Intelligent ventilation method and device for long tunnel based on neural network model

Abstract

The invention provides a long tunnel intelligent ventilation method and device based on a neural network model, and the method comprises the steps: obtaining a ventilation system design scheme corresponding to a tunnel; the ventilation system design scheme is optimized and adjusted in the tunnel construction process; wherein the optimized and adjusted design scheme of the ventilation system is used for arranging the ventilation system in the construction process of the tunnel; ventilation monitoring information of a ventilation system and construction information of a tunnel are obtained; pollutant diffusion prediction is carried out based on the tunnel model corresponding to the tunnel, the ventilation system design scheme and the ventilation monitoring information, and pollutant diffusion prediction information in the tunnel is obtained; and controlling the ventilation system based on at least one of the ventilation monitoring information, the construction information, and the pollutant diffusion prediction information. According to the scheme, the ventilation system design scheme better meeting the real conditions of the tunnel can be generated, the ventilation system is intelligently controlled according to the actual conditions, and the construction safety of the tunnel is guaranteed.

Description

Technical Field

[0001] The present application relates to the field of tunnel ventilation technology, and in particular to a method, device, equipment and storage medium for intelligent ventilation of long and large tunnels based on a neural network model. Background Art

[0002] In the related technologies, the tunnel ventilation process lacks actual parameter monitoring, ventilation control lacks a basis, the ventilation volume is completely based on the experience of the construction personnel, and the ventilation quality cannot be guaranteed; and tunnel ventilation basically relies on manual control, and the parameters are basically not adjusted after the fan is started. It is impossible to adjust in real time according to changes in tunnel construction distance, changes in tunnel construction air quality, and ventilation abnormalities, and the degree of intelligence is extremely low; it relies entirely on manual on-site inspections to determine whether the ventilation system is abnormal, and it is impossible to accurately lock the damaged point of the wind tube for rapid processing. Summary of the invention

[0003] The present application aims to solve one of the technical problems in the related art at least to some extent.

[0004] In the first aspect, the present application proposes an intelligent ventilation method for long and large tunnels based on a neural network model, the method comprising: obtaining a ventilation system design scheme corresponding to the tunnel; optimizing and adjusting the ventilation system design scheme during the construction of the tunnel; wherein the optimized and adjusted ventilation system design scheme is used to arrange the ventilation system during the construction of the tunnel; obtaining ventilation monitoring information of the ventilation system and construction information of the tunnel; performing pollutant diffusion prediction based on a tunnel model corresponding to the tunnel, the ventilation system design scheme and the ventilation monitoring information, and obtaining pollutant diffusion prediction information in the tunnel; and controlling the ventilation system based on at least one of the ventilation monitoring information, the construction information and the pollutant diffusion prediction information.

[0005] In one implementation, the step of obtaining a ventilation system design scheme corresponding to a tunnel includes: obtaining a tunnel model, climate and environmental information, geological and topographic information, initial construction information, and gas index information corresponding to the tunnel; obtaining multiple initial ventilation system design schemes based on the tunnel model, the climate and environmental information, the geological and topographic information, and the initial construction information; obtaining scheme data corresponding to each of the initial ventilation system design schemes; wherein the scheme data includes at least one of different air duct cross-sectional positions, distances from the air duct to the working surface, and air duct diameters; based on the scheme data corresponding to each of the initial ventilation system design schemes, obtaining evaluation index data corresponding to each of the initial ventilation system design schemes; wherein the evaluation index data includes at least one of wind flow field data and pollutant purification efficiency; and selecting the ventilation system design scheme from the multiple initial ventilation system design schemes based on the evaluation index data.

[0006] In an optional implementation, the climate and environment information includes at least one of the following: altitude information; air pressure information; oxygen content information; temperature information; humidity information; wind speed information; and wind direction information.

[0007] In an optional implementation, the geological and topographic information includes at least one of the following: geological structure information; topographic condition information.

[0008] In one implementation, the ventilation system design scheme is optimized and adjusted during the construction of the tunnel, including: obtaining actual ventilation monitoring information of the first part of the ventilation system; wherein the first part of the ventilation system is the ventilation system arranged in the first part of the tunnel, and the first part of the tunnel is the part of the tunnel that has been completed and is under construction in the tunnel; obtaining actual geological condition information of the second part of the tunnel; wherein the second part of the tunnel is the part of the tunnel to be constructed in the tunnel; optimizing and adjusting the ventilation system design scheme based on the actual ventilation monitoring information and the actual geological condition information to obtain the optimized and adjusted ventilation system design scheme.

[0009] In one implementation, the pollutant diffusion prediction is performed based on the tunnel model corresponding to the tunnel, the ventilation system design plan and the ventilation monitoring information to obtain the pollutant diffusion prediction information in the tunnel, including: data cleaning of the ventilation monitoring information to obtain standard monitoring data; inputting the standard monitoring data, the tunnel model and the ventilation system design plan into a pre-trained pollutant diffusion prediction model to obtain the pollutant diffusion prediction information; wherein the pollutant diffusion prediction model has been pre-trained to obtain the ability to perform pollutant diffusion prediction based on the standard monitoring data, the tunnel model and the ventilation system design plan.

[0010] In an optional implementation, the pollutant diffusion prediction model is pre-trained through the following steps: obtaining multiple initial pollutant concentrations; performing fluid dynamics numerical simulation calculations based on different initial pollutant concentrations and different operating condition data of ventilation equipment in the ventilation system to obtain pollutant diffusion sample results; training the initial pollutant diffusion model based on the multiple initial pollutant concentrations, the operating condition data and the pollutant diffusion sample results to obtain the pollutant diffusion prediction model.

[0011] In one implementation, the ventilation monitoring information includes at least one of the following: pollutant monitoring information; ventilation equipment monitoring information; construction personnel monitoring information; construction equipment monitoring information.

