

[0114] Curvature module: For each airflow path point, calculate the absolute difference of the flow direction angle between the corresponding airflow path point and the next adjacent airflow path point, and use the absolute difference as the curvature of each airflow path point;

[0115] Curvature change value module: For each airflow path point, subtract the curvature of the corresponding airflow path point from the curvature of the next adjacent airflow path point, divide the difference by the distance between the corresponding airflow path point and its next adjacent airflow path point, and take the absolute value of the division result as the curvature change value of the corresponding airflow path point.

[0116] Complexity Value Module: Multiplies the curvature and curvature change values ​​of each airflow path point, and uses the result of the multiplication as the complexity value of the corresponding airflow path point;

[0117] Airflow path structure complexity value module: The maximum-minimum normalization method is used to map the complexity values ​​of all airflow path points to the range of 0-1, and the mean of the normalized complexity values ​​of all airflow path points is used as the airflow path structure complexity value of the target area.

[0118] In one embodiment, the control module includes:

[0119] Percentage Calculation Module: Compares the overall controllable value of each target area with the preset threshold, and calculates the percentage of target areas with an overall controllable value not less than the preset threshold and the percentage of target areas with an overall controllable value less than the preset threshold.

[0120] First control module: If the proportion of target areas with overall controllable values ​​not less than the preset threshold is greater than the proportion of target areas with overall controllable values ​​less than the preset threshold, then the negative pressure control method for subsequent surgeries will be overall negative pressure control.

[0121] Second control module: If the proportion of target areas with overall controllable values ​​less than the preset threshold is greater than the proportion of target areas with overall controllable values ​​less than the preset threshold, then the negative pressure control method for subsequent surgeries will be local negative pressure control.

[0122] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A fresh air control method for purifying an operating room, characterized by, The method comprises the following steps: Before the operation starts, each local negative pressure control area of the operating room is recorded as a target area, and the air parameters of the target area are collected in real time; According to the subsequent operation type of the operating room and the air parameters of the target area, the target areas of the operating room are simulated and controlled by overall negative pressure control, and a real-time air distribution map is generated; The overall controllable value of the target area is calculated according to the real-time air distribution map; The overall controllable value of each target area is compared with a preset threshold value, and the control mode of the subsequent operation is determined according to the comparison result, that is, whether the overall negative pressure control or the local negative pressure control is adopted; The step of calculating the overall controllable value of the target area according to the real-time air distribution map comprises the following steps: The space pressure difference gradient balance value and the airflow path structure complexity value of each target area are calculated according to the real-time air distribution map, the space pressure difference gradient balance value of each target area is subtracted by the airflow path structure complexity value, and the overall controllable value of each target area is obtained; The calculation step of the space pressure difference gradient balance value comprises the following steps: For each target region, a two-dimensional differential pressure distribution matrix of the target region is extracted from the real-time air distribution map , represents the differential pressure value at the grid point of the target region, the th row, and the th column ; For each grid point , the local pressure difference coupling gradient , is calculated as: ; The gradient change of each grid point is mapped to an angle to obtain a local gradient direction angle of each point , and the mapping formula is: , wherein represents the local gradient direction angle of the i th point. The gradient phase difference in different directions of each grid point The gradient direction difference of the grid point The formula for calculating is: ; The gradient direction difference of the grid point in different directions is represented by ​​ The gradient direction difference value and the local pressure difference coupling gradient of each grid point are mapped to the interval of 0-1 by maximum-minimum normalization, the normalized gradient direction difference value is subtracted by the normalized local pressure difference coupling gradient, and the local pressure difference balance response value of each grid point is obtained; The average value of the local pressure difference balance response values of all grid points in the target area is calculated as the space pressure difference gradient balance value of the target area; The calculation step of the airflow path structure complexity value comprises the following steps: For each target area, the airflow path data is extracted from the real-time air distribution map, the airflow path data includes a plurality of airflow path points in the target area, and the path data of each path point includes the flow direction angle of the corresponding airflow; For each airflow path point, the absolute difference value of the flow direction angle between the corresponding airflow path point and the next adjacent airflow path point is calculated, and the absolute difference value is taken as the bending degree of each airflow path point; For each airflow path point, the bending degree of the next adjacent airflow path point is subtracted by the bending degree of the corresponding airflow path point, and the difference value is divided by the distance between the corresponding airflow path point and the next adjacent airflow path point, and the absolute value of the division result is taken as the curvature change value of the corresponding airflow path point; The bending degree and the curvature change value of each airflow path point are multiplied, and the multiplication result is taken as the complexity value of the corresponding airflow path point; The complexity values of all airflow path points are mapped to the interval of 0-1 by maximum-minimum normalization, and the average value of the normalized complexity values of all airflow path points is taken as the airflow path structure complexity value of the target area; The step of determining the control mode of the subsequent operation according to the comparison result comprises the following steps: The overall controllable value of each target area is compared with a preset threshold value, and the proportion of the number of target areas whose overall controllable value is not less than the preset threshold value and the proportion of the number of target areas whose overall controllable value is less than the preset threshold value are calculated. If the proportion of the number of target regions with the overall controllable value not less than the preset threshold value is greater than the proportion of the number of target regions with the overall controllable value less than the preset threshold value, the negative pressure state control mode of the subsequent surgery is the overall negative pressure control. If the proportion of the number of target regions with the overall controllable value less than the preset threshold value is greater than the proportion of the number of target regions with the overall controllable value less than the preset threshold value, the negative pressure state control mode of the subsequent surgery is the local negative pressure control.

