Early warning system for water intake of nuclear power plant blocked by algae

Abstract

The invention discloses an early warning system for algae blocking of a water intake of a nuclear power plant, and relates to the technical field of alarm devices, the early warning system comprises an alarm device, the alarm device is in communication connection with a data acquisition module, an FVCOM model module, a prediction correction module, a warning line setting module, a real-time display module, a ship AIS information integration module and a decision support module, the modules are in electric signal connection; the data acquisition module is used for collecting various data related to algae growth and marine environment. By monitoring and predicting the algae drifting path in real time, the nuclear power plant is ensured to know the algae distribution condition around the water intake in time, the high-precision FVCOM model and the satellite remote sensing technology are utilized, and the GIS platform is combined to dynamically display the algae motion state in real time, so that the nuclear power plant can find the potential blocking risk in advance, and the safety of the nuclear power plant is improved. The operation safety of the nuclear power plant is remarkably improved, the influence of algae blockage is avoided, and stable power generation of the nuclear power plant is guaranteed.

Description

Technical Field

[0001] The invention relates to the technical field of alarm devices, and in particular to an early warning system for algae blocking a water intake of a nuclear power plant. Background Art

[0002] With global warming and complex changes in the marine environment, spring and summer have become the peak seasons for explosive algae reproduction. The massive reproduction of these algae not only affects the ecological balance of the ocean, but also poses a serious threat to the safe operation of nuclear power plants. Algae block the water intake of nuclear power plants, which will directly lead to insufficient water intake in the cooling system, thereby reducing the working performance of the cooling system and ultimately affecting the overall power generation efficiency of the nuclear power plant.

[0003] In the existing technology, there is a lack of effective early warning and alarm means to deal with the problem of algae blocking the water intake of nuclear power plants. Therefore, how to predict and correct the drift path of algae and specifically alarm the algae blockage state is the problem we need to solve. To this end, an algae blockage nuclear power plant water intake early warning system is proposed. Summary of the invention

[0004] The purpose of the present invention is to provide an early warning system for algae blocking the water intake of a nuclear power plant, so as to solve the problems raised in the above-mentioned background technology.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is: An early warning system for algae blocking a water intake of a nuclear power plant comprises an alarm device, wherein the alarm device is communicatively connected with a data acquisition module, an FVCOM model module, a prediction and correction module, a warning line setting module, a real-time display module, a ship AIS information integration module and a decision support module, wherein electrical signals are connected between the modules; The data acquisition module is used to collect various data related to algae growth and marine environment, use satellite remote sensing technology to monitor the distribution and drift of algae in the sea area in real time, provide real-time data of algae coverage areas, and provide comprehensive and accurate basic data support for subsequent model prediction; The FVCOM model module is used to simulate and predict algae drift using the hydrodynamic module and particle tracking module of the FVCOM model, wherein the hydrodynamic module provides a simulation of the three-dimensional tidal field in the prediction area, and the particle tracking module uses Lagrangian technology to simulate and predict the migration path of algae, providing refined ocean flow field information to improve the prediction accuracy; in particular, the grid resolution of the water intake is not less than 20m, and the grid resolution within a radius of 10km from the water inlet is not less than 100m; The prediction and correction module is used to predict the algae drift path using the FVCOM model module, and to correct the particle drift trajectory predicted by the model for the next day using the remote sensing satellite images of the day, thereby improving the accuracy and timeliness of the prediction of the algae drift trajectory through continuous prediction and correction cycles; The warning line setting module is used to set warning lines of different radii around the water intake of the nuclear power plant, distinguish different disaster levels, and provide clear warning thresholds for the alarm device to facilitate timely preventive measures. The warning lines of different radii are 1000m, 500m, 200m and 100m respectively; The real-time display module is used to display the information of ocean currents, drift trajectories of algae and water intake warning lines based on the GIS platform and in combination with satellite images, and to dynamically display the movement status of algae in real time. When the algae enter the warning line, the alarm device triggers an alarm to remind relevant personnel to take preventive measures. The ship AIS information integration module is used to superimpose the ship AIS information into the alarm device, and combine it with the algae drift track to display the real-time position and dynamics of the ship in the sea area, helping decision makers to consider the navigation situation of the ship when formulating preventive measures; The decision support module is used to provide decision makers with preventive and response measures based on the output information of the alarm device and the ship's AIS information, ensuring that when the risk of algae blockage occurs, the nuclear power plant can respond quickly and effectively to reduce the losses caused by algae blockage.