[0012] In one implementation, based on the pollutant diffusion prediction information, a pollutant diffusion area is determined; based on the ventilation monitoring information, target ventilation equipment monitoring information and maximum ventilation efficiency of the target ventilation equipment in the ventilation system within the pollutant diffusion area, as well as target pollutant monitoring information of the pollutant diffusion area are obtained; based on the target ventilation equipment monitoring information, a current ventilation efficiency of the pollutant diffusion area is determined; based on the pollutant monitoring information, the current ventilation efficiency, the maximum ventilation efficiency and the pollutant diffusion prediction information, a minimum predicted pollutant index of the pollutant diffusion area is determined; if it is determined that the minimum predicted pollutant index is greater than or equal to a preset index threshold, an alarm message is issued, or, if it is determined that the minimum predicted pollutant index is less than the preset threshold, the target air duct is controlled based on the predicted pollutant index.

[0013] In one implementation, the construction information includes at least one of construction progress information, construction personnel information, construction equipment information and construction process information. The control of the ventilation system based on at least one of the ventilation monitoring information, the construction information and the pollutant diffusion prediction information includes: obtaining regional construction personnel information, regional construction equipment information and regional construction process information in a first construction area based on the construction information and the construction progress information; wherein the first construction area is any one of at least one construction area pre-demarcated in the tunnel based on the construction progress information; determining the regional ventilation demand of the first construction area based on the regional construction personnel information, the regional construction equipment information and the regional construction process information; and controlling the ventilation system based on the regional ventilation demand.

[0014] In the second aspect, the present application proposes an intelligent ventilation device for a long and large tunnel based on a neural network model, the device comprising: a first acquisition module, used to acquire a ventilation system design scheme corresponding to the tunnel; a first processing module, used to optimize and adjust the ventilation system design scheme during the construction of the tunnel; wherein the ventilation system design scheme after optimization and adjustment is used to arrange the ventilation system during the construction of the tunnel; a second acquisition module, used to acquire ventilation monitoring information of the ventilation system and construction information of the tunnel; a second processing module, used to predict pollutant diffusion based on a tunnel model corresponding to the tunnel, the ventilation system design scheme and the ventilation monitoring information, and acquire pollutant diffusion prediction information in the tunnel; a third processing module, used to control the ventilation system based on at least one of the ventilation monitoring information, the construction information and the pollutant diffusion prediction information.

[0015] In one implementation, the first processing module can be used to: obtain a tunnel model, climate and environmental information, geological and topographic information, initial construction information and gas index information corresponding to the tunnel; obtain multiple initial ventilation system design schemes based on the tunnel model, the climate and environmental information, the geological and topographic information and the initial construction information; obtain scheme data corresponding to each of the initial ventilation system design schemes; wherein the scheme data includes at least one of different air duct cross-sectional positions, distances from the air duct to the working surface, and air duct diameters; based on the scheme data corresponding to each of the initial ventilation system design schemes, obtain evaluation index data corresponding to each of the initial ventilation system design schemes; wherein the evaluation index data includes at least one of wind flow field data and pollutant purification efficiency; select the ventilation system design scheme from the multiple initial ventilation system design schemes based on the evaluation index data.

[0016] In an optional implementation, the climate and environment information includes at least one of the following: altitude information; air pressure information; oxygen content information; temperature information; humidity information; wind speed information; and wind direction information.

[0017] In an optional implementation, the geological and topographic information includes at least one of the following: geological structure information; topographic condition information.

[0018] In one implementation, the first processing module can be used to: obtain actual ventilation monitoring information of the first part of the ventilation system; wherein the first part of the ventilation system is a ventilation system arranged in the first part of the tunnel, and the first part of the tunnel is a part of the tunnel that has been completed and is under construction in the tunnel; obtain actual geological condition information of the second part of the tunnel; wherein the second part of the tunnel is a part of the tunnel to be constructed in the tunnel; optimize and adjust the ventilation system design plan based on the actual ventilation monitoring information and the actual geological condition information to obtain the optimized and adjusted ventilation system design plan.

[0019] In one implementation, the second processing module can be used to: perform data cleaning on the ventilation monitoring information to obtain standard monitoring data; input the standard monitoring data, the tunnel model and the ventilation system design plan into a pre-trained pollutant diffusion prediction model to obtain the pollutant diffusion prediction information; wherein the pollutant diffusion prediction model has been pre-trained to obtain the ability to perform pollutant diffusion prediction based on the standard monitoring data, the tunnel model and the ventilation system design plan.

[0020] In an optional implementation, the pollutant diffusion prediction model is pre-trained through the following steps: obtaining multiple initial pollutant concentrations; performing fluid dynamics numerical simulation calculations based on different initial pollutant concentrations and different operating condition data of ventilation equipment in the ventilation system to obtain pollutant diffusion sample results; training the initial pollutant diffusion model based on the multiple initial pollutant concentrations, the operating condition data and the pollutant diffusion sample results to obtain the pollutant diffusion prediction model.

[0021] In one implementation, the ventilation monitoring information includes at least one of the following: pollutant monitoring information; ventilation equipment monitoring information; construction personnel monitoring information; construction equipment monitoring information.

[0022] In one implementation, the third processing module can be used to: determine the pollutant diffusion area based on the pollutant diffusion prediction information; obtain the target ventilation equipment monitoring information and maximum ventilation efficiency of the target ventilation equipment in the ventilation system within the pollutant diffusion area, and the target pollutant monitoring information of the pollutant diffusion area based on the ventilation monitoring information; determine the current ventilation efficiency of the pollutant diffusion area based on the target ventilation equipment monitoring information; determine the minimum predicted pollutant index of the pollutant diffusion area based on the pollutant monitoring information, the current ventilation efficiency, the maximum ventilation efficiency and the pollutant diffusion prediction information; determine that the minimum predicted pollutant index is greater than or equal to a preset index threshold, and issue an alarm message, or determine that the minimum predicted pollutant index is less than the preset threshold, and control the target air duct based on the predicted pollutant index.

