Combustible toxic gas monitoring and early warning method and system, terminal and storage medium
By building digital models and using neural networks to identify abnormalities, the problem of large amount of monitoring and calculation of combustible and toxic gases in metallurgical production is solved, and efficient monitoring and early warning is achieved.
Patent Information
- Application Number
- CN202411478784.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-22
- Publication Date
- 2025-03-14
AI Technical Summary
During the metallurgical production process, it is difficult for the existing technology to effectively monitor and early warning of abnormal situations of combustible and toxic gases, and the calculation volume is large and the calculation ability of the regulatory system is high.
By building an equal-scale digital model, sensor identification is generated, and the pre-trained neural network model is used to identify the display interface image, automatically identify the exception type, and send early warning information.
The intuitive display of abnormal gas concentration is realized, which reduces the calculation amount and improves monitoring efficiency without considering the structured relationship between sensors.
Smart Images
Figure CN119625933A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of metallurgical monitoring, and in particular relates to a combustible and toxic gas monitoring and early warning method, system, terminal and storage medium. Background Art
[0002] In the process of metallurgical production, a large amount of flammable and toxic gases are generated, such as coal gas, hydrogen, hydrogen sulfide, etc. There are flammable and toxic gas hazard sources in different areas of metallurgical enterprises, and flammable and toxic gas alarm devices need to be installed. At present, the number of flammable and toxic gas alarms installed in metallurgical enterprises is large, wide-ranging and scattered.
[0003] The amount of calculation required to sort out the production line locations corresponding to each sensor and to identify the factors that lead to abnormal combustible and toxic gases based on the relationship between sensors is too large. Once the relationship between sensors is established, the subsequent addition and deletion of sensors requires the update of structured data, which places high demands on the computing power of the supervision system. Summary of the invention
[0004] In view of the above-mentioned deficiencies in the prior art, the present invention provides a combustible and toxic gas monitoring and early warning method, system, terminal and storage medium to solve the above-mentioned technical problems.
[0005] In a first aspect, the present invention provides a combustible and toxic gas monitoring and early warning method, comprising: Constructing a scaled digital model for the production line of the factory in advance, and generating sensor marks at corresponding positions of the digital model; Acquiring the concentration of the combustible and toxic gas detected by the sensor, and if the concentration exceeds a preset concentration threshold, setting the corresponding sensor identifier in the digital model to a warning color; Along the upstream and downstream relationship of the sensor identifiers in the digital model, a local area of the model between adjacent sensor identifiers set to a warning color is set to a warning color; Collecting a display interface image where the digital model is located, and using a pre-trained neural network model to identify the display interface image to obtain an abnormality type; Based on the pre-set correspondence between the abnormality type and the warning terminal, the warning information is sent to the corresponding warning terminal.
[0006] In an optional implementation, a proportional digital model is constructed in advance for the production line of the plant, and sensor identifiers are generated at corresponding positions of the digital model, including: Use modeling software to build a proportional two-dimensional model of the factory production line to obtain a digital model; Based on the actual deployment location of the sensor on the production line, a sensor identifier is generated at the corresponding location of the digital model, and a mapping relationship between the sensor identifier and the sensor address is established; A display window is created for the digital model.
[0007] In an optional embodiment, obtaining the concentration of the combustible and toxic gas detected by the sensor, and setting the corresponding sensor identifier in the digital model to a warning color if the concentration exceeds a preset concentration threshold, includes: Create multiple threads to concurrently process the concentration detected by the sensor; If the concentration detected by the sensor reaches the concentration threshold, the corresponding address is obtained; Based on the mapping relationship and the address, the corresponding sensor identification is set as a warning color, and the warning color is a highlight color.
[0008] In an optional implementation, along the upstream and downstream relationship of the sensor identifiers in the digital model, setting the local area of the model between adjacent sensor identifiers set to the warning color to the warning color includes: Get the display color of the adjacent upstream sensor mark of the sensor mark set to the warning color; If the display color of the adjacent upstream sensor mark is a warning color, the local area of the model between the two sensor marks is set to the warning color.
