A method for detecting the local ventilation control effect based on background schlieren

Abstract

A method for detecting the effect of local ventilation control based on background schlieren, which relates to the field of detecting the effect of airborne pollutant control. To solve the technical problem existing in the prior art that the existing patents related to background schlieren technology mainly focus on background schlieren optical imaging devices, quantitative flow field parameter algorithms, and pollution airflow intensity identification and control methods, lacking a solution for using background schlieren technology to detect the ventilation control effect, the technical solution provided by the present invention is: A method for selecting a local ventilation control area based on background schlieren, the method includes: steps of collecting a background image of the area to be detected on the target feature plane and collecting a real-time schlieren image; steps of converting the real-time schlieren image into a grayscale image; steps of setting the target plane control area in the ventilation system where the target feature plane is located according to the grayscale image. Calculating and evaluating the R A index module. It is suitable for application in the detection work of local ventilation control effect.

Description

Technical Field

[0001] It relates to the field of detection of the control effect of airborne pollutants, and specifically to the detection of the local ventilation control effect based on the background schlieren imaging technology. Background Art

[0002] In the fields of industrial processing and manufacturing, process operations are often accompanied by the emission of high-temperature polluted airflows, which contain particulate matter and toxic gases. Although local exhaust systems are usually used to control these pollutants, due to process conditions, airborne pollutants often escape during the actual operation of local exhaust systems. This leads to excessive pollutants in the entire plant environment, endangering the environment inside and outside the plant. Using on-site quantitative measurement techniques to evaluate the local ventilation control effect will help better control the environmental quality in the plant.

[0003] Currently, the smoke line method is often used to check and evaluate the control effect of exhaust hoods for local ventilation control. However, the smoke line method has two obvious drawbacks: 1. This method only uses low-temperature and low-momentum smoke lines to test the flow state at the control points of the exhaust hood, without considering the high temperature and strong emission of the emission source. Even if the smoke line method shows good control of the local exhaust hood, it cannot guarantee that there are no problems with the smoke flow state during actual process operations; 2. There is a lack of a quantitative standard for the actual capture effect of the local ventilation system. Most studies quantify the control effect of the local ventilation system through numerical simulation, but this method has numerical deviations. Therefore, there is an urgent need to invent a detection method for quantifying the control effect of on-site local ventilation systems.

[0004] The background schlieren imaging technology utilizes the principle that the refractive index gradient of light in the measured flow field is proportional to the air density, and transforms the change in density gradient in the flow field into the change in relative light intensity on the recording plane. The background schlieren imaging principle is the same as that of the schlieren imaging technology, and it is an optical measurement method with a relatively wide test space range. In recent years, related patents based on the background schlieren technology mainly focus on background schlieren optical imaging devices, quantitative flow field parameter algorithms (US202318375025, 2024; CN202310343644.X, 2023), and pollution airflow intensity identification and control methods (CN202011321450.2, 2020). There are few reports on patents or literature using the background schlieren technology to detect the ventilation control effect. Summary of the Invention

[0005] To solve the technical problem existing in the prior art that related patents of the existing background schlieren technology mainly focus on background schlieren optical imaging devices, quantitative flow field parameter algorithms, and pollution airflow intensity identification and control methods, and lack a solution for using the background schlieren technology to detect the ventilation control effect, the technical solution provided by the present invention is as follows:

[0006] A method for selecting a local ventilation control area based on background schlieren, the method comprising:

[0007] The steps of collecting the background image of the area to be detected on the target feature plane and collecting the real-time schlieren image;

[0008] The step of converting the real-time schlieren image into a grayscale image;

[0009] The step of setting the target plane control area in the ventilation system where the target feature plane is located according to the grayscale image.

[0010] Further, a preferred embodiment is provided, in which in the grayscale image, the gray level represents the pollutant concentration and the density gradient difference thereof.

[0011] Further, a preferred embodiment is provided, in which the target plane control area is located at the center position of the pollution source.

[0012] Further, a preferred embodiment is provided, in which the real-time schlieren image is collected under the action of the local ventilation air flow.

[0013] Based on the same inventive concept, the present invention further provides a device for selecting a local ventilation control area based on background schlieren, the device comprising:

[0014] A module for collecting the background image of the area to be detected on the target feature plane and collecting the real-time schlieren image under the action of the local ventilation air flow;

[0015] A module for converting the real-time schlieren image into a grayscale image;

[0016] A module for setting the target plane control area in the ventilation system where the target feature plane is located according to the grayscale image.