[0023] In one implementation, the construction information includes at least one of construction progress information, construction personnel information, construction equipment information and construction process information. The third processing module can be used to: obtain regional construction personnel information, regional construction equipment information and regional construction process information in the first construction area based on the construction information and the construction progress information; wherein the first construction area is any one of the at least one construction area pre-demarcated in the tunnel based on the construction progress information; determine the regional ventilation demand of the first construction area based on the regional construction personnel information, the regional construction equipment information and the regional construction process information; and control the ventilation system based on the regional ventilation demand.

[0024] In a third aspect, the present application proposes an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the intelligent ventilation method for long and large tunnels based on a neural network model as described in the first aspect.

[0025] In a fourth aspect, the present application proposes a computer-readable storage medium for storing instructions, which, when executed, enables the method described in the first aspect to be implemented.

[0026] In a fifth aspect, the present application proposes a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the intelligent ventilation method for long and large tunnels based on a neural network model as described in the first aspect.

[0027] The method, device, equipment and storage medium for intelligent ventilation of long tunnels based on neural network model provided by the present application can arrange corresponding ventilation system in the construction process based on ventilation system design scheme corresponding to the tunnel, and obtain ventilation monitoring information of ventilation system and construction information of tunnel; at the same time, pollutant diffusion prediction is performed based on tunnel model corresponding to the tunnel, ventilation system design scheme and ventilation monitoring information, and pollutant diffusion prediction information in the tunnel is obtained, so as to control the ventilation system based on at least one of the above information. It can generate ventilation system design scheme that is more in line with the real conditions of the tunnel, and intelligently control the ventilation system according to the actual situation to ensure the construction safety of the tunnel.

[0028] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0030] Figure 1 It is a flow chart of a method for intelligent ventilation of a long tunnel based on a neural network model provided in an embodiment of the present application;

[0031] Figure 2 It is a flow chart of another intelligent ventilation method for long tunnels based on a neural network model provided in an embodiment of the present application;

[0032] Figure 3It is a flow chart of another method for intelligent ventilation of long tunnels based on a neural network model provided in an embodiment of the present application;

[0033] Figure 4 It is a flow chart of another method for intelligent ventilation of long tunnels based on a neural network model provided in an embodiment of the present application;

[0034] Figure 5 It is a flow chart of another method for intelligent ventilation of long tunnels based on a neural network model provided in an embodiment of the present application;

[0035] Figure 6 It is a structural schematic diagram of a long tunnel intelligent ventilation device based on a neural network model provided in an embodiment of the present application;

[0036] Figure 7 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0037] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0038] The following describes the intelligent ventilation method and device for long tunnels based on a neural network model according to an embodiment of the present application with reference to the accompanying drawings.

[0039] Figure 1 1 is a flow chart of a method for intelligent ventilation of a long tunnel based on a neural network model provided in an embodiment of the present application. Figure 1 As shown, the method may include but is not limited to the following steps:

[0040] Step S101: Obtain a ventilation system design plan corresponding to the tunnel.

[0041] Exemplarily, a ventilation system design scheme for the tunnel is established based on the planning information and engineering design information of the tunnel.

[0042] The above ventilation system design includes equipment information of the ventilation equipment (eg, equipment model) and location information of the ventilation equipment in the tunnel.

[0043] Step S102: Optimizing and adjusting the ventilation system design during the tunnel construction process to obtain an optimized and adjusted ventilation system design.

[0044] Among them, the optimized and adjusted ventilation system design plan is used to arrange the ventilation system during the construction process of the tunnel.

[0045] Illustratively, corresponding ventilation equipment is arranged during the construction of the tunnel based on the ventilation system design plan, and the ventilation system design plan is continuously optimized based on relevant information obtained during the construction process, so that the ventilation system is arranged in part of the newly constructed tunnel based on the optimized ventilation system design plan.

[0046] Step S103: Acquire ventilation monitoring information of the ventilation system and construction information of the tunnel.

[0047] Exemplarily, ventilation monitoring information of the ventilation system is obtained based on sensors in the ventilation system, and construction information during tunnel construction is obtained.

[0048] Step S104: performing pollutant diffusion prediction based on the tunnel model corresponding to the tunnel, the ventilation system design scheme and the ventilation monitoring information, and obtaining pollutant diffusion prediction information in the tunnel.

[0049] Exemplarily, a BIM (Building Information Modeling) model corresponding to the tunnel is obtained, and pollutant information at various locations in the tunnel is obtained based on ventilation monitoring information. Fluid mechanics analysis is performed based on the pollutant information, tunnel model and ventilation system design scheme to obtain pollutant diffusion prediction information in the tunnel.

[0050] Step S105: Control the ventilation system based on at least one of the ventilation monitoring information, the construction information and the pollutant diffusion prediction information.

[0051] For example, if it is determined based on the ventilation monitoring information that the concentration of pollutants at a target location in the tunnel has increased, the ventilation efficiency of the ventilation equipment in the target area is increased.

[0052] Exemplarily, the ventilation monitoring information may include the temperature and humidity in the tunnel, so that the ventilation system may be controlled according to the temperature and humidity in the tunnel to keep the temperature and humidity in the tunnel within a preset range.

[0053] By implementing the embodiments of the present application, the corresponding ventilation system can be arranged during the construction process based on the ventilation system design scheme corresponding to the tunnel, and the ventilation monitoring information of the ventilation system and the construction information of the tunnel can be obtained; at the same time, pollutant diffusion prediction can be performed based on the tunnel model corresponding to the tunnel, the ventilation system design scheme and the ventilation monitoring information, and the pollutant diffusion prediction information in the tunnel can be obtained, so as to control the ventilation system based on at least one of the above information. A ventilation system design scheme that is more in line with the actual conditions of the tunnel can be generated, and the ventilation system can be intelligently controlled according to the actual situation to ensure the construction safety of the tunnel.