2. A fresh air control device for purifying an operating room, characterized by The device comprises: The acquisition module records each local negative pressure control corresponding region in the operating room as a target region before the start of the surgery, and acquires the air parameters of the target region in real time; The simulation module simulates and controls each target region in the operating room through the overall negative pressure control according to the subsequent surgery type of the operating room and the air parameters of the target region, and generates a real-time air distribution map; The calculation module calculates the overall controllable value of the target region according to the real-time air distribution map; The control module compares the overall controllable value of each target region with the preset threshold value, and determines whether the negative pressure state control mode of the subsequent surgery is the overall negative pressure control or the local negative pressure control according to the comparison result; The calculation module comprises: The overall controllable value calculation module calculates the spatial pressure difference gradient balance value and the airflow path structure complexity value of each target region according to the real-time air distribution map, subtracts the airflow path structure complexity value from the spatial pressure difference gradient balance value of each target region, and obtains the overall controllable value of each target region; The overall controllable value calculation module further comprises: Differential pressure value module: for each target region, extract the two-dimensional differential pressure distribution matrix of the target region from the real-time air distribution map , represents the differential pressure value at the grid point of the target region, the i-th row, and the j-th column , ​​ Local pressure difference coupled gradient module: for each grid point , compute its local pressure difference coupled gradient , the formula is: ; Local gradient direction angle module: mapping the gradient change of each grid point to an angle to obtain the local gradient direction angle of each point, and the formula is: , wherein represents the local gradient direction angle of the i th point; Gradient direction difference module: calculate gradient direction difference of each grid point Gradient direction difference of each grid point in different directions The formula for calculating is: ; Gradient direction difference of each grid point in different directions Gradient direction difference of each grid point in different directions​ The local pressure difference balance response value module maps the gradient direction difference value and the local pressure difference coupling gradient of each grid point in the range of 0-1 through the maximum-minimum normalization of the gradient direction difference value and the local pressure difference coupling gradient of each grid point, subtracts the normalized local pressure difference coupling gradient from the normalized gradient direction difference value, and obtains the local pressure difference balance response value of each grid point; The spatial pressure difference gradient balance value module calculates the average value of the local pressure difference balance response values of all grid points in the target region as the spatial pressure difference gradient balance value of the target region; The overall controllable value calculation module further comprises: The data acquisition module extracts airflow path data from the real-time air distribution map for each target region, and the airflow path data includes multiple airflow path points in the target region, and the path data of each path point includes the flow direction angle of the corresponding airflow; The bending degree module calculates the absolute difference value of the flow direction angle between the corresponding airflow path point and the next adjacent airflow path point for each airflow path point, and takes the absolute difference value as the bending degree of each airflow path point; The curvature change value module calculates the difference value between the bending degree of the next adjacent airflow path point and the bending degree of the corresponding airflow path point, divides the difference value by the distance between the corresponding airflow path point and the next adjacent airflow path point, and takes the absolute value of the division result as the curvature change value of the corresponding airflow path point; The complexity value module multiplies the bending degree and the curvature change value of each airflow path point, and takes the multiplication result as the complexity value of the corresponding airflow path point; The air flow path structure complexity value module maps complexity values of all air flow path points to a range of 0-1 by using maximum-minimum normalization, and takes the average of the normalized complexity values of all air flow path points as the air flow path structure complexity value of the target region; The control module comprises: The proportion calculation module compares the overall controllable value of each target region with the preset threshold value, and calculates the proportion of the number of target regions whose overall controllable value is not less than the preset threshold value and the proportion of the number of target regions whose overall controllable value is less than the preset threshold value; The first control module: if the proportion of the number of target regions whose overall controllable value is not less than the preset threshold value is greater than the proportion of the number of target regions whose overall controllable value is less than the preset threshold value, the negative pressure state control mode of the subsequent surgery is overall negative pressure control; The second control module: if the proportion of the number of target regions whose overall controllable value is less than the preset threshold value is greater than the proportion of the number of target regions whose overall controllable value is less than the preset threshold value, the negative pressure state control mode of the subsequent surgery is local negative pressure control.

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