[0006] A further improvement of the technical solution of the present invention is that in the data acquisition module, the process of collecting algae growth and marine environment data is as follows: Determine the target sea area, use the remote sensing sensors carried by the satellite to scan the target sea area in real time, monitor the drift and distribution of algae in the sea area in real time, and obtain algae data and marine environment data; The collected remote sensing data is transmitted to the alarm device, and the received satellite remote sensing data is preprocessed, including radiation correction, geometric correction and atmospheric correction steps, to eliminate the influence of various interference factors on data quality; Analyze the preprocessed images, identify and classify algae, and extract geographic information of the algae coverage area; The various types of data collected are integrated to form a complete algae growth and marine environment data set, and stored in a data warehouse.

[0007] A further improvement of the technical solution of the present invention is that in the FVCOM model module, the process of simulating and predicting algae drift is: Obtain and process the terrain data and shoreline data of the target area. The terrain data and shoreline data are the basis for model construction. According to the needs, the target area is gridded so that the grid resolution of the water intake of the nuclear power plant and its surrounding areas meets the needs. The grid resolution of the water intake is not less than 20m, and the grid resolution within a radius of 10km from the water inlet is not less than 100m. Configure the parameters of the FVCOM model, including the relevant settings of the hydrodynamic module and particle tracking module; The hydrodynamic module of the FVCOM model is used to simulate the three-dimensional tidal field in the prediction area. Based on the given initial flow field, initial conditions of the temperature field and boundary conditions of the current speed, direction, temperature and salinity, the three-dimensional tidal field in the study area is simulated. The Lagrangian particle tracking technology is used to treat algae as particles and track them in the simulated three-dimensional tidal field. According to the movement trajectory of the particles, combined with the flow velocity, flow direction, and turbulent diffusion factors, the migration path and distribution range of the algae are predicted. Combined with the simulation results of the hydrodynamic module, the algae drift process is simulated in a refined manner to improve the prediction accuracy. The particles in the fluid are tracked according to the particle tracking equation, and the movement trajectory of the particles in the fluid is calculated. The specific expression is: ; in, is the particle position, i is the fluid velocity at that position, is the rate of change of the particle's position with time; Visualization tools are used to display and analyze the simulation results, and the simulation results are compared and verified with the measured data to evaluate the reliability and accuracy of the model.

[0008] The further improvement of the technical solution of the present invention is: based on the Navier-Stokes equation, the fluid velocity field is calculated, and the calculation is performed according to the continuity equation to ensure the conservation of mass, describe the change of fluid density with time and space, and the compressibility of the fluid, and the specific expression is: ; ; Where u is the fluid velocity vector, p is the pressure, is the fluid density, is the dynamic viscosity coefficient, f is the body force, is the sea level, is the partial derivative of the fluid velocity with time, is the gradient tensor of the fluid velocity, is the Laplace operator; Through fine grid division and high-precision numerical simulation algorithm, the simulation results reflect the flow field characteristics of the water intake of the nuclear power plant and its surrounding areas. The heat transfer and conversion in the ocean are described according to the thermodynamic equation, including heat diffusion, convection and source / sink terms, to achieve the simulation of the ocean temperature field. The specific expression is: ; Where T is the temperature, is the specific heat capacity, a is the thermal diffusivity, and Q is the heat source / sink; The salinity equation is used to describe the diffusion and source / sink process of salinity in the ocean and analyze the distribution and change of ocean salinity. The specific expression is: ; Where S is the salinity, K is the salt diffusion coefficient, is a salinity source / sink; According to the turbulence model, turbulent diffusion is described and calculated, and the effective viscosity and diffusion coefficient are calculated. The specific expressions are: k transport equation: ; Transport equation: ; where k is the turbulent kinetic energy, is the turbulent dissipation rate, is the turbulent viscosity coefficient, is the turbulence generation rate, is a constant in the turbulence model, and is a constant in the turbulence model.