[0054] In some embodiments, the above-mentioned pollutant diffusion prediction is performed based on the tunnel model, ventilation system design plan and ventilation monitoring information corresponding to the tunnel to obtain the pollutant diffusion prediction information in the tunnel, including: data cleaning of the ventilation monitoring information to obtain standard monitoring data; inputting the standard monitoring data, tunnel model and ventilation system design plan into a pre-trained pollutant diffusion prediction model to obtain pollutant diffusion prediction information.

[0055] Among them, the pollutant diffusion prediction model has been pre-trained to obtain the ability to predict pollutant diffusion based on standard monitoring data, tunnel models and ventilation system design plans.

[0056] In some embodiments, the pollutant diffusion prediction model is pre-trained through the following steps: obtaining multiple initial pollutant concentrations; performing fluid dynamics numerical simulation calculations based on different initial pollutant concentrations and different operating condition data of ventilation equipment in the ventilation system to obtain pollutant diffusion sample results; training the initial pollutant diffusion model based on multiple initial pollutant concentrations, operating condition data and pollutant diffusion sample results to obtain a pollutant diffusion prediction model.

[0057] In some embodiments, an optimization design can be performed based on the relevant information of the tunnel to obtain a design solution for the ventilation system of the tunnel. As an example, see Figure 2 , Figure 2 FIG. 1 is a flow chart of another intelligent ventilation method for long tunnels based on a neural network model provided in an embodiment of the present application. Figure 2 As shown, the method may include but is not limited to the following steps:

[0058] Step S201: obtaining a tunnel model, climate and environment information, geological and topographic information, initial construction information and gas index information corresponding to the tunnel;

[0059] In one implementation, the climate and environment information includes at least one of the following: altitude information; air pressure information; oxygen content information; temperature information; humidity information; wind speed information; and wind direction information.

[0060] In one implementation, the geological and topographic information includes at least one of the following: geological structure information; topographic condition information, including underwater tunnel environment, plateau mountainous area and other undulating terrain.

[0061] The above geological structure information may include but is not limited to faults, shallow buried bias, toxic and harmful gases, high ground stress, fracture zones, caves, etc.

[0062] The terrain condition information may include but is not limited to underwater tunnel environment, plateau mountainous area and other undulating terrain information.

[0063] Step S202: Acquire multiple initial ventilation system design solutions based on the tunnel model, climate and environmental information, geological and topographic information, and initial construction information.

[0064] Exemplarily, a fluid mechanics analysis is performed based on a tunnel model, climate and environmental information, geological and topographic information, and initial construction information to obtain analysis results, and a plurality of ventilation system design schemes are set according to the analysis results.

[0065] Step S203: Acquire the scheme data corresponding to each initial ventilation system design scheme.

[0066] The scheme data includes at least one of the positions of different air duct sections, the distance from the air duct to the working surface, and the diameter of the air duct;

[0067] Step S204: Based on the scheme data corresponding to each initial ventilation system design scheme, obtaining the evaluation index data corresponding to each initial ventilation system design scheme.

[0068] The evaluation index data includes at least one of wind flow field data and pollutant purification efficiency.

[0069] Exemplarily, a wind flow field analysis is performed based on the scheme data of each initial ventilation system design scheme to obtain at least one of the wind flow field data and the pollutant purification efficiency.

[0070] Step S205: selecting a ventilation system design scheme from a plurality of initial ventilation system design schemes based on the evaluation index data.

[0071] Exemplarily, corresponding weight values ​​are set in advance for different evaluation index data, so as to obtain the evaluation value of each initial ventilation system design scheme based on the weight value and the evaluation index data of each initial ventilation system design scheme, and select the initial ventilation system design scheme with the highest evaluation value as the ventilation system design scheme.

[0072] Step S206: Optimizing and adjusting the ventilation system design during the tunnel construction process to obtain an optimized and adjusted ventilation system design.

[0073] In the embodiments of the present application, step S206 can be implemented by any of the methods in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0074] Step S207: Acquire ventilation monitoring information of the ventilation system and construction information of the tunnel.

[0075] In the embodiments of the present application, step S207 can be implemented by any of the methods in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0076] Step S208: performing pollutant diffusion prediction based on the tunnel model, ventilation system design scheme and ventilation monitoring information corresponding to the tunnel, and obtaining pollutant diffusion prediction information in the tunnel.

[0077] In the embodiments of the present application, step S208 can be implemented in any of the ways in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0078] Step S209: Control the ventilation system based on at least one of the ventilation monitoring information, the construction information and the pollutant diffusion prediction information.

[0079] In the embodiments of the present application, step S209 can be implemented in any of the ways in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0080] By implementing the embodiments of the present application, multiple initial ventilation system design schemes can be obtained based on the tunnel model, climate and environmental information, geological and topographic information, initial construction information and gas index information of the tunnel, and the initial ventilation system design schemes can be compared to determine the ventilation system design scheme. The effectiveness of the ventilation system design scheme is ensured to ensure the smooth progress of tunnel construction.

[0081] In some embodiments, the ventilation system design can be further optimized based on the data obtained during the tunnel construction process. As an example, see Figure 3 , Figure 3 FIG. 1 is a flow chart of another method for intelligent ventilation of long tunnels based on a neural network model provided in an embodiment of the present application. Figure 3 As shown, the method may include but is not limited to the following steps:

[0082] Step S301: Obtain a ventilation system design plan corresponding to the tunnel.

