Method for identifying and quantifying VOC gas cloud imaging by using total hydrocarbon FID module

Abstract

The invention discloses a method for identifying and quantifying VOC gas cloud imaging by using a total hydrocarbon FID module, and belongs to the field of VOC leakage monitoring. According to the method, through obtaining an imaging corresponding relation table, constructing a total hydrocarbon real-time data network, determining a covered FID module set and obtaining a background image, when VOC leakage is monitored, historical and real-time data of FID modules are utilized to calculate background concentration, concentration increment and gray scale increment, and a concentration value corresponding to unit gray scale is obtained. And calculating the total hydrocarbon distribution concentration of the leaked gas mass, rendering diffusion distribution in combination with a twin model, and marking a high-concentration point location. According to the method, quantitative identification and distribution presentation of the total hydrocarbon of the VOC leakage gas mass are realized, and effective data support is provided for pollution abatement and economic loss evaluation.

Description

Technical Field

[0001] The present invention belongs to the technical field of VOC leakage monitoring and relates to a method for identifying and quantifying VOC gas cloud imaging by utilizing a total hydrocarbon FID module. Background Art

[0002] Hydrocarbons are the precursors of photochemical smog and the main components of VOCs. VOC leakage and emissions in the production of petroleum, petrochemical and other chemical companies not only cause a series of environmental pollution such as photochemical smog, but also bring huge economic losses to the companies.

[0003] VOC cloud imaging analysis, based on medium-wave infrared absorption technology, has gained widespread application in orbital mode due to its ability to provide infrared imaging of VOC leaks from production facilities. To expand the application of VOC cloud imaging to total hydrocarbons, a method is needed to integrate VOC cloud imaging with existing total hydrocarbon FID monitoring systems in chemical companies to quantitatively identify total hydrocarbon leaks, thereby addressing photochemical pollution and assessing economic losses to companies. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for identifying and quantifying VOC gas cloud imaging using a total hydrocarbon FID module. The specific technical solution is as follows.

[0005] The method for identifying and quantifying VOC gas cloud imaging using a total hydrocarbon FID module includes the following steps: S1: Construct a real-time monitoring network for total hydrocarbon FID in the monitoring area; S2: Obtain the corresponding relationship table T(d) of the VOC gas cloud imaging system’s imaging object size, distance, and image pixels; S3: Determine the total hydrocarbon FID module set F covered by the current VOC gas cloud imaging scan; S4: Timed scanning of each module in the set F to obtain the background infrared image B(f); S5: When VOC leakage is detected: S5-1: Query the historical hourly data D(f,h) and real-time data D(f,r) of each module in the set F; S5-2: Calculate the total hydrocarbon background concentration d; S5-3: Identify the FID module with the maximum concentration increment d(p), capture its infrared image and compare it with B(f) to obtain the grayscale increment d(g); S5-4: Calculate the concentration-grayscale conversion factor Si = d(p) / d(g); S5-5: Generate a total hydrocarbon concentration distribution map of the leaking air mass based on the formula F(d,i) = G(d,i) × Si - d; where F(d,i) represents the total hydrocarbon concentration at each pixel of the VOC leaking air mass, and G(d,i) represents the grayscale value of each pixel in the infrared image of the VOC leaking air mass; S6: Combine the digital twin model to render the leakage diffusion distribution and mark the high concentration points.

[0006] Furthermore, the total hydrocarbon FID monitoring network in step S1 includes: Portable total hydrocarbon FID modules distributed at monitoring points, with unique codes and three-dimensional coordinates; FID data server, which receives real-time data through the communication network and stores it in the database; Data interaction interface, supporting basic information query and data query functions.

[0007] Furthermore, the method for determining the set F in step S3 is: A circular area with a scanning radius R and a VOC gas cloud imaging latitude and longitude as the center was constructed using ArcGIS; Call the Intersects function to obtain all total hydrocarbon FID modules in the area.

[0008] Furthermore, the grayscale increment d(g) in step S5-3 is calculated as follows: Control the VOC gas cloud imaging gimbal to aim at the target FID module to capture infrared images; Compare the grayscale value difference between the leakage image and the background image B(f) pixel by pixel.

[0009] Furthermore, the concentration distribution map rendering method in step S5-5 is: Use a color caliper to perform color mapping of F(d,i); Generate gridded diffusion distribution maps in digital twin models.

[0010] Furthermore, the background concentration d in step S5-2 is calculated by taking the arithmetic mean of the historical hourly data D(f,h).