[0009] A further improvement of the technical solution of the present invention is that in the prediction and correction module, the process of correcting the particle drift trajectory predicted by the model on the second day is: According to the collected historical data, the initial conditions of the FVCOM model are set, including ocean current field, temperature, salinity, and density. The FVCOM model is used to predict the drift path of algae and simulate the movement trajectory of algae particles in the ocean. Output the predicted algae drift trajectory data for the next day, and process the remote sensing satellite data of the day to extract the algae distribution information; Compare the algae drift trajectory predicted by the FVCOM model with the algae distribution in the remote sensing data, identify the difference areas, adjust the model parameters, adjust the flow field and wind field parameters of the FVCOM model according to the difference areas, and re-run the model for correction; The above prediction and correction process is repeated until the preset accuracy or number of cycles is reached, and the corrected algae drift trajectory is output for use.

[0010] A further improvement of the technical solution of the present invention is that: the model correction includes position correction, drift speed correction and direction correction; The position correction adjusts the particle position to match the actual position of the algae in the remote sensing data, and its expression is: ; ; in, is the position correction, is the position predicted by the model, is the observation location, It is the position difference; The drift velocity correction is performed by adjusting the particle drift velocity to reflect the actual observed algae drift velocity, and its expression is: ; in, is the speed correction, is the speed predicted by the model, is the observed velocity, k is the adjustment factor used to determine the strength of the correction; The direction correction is achieved by adjusting the particle drift direction to match the actual observed algae drift direction, and its expression is: ; ; in, is the direction correction, is the predicted direction, is the observation direction, It is a directional difference.

[0011] A further improvement of the technical solution of the present invention is that in the warning line setting module, the process of dividing the warning lines of different radii is as follows: Determine the sea area where the cordon needs to be set up based on the geographical location and operational requirements of the nuclear power plant's water intake; According to the actual situation and potential disaster risks of the water intake of the nuclear power plant, based on the historical disaster data, topography, the importance of the water intake and the comprehensive analysis of the surrounding environmental factors, four warning lines with different radii are set, namely 1000m, 500m, 200m and 100m, and the disaster levels represented by the warning lines with different radii are defined, among which the 1000m radius represents the low risk warning level, the 500m radius represents the medium risk warning level, the 200m radius represents the high risk warning level, and the 100m radius represents the extremely high risk warning level; On the GIS platform, according to the defined disaster levels, warning lines with radii of 1000m, 500m, 200m and 100m were drawn around the water intake of the nuclear power plant, and the boundaries of each warning area were marked.

[0012] A further improvement of the technical solution of the present invention is that: in the real-time display module, the process of real-time dynamic display of the movement state of algae is: Integrate high-resolution satellite image data as a background layer, and obtain real-time ocean current data. Generate ocean current arrows through model calculation or measured data to display the direction and speed of water flow in the sea area. At the same time, based on ocean current data and algae characteristics, establish an algae drift trajectory model to simulate and display the movement status of algae in real time; Overlay satellite images and ocean current data with warning lines, track the drifting trajectory of algae in real time, and compare and analyze it with the warning line. When the algae trajectory is predicted to enter or has entered the warning line area, the early warning mechanism is automatically triggered. Once algae enters the cordon area, the alarm device will send out an alarm signal through sound alarms, flashing lights, and text message notifications to remind relevant personnel to pay attention and take necessary preventive measures.

[0013] A further improvement of the technical solution of the present invention is that in the ship AIS information integration module, the process of displaying the real-time position and dynamics of the ship in the sea area is: Through AIS receiving equipment, the AIS information of ships in nearby waters is captured in real time. AIS information includes dynamic information such as ship name, call sign, MMSI code, ship position, speed, and heading, as well as static information such as ship type, length, and width; Parse and pre-process the received AIS information to extract key information, including the ship's real-time position, speed, and heading, and verify the accuracy and completeness of the information; The pre-processed AIS data is fused with the drift trajectory of algae, and the AIS data is integrated on the GIS platform to ensure that the data can be correctly displayed in the geographic information system, and the real-time position and dynamics of the ship, as well as the distribution and drift trend of the algae are intuitively displayed in the form of maps and charts; The integrated information is connected to the alarm device to analyze the relationship between the ship's position and the drift trajectory of the algae, and to evaluate the risk of conflict between the ship and the algae blockage area. When the ship approaches or enters the algae blockage area, the alarm device automatically triggers an alarm signal to remind people to pay attention and take corresponding preventive measures, adjust the ship's route or issue a navigation warning.