[0017] Based on the same inventive concept, the present invention further provides a method for detecting the local ventilation control effect based on background schlieren, including

[0018] The step of obtaining the target plane control area in the ventilation system where the target feature plane is located according to the method described above;

[0019] The step of calculating and evaluating the R A index of the plane control area.

[0020] Based on the same inventive concept, the present invention further provides a device for detecting the local ventilation control effect based on background schlieren, including:

[0021] A module for obtaining the target plane control area in the ventilation system where the target feature plane is located according to the device described above;

[0022] Calculating and evaluating the R of the plane control areaA Module of the indicator.

[0023] Based on the same inventive concept, the present invention also provides a computer storage medium for storing a computer program, and when the computer program is read by a computer, the computer executes the method described above.

[0024] Based on the same inventive concept, the present invention also provides a computer, including a processor and a storage medium, and when the processor reads the computer program stored in the storage medium, the computer executes the method described above.

[0025] Based on the same inventive concept, the present invention also provides a computer program product embedded with a computer program, and when the computer program is run, the method described above is implemented.

[0026] Compared with the prior art, the beneficial effects of the technical solution provided by the present invention are as follows:

[0027] A method for detecting the local ventilation control effect based on background schlieren provided by the present invention, a method for detecting the local ventilation control effect based on background schlieren technology, through tracer-free operation, real-time monitoring and quantitative evaluation, overcomes many deficiencies of the traditional method. Compared with the trunk line method and the numerical simulation method, this technology provides a more real, accurate and scientific means for evaluating the performance of the ventilation system, and provides strong technical support for environmental control in industrial sites.

[0028] A method for detecting the local ventilation control effect based on background schlieren provided by the present invention avoids the interference and pollution that may be brought by tracers in the traditional method and simplifies the operation process. The distribution and flow state of the polluted air flow in the ventilation control area during the entire process operation are obtained through background schlieren imaging technology. Compared with the smoke line method (relying on the visible smoke line of the tracer), the background schlieren technology can more truly reflect the state of the high-temperature polluted air flow and avoid the problem of uneven dispersion of the tracer.

[0029] A method for detecting the local ventilation control effect based on background schlieren provided by the present invention realizes the quantitative evaluation of the capture performance of the ventilation system and provides a scientific evaluation standard. The scoring index R is calculated through a formula A , and the grayscale image data is converted into a quantitative index. The value range of R A is [0, 1], and it is divided into four grades (excellent, good, medium, poor). The traditional method lacks a unified quantitative standard and relies on empirical judgment. Through the scoring index, the background schlieren technology can provide objective and reproducible evaluation results, which is helpful for the optimization and improvement of the ventilation system.

[0030] A method for detecting the local ventilation control effect based on background schlieren improves the real-time performance and accuracy of detection, and can timely discover and solve problems in the ventilation system. By using the background schlieren imaging technology, it can collect and process the images of polluted airflows during the operation of the ventilation system in real time, and calculate and update the scoring index R in real time. A . The smoke line method and numerical simulation methods usually cannot achieve real-time monitoring, and there are model deviations in numerical simulation. However, the background schlieren technology can reflect the actual working conditions in real time, avoiding these problems.

[0031] A method for detecting the local ventilation control effect based on background schlieren provided by the present invention provides a basis for the intelligent and energy-saving operation of the ventilation system, may reduce energy consumption, and improve system efficiency. Through the real-time monitoring and evaluation of the scoring index R A , the optimal operating parameters of the ventilation system are identified to achieve intelligent regulation. Traditional methods mainly rely on manual adjustment and are difficult to achieve intelligent control. The data support provided by the background schlieren technology makes intelligent control possible, which helps to optimize the operating efficiency of the ventilation system.

[0032] A method for detecting the local ventilation control effect based on background schlieren provided by the present invention is suitable for the detection work of local ventilation control effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a schematic installation diagram of the device for detecting the local ventilation control effect on the XOZ plane.

[0034] Figure 2 It is a flow chart of the post-processing algorithm for local ventilation control effect.

[0035] Figure 3 It is a schematic diagram of the spatial distribution of polluted airflows under the action of background schlieren in the local ventilation airflow, where a is when the air supply fan is closed and b is when the air supply fan is turned on.