[0011] A system for implementing the above method, comprising: VOC gas cloud imaging analyzer, including infrared camera and pan-tilt control system; Total hydrocarbon FID monitoring module network; FID data server, including data receiving module and interactive interface; Digital twin model platform.

[0012] Furthermore, the interactive interface of the FID data server supports: Total hydrocarbon FID basic information query: returns module code, coordinates and status; Total hydrocarbon FID data query: returns real-time / historical concentration data.

[0013] A computer-readable storage medium stores a computer program, which implements the steps of the above method when executed.

[0014] A computer program product, which implements the steps of the above method when the program is executed.

[0015] The present invention has the following beneficial technical effects: through a series of operations such as building a data network, obtaining background information, real-time monitoring and calculation, and rendering distribution, it realizes the quantitative identification and diffusion distribution presentation of the total carbon and hydrogen in VOC leakage air masses, providing comprehensive data support for pollution control and economic loss assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is the total hydrocarbon FID monitoring network architecture diagram; Figure 2 This is the flow chart of VOC gas cloud imaging and FID module spatial matching; Figure 3 This is a rendering of the leak in the digital twin model after a certain monitoring session. DETAILED DESCRIPTION

[0017] The following is a clear and complete description of the technical solution of the present invention in conjunction with the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0018] A method for identifying and quantifying VOC gas cloud imaging using a total hydrocarbon FID module includes the following steps: Step 1: Build a real-time total hydrocarbon data network based on the existing total hydrocarbon FID monitoring system in the monitoring area, as shown in Figure 1. This network consists of terminal devices and an FID data server. The terminal devices contain several total hydrocarbon FID monitoring modules, including portable ones, distributed across various monitoring points within the monitoring area. Each total hydrocarbon FID monitoring module has a unique code and longitude, latitude, and altitude information. Each total hydrocarbon FID monitoring module transmits data to the data receiving module of the FID data server via the 5G network. After receiving the real-time monitoring data from the total hydrocarbon FID monitoring modules, the FID data server's data receiving module automatically formats the data based on the point number information and stores it in a database. The FID data server also provides a data interaction interface that supports data requests and returns. This interface includes functions for querying basic total hydrocarbon FID information and total hydrocarbon FID data.

[0019] Step 2: Obtain a table T(d) of correspondences between the object size, distance, and image pixels for the VOC gas cloud imaging system. This table is established by imaging standard objects of known size at different distances, recording the correspondences between the object size, distance, and image pixels. This table clearly defines the relationship between the actual object size, distance, and image pixels in the imaging system.

[0020] Step 3: Get the total hydrocarbon FID module set F covered by the current VOC gas cloud imaging scan, as follows Figure 2 The VOC cloud imaging analysis accesses the data interaction interface on the FID server to query the basic total hydrocarbon FID information. Based on the input VOC cloud imaging latitude and longitude information and the scanning radius R, ArcGIS is used to construct a circular scanning area. The Intersects function in the ArcGIS library is used to obtain all total hydrocarbon FID modules within the area currently covered by the VOC cloud imaging analyzer, which is recorded as the set F.

[0021] Step 4: VOC Cloud Imaging. In practice, each total hydrocarbon FID module in the alignment set F is periodically scanned to acquire an infrared image, recorded as background image B(f). The timing period can be set according to actual needs to ensure that the background image accurately reflects the normal state when there is no VOC leakage.

[0022] Step 5: When the VOC gas cloud imaging real-time scan detects several VOC gas leaks in the device, follow the steps below: 5-1: Access the Total Hydrocarbon FID data query function in the data interaction interface shown in Figure 1 to obtain the historical hourly data D (f,h) and real-time monitoring data D (f,r) corresponding to each Total Hydrocarbon FID module in set F. The historical hourly data D (f,h) is the monitoring data for the past 24 hours.

[0023] 5-2: Calculate the mean of D (f,h) by adding up all historical hourly data and dividing by the number of data to obtain the background concentration d of total hydrocarbons in the current monitoring area.

[0024] 5-3: As VOC leaks continue, the real-time concentration of the total hydrocarbon FID module within the current monitoring area will gradually increase due to the diffusion of the leaked gas. The monitoring increments for each total hydrocarbon FID module are calculated, and the total hydrocarbon FID module with the maximum concentration increment d(p) is found. The VOC gas cloud imaging analyzer pan / tilt is then controlled to rotate and align with this total hydrocarbon FID module. An infrared image is captured and grayscale comparison is performed with the background image B(f). Grayscale comparison is performed by calculating the grayscale difference between the corresponding pixels in the infrared image and the background image B(f) to calculate the grayscale increment d(g).