[0009] In an optional implementation, the display interface image where the digital model is located is collected, and the display interface image is identified using a pre-trained neural network model to obtain the abnormality type, including: Confirm that the display color of the digital model is updated and use the screenshot command to regularly obtain images of the display interface; The image is input into a pre-trained neural network model to obtain the abnormality type.
[0010] In a second aspect, the present invention provides a combustible and toxic gas monitoring and early warning system, comprising: A model building module, used to build a proportional digital model for the production line of the factory in advance, and generate sensor identification at the corresponding position of the digital model; An identification setting module, used for obtaining the concentration of the combustible and toxic gas detected by the sensor, and setting the corresponding sensor identification in the digital model to a warning color if the concentration exceeds a preset concentration threshold; A model setting module, used for setting a local area of the model between adjacent sensor identifiers set to a warning color as a warning color along the upstream and downstream relationship of the sensor identifiers in the digital model; An image recognition module is used to collect the display interface image where the digital model is located, and use a pre-trained neural network model to recognize the display interface image to obtain an abnormality type; The warning processing module is used to send warning information to the corresponding warning terminal based on the preset correspondence between the abnormal type and the warning terminal.
[0011] In an optional embodiment, the model building module includes: A two-dimensional modeling unit is used to construct a proportional two-dimensional model of the plant production line using modeling software to obtain a digital model; An identification generating unit, used to generate a sensor identification at a corresponding position of the digital model based on the actual deployment position of the sensor on the production line, and to establish a mapping relationship between the sensor identification and the sensor address; A window creation unit is used to create a display window for the digital model.
[0012] In an optional implementation, the identification setting module includes: A concurrent processing unit, used to create multiple threads to concurrently process the concentration detected by the sensor; An address acquisition unit, configured to acquire a corresponding address if the concentration detected by the sensor reaches the concentration threshold; The color setting unit is used to set the corresponding sensor identification as a warning color based on the mapping relationship and the address, and the warning color is a highlight color.
[0013] In a third aspect, a terminal is provided, including: processor, memory, wherein: The memory is used to store computer programs. The processor is used to call and run the computer program from the memory, so that the terminal executes the above-mentioned terminal method.
[0014] According to a fourth aspect, a computer storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed on a computer, the computer executes the methods described in the above aspects.
[0015] The beneficial effect of the present invention is that the flammable and toxic gas monitoring and early warning method, system, terminal and storage medium provided by the present invention realize intuitive display of abnormal gas concentration by constructing a model, and use image recognition technology to identify the display interface, and can directly obtain the abnormal type without considering the structured relationship between sensors. The present invention reduces the amount of calculation and improves the monitoring efficiency.
[0016] In addition, the invention has a reliable design principle, a simple structure and a very broad application prospect. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0018] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention.
[0019] Figure 2 is a schematic block diagram of a system according to an embodiment of the present invention.
[0020] Figure 3 A schematic diagram of the structure of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0021] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments 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 creative work should fall within the scope of protection of the present invention.
[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.
[0023] The combustible and toxic gas monitoring and early warning method provided in the embodiment of the present invention is executed by a computer device, and accordingly, the combustible and toxic gas monitoring and early warning system runs in the computer device.
[0024] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention. Figure 1 The execution subject may be a combustible and toxic gas monitoring and early warning system. According to different requirements, the order of the steps in the flow chart may be changed, and some may be omitted.