[0036] Figure 4 It is the control area selection and corresponding pollution control score values, where a is the state when the air supply fan is closed and b is the state when the air supply fan is turned on. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] To make the advantages and beneficial effects of the technical solutions provided by the present invention more clearly manifested, the technical solutions provided by the present invention are further described in detail below with reference to the accompanying drawings. Specifically:

[0038] Embodiment 1. This embodiment provides a method for selecting a local ventilation control area based on background schlieren. The method includes:

[0039] Steps of collecting the background image of the area to be detected on the target feature plane and collecting the real-time schlieren image;

[0040] The step of converting the real-time schlieren image into a grayscale image;

[0041] According to the grayscale image, the step of setting the target plane control region in the ventilation system where the target feature plane is located.

[0042] Specifically,

[0043] Step 1: Collect the background image and the real-time schlieren image

[0044] Before the process production, collect the background image of the area to be detected on the feature plane, and collect the real-time schlieren image under the action of the local ventilation air flow.

[0045] Set up the test device, including a background board, a light source, and a camera. The background board and the light source are respectively placed on both sides of the area to be detected. The camera is on the same side as the light source and is connected to the data processing module.

[0046] Before the ventilation system is started, collect the background image of the area to be detected.

[0047] When the ventilation system is running, collect the schlieren image in real time to obtain the visualization pattern of the background schlieren flow field. This pattern area is called the ROI area.

[0048] Step 2: Convert to a grayscale image

[0049] Convert the background schlieren visualization flow field pattern into a grayscale value map.

[0050] Use an image processing algorithm to convert the real-time collected schlieren image into a grayscale image I, where the grayscale value I represents the pollutant concentration and its density gradient difference.

[0051] Step 3: Select the control region

[0052] Select the plane control region of the local ventilation system.

[0053] The control region is defined as the quadrilateral enclosed by the projection hood surface length of the exhaust hood and the projection length of the pollution source. The geometric centroid of this quadrilateral is located at the center position of the exhaust hood and the pollution source. In practical applications, the control region of the local ventilation system of an intermediate frequency furnace is called Area A.

[0054] Step 4: Calculate the scoring index

[0055] Calculate the average pollutant control effect scoring index R of the ventilation system A , calculate R A value.

[0056] Step 5: Evaluate the ventilation control effect

[0057] According to R AEvaluate the control effect of the local ventilation system.

[0058] R A The value range is [0, 1]. When the value of R A is close to 1, it indicates that the control effect of the ventilation system is excellent; when the value of R A is close to 0, it indicates that the control effect is poor.

[0059] According to the different values of R A the control effect of the ventilation system is divided into four levels: excellent ([0.8, 1]), good ([0.7, 0.8]), medium ([0.6, 0.7]), poor ([0, 0.6])

[0060] Embodiment 2: This embodiment further limits a method for selecting a local ventilation control area based on background schlieren provided in Embodiment 1. In the grayscale image, the gray level represents the pollutant concentration and the density gradient difference.

[0061] Embodiment 3: This embodiment further limits a method for selecting a local ventilation control area based on background schlieren provided in Embodiment 1. The target plane control area is located at the center position of the pollution source.

[0062] Embodiment 4: This embodiment further limits a method for selecting a local ventilation control area based on background schlieren provided in Embodiment 1. Collect real-time schlieren images under the action of the local ventilation air flow.

[0063] Embodiment 5: This embodiment provides a device for selecting a local ventilation control area based on background schlieren. The device includes:

[0064] A module for collecting the background image of the area to be detected on the target feature plane and collecting real-time schlieren images under the action of the local ventilation air flow;

[0065] A module for converting the real-time schlieren image into a grayscale image;

[0066] A module for setting the target plane control area in the ventilation system where the target feature plane is located according to the grayscale image.

[0067] Embodiment 6: This embodiment provides a method for detecting the control effect of local ventilation based on background schlieren, including

[0068] The step of obtaining the target plane control area in the ventilation system where the target feature plane is located according to the method provided in Embodiment 1;

[0069] The step of calculating and evaluating the R A index of the plane control area.

[0070] Embodiment Seven. This embodiment provides a device for detecting the local ventilation control effect based on background schlieren, including:

[0071] A module that, according to the device provided in Embodiment Five, obtains the plane control area of the target plane in the ventilation system where the target feature plane is located;

[0072] A module that calculates and evaluates the R A index of the said plane control area.