[0083] In the embodiments of the present application, step S301 can be implemented in any of the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0084] Step S302: Acquire actual ventilation monitoring information of the first part of the ventilation system.

[0085] Among them, the first part of the ventilation system is the ventilation system that has been arranged in the first part of the tunnel, and the first part of the tunnel is the part of the tunnel that has been completed and is under construction.

[0086] Among them, the above-mentioned actual ventilation monitoring information includes at least one of the following: pollutant monitoring information; ventilation equipment monitoring information; construction personnel monitoring information; construction equipment monitoring information.

[0087] Step S303: Acquire actual geological condition information of the second part of the tunnel.

[0088] Among them, the second part of the tunnel is the part of the tunnel to be constructed.

[0089] For example, actual geological condition information of a portion of the tunnel to be constructed is obtained through field survey.

[0090] It should be noted that the second partial tunnel mentioned above is a partial tunnel of a preset length adjacent to the tunnel working face.

[0091] Step S304: Optimizing and adjusting the ventilation system design scheme based on the actual ventilation monitoring information and the actual geological condition information to obtain an optimized and adjusted ventilation system design scheme.

[0092] For example, the ventilation network is solved to simulate the wind flow distribution and ventilation effect under the current ventilation system design scheme. The results of the ventilation network solution are combined with the actual ventilation monitoring information and the actual geological conditions information to perform optimization and adjustment to improve the overall ventilation efficiency of the ventilation system and obtain the optimized ventilation system design scheme.

[0093] The above optimization and adjustment may include but are not limited to: changing the settings of dampers and windows, optimizing the cross-sectional size or shape of the tunnel, adding new ventilation facilities, etc.

[0094] Step S305: Acquire ventilation monitoring information of the ventilation system and construction information of the tunnel.

[0095] In the embodiments of the present application, step S305 can be implemented in any of the ways in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0096] Step S306: performing pollutant diffusion prediction based on the tunnel model, ventilation system design scheme and ventilation monitoring information corresponding to the tunnel, and obtaining pollutant diffusion prediction information in the tunnel.

[0097] In the embodiments of the present application, step S306 can be implemented in any of the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0098] Step S307: Control the ventilation system based on at least one of the ventilation monitoring information, the construction information and the pollutant diffusion prediction information.

[0099] In the embodiments of the present application, step S307 can be implemented by any of the methods in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0100] By implementing the embodiments of the present application, the ventilation system design scheme can be optimized and adjusted based on the actual information obtained during the tunnel construction process, an optimized and adjusted ventilation system design scheme can be obtained, and the ventilation system can be arranged according to the optimized and adjusted ventilation system design scheme to enhance the actual ventilation efficiency of the ventilation system and ensure the smooth progress of the tunnel construction.

[0101] In some embodiments, the ventilation effects of different areas can be determined based on relevant information, and the ventilation system can be controlled in combination with the actual gas monitoring data of different areas. Figure 4 , Figure 4 FIG. 1 is a flow chart of another method for intelligent ventilation of long tunnels based on a neural network model provided in an embodiment of the present application. Figure 4 The method may include but is not limited to the following steps:

[0102] Step S401: Obtain a ventilation system design plan corresponding to the tunnel.

[0103] In the embodiments of the present application, step S401 can be implemented by any of the methods in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0104] Step S402: Optimizing and adjusting the ventilation system design during the tunnel construction process to obtain an optimized and adjusted ventilation system design.

[0105] In the embodiments of the present application, step S402 can be implemented by any of the methods in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0106] Step S403: Acquire ventilation monitoring information of the ventilation system and construction information of the tunnel.

[0107] In the embodiments of the present application, step S403 can be implemented by any of the methods in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0108] Step S404: performing pollutant diffusion prediction based on the tunnel model corresponding to the tunnel, the ventilation system design scheme and the ventilation monitoring information, and obtaining pollutant diffusion prediction information in the tunnel.

[0109] In the embodiments of the present application, step S404 can be implemented by any of the methods in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0110] Step S405: Determine the pollutant diffusion area based on the pollutant diffusion prediction information.

[0111] Exemplarily, an area where the pollutant concentration is greater than or equal to a preset concentration threshold is determined as a target area, and an area adjacent to the target area is determined as a pollutant diffusion area.

[0112] Step S406: Based on the ventilation monitoring information, the target ventilation equipment monitoring information and the maximum ventilation efficiency of the target ventilation equipment in the pollutant diffusion area of ​​the ventilation system and the target pollutant monitoring information of the pollutant diffusion area are obtained.

[0113] Exemplarily, based on ventilation monitoring information, ventilation equipment monitoring information and equipment information of target ventilation equipment in the pollutant diffusion area of ​​the ventilation system are obtained to determine the maximum ventilation efficiency of the target ventilation equipment based on the equipment information, and to obtain target pollutant monitoring information of the pollutant diffusion area.

[0114] Step S407: Determine the current ventilation efficiency of the pollutant diffusion area based on the target ventilation equipment monitoring information.

[0115] Step S408: Determine the minimum predicted pollutant index of the pollutant diffusion area based on the pollutant monitoring information, the current ventilation efficiency, the maximum ventilation efficiency and the pollutant diffusion prediction information.

[0116] Exemplarily, the predicted pollutant concentration in the pollutant diffusion area is determined based on the pollutant monitoring information and the pollutant diffusion information after the pollutants diffuse into the pollutant diffusion area, and the effectiveness of reducing the pollutant concentration in the pollutant diffusion area is determined based on the current ventilation efficiency and the maximum ventilation efficiency of the target ventilation equipment in the pollutant diffusion area, thereby determining the minimum predicted pollutant index of the pollutant diffusion area based on the efficiency of reducing the pollutant concentration and the predicted pollutant concentration.