[0025] like Figure 1 As shown, the method includes: Step 110, constructing a proportional digital model for the production line of the factory in advance, and generating sensor identifiers at corresponding positions of the digital model; Step 120, obtaining the concentration of the combustible and toxic gas detected by the sensor, and if the concentration exceeds a preset concentration threshold, setting the corresponding sensor identifier in the digital model to a warning color; Step 130, along the upstream and downstream relationship of the sensor identifiers in the digital model, setting the local area of the model between adjacent sensor identifiers set to a warning color as a warning color; Step 140, collecting the display interface image where the digital model is located, using the pre-trained neural network model to identify the display interface image, and obtaining the abnormality type; Step 150: Send warning information to the corresponding warning terminal based on the preset correspondence between the abnormality type and the warning terminal.
[0026] To facilitate understanding of the present invention, the combustible and toxic gas monitoring and early warning method provided by the present invention is further described below based on the principle of the combustible and toxic gas monitoring and early warning method of the present invention and in combination with the process of monitoring and early warning of combustible and toxic gases in the embodiment.
[0027] Specifically, the flammable and toxic gas monitoring and early warning methods include: S1. Construct a proportional digital model for the production line of the factory in advance, and generate sensor identifiers at corresponding positions of the digital model.
[0028] A proportional two-dimensional model is constructed for the production line of the factory area using modeling software to obtain a digital model; based on the actual deployment position of the sensor on the production line, a sensor identifier is generated at the corresponding position of the digital model, and a mapping relationship between the sensor identifier and the sensor address is established; and a display window is created for the digital model.
[0029] Specifically, advanced CAD is used to perform high-precision three-dimensional modeling of the factory production line, rather than just two-dimensional, to more intuitively reflect the production line layout and spatial relationships. During the construction process, the model size is ensured to be strictly proportional to the actual production line to ensure the accuracy of subsequent analysis. Subsequently, based on the actual installation position and angle of the sensor on the production line, the sensor identification is accurately generated at the corresponding position of the digital model, and a two-way mapping relationship between each sensor identification and its unique address is established. This not only facilitates tracking, but also ensures the accuracy of subsequent data processing. At the same time, a user-friendly display window is designed for the digital model for real-time monitoring and interaction.
[0030] S2. Acquire the concentration of the combustible and toxic gas detected by the sensor. If the concentration exceeds a preset concentration threshold, set the corresponding sensor mark in the digital model to a warning color.
[0031] Create multiple threads to concurrently process the concentration detected by the sensor; if the concentration detected by the sensor reaches the concentration threshold, obtain the corresponding address; based on the mapping relationship and the address, set the corresponding sensor identifier to a warning color, and the warning color is a highlight color.
[0032] Specifically, an efficient multi-threaded concurrent processing system is implemented to continuously monitor the concentration data of combustible and toxic gases uploaded by each sensor. Once the concentration data of a sensor is detected to exceed the preset safety threshold, the early warning mechanism is triggered immediately. The corresponding sensor logo in the digital model is quickly located through the mapping relationship, and its color is changed to a striking warning color (such as red highlight) to intuitively display the dangerous area. In addition, the system should also record detailed information such as the time and magnitude of the excess to provide data support for subsequent analysis.
[0033] S3. Along the upstream and downstream relationship of the sensor identifiers in the digital model, a local area of the model between adjacent sensor identifiers that are set to a warning color is set to a warning color.
[0034] The display color of the adjacent upstream sensor identifier of the sensor identifier set to the warning color is obtained; if the display color of the adjacent upstream sensor identifier is the warning color, the local area of the model between the two sensor identifiers is set to the warning color.
[0035] Specifically, in order to more comprehensively assess potential risks, the system needs to automatically analyze the upstream and downstream relationships between sensor markers. For sensor markers that have been set to warning colors, the system will further check their adjacent upstream and downstream sensor markers. If the display color of the adjacent upstream or downstream sensor marker is also a warning color, it indicates that the risk may have spread along the production line. At this time, the system will automatically set the local model area between these sensor markers to the warning color as well, forming a continuous risk area display, providing managers with an intuitive risk spread path.
[0036] S4. Collect the display interface image where the digital model is located, and use the pre-trained neural network model to identify the display interface image to obtain the abnormality type.