[0073] Embodiment Eight. This embodiment provides a computer storage medium for storing a computer program. When the computer program is read by a computer, the computer executes the method provided in Embodiment One.

[0074] Embodiment Nine. This embodiment provides a computer, including a processor and a storage medium. When the processor reads the computer program stored in the storage medium, the computer executes the method provided in Embodiment One.

[0075] Embodiment Ten. This embodiment provides a computer program product embedded with a computer program. When the computer program is run, it implements the method provided in Embodiment One.

[0076] Embodiment Eleven. Combining Figures 1-4 with this embodiment, this embodiment further describes the above-provided technical solutions in detail through specific examples. Specifically:

[0077] The technical solution provided in this embodiment solves the technical problem that the existing methods cannot monitor the local ventilation control effect in real time on site.

[0078] To solve the above technical problems, this embodiment adopts the following technical solutions to achieve:

[0079] A method for detecting the local ventilation control effect based on background schlieren technology, including:

[0080] Step 1: Collect the background image of the area to be detected on the feature plane 1 (such as XOZ) before the process production and the real-time schlieren image under the action of the local ventilation airflow, and obtain the background schlieren flow field visualization pattern on the XOZ plane. The entire schlieren pattern area is called the ROI area;

[0081] Step 2: Collect the flow field visualization patterns of the remaining feature planes (n = 2, 3, 4...), and repeat Step 1;

[0082] Step 3: Select the plane control area of the local ventilation system. The control area is a quadrilateral enclosed by the length of the projection hood surface of the exhaust hood and the length of the projection of the pollution source. The geometric centroid of the control area quadrilateral is located at the center position of the exhaust hood and the pollution source. The control area is called Area A;

[0083] Step 4: Convert the background schlieren visualization flow field pattern into a grayscale value image I with values ranging from 0 to 255. The higher the pollutant concentration and the greater the density gradient difference, the higher the grayscale value I. For a pure color background with no flow, the grayscale value I is the minimum value of the entire image.

[0084] Step 5: Calculate the scoring index R of the average pollutant control effect of the ventilation system at 0 - t moments (t > 15 min) through formula (1). A 。

[0085]

[0086] Wherein, n represents the number of characteristic planes photographed (n ≥ 1); t represents the time from when the schlieren camera starts to collect data to the end at t moments after the local ventilation system operates stably; S A and S ROI are the pixel areas of the images in the control area and the observation area; A is the control area of the local ventilation system; ROI is the area where the camera collects the schlieren pattern; I(x, y) is the grayscale value at the point (x, y) of the image; min(I(x, y)) is the minimum grayscale value of the entire image area, reducing the influence of the initial background grayscale. The numerical value range of R A is [0, 1].

[0087] When R A → 1, it indicates that the control effect of the local ventilation system on pollutants is better;

[0088] When R A → 0, it indicates that the control effect of the local ventilation system on pollutants is worse.

[0089] Among them, when the value of R A is in [0.8, 1], it indicates that the control effect of the local ventilation system is excellent; when the value of R A is in [0.7, 0.8], it indicates that the control effect of the local ventilation system is good; when the value of R A is in [0.6, 0.7], it indicates that the control effect of the local ventilation system is medium; when the value of R A is in [0, 0.6], it indicates that the control effect of the local ventilation system is poor.

[0090] This embodiment also discloses a background schlieren imaging system applied to an industrial site, which includes the following modules:

[0091] The background schlieren imaging module is used to collect schlieren images when the polluted air flow is emitted;

[0092] Specifically, the background schlieren imaging module includes a large background board and its support system, a light source, and a camera. The background board and the light source are respectively arranged on both sides of the area to be detected, the camera is arranged on the same side as the light source, and the camera is connected to the data processing module.

[0093] There is a speckle pattern on the large background board, and the size of the background board needs to cover the entire local exhaust observation area.

[0094] Combined with the attached Figures 1-4 ,

[0095] In this embodiment, taking the local ventilation system of the intermediate frequency furnace in the foundry workshop as an example, the control effect of the local ventilation system under different ventilation parameters is explored. The following details the method for identifying the intensity of polluted air flow based on background schlieren imaging in this embodiment, which specifically includes the following steps:

[0096] The test device uses a background schlieren imaging system applied in the industrial field. This system includes the following modules: a large background board and its support system, a light source, and a camera. The background board and the light source are respectively arranged on both sides of the area to be detected, the camera is arranged on the same side as the light source, and the camera is connected to the data processing module. There is a speckle pattern on the large background board, and the size of the background board needs to cover the entire local exhaust observation area, as Figure 1 shown.