[0025] 5-4: Calculate the ratio Si of d (p) to d (g), which represents the total hydrocarbon concentration value corresponding to the unit grayscale of the infrared image.

[0026] 5-5: Obtain an infrared image of the VOC leak plume, calculate the total hydrocarbon distribution concentration of the VOC leak plume using the following formula, and render a chromatographic diffusion map: F (d,i) = G (d,i) × Si - d. Here, F (d,i) represents the total hydrocarbon concentration at each pixel of the VOC leak plume; G (d,i) represents the grayscale value of each pixel in the infrared image of the VOC leak plume; and d represents the total hydrocarbon background concentration.

[0027] Step 6: Use a color caliper to render F (d,i). Different total hydrocarbon concentrations correspond to different colors, forming total hydrocarbon leakage diffusion distribution data and combining it with the twin model for grid rendering. The size of the grid can be adjusted according to the monitoring accuracy requirements. Finally, high-concentration points are marked in the twin model. Figure 3 shows a VOC gas cloud imaging track inspection mode. The total hydrocarbon FID model is used to quantitatively identify the monitoring results of the VOC gas cloud imaging analyzer, and the twin model is combined to render the total hydrocarbon leakage effect diagram.

[0028] Although the embodiments of the present invention have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention without departing from the principles and intent of the present invention. The scope of protection of the present invention is defined by the claims and their equivalents.

Claims

1. A method for identifying and quantifying VOC gas cloud imaging using a total hydrocarbon FID module, characterized in that: The following steps are involved: S1: Construct a real-time monitoring network for total hydrocarbon FID in the monitoring area; S2: Obtain the corresponding relationship table T(d) of the VOC gas cloud imaging system’s imaging object size, distance, and image pixels; S3: Determine the total hydrocarbon FID module set F covered by the current VOC gas cloud imaging scan; S4: Timed scanning of each module in the set F to obtain the background infrared image B(f); S5: When VOC leakage is detected: S5-1: Query the historical hourly data D(f,h) and real-time data D(f,r) of each module in the set F; S5-2: Calculate the total hydrocarbon background concentration d; S5-3: Identify the FID module with the maximum concentration increment d(p), capture its infrared image and compare it with B(f) to obtain the grayscale increment d(g); S5-4: Calculate the concentration-grayscale conversion factor Si = d(p) / d(g); S5-5: Generate a total hydrocarbon concentration distribution map of the leaking air mass based on the formula F(d,i) = G(d,i) × Si - d; where F(d,i) represents the total hydrocarbon concentration at each pixel of the VOC leaking air mass, and G(d,i) represents the grayscale value of each pixel in the infrared image of the VOC leaking air mass; S6: Combine the digital twin model to render the leakage diffusion distribution and mark the high concentration points.

2. The method according to claim 1, wherein The total hydrocarbon FID monitoring network in step S1 includes: Portable total hydrocarbon FID modules distributed at monitoring points, with unique codes and three-dimensional coordinates; FID data server, which receives real-time data through the communication network and stores it in the database; Data interaction interface, supporting basic information query and data query functions.

3. The method according to claim 1, wherein The method for determining the set F in step S3 is: A circular area with a scanning radius R and a VOC gas cloud imaging latitude and longitude as the center was constructed using ArcGIS; Call the Intersects function to obtain all total hydrocarbon FID modules in the area.

4. The method according to claim 1, wherein The grayscale increment d(g) in step S5-3 is calculated as follows: Control the VOC gas cloud imaging gimbal to aim at the target FID module to capture infrared images; Compare the grayscale value difference between the leakage image and the background image B(f) pixel by pixel.

5. The method according to claim 1, wherein The concentration distribution map rendering method in step S5-5 is: Use a color caliper to perform color mapping of F(d,i); Generate gridded diffusion distribution maps in digital twin models.

6. The method according to claim 1, wherein The background concentration d in step S5-2 is calculated by taking the arithmetic mean of the historical hourly data D(f,h).

7. A system for implementing the method according to any one of claims 1 to 6, characterized in that: include: VOC gas cloud imaging analyzer, including infrared camera and pan-tilt control system; Total hydrocarbon FID monitoring module network; FID data server, including data receiving module and interactive interface; Digital twin model platform.

8. The system according to claim 7, wherein: The interactive interface of the FID data server supports: Total hydrocarbon FID basic information query: returns module code, coordinates and status; Total hydrocarbon FID data query: returns real-time / historical concentration data.

9. A computer-readable storage medium storing a computer program, characterized in that: When the program is executed, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that When the program is executed, the steps of the method according to any one of claims 1 to 6 are implemented.

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