[0037] Confirm that the display color of the digital model has been updated, and use the screenshot command to regularly obtain images of the display interface. In order to improve the processing efficiency of the neural network model, the non-warning color part can be hidden by setting the brightness and contrast of the image. The processed image is input into the pre-trained neural network model to obtain the abnormal type.
[0038] Since multiple images may be captured during the color update process of the digital model, multiple corresponding abnormal types can be obtained, and the abnormal type with the most repetitions is output as the final recognition result.
[0039] Specifically, to ensure the accuracy and timeliness of early warning information, the system introduces deep learning technology and uses a pre-trained neural network model to intelligently identify the display interface image of the digital model. Whenever a display color update is detected, the system will regularly capture the display interface image through a screenshot command and input it into the neural network model for processing. Since multiple images may be generated during the color update process, the system will identify each image and count the recognition results. Finally, the abnormal type that appears the most times will be output as the final recognition result to ensure the accuracy and reliability of the early warning information.
[0040] Since the number of abnormal types is small, the neural network model can converge quickly during training. The construction and training of the neural network model are both existing technologies and will not be described in detail.
[0041] S5. Based on the preset correspondence between the abnormality type and the warning terminal, send warning information to the corresponding warning terminal.
[0042] Specifically, according to the pre-set correspondence between the abnormal type and the early warning terminal, the system will automatically match and generate the corresponding early warning information. These early warning information not only includes key information such as abnormal type, location, time, etc., but may also include risk spread trend analysis, recommended response measures, etc. Subsequently, the system will send the early warning information to the relevant responsible person or early warning terminal through the preset communication channels (such as SMS, email, APP push, etc.) to ensure the timely communication and effective response of the early warning information.
[0043] In some embodiments, the combustible and toxic gas monitoring and early warning system may include a plurality of functional modules composed of computer program segments. The computer programs of the various program segments in the combustible and toxic gas monitoring and early warning system may be stored in the memory of a computer device and executed by at least one processor to execute (see Figure 1 Description) The function of monitoring and early warning of combustible and toxic gases.
[0044] In this embodiment, the combustible and toxic gas monitoring and early warning system can be divided into multiple functional modules according to the functions it performs, such as Figure 2 As shown. The functional modules of the system 200 may include: a model building module 210, an identification setting module 220, a model setting module 230, an image recognition module 240 and an early warning processing module 250. The module referred to in the present invention refers to a series of computer program segments that can be executed by at least one processor and can complete fixed functions, which are stored in a memory. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.
[0045] A model building module, used to build a proportional digital model for the production line of the factory in advance, and generate sensor identification at the corresponding position of the digital model; An identification setting module, used for obtaining the concentration of the combustible and toxic gas detected by the sensor, and setting the corresponding sensor identification in the digital model to a warning color if the concentration exceeds a preset concentration threshold; A model setting module, used for setting a local area of the model between adjacent sensor identifiers set to a warning color as a warning color along the upstream and downstream relationship of the sensor identifiers in the digital model; An image recognition module is used to collect the display interface image where the digital model is located, and use a pre-trained neural network model to recognize the display interface image to obtain an abnormality type; The warning processing module is used to send warning information to the corresponding warning terminal based on the preset correspondence between the abnormal type and the warning terminal.
[0046] Optionally, as an embodiment of the present invention, the model building module includes: A two-dimensional modeling unit is used to construct a proportional two-dimensional model of the plant production line using modeling software to obtain a digital model; An identification generating unit, used to generate a sensor identification at a corresponding position of the digital model based on the actual deployment position of the sensor on the production line, and to establish a mapping relationship between the sensor identification and the sensor address; A window creation unit is used to create a display window for the digital model.