[0014] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art: The present invention provides an early warning system for algae clogging a water intake of a nuclear power plant. By real-time monitoring and predicting the drift path of algae, the nuclear power plant is ensured to timely understand the distribution of algae around the water intake. The high-precision FVCOM model and satellite remote sensing technology are used in combination with a GIS platform to dynamically display the movement status of algae in real time, so that the nuclear power plant can discover potential blockage risks in advance, significantly improving the operational safety of the nuclear power plant, avoiding the impact of algae blockage, and ensuring stable power generation of the nuclear power plant.

[0015] The present invention provides an early warning system for algae blocking a water intake of a nuclear power plant. By integrating ship AIS information, prediction of algae drift trajectory and real-time display function of a GIS platform, the timeliness and accuracy of early warning are greatly improved, and the distribution and drift of algae in the sea area are monitored in real time. Once it is predicted that algae may approach or block the water intake of a nuclear power plant, an alarm mechanism is immediately triggered. Compared with traditional manual monitoring or regular inspections, potential risks can be discovered earlier, and valuable response time can be gained for decision makers. At the same time, combined with ship AIS information, the system can also accurately determine the relative position of the ship and the algae area, further improving the accuracy of early warning and reducing the probability of false alarms and missed alarms.

[0016] The present invention provides an early warning system for algae clogging a water intake of a nuclear power plant. By setting warning lines of different radii, a clear early warning threshold is provided for the nuclear power plant. When the algae enter the warning line, an alarm is triggered to remind relevant personnel to take preventive measures, so that the nuclear power plant can respond quickly, formulate and implement emergency plans. By optimizing the emergency response mechanism, the nuclear power plant can more effectively manage algae clogging incidents and reduce the impact on power generation efficiency and the environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0018] Figure 1 It is a module structure diagram of the present invention; Figure 2 A flow chart for collecting algae growth and marine environment data of the present invention; Figure 3 A flow chart for simulating and predicting algae drift in the present invention; Figure 4 The present invention is a flow chart for correcting the particle drift trajectory predicted by the model on the second day. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] Examples, such as Figure 1-4 As shown, the present invention provides an early warning system for algae blocking a water intake of a nuclear power plant, including an alarm device, the alarm device is communicatively connected with a data acquisition module, an FVCOM model module, a prediction correction module, a warning line setting module, a real-time display module, a ship AIS information integration module and a decision support module, wherein the modules are connected by electrical signals; The data acquisition module is used to collect various data related to algae growth and marine environment, use satellite remote sensing technology to monitor the distribution and drift of algae in the sea area in real time, provide real-time data of algae coverage area, and provide comprehensive and accurate basic data support for subsequent model predictions. The target sea area is determined, and the target sea area is scanned in real time by remote sensing sensors carried by satellites. The drift and distribution of algae in the sea area are monitored in real time, and algae data and marine environment data are obtained. The collected remote sensing data is transmitted to the alarm device, and the received satellite remote sensing data is pre-processed, including radiation correction, geometric correction and atmospheric correction steps, to eliminate the influence of various interference factors on data quality, analyze the pre-processed images, identify and classify algae, extract the geographic information of the algae coverage area, integrate the various types of collected data to form a complete algae growth and marine environment data set, and store it in the data warehouse; The FVCOM model module is used to simulate and predict the drift of algae using the hydrodynamic module and particle tracking module of the FVCOM model. The hydrodynamic module provides simulation of the three-dimensional tidal field in the prediction area, and the particle tracking module uses Lagrangian technology to simulate and predict the migration path of algae, providing refined ocean flow field information to improve the prediction accuracy; ensuring that the flow field simulation at the water intake of the nuclear power plant and its surrounding areas has high accuracy, especially the grid resolution of the water intake is not less than 20m, and the grid resolution within a radius of 10km from the water inlet is not less than 100m; obtaining and processing the terrain data and shoreline data of the target area, terrain data and The shoreline data is used as the basis for model construction, and the target area is gridded according to the requirements, so that the grid resolution of the water intake of the nuclear power plant and its surrounding areas meets the requirements. Among them, the grid resolution