[0097] Figure 2 The following is the step process for the test effect of the entire ventilation system, and the specific content is as follows:

[0098] Step 1: Collect the background image of the area to be detected on the feature plane before the process production and the real-time schlieren image under the action of the local ventilation air flow, and obtain the background schlieren flow field visualization pattern on the XOZ plane. The entire schlieren pattern area is called the ROI area ( Figure 2 , S1 - S3);

[0099] Step 2: In this embodiment, only one feature plane is collected, so there are no other plane situations and steps.

[0100] Step 3: Select the plane control area of the local ventilation system. The control area is a quadrilateral enclosed by the projection hood surface length of the exhaust hood and the projection length of the pollution source. The geometric centroid of the control area quadrilateral is located at the center position of the exhaust hood and the pollution source. The control area of the intermediate frequency furnace local ventilation system is called Area A ( Figure 2 , S4);

[0101] Step 4: Convert the background schlieren visualization flow field pattern into a grayscale value map I of 0 - 255. Among them, the higher the pollutant concentration and the greater the density gradient difference, the higher the grayscale value I; for a pure color background without flow, the grayscale value I is the minimum value of the entire image. The spatial distribution of the polluted air flow under the action of the background schlieren is asFigure 3 as shown

[0102] Step 5: Calculate the scoring index R of the average pollutant control effect of the local ventilation system of the intermediate frequency furnace through formula (1) A ( Figure 2 , S5 - S6). The calculated pollution control score value is classified. Among them, the performance scoring index R of the local ventilation system before renovation A is 0.541, belonging to the poor grade, as Figure 4 shown in a; the performance scoring index R of the local ventilation system after renovation A is 0.849, belonging to the excellent grade, as Figure 4 shown in b.

[0103] The above further describes the technical solutions provided by the present invention in several specific embodiments to highlight the advantages and beneficial effects of the technical solutions provided by the present invention. However, the above-mentioned several specific embodiments are not used as limitations to the present invention. Any reasonable modifications, improvements, combinations of implementation manners, equivalent replacements, etc. based on the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for selecting a local ventilation control area based on background schlieren, characterized in that: The method comprises: The steps of collecting a background image of the area to be detected on the target feature plane and collecting a real-time schlieren image; The step of converting the real-time schlieren image into a grayscale image; A step of setting a target plane control area in the ventilation system where the target feature plane is located according to the grayscale image; The real-time schlieren image is converted into a grayscale image as follows: Step 1, collecting the background image of the area to be detected on the feature plane XOZ before the process production and the real-time Schlieren image under the action of the local ventilation airflow, and obtaining the background Schlieren flow field visualization pattern of the XOZ plane, and the area where the background Schlieren flow field visualization pattern is located is called the ROI area; Step 2, repeating step 1 to collect background Schlieren flow field visualization patterns of other feature planes; Step 3, select the plane control area of ​​the local ventilation system. The plane control area is a quadrilateral formed by the projection length of the exhaust hood and the projection length of the pollution source. The geometric centroid of the quadrilateral is located at the center of the exhaust hood and the pollution source. The plane control area is called area A; Step 4: Convert the background Schlieren flow field visualization pattern into a grayscale numerical image of 0-255, where the higher the pollutant concentration is and the greater the density gradient difference is, the higher the grayscale value I is; if there is no flow in the pure color background, the grayscale value I is the minimum value of the entire image.

2. The method for selecting a local ventilation control area based on background schlieren according to claim 1, characterized in that: In the grayscale image, the grayscale represents the difference in pollutant concentration and its density gradient.

3. The method for selecting a local ventilation control area based on background schlieren according to claim 1, characterized in that: The target plane control area is located at the center of the pollution source.

4. The method for selecting a local ventilation control area based on background schlieren according to claim 1, characterized in that: Real-time Schlieren images are collected under the action of local ventilation airflow.