[0117] Step S409: Determine that the minimum predicted pollutant index is greater than or equal to a preset index threshold, and issue an alarm message; or, determine that the minimum predicted pollutant index is less than a preset threshold, and control the target air duct based on the predicted pollutant index.

[0118] Exemplarily, it is determined that the minimum predicted pollutant index is greater than or equal to a preset index threshold, and an alarm message is issued.

[0119] Exemplarily, it is determined that the minimum predicted pollutant index is less than a preset threshold, and the target wind duct is controlled based on the predicted pollutant index, for example, the wind speed of the wind duct is increased to minimize the pollutant concentration in the pollutant diffusion area.

[0120] By implementing the embodiments of the present application, the impact of pollutant diffusion on different areas of the tunnel can be determined based on the pollutant diffusion prediction information. The ventilation system can be controlled in combination with the current ventilation efficiency and maximum ventilation efficiency of different areas. This prevents the impact of excessive pollutants on construction personnel and ensures the smooth progress of tunnel construction.

[0121] In some embodiments, the construction information includes at least one of construction progress information, construction personnel information, construction equipment information, and construction process information, so that the ventilation system can be controlled based on the relevant information of personnel and construction equipment in the preset area. As an example, see Figure 5 , Figure 5 FIG. 1 is a flow chart of another method for intelligent ventilation of long tunnels based on a neural network model provided in an embodiment of the present application. Figure 5 The method may include but is not limited to the following steps:

[0122] Step S501: Obtain a ventilation system design plan corresponding to the tunnel.

[0123] In the embodiments of the present application, step S501 can be implemented by any of the methods in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0124] Step S502: Optimizing and adjusting the ventilation system design during the tunnel construction process to obtain an optimized and adjusted ventilation system design.

[0125] In the embodiments of the present application, step S502 can be implemented by any of the methods in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0126] Step S503: Acquire ventilation monitoring information of the ventilation system and construction information of the tunnel.

[0127] In the embodiments of the present application, step S503 can be implemented by any of the methods in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0128] Step S504: performing pollutant diffusion prediction based on the tunnel model corresponding to the tunnel, the ventilation system design scheme and the ventilation monitoring information, and obtaining pollutant diffusion prediction information in the tunnel.

[0129] In the embodiments of the present application, step S504 can be implemented in any of the ways in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be described in detail.

[0130] Step S505: Based on the construction information and the construction progress information, obtain the regional construction personnel information, regional construction equipment information and regional construction process information in the first construction area.

[0131] The first construction area is any one of at least one construction area pre-demarcated in the tunnel based on construction progress information.

[0132] Exemplarily, parts of the tunnel that have been completed and are under construction are divided into multiple areas in advance, and based on the construction information and construction progress information, regional construction personnel information, regional construction equipment information and regional construction process information in the first construction area are obtained.

[0133] Step S506: Determine the regional ventilation demand of the first construction area based on the regional construction personnel information, regional construction equipment information and regional construction process information.

[0134] Exemplarily, the number of personnel in the first construction area is determined based on the regional construction personnel information, and the personnel ventilation needs of the construction personnel in the first construction area are determined based on the number of personnel. The equipment ventilation needs corresponding to the operation of the construction equipment in the first construction area (for example, based on the pollutants generated by the equipment operation) are determined based on the regional construction equipment information. The construction ventilation needs are determined based on the regional construction process information of the ongoing construction in the first construction area (for example, the concentration of pollutants generated by the construction process is determined based on the construction process). In this way, the regional ventilation needs of the first construction area are determined based on the personnel ventilation needs, equipment ventilation needs and construction ventilation needs.

[0135] Step S507: Control the ventilation system based on the regional ventilation demand.

[0136] Exemplarily, the rotation speeds of the wind cylinders in the first construction area and other related areas (eg, areas adjacent to the first construction area) are controlled based on the regional ventilation demand.

[0137] By implementing the embodiments of the present application, the ventilation requirements of the construction area can be determined based on the construction personnel information, construction equipment information and construction process information in the construction area, so as to control the ventilation system according to the ventilation requirements of each construction area, thereby improving ventilation efficiency and ensuring construction safety.

[0138] See also Figure 6 , Figure 6 Schematic diagram of the structure of a long tunnel intelligent ventilation device based on a neural network model provided in an embodiment of the present application. Figure 6As shown, the device 600 includes: a first acquisition module 601, used to acquire a ventilation system design scheme corresponding to a tunnel; a first processing module 602, used to optimize and adjust the ventilation system design scheme during the construction of the tunnel; wherein the optimized and adjusted ventilation system design scheme is used to arrange the ventilation system during the construction of the tunnel; a second acquisition module 603, used to acquire ventilation monitoring information of the ventilation system and construction information of the tunnel; a second processing module 604, used to predict pollutant diffusion based on a tunnel model corresponding to the tunnel, the ventilation system design scheme and the ventilation monitoring information, and acquire pollutant diffusion prediction information in the tunnel; a third processing module 605, used to control the ventilation system based on at least one of the ventilation monitoring information, construction information and pollutant diffusion prediction information.

[0139] In one implementation, the first processing module 602 can be used to: obtain a tunnel model, climate and environmental information, geological and topographic information, initial construction information and gas index information corresponding to the tunnel; obtain multiple initial ventilation system design schemes based on the tunnel model, climate and environmental information, geological and topographic information and initial construction information; obtain scheme data corresponding to each initial ventilation system design scheme; wherein the scheme data includes at least one of different air duct cross-sectional positions, distances from the air duct to the working surface, and air duct diameters; based on the scheme data corresponding to each initial ventilation system design scheme, obtain evaluation index data corresponding to each initial ventilation system design scheme; wherein the evaluation index data includes at least one of wind flow field data and pollutant purification efficiency; and select a ventilation system design scheme from multiple initial ventilation system design schemes based on the evaluation index data.

