A dust concentration control method for tunnel construction of a pumped storage power station

Abstract

The application discloses a dust concentration control method for tunnel construction of a pumped storage power station, and belongs to the technical field of tunnel construction of a pumped storage power station, and comprises the following steps: S1, installing various sensors required by construction sites in an underground cavern group; S2, installing a dust concentration monitoring sensor at an air outlet, which is used for monitoring the dust concentration discharged within a specific time period in real time; S3, establishing an underground cavern group model based on a computational fluid dynamics numerical simulation and a three-dimensional simulation analysis platform, and visually simulating the ventilation air volume, the wind speed and the dust concentration of each main cavern at different construction stages; and S4, constructing a training data set by using field measurement data and CFD numerical simulation results under multiple working conditions of complex cavern linkage ventilation smoke dispersion, and establishing a flue gas dissipation and dust control neural network model. The application can help managers accurately identify a high dust generation stage, so that the construction plan and the air exhaust strategy can be adjusted accordingly.

Description

Technical Field

[0001] This invention belongs to the field of pumped storage hydropower station tunnel construction technology, and in particular, it is a method for controlling dust concentration during pumped storage hydropower station tunnel construction. Background Technology

[0002] A pumped-storage hydroelectric power station is a highly efficient energy storage facility that utilizes surplus electricity during off-peak hours to pump water from a lower reservoir to an upper reservoir, and then releases the water to generate electricity during peak demand periods. These power stations typically include an upper reservoir, a lower reservoir, a water conveyance system (including inlet / outlet ports, pressure pipelines, and surge tanks), an underground powerhouse, a tailrace system, and tunnels and caverns connecting these components. Tunnel construction is a crucial part of the construction process, involving multiple complex procedures such as geological exploration, blasting excavation, support reinforcement, and ventilation / dust removal.

[0003] In the construction of pumped-storage hydropower stations, tunnels are mainly used to connect the upper and lower reservoirs and provide necessary water flow channels for the generator units. Tunnel construction not only needs to deal with complex geological conditions (such as rock strata stability and groundwater level), but also needs to consider how to effectively manage dust and other harmful substances generated during construction to ensure the health and safety of workers.

[0004] During construction, especially after blasting operations, a large amount of dust is generated. If not effectively controlled, this dust not only affects workers' health, but existing ventilation systems lack effective monitoring of dust concentration, making it difficult to assess their actual efficiency. Most ventilation systems focus only on ventilation volume and velocity, neglecting dust concentration monitoring. Ventilation system designs are often based on theoretical calculations rather than actual operational data, leading to discrepancies between actual and expected results. If the ventilation system fails to effectively remove dust, dust concentration in the construction area will continue to rise, increasing worker health risks. Even when ventilation is operating normally, the actual amount of dust discharged is far lower than expected due to the lack of dust concentration monitoring. As a result, dust concentration in the construction area remains high, forcing workers to frequently stop work for cleaning, severely impacting construction progress. Summary of the Invention

[0005] The purpose of this invention is to provide a method for controlling dust concentration during the construction of pumped storage hydropower station tunnels, in order to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for controlling dust concentration during tunnel construction of a pumped storage hydropower station, comprising the following steps:

[0007] S1: Install various sensors required for construction sites in the underground cavern complex to monitor ventilation volume, wind speed and dust concentration in the tunnel in real time;

[0008] S2: Install dust concentration monitoring sensors at the exhaust vents to monitor the dust concentration discharged within a specific time period in real time. By comparing and analyzing these three datasets (discharge, remaining, and generated dust concentrations) based on the dust concentration values ​​remaining in the cavern during that time period and the dust concentration generated at the current stage, it is possible to accurately identify which construction stage generates more dust and the efficiency of the ventilation system in the cavern during that stage of construction.