5. A device for selecting a local ventilation control area based on background schlieren, characterized in that: The device comprises: A module for collecting background images of the area to be detected on the target feature plane and collecting real-time schlieren images under the action of local ventilation airflow; A module for converting the real-time schlieren image into a grayscale image; According to the grayscale image, a module of a target plane control area in the ventilation system where the target feature plane is located is set; The real-time schlieren image is converted into a grayscale image as follows: Step 1, collecting the background image of the area to be detected on the feature plane XOZ before the process production and the real-time Schlieren image under the action of the local ventilation airflow, and obtaining the background Schlieren flow field visualization pattern of the XOZ plane, and the area where the background Schlieren flow field visualization pattern is located is called the ROI area; Step 2, repeating step 1 to collect background Schlieren flow field visualization patterns of other feature planes; Step 3, select the plane control area of ​​the local ventilation system. The plane control area is a quadrilateral formed by the projection length of the exhaust hood and the projection length of the pollution source. The geometric centroid of the quadrilateral is located at the center of the exhaust hood and the pollution source. The plane control area is called area A; Step 4: Convert the background Schlieren flow field visualization pattern into a grayscale numerical image of 0-255, where the higher the pollutant concentration is and the greater the density gradient difference is, the higher the grayscale value I is; if there is no flow in the pure color background, the grayscale value I is the minimum value of the entire image.

6. A method for detecting the effect of local ventilation control based on background schlieren, characterized in that: include The method according to claim 1, comprising the step of obtaining a target plane control area in the ventilation system where the target characteristic plane is located; Calculate and evaluate the R of the plane control area A Steps of indicators; The scoring index R of the average pollutant control effect of the ventilation system at time 0-t, t>15min, is calculated by the following formula: A : Where n represents the number of feature planes captured, n≥1; t represents the time from when the local ventilation system starts to run stably, when the schlieren camera starts to collect data, to when t ends; S A and S ROI is the pixel area of ​​the control area and the observation area; A is the control area of ​​the local ventilation system; ROI is the camera acquisition schlieren pattern area; I(x, y) is the gray value at the image point (x, y); min(I(x, y)) is the minimum gray value of the entire image area, R A The value range of is [0, 1]; When R A When it tends to 1, it indicates that the control effect of the local ventilation system of pollutants is better; When R A When it tends to 0, it indicates that the control effect of the local ventilation system of pollutants is worse; Among them, when R A When the value is (0.8, 1], it indicates that the local ventilation system has excellent control effect; when R A When the value is [0.7, 0.8], it indicates that the local ventilation system has a good control effect; when R A When the value is in [0.6, 0.7), it indicates that the local ventilation system has a moderate control effect; when R A When the value is [0, 0.6), it indicates that the local ventilation system has poor control effect.

7. A local ventilation control effect detection device based on background schlieren, characterized in that: include: According to the device of claim 5, a module of a target plane control area in a ventilation system where a target characteristic plane is located is obtained; Calculate and evaluate the R of the plane control area A Modules of indicators; Specifically, The scoring index R of the average pollutant control effect of the ventilation system at time 0-t, t>15min, is calculated by the following formula: A : Where n represents the number of feature planes captured, n≥1; t represents the time from when the local ventilation system starts to run stably, when the schlieren camera starts to collect data, to when t ends; S A and S ROI is the pixel area of ​​the control area and the observation area; A is the control area of ​​the local ventilation system; ROI is the camera acquisition schlieren pattern area; I(x, y) is the gray value at the image point (x, y); min(I(x, y)) is the minimum gray value of the entire image area, R A The value range of is [0, 1]; When R A When it tends to 1, it indicates that the control effect of the local ventilation system of pollutants is better; When R A When it tends to 0, it indicates that the control effect of the local ventilation system of pollutants is worse; Among them, when R A When the value is (0.8, 1], it indicates that the local ventilation system has excellent control effect; when R A When the value is [0.7, 0.8], it indicates that the local ventilation system has a good control effect; when R A When the value is in [0.6, 0.7), it indicates that the local ventilation system has a moderate control effect; when R A When the value is [0, 0.6), it indicates that the local ventilation system has poor control effect.

8. A computer storage medium for storing a computer program, characterized in that: When the computer program is read by a computer, the computer executes the method of claim 1 .

9. A computer, comprising a processor and a storage medium, characterized in that: When the processor reads the computer program stored in the storage medium, the computer executes the method of claim 1 .

10. A computer program product, embedded with a computer program, characterized in that When the computer program is executed by a computer, the method according to claim 1 is implemented.

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