[0047] Optionally, as an embodiment of the present invention, the identification setting module includes: A concurrent processing unit, used to create multiple threads to concurrently process the concentration detected by the sensor; An address acquisition unit, configured to acquire a corresponding address if the concentration detected by the sensor reaches the concentration threshold; The color setting unit is used to set the corresponding sensor identification as a warning color based on the mapping relationship and the address, and the warning color is a highlight color.
[0048] Figure 3 A schematic diagram of the structure of a terminal 300 provided in an embodiment of the present invention. The terminal 300 can be used to execute the combustible and toxic gas monitoring and early warning method provided in an embodiment of the present invention.
[0049] The terminal 300 may include: a processor 310, a memory 320 and a communication unit 330. These components communicate via one or more buses. Those skilled in the art will appreciate that the server structure shown in the figure does not limit the present invention, and it may be a bus structure or a star structure, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.
[0050] The memory 320 can be used to store the execution instructions of the processor 310, and the memory 320 can be implemented by any type of volatile or non-volatile storage terminal or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. When the execution instructions in the memory 320 are executed by the processor 310, the terminal 300 can perform some or all of the steps in the following method embodiments.
[0051] The processor 310 is the control center of the storage terminal, and uses various interfaces and lines to connect various parts of the entire electronic terminal. It runs or executes software programs and / or modules stored in the memory 320, and calls data stored in the memory to perform various functions of the electronic terminal and / or process data. The processor can be composed of an integrated circuit (IC), for example, it can be composed of a single packaged IC, or it can be composed of multiple packaged ICs with the same or different functions. For example, the processor 310 can only include a central processing unit (CPU). In the embodiment of the present invention, the CPU can be a single computing core or multiple computing cores.
[0052] The communication unit 330 is used to establish a communication channel so that the storage terminal can communicate with other terminals, receive user data sent by other terminals or send user data to other terminals.
[0053] The present invention also provides a computer storage medium, wherein the computer storage medium may store a program, and when the program is executed, the program may include some or all of the steps in each embodiment provided by the present invention. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM).
[0054] Therefore, the present invention realizes intuitive display of abnormal gas concentration by constructing a model, and uses image recognition technology to identify the display interface, and can directly obtain the abnormal type without considering the structural relationship between sensors. The present invention reduces the amount of calculation and improves the monitoring efficiency. The technical effects that can be achieved by this embodiment can be found in the description above and will not be repeated here.
[0055] Those skilled in the art can clearly understand that the technology in the embodiments of the present invention can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the technical solution in the embodiments of the present invention, in essence or in other words, the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, and other media that can store program codes, including several instructions for enabling a computer terminal (which can be a personal computer, a server, or a second terminal, a network terminal, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention.
[0056] In this specification, the same or similar parts between the various embodiments can be referred to each other. In particular, for the terminal embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method embodiment.
[0057] In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or modules, which can be electrical, mechanical or other forms.
[0058] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0059] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.
[0060] Although the present invention has been described in detail with reference to the accompanying drawings and in combination with the preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, a person of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and these modifications or substitutions shall be within the scope of the present invention. Any person of ordinary skill in the art may easily think of changes or substitutions within the technical scope disclosed by the present invention, and these shall be within the scope of protection of the present invention.
Claims
1. A combustible and toxic gas monitoring and early warning method, characterized in that: include: Constructing a scaled digital model for the production line of the factory in advance, and generating sensor marks at corresponding positions of the digital model; Acquiring the concentration of the combustible and toxic gas detected by the sensor, and if the concentration exceeds a preset concentration threshold, setting the corresponding sensor identifier in the digital model to a warning color; Along the upstream and downstream relationship of the sensor identifiers in the digital model, a local area of the model between adjacent sensor identifiers set to a warning color is set to a warning color; Collecting a display interface image where the digital model is located, and using a pre-trained neural network model to identify the display interface image to obtain an abnormality type; Based on the pre-set correspondence between the abnormality type and the warning terminal, the warning information is sent to the corresponding warning terminal.