of the water intake is not less than 20m, and the grid resolution within a radius of 10km from the water inlet is not less than 100m. The parameters of the FVCOM model are configured, including the relevant settings of the hydrodynamic module and the particle tracking module. The hydrodynamic module of the FVCOM model is used to simulate the three-dimensional tidal field of the prediction area. Based on the given initial flow field, initial conditions of the temperature field and boundary conditions of the current speed, direction, temperature and salinity, the three-dimensional tidal field of the study area is simulated. Furthermore, based on the Navier-Stokes equation, the fluid velocity field is calculated, and the continuity equation is used to ensure mass conservation, describe the change of fluid density with time and space, and the compressibility of the fluid. The specific expression is: ; ; Where u is the fluid velocity vector, p is the pressure, is the fluid density, is the dynamic viscosity coefficient, f is the body force, is the sea level, is the partial derivative of the fluid velocity with time, is the gradient tensor of the fluid velocity, is the Laplace operator; Through fine grid division and high-precision numerical simulation algorithm, the simulation results reflect the flow field characteristics of the water intake of the nuclear power plant and its surrounding areas. The heat transfer and conversion in the ocean are described according to the thermodynamic equation, including heat diffusion, convection and source / sink terms, to achieve the simulation of the ocean temperature field. The specific expression is: ; Where T is the temperature, is the specific heat capacity, a is the thermal diffusivity, and Q is the heat source / sink; The salinity equation is used to describe the diffusion and source / sink process of salinity in the ocean and analyze the distribution and change of ocean salinity. The specific expression is: ; Where S is the salinity, K is the salt diffusion coefficient, is a salinity source / sink; According to the turbulence model, turbulent diffusion is described and calculated, and the effective viscosity and diffusion coefficient are calculated. The specific expressions are: k transport equation: ; Transport equation: ; where k is the turbulent kinetic energy, is the turbulent dissipation rate, is the turbulent viscosity coefficient, is the turbulence generation rate, is a constant in the turbulence model, and is a constant in the turbulence model; Furthermore, the Lagrangian particle tracking technology is used to treat algae as particles and track them in the simulated three-dimensional tidal field. According to the movement trajectory of the particles, combined with the flow velocity, flow direction, and turbulent diffusion factors, the migration path and distribution range of the algae are predicted. Combined with the simulation results of the hydrodynamic module, the algae drift process is simulated in a refined manner to improve the prediction accuracy. The particles in the fluid are tracked according to the particle tracking equation, and the movement trajectory of the particles in the fluid is calculated. The specific expression is: ; in, is the particle position, i is the fluid velocity at that position, It is the rate of change of particle position over time. The simulation results are displayed and analyzed using visualization tools, and the simulation results are compared and verified with the measured data to evaluate the reliability and accuracy of the model; A prediction and correction module is used to predict the drift path of algae using the FVCOM model module, and to correct the particle drift trajectory of the next day predicted by the model through the remote sensing satellite image of the day. Through continuous prediction and correction cycles, the accuracy and timeliness of the prediction of the algae drift trajectory are improved, and the reliability of the alarm device is ensured. According to the collected historical data, the initial conditions of the FVCOM model are set, including the ocean flow field, temperature, salinity, and density. The FVCOM model is used to predict the drift path of algae, simulate the movement trajectory of algae particles in the ocean, output the predicted algae drift trajectory data of the next day, and process the remote sensing satellite image data of the day to extract the algae distribution information. The algae drift trajectory predicted by the FVCOM model is compared with the algae distribution in the remote sensing data, the difference area is identified, and the model parameters are adjusted. According to the difference area, the flow field and wind field parameters of the FVCOM model are adjusted, and the model is re-run for correction. The above prediction and correction process is repeated until the preset accuracy or number of cycles is reached, and the corrected algae drift trajectory is output for use; Furthermore, the model correction includes position correction, drift velocity correction and direction correction; Position correction is performed by adjusting the particle position to match the actual position of the algae in the remote sensing data. The expression is: ; ; in, is the position correction, is the position predicted by the model, is the observation location, It is the position difference; The drift velocity correction adjusts the particle drift velocity to reflect the actual observed algae drift velocity, and its expression is: ; in, is the speed correction, is the speed predicted by the model, is the observed velocity, k is the adjustment factor used to determine the strength of the correction; Direction correction adjusts