[0009] S3: Establish an underground cavern group model based on computational fluid dynamics (CFD) numerical simulation and three-dimensional simulation analysis platform (Ventsim), visualize the ventilation volume, wind speed and dust concentration of each main cavern at different construction stages, and verify and correct the model based on on-site measured data;

[0010] S4: Utilize on-site measured data and CFD numerical simulation results under various working conditions of complex cavern ventilation and smoke dispersion to construct a training dataset, establish a neural network model for smoke dissipation and dust control. This model can intelligently formulate the optimal solution (control scheme) for the control of toxic gases and dust at the working face, and realize intelligent control and adjustment of ventilation equipment and parameters.

[0011] In this preferred embodiment, during construction, the dust concentration generated at the current construction stage is monitored in real time, and a dust floating path range is determined with the construction center point as the center. Based on this path range, a model is built to calculate the dust concentration center point and multiple dust concentration edge points.

[0012] In this preferred embodiment, the dust concentration edge point represents the boundary area of ​​this path range, where the concentration is lower than that of the center point. Workers should prioritize working at these edge points with lower dust concentrations. When an edge point becomes a new center point after construction, the worker needs to move to another edge point within the previous dust path range to continue working. This process is repeated to ensure that workers are always working in a safe area where the dust concentration is lower than that of the center point or the warning value, thereby protecting the health of the workers.

[0013] In this preferred embodiment, after establishing the dust concentration center point and dust concentration edge point, the dust generated at this stage mixes with the remaining dust in the cavern. Even after mixing, the dust is discharged through exhaust ventilation, which does not affect the establishment and monitoring of the dust concentration center point and dust concentration edge point. When the concentration of the remaining dust and the dust generated at this stage exceeds the warning value, an alarm mechanism will be activated.

[0014] The preferred approach in this scheme involves real-time monitoring and calculation of a dust concentration distribution model, with the construction center point as the reference point. With center at and radius at, The circular region is defined as the dust floating path range. Within this range, the dust concentration distribution is estimated using a Gaussian diffusion model.

[0015]

[0016] in, Indicates distance from the center point for Dust concentration at the location;

[0017] It is the center point Maximum dust concentration at the location;

[0018] It is the standard deviation, which reflects the degree of dust diffusion.

[0019] In this preferred embodiment, when the concentration of the mixed dust exceeds the preset warning value, the system will automatically trigger an alarm mechanism to notify relevant personnel to take further measures. The exhaust system will discharge some dust during operation; assuming the exhaust efficiency is:

[0020]

[0021] Indicates the efficiency of the ventilation system;

[0022] It is the total amount of dust discharged through the ventilation system within a certain period of time;

[0023]

[0024] The preferred approach in this scheme is that at each time step... Recalculate dust concentration distribution:

[0025]

[0026] in, It represents the increase in dust concentration newly generated within the current time step. Based on the latest dust concentration distribution, the center point of dust concentration is redefined. and multiple dust concentration edge points

[0027]

[0028] in, This indicates the location with the highest dust concentration;

[0029] This represents the set of locations where the dust concentration is below a threshold.

[0030] In a preferred embodiment of this scheme, the method further integrates Web, GIS, BIM, and visualization to construct an intelligent management platform that coordinates the Internet of Things (IoT), wireless local area network, and cloud platform for forecasting, prediction, and intelligent control of the construction environment inside the tunnel.

[0031] In this preferred embodiment, the intelligent management platform includes a three-dimensional simulation for visually displaying the ventilation volume, wind speed, and dust concentration of each main chamber in different construction stages of a large pumped storage cavern.

[0032] In a preferred embodiment of this solution, the intelligent management integrated platform further includes on-site monitoring and artificial intelligence training. By integrating real-time data from sensors of various gases, smoke, and harmful gases provided by the monitoring system with simulation model calculation results, a neural network evaluation model is constructed.

[0033] Compared with the prior art, the technical effects and advantages of the present invention are as follows:

[0034] This dust concentration control method for pumped-storage hydropower station tunnel construction utilizes multiple sensors (such as anemometers and dust concentration sensors) installed in the underground cavern complex. This allows for real-time monitoring of ventilation volume, wind speed, and dust concentration within the tunnel. The sensors transmit data to a central control system via an Internet of Things (IoT) platform. The system processes and analyzes the data in real time, generating visualized reports for decision-making reference. In contrast, traditional construction environments typically rely on limited fixed sensors or manual sampling, failing to comprehensively reflect the dust distribution across the entire construction area. This method achieves comprehensive monitoring of all key locations within the construction area, ensuring data real-time accuracy. Workers and managers can readily grasp the current environmental conditions and take timely measures to address areas with high dust concentrations.