[0140] In one implementation, the first processing module 602 can be used to: obtain actual ventilation monitoring information of the first part of the ventilation system; wherein the first part of the ventilation system is the ventilation system arranged in the first part of the tunnel, and the first part of the tunnel is the part of the tunnel that has been completed and is under construction in the tunnel; obtain actual geological condition information of the second part of the tunnel; wherein the second part of the tunnel is the part of the tunnel to be constructed in the tunnel; optimize and adjust the ventilation system design plan based on the actual ventilation monitoring information and the actual geological condition information to obtain the optimized and adjusted ventilation system design plan.

[0141] In an optional implementation, the climate and environment information includes at least one of the following: altitude information; air pressure information; oxygen content information; temperature information; humidity information; wind speed information; and wind direction information.

[0142] In an optional implementation, the geological and topographic information includes at least one of the following: geological structure information; topographic condition information.

[0143] In one implementation, the second processing module 604 can be used to: perform data cleaning on the ventilation monitoring information to obtain standard monitoring data; input the standard monitoring data, tunnel model and ventilation system design plan into a pre-trained pollutant diffusion prediction model to obtain pollutant diffusion prediction information; wherein the pollutant diffusion prediction model has been pre-trained to obtain the ability to predict pollutant diffusion based on standard monitoring data, tunnel model and ventilation system design plan.

[0144] In an optional implementation, the pollutant diffusion prediction model is pre-trained through the following steps: obtaining multiple initial pollutant concentrations; performing fluid dynamics numerical simulation calculations based on different initial pollutant concentrations and different operating condition data of ventilation equipment in the ventilation system to obtain pollutant diffusion sample results; training the initial pollutant diffusion model based on multiple initial pollutant concentrations, operating condition data and pollutant diffusion sample results to obtain a pollutant diffusion prediction model.

[0145] In one implementation, the ventilation monitoring information includes at least one of the following: pollutant monitoring information; ventilation equipment monitoring information; construction personnel monitoring information; construction equipment monitoring information.

[0146] In one implementation, the third processing module 605 can be used to: determine the pollutant diffusion area based on pollutant diffusion prediction information; obtain target ventilation equipment monitoring information and maximum ventilation efficiency of the target ventilation equipment in the pollutant diffusion area of ​​the ventilation system, as well as target pollutant monitoring information of the pollutant diffusion area based on ventilation monitoring information; determine the current ventilation efficiency of the pollutant diffusion area based on the target ventilation equipment monitoring information; determine the minimum predicted pollutant index of the pollutant diffusion area based on the pollutant monitoring information, the current ventilation efficiency, the maximum ventilation efficiency and the pollutant diffusion prediction information; determine that the minimum predicted pollutant index is greater than or equal to a preset index threshold, and issue an alarm message, or determine that the minimum predicted pollutant index is less than the preset threshold, and control the target air duct based on the predicted pollutant index.

[0147] In one implementation, the construction information includes at least one of construction progress information, construction personnel information, construction equipment information and construction process information. The third processing module 605 can be used to: obtain regional construction personnel information, regional construction equipment information and regional construction process information in the first construction area based on the construction information and construction progress information; wherein the first construction area is any construction area within at least one construction area pre-demarcated in the tunnel based on the construction progress information; determine the regional ventilation demand of the first construction area based on the regional construction personnel information, regional construction equipment information and regional construction process information; and control the ventilation system based on the regional ventilation demand.

[0148] Through the device of the embodiment of the present application, the corresponding ventilation system can be arranged during the construction process based on the ventilation system design scheme corresponding to the tunnel, and the ventilation monitoring information of the ventilation system and the construction information of the tunnel can be obtained; at the same time, based on the tunnel model corresponding to the tunnel, the ventilation system design scheme and the ventilation monitoring information, pollutant diffusion prediction is performed, and pollutant diffusion prediction information in the tunnel is obtained, so as to control the ventilation system based on at least one of the above information. The ventilation system can be intelligently controlled according to the actual situation to ensure the construction safety of the tunnel.

[0149] It should be noted that the aforementioned explanation of the embodiment of the intelligent ventilation method for long tunnels based on a neural network model is also applicable to the intelligent ventilation device for long tunnels based on a neural network model in this embodiment, and will not be repeated here.

[0150] In order to implement the above embodiment, the present application also proposes an electronic device. Figure 7 , Figure 7 Schematic diagram of the structure of the electronic device provided in the embodiment of the present application. Figure 7 As shown, the electronic device 700 includes: a processor 701, and a memory 702 communicatively connected to the processor 701; the memory 702 stores computer-executable instructions; the processor 701 executes the computer-executable instructions stored in the memory to implement the method provided in the aforementioned embodiment.

[0151] In order to implement the above embodiments, the present application also proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the above embodiments.

[0152] In order to implement the above embodiments, the present application also proposes a computer program product, including a computer program, which implements the methods provided by the above embodiments when executed by a processor.

[0153] In the description of this application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; “and / or” in this article is merely a way to describe the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0154] In the description of the aforementioned embodiments, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0155] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0156] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0157] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0158] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0159] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0160] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0161] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A digital-based intelligent ventilation method for long and large tunnels, characterized in that: include: Obtain the ventilation system design plan corresponding to the tunnel; During the construction of the tunnel, the ventilation system design is optimized and adjusted; wherein the ventilation system design after optimization and adjustment is used to arrange the ventilation system during the construction of the tunnel; Acquiring ventilation monitoring information of the ventilation system and construction information of the tunnel; Perform pollutant diffusion prediction based on the tunnel model corresponding to the tunnel, the ventilation system design scheme and the ventilation monitoring information to obtain pollutant diffusion prediction information in the tunnel; The ventilation system is controlled based on at least one of the ventilation monitoring information, the construction information and the pollutant diffusion prediction information.