2. The method according to claim 1, characterized in that A proportional digital model is constructed in advance for the production line of the factory area, and sensor identification is generated at the corresponding position of the digital model, including: Use modeling software to build a proportional two-dimensional model of the factory production line to obtain a digital model; Based on the actual deployment location of the sensor on the production line, a sensor identifier is generated at the corresponding location of the digital model, and a mapping relationship between the sensor identifier and the sensor address is established; A display window is created for the digital model.
3. The method according to claim 2, characterized in that Acquiring the concentration of the combustible and toxic gas detected by the sensor, and setting the corresponding sensor identification in the digital model to a warning color if the concentration exceeds a preset concentration threshold, including: Create multiple threads to concurrently process the concentration detected by the sensor; If the concentration detected by the sensor reaches the concentration threshold, the corresponding address is obtained; Based on the mapping relationship and the address, the corresponding sensor identification is set as a warning color, and the warning color is a highlight color.
4. The method according to claim 1, characterized in that Along the upstream and downstream relationship of the sensor identifiers in the digital model, the local area of the model between the adjacent sensor identifiers set to the warning color is set to the warning color, including: Get the display color of the adjacent upstream sensor mark of the sensor mark set to the warning color; If the display color of the adjacent upstream sensor mark is a warning color, the local area of the model between the two sensor marks is set to the warning color.
5. The method according to claim 1, characterized in that Collect the display interface image where the digital model is located, use the pre-trained neural network model to identify the display interface image, and obtain the abnormal type, including: Confirm that the display color of the digital model is updated and use the screenshot command to regularly obtain images of the display interface; The image is input into a pre-trained neural network model to obtain the abnormality type.
6. A flammable and toxic gas monitoring and early warning system, characterized in that: include: A model building module, used to build a proportional digital model for the production line of the factory in advance, and generate sensor identification at the corresponding position of the digital model; An identification setting module, used for obtaining the concentration of the combustible and toxic gas detected by the sensor, and setting the corresponding sensor identification in the digital model to a warning color if the concentration exceeds a preset concentration threshold; A model setting module, used for setting a local area of the model between adjacent sensor identifiers set to a warning color as a warning color along the upstream and downstream relationship of the sensor identifiers in the digital model; An image recognition module is used to collect the display interface image where the digital model is located, and use a pre-trained neural network model to recognize the display interface image to obtain an abnormality type; The warning processing module is used to send warning information to the corresponding warning terminal based on the preset correspondence between the abnormal type and the warning terminal.
7. The system according to claim 6, characterized in that The model building module includes: A two-dimensional modeling unit is used to construct a proportional two-dimensional model of the plant production line using modeling software to obtain a digital model; An identification generating unit, used to generate a sensor identification at a corresponding position of the digital model based on the actual deployment position of the sensor on the production line, and to establish a mapping relationship between the sensor identification and the sensor address; A window creation unit is used to create a display window for the digital model.
8. The system according to claim 7, characterized in that The identification setting module includes: A concurrent processing unit, used to create multiple threads to concurrently process the concentration detected by the sensor; An address acquisition unit, configured to acquire a corresponding address if the concentration detected by the sensor reaches the concentration threshold; The color setting unit is used to set the corresponding sensor identification as a warning color based on the mapping relationship and the address, and the warning color is a highlight color.
9. A terminal, characterized in that: include: A memory device for storing a combustible and toxic gas monitoring and early warning program; A processor is used to implement the steps of the combustible and toxic gas monitoring and early warning method as described in any one of claims 1 to 5 when executing the combustible and toxic gas monitoring and early warning program.
10. A computer-readable storage medium storing a computer program, characterized in that: The readable storage medium stores a combustible and toxic gas monitoring and early warning program, and when the combustible and toxic gas monitoring and early warning program is executed by the processor, the steps of the combustible and toxic gas monitoring and early warning method as described in any one of claims 1-5 are implemented.