[0035] This technical solution continuously monitors the concentration of exhaust dust using sensors at the exhaust vents and sends the data to a central control system. The system then uses data analysis algorithms to compare three datasets to identify the source and distribution of dust. By monitoring the dust concentration emitted within a specific time period in real time, and comparing the remaining dust concentration in the cavern with the dust concentration generated at that stage, the system can accurately identify which construction stage generates the most dust and the efficiency of the cavern's exhaust system during that stage. This improves the accuracy of the exhaust system's efficiency assessment, helping managers accurately identify high-dust-generating stages and adjust construction plans and exhaust strategies accordingly.

[0036] A model of the underground cavern complex was established using computational fluid dynamics numerical simulation and 3D simulation analysis platform. The ventilation volume, wind speed, and dust concentration of each major cavern at different construction stages were visualized and simulated. The model was verified and corrected based on on-site measured data, providing more accurate ventilation design and optimization suggestions. This reduced the dust accumulation problem caused by unreasonable design and improved the overall safety of the construction environment. Attached Figure Description

[0037] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0038] Figure 1 A flowchart of a dust concentration control method for tunnel construction of a pumped storage hydropower station according to the present invention;

[0039] Figure 2 This is a flowchart of the dust concentration monitoring and early warning system of the present invention;

[0040] Figure 3 This is a flowchart of the ventilation design optimization based on CFD numerical simulation of the present invention;

[0041] Figure 4 This is a flowchart illustrating the establishment and application of the neural network model of the present invention.

[0042] Figure 5 This is a flowchart illustrating the dynamic adjustment of worker work positions according to the present invention. Detailed Implementation

[0043] In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the invention. However, it will be apparent to those skilled in the art that the invention can be practiced without one or more of these details. In other instances, certain technical features well-known in the art have not been described in order to avoid obscuring the invention.

[0044] Unless otherwise defined, the directions mentioned herein, such as up, down, left, right, front, back, inside, and outside, are based on the directions shown in the figures of this invention, and are explained here together.

[0045] This embodiment provides, for example Figures 1 to 5 This paper presents a method for controlling dust concentration during the construction of a pumped storage hydropower station tunnel.

[0046] Multiple sensors (such as anemometers and dust concentration sensors) are installed in the underground cavern complex to monitor ventilation volume, wind speed, and dust concentration in the tunnel in real time. Additionally, dust concentration monitoring sensors are installed at the exhaust vents to monitor the concentration of dust emitted within a specific time period. By comparing and analyzing three datasets (i.e., the concentration of emitted dust, the current remaining dust, and the dust generated at this stage), it is possible to accurately identify which construction stage generates the most dust and the efficiency of the cavern's ventilation system during that stage. The sensors at the exhaust vents continuously monitor the emitted dust concentration and send the data to the central control system. The central control system compares and analyzes data from different time periods to determine the source and distribution of dust, sets the data acquisition cycle for the sensors (e.g., once per hour), and uploads the data to the central control system. Data analysis algorithms (such as difference analysis) are then used to compare the three datasets to identify the source and distribution of dust.

[0047] A model of an underground cavern complex was established using computational fluid dynamics (CFD) numerical simulation and a 3D simulation analysis platform (Ventsim). The ventilation volume, wind speed, and dust concentration of each major cavern at different construction stages were visualized and simulated. The model was verified and corrected based on on-site measured data. CFD software was used for numerical simulation to generate a 3D model and predict ventilation effects. The model was then calibrated using actual monitoring data to improve its accuracy. This modeling method can more accurately predict dust diffusion paths and concentration distribution, thereby optimizing the design and operation strategies of the ventilation system.