2. The method according to claim 1, characterized in that The obtaining of the ventilation system design scheme corresponding to the tunnel includes: Obtain the tunnel model, climate and environmental information, geological and topographic information, initial construction information and gas index information corresponding to the tunnel; Acquire a plurality of initial ventilation system design solutions based on the tunnel model, the climate and environment information, the geological and topographic information, and the initial construction information; Acquire solution data corresponding to each of the initial ventilation system design solutions; wherein the solution data includes at least one of different air duct cross-sectional positions, distances from the air duct to the working surface, and air duct diameters; Based on the scheme data corresponding to each of the initial ventilation system design schemes, obtaining evaluation index data corresponding to each of the initial ventilation system design schemes; wherein the evaluation index data includes at least one of wind flow field data and pollutant purification efficiency; The ventilation system design scheme is selected from the plurality of initial ventilation system design schemes based on the evaluation index data.

3. The method according to claim 2, characterized in that The climate and environment information includes at least one of the following: Altitude information; Air pressure information; Oxygen content information; Temperature information; Humidity information; Wind speed information; Wind direction information.

4. The method according to claim 2, characterized in that The geological and topographic information includes at least one of the following: geological structure information; Information on terrain conditions.

5. The method according to claim 1, characterized in that The step of optimizing and adjusting the ventilation system design during the construction of the tunnel includes: Acquire actual ventilation monitoring information of the first ventilation system; wherein the first ventilation system is a ventilation system arranged in the first tunnel, and the first tunnel is a tunnel that has been completed and is under construction in the tunnel; Acquire actual geological condition information of the second part of the tunnel; wherein the second part of the tunnel is a part of the tunnel to be constructed in the tunnel; The ventilation system design scheme is optimized and adjusted based on the actual ventilation monitoring information and the actual geological condition information to obtain the optimized and adjusted ventilation system design scheme.

6. The method according to claim 1, characterized in that The pollutant diffusion prediction is performed based on the tunnel model corresponding to the tunnel, the ventilation system design scheme and the ventilation monitoring information to obtain the pollutant diffusion prediction information in the tunnel, including: Performing data cleaning on the ventilation monitoring information to obtain standard monitoring data; The standard monitoring data, the tunnel model and the ventilation system design plan are input into a pre-trained pollutant diffusion prediction model to obtain the pollutant diffusion prediction information; wherein the pollutant diffusion prediction model has been pre-trained to obtain the ability to predict pollutant diffusion based on the standard monitoring data, the tunnel model and the ventilation system design plan.

7. The method according to claim 6, characterized in that The pollutant diffusion prediction model is pre-trained by the following steps: obtaining multiple initial pollutant concentrations; Based on different initial pollutant concentrations and different operating condition data of ventilation equipment in the ventilation system, fluid dynamics numerical simulation calculations are performed to obtain pollutant diffusion sample results; Based on the multiple initial pollutant concentrations, the operating condition data and the pollutant diffusion sample results, an initial pollutant diffusion model is trained to obtain the pollutant diffusion prediction model.

8. The method according to any one of claims 1 to 6, characterized in that The ventilation monitoring information includes at least one of the following: Pollutant monitoring information; Ventilation equipment monitoring information; Construction personnel monitoring information; Construction equipment monitoring information.

9. The method according to claim 8, characterized in that The controlling the ventilation system based on at least one of the ventilation monitoring information, the construction information and the pollutant diffusion prediction information includes: Determining a pollutant diffusion area based on the pollutant diffusion prediction information; Based on the ventilation monitoring information, acquiring target ventilation equipment monitoring information and maximum ventilation efficiency of the target ventilation equipment in the pollutant diffusion area of ​​the ventilation system, and target pollutant monitoring information of the pollutant diffusion area; Determining the current ventilation efficiency of the pollutant diffusion area based on the target ventilation equipment monitoring information; Determining a minimum predicted pollutant index of the pollutant diffusion area based on the pollutant monitoring information, the current ventilation efficiency, the maximum ventilation efficiency and the pollutant diffusion prediction information; Determine that the minimum predicted pollutant index is greater than or equal to a preset index threshold, issue an alarm message, or determine that the minimum predicted pollutant index is less than the preset threshold, control the target air duct based on the predicted pollutant index.

10. The method according to claim 1, characterized in that The construction information includes at least one of construction progress information, construction personnel information, construction equipment information and construction process information. The controlling of the ventilation system based on at least one of the ventilation monitoring information, the construction information and the pollutant diffusion prediction information includes: Based on the construction information and the construction progress information, obtaining regional construction personnel information, regional construction equipment information and regional construction process information in a first construction area; wherein the first construction area is any one construction area in at least one construction area pre-demarcated in the tunnel based on the construction progress information; Determining the regional ventilation demand of the first construction area based on the regional construction personnel information, the regional construction equipment information and the regional construction process information; The ventilation system is controlled based on the zone ventilation demand.

11. A digital-based intelligent ventilation device for long and large tunnels, characterized in that: include: The first acquisition module is used to obtain a ventilation system design scheme corresponding to the tunnel; A first processing module is used to optimize and adjust the ventilation system design scheme during the construction of the tunnel; wherein the ventilation system design scheme after optimization and adjustment is used to arrange the ventilation system during the construction of the tunnel; A second acquisition module is used to acquire ventilation monitoring information of the ventilation system and construction information of the tunnel; A second processing module is used to predict pollutant diffusion based on a tunnel model corresponding to the tunnel, the ventilation system design scheme and the ventilation monitoring information, and obtain pollutant diffusion prediction information in the tunnel; The third processing module is used to control the ventilation system based on at least one of the ventilation monitoring information, the construction information and the pollutant diffusion prediction information.

12. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method according to any one of claims 1 to 10.

14. A computer program product, characterized in that The method comprises a computer program, which implements the method according to any one of claims 1 to 10 when executed by a processor.

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