[0048] During construction, the dust concentration generated at each construction stage is monitored in real time. A dust dispersion path is defined with the construction center point as the center. A model is built based on this path to calculate the dust concentration center point and multiple dust concentration edge points. These edge points represent the boundary areas of the path, where the dust concentration is lower than that at the center point. Workers should prioritize working at these edge points with lower dust concentrations. When an edge point becomes a new center point after construction, the worker must move to another edge point within the previous dust dispersion path to continue working. This process is repeated to ensure that workers are always within a safe area where the dust concentration is below the center point or the warning value, thus protecting worker health. Determining the dust dispersion path based on real-time monitoring results guides workers to prioritize work at edge points with lower dust concentrations, reducing the risk of exposure to high dust concentrations. Dynamically adjusting worker positions ensures they are always in low-dust-concentration areas, improving overall construction efficiency.

[0049] After establishing the dust concentration center point and dust concentration edge point, the dust generated at this stage will mix with the remaining dust in the cavern. Even after mixing, the dust will be exhausted through ventilation, which will not affect the establishment and monitoring of the dust concentration center point and dust concentration edge point. When the combined concentration of the remaining dust and the dust generated at this stage exceeds the warning value, an alarm mechanism will be activated to notify relevant personnel to take further measures. For example, setting a dust concentration warning value (e.g., 5 mg / m³). 3 The system monitors dust concentration in real time and compares it with the warning value. When the concentration exceeds the warning value, the system automatically issues an alarm and records the event.

[0050] By real-time monitoring and calculation of the dust concentration distribution model, a construction center point is set. With center at and radius at, The circular region is defined as the dust floating path range. Within this range, the dust concentration distribution is estimated using a Gaussian diffusion model.

[0051]

[0052] in, Indicates distance from the center point for Dust concentration at the location;

[0053] It is the center point Maximum dust concentration at the location;

[0054] It is the standard deviation, which reflects the degree of dust diffusion.

[0055] When the concentration of the mixed dust exceeds the preset warning value, the system will automatically trigger an alarm mechanism to notify relevant personnel to take further measures. The exhaust system will discharge some dust during operation; assuming the exhaust efficiency is:

[0056]

[0057] Indicates the efficiency of the ventilation system;

[0058] It is the total amount of dust discharged through the ventilation system within a certain period of time;

[0059]

[0060] At each time step Recalculate the dust concentration distribution:

[0061]

[0062] in, It represents the increase in dust concentration newly generated within the current time step;

[0063] Based on the latest dust concentration distribution, the dust concentration center point has been redefined. and multiple dust concentration edge points

[0064] ;

[0065] in, This indicates the location with the highest dust concentration;

[0066] This represents the set of locations where the dust concentration is below a threshold.

[0067] Analyze the layout and efficiency of the current exhaust system, adjust the location and power of the exhaust system according to the dust concentration distribution, and dynamically adjust the exhaust strategy to ensure that the dust concentration at the edge point is kept at the lowest level.

[0068] The aforementioned methods are used to determine the main ventilation parameters, including required air volume, air velocity, and air pressure, within the underground cavern complex, in order to propose the necessary ventilation solutions for the construction site. The intelligent management platform also includes a 3D simulation function, used to visualize the ventilation volume, air velocity, and dust concentration of each main cavern at different construction stages of the large pumped storage cavern. Furthermore, the intelligent management platform includes on-site monitoring and artificial intelligence training functions, constructing a neural network evaluation model by integrating real-time data from various gas, smoke, and harmful gas sensors provided by the monitoring system with simulation model calculation results.

[0069] It should be noted that, in this document, relational terms such as "one" and "two" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, the phrase "comprising an element defined as..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0070] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for controlling dust concentration during tunnel construction in a pumped-storage hydropower station, characterized in that, Includes the following steps: S1: Install various sensors required for construction sites in the underground cavern complex to monitor ventilation volume, wind speed and dust concentration in the tunnel in real time; S2: Install a dust concentration monitoring sensor at the exhaust vent to monitor the dust concentration discharged within a specific time period in real time. Based on the dust concentration value remaining in the cavern during that time period and the dust concentration generated at the current stage, by comparing and analyzing the dust concentration of the three datasets of discharged, remaining, and generated at the current stage, it is possible to accurately identify which construction stage generates more dust and the efficiency of the ventilation system in the cavern during construction at that stage. S3: Establish an underground cavern group model based on a computational fluid dynamics numerical simulation and three-dimensional simulation analysis platform, visualize the ventilation volume, wind speed and dust concentration of each major cavern at different construction stages, and verify and correct the model based on on-site measured data; S4: Construct a training dataset using on-site measured data and CFD numerical simulation results under various working conditions of complex cavern ventilation and smoke dispersion, and establish a neural network model for smoke dissipation and dust control. S5: The neural network model for flue gas dissipation and dust control can intelligently formulate control schemes for toxic gases and dust at the working face, and realize intelligent control and adjustment of ventilation equipment and parameters.

2. The method for controlling dust concentration during tunnel construction of a pumped storage hydropower station according to claim 1, characterized in that: During construction, by monitoring the dust concentration generated at the current construction stage in real time, and taking the construction center point as the center, a dust floating path range is determined. Based on this path range, a model is built to calculate the dust concentration center point and multiple dust concentration edge points.

3. The method for controlling dust concentration during tunnel construction of a pumped storage hydropower station according to claim 2, characterized in that: The dust concentration edge points refer to the boundary areas of this path range, where the concentration is lower than that at the center point. Workers should prioritize working at these edge points with lower dust concentrations.

4. The dust concentration control method for tunnel construction of a pumped storage hydropower station according to claim 3, characterized in that: After establishing the dust concentration center point and dust concentration edge point, the dust generated at this stage mixes with the remaining dust in the cave and is discharged through exhaust ventilation. When the concentration of the remaining dust and the dust generated at this stage exceeds the warning value, the alarm mechanism will be activated.

5. The dust concentration control method for tunnel construction of a pumped storage hydropower station according to claim 4, characterized in that: By real-time monitoring and calculation of the dust concentration distribution model, a construction center point is set. With center at and radius at, The circular region is defined as the dust floating path range. Within this range, the dust concentration distribution is estimated using a Gaussian diffusion model. in, Indicates distance from the center point for Dust concentration at the location; It is the center point The maximum dust concentration at the location; It is the standard deviation, which reflects the degree of dust diffusion.

6. The dust concentration control method for tunnel construction of a pumped storage hydropower station according to claim 5, characterized in that: When the concentration of the mixed dust exceeds the preset warning value, the system will automatically trigger an alarm mechanism to notify relevant personnel to take further measures. The exhaust system will discharge some dust during operation; assuming the exhaust efficiency is: Indicates the efficiency of the ventilation system; It is the total amount of dust discharged through the ventilation system within a certain period of time; 。 7. The dust concentration control method for tunnel construction of a pumped storage hydropower station according to claim 6, characterized in that: At each time step Recalculate dust concentration distribution: in, It represents the increase in dust concentration newly generated within the current time step. Based on the latest dust concentration distribution, the center point of dust concentration is redefined. And multiple dust concentration edge points: in, This indicates the location with the highest dust concentration; This represents the set of locations where the dust concentration is below a threshold.

8. The method for controlling dust concentration during tunnel construction of a pumped storage hydropower station according to claim 7, characterized in that: The method also combines Web, GIS, BIM and visualization to build an intelligent management platform that coordinates the Internet of Things, wireless LAN and cloud platform for forecasting and intelligent control of the tunnel construction environment.

9. A method for controlling dust concentration during tunnel construction of a pumped storage hydropower station according to claim 8, characterized in that: The intelligent management platform includes a three-dimensional simulation for visually displaying the ventilation volume, wind speed, and dust concentration of each main chamber at different construction stages of the pumped storage large cavern.

10. A method for controlling dust concentration during tunnel construction of a pumped storage hydropower station according to claim 9, characterized in that: The intelligent management platform also includes a neural network evaluation model constructed by integrating real-time data from sensors monitoring various gases, smoke, and harmful gases with simulation model calculation results.

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