the particle drift direction to match the actual observed algae drift direction, and its expression is: ; ; in, is the direction correction, is the predicted direction, is the observation direction, It is a directional difference; The warning line setting module is used to set warning lines of different radius around the water intake of the nuclear power plant, distinguish different disaster levels, provide clear warning thresholds for the alarm device, and facilitate timely preventive measures. The warning lines of different radius are 1000m, 500m, 200m and 100m respectively. According to the geographical location and operation requirements of the water intake of the nuclear power plant, the sea area where the warning line needs to be set is determined. According to the actual situation and potential disaster risks of the water intake of the nuclear power plant, based on the comprehensive analysis of historical disaster data, topography, importance of the water intake and surrounding environmental factors, four warning lines are set. The warning lines of different radii are 1000m, 500m, 200m and 100m, and the disaster levels represented by the warning lines of different radii are defined. Among them, the radius of 1000m represents the low risk warning level, the radius of 500m represents the medium risk warning level, the radius of 200m represents the high risk warning level, and the radius of 100m represents the extremely high risk warning level. On the GIS platform, according to the defined disaster levels, the warning lines of radii of 1000m, 500m, 200m and 100m are drawn around the water intake of the nuclear power plant, and the boundaries of each warning area are marked; The real-time display module is used to display the information of the current arrow, the drift trajectory of algae and the water intake warning line based on the GIS platform and in combination with satellite images, and to display the movement status of algae in real time and dynamically. When the algae enters the warning line, the alarm device triggers the alarm to remind relevant personnel to take preventive measures. The high-resolution satellite image data is integrated as the background layer, and the real-time ocean current data is obtained. The ocean current arrow is generated through model calculation or measured data to display the direction and speed of the water flow in the sea area. At the same time, based on the ocean current data and algae characteristics, an algae drift trajectory model is established to simulate and display the movement status of algae in real time, and the satellite image and ocean current arrow data are superimposed and displayed with the warning line. The drift trajectory of algae is tracked in real time and compared and analyzed with the warning line. When the algae trajectory is predicted to enter or has entered the warning line area, the early warning mechanism is automatically triggered. Once the algae enters the warning line area, the alarm device sends an alarm signal by sound alarm, flashing lights, and SMS notification to remind relevant personnel to pay attention and take necessary preventive measures; The ship AIS information integration module is used to superimpose the ship AIS information into the alarm device, and combine it with the algae drift trajectory to display the real-time position and dynamics of the ship in the sea area, helping decision makers to consider the navigation conditions of the ship when formulating preventive measures, avoiding conflicts between ships and algae blocking areas, and ensuring maritime traffic safety. Through the AIS receiving equipment, the AIS information of ships in the nearby sea area is captured in real time. The AIS information includes the dynamic information of the ship name, call sign, MMSI code, ship position, speed, and heading, as well as the static information of the ship type, length, and width. The received AIS information is parsed and preprocessed to extract key information, including the real-time position, speed, and heading of the ship. , and verify the accuracy and completeness of the information to ensure the reliability of subsequent applications, fuse the pre-processed AIS data with the algae drift trajectory, and integrate the AIS data on the GIS platform to ensure that the data can be correctly displayed in the geographic information system, and intuitively display the real-time position and dynamics of the ship, as well as the distribution and drift trend of the algae through maps and charts. The integrated information is connected to the alarm device to analyze the relationship between the ship's position and the algae drift trajectory, and assess the risk of conflict between the ship and the algae blockage area. When the ship approaches or enters the algae blockage area, the alarm device automatically triggers an alarm signal to remind attention and take corresponding preventive measures, adjust the ship's route or issue a navigation warning; The decision support module is used to provide decision makers with prevention and response measures based on the output information of the alarm device and the ship's AIS information, ensuring that the nuclear power plant can respond quickly and effectively when the risk of algae blockage occurs, reducing the losses caused by algae blockage and ensuring the safe and stable operation of the nuclear power plant.

[0021] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An early warning system for algae blocking a water intake of a nuclear power plant, comprising an alarm device, characterized in that: The alarm device is communicatively connected with a data acquisition module, an FVCOM model module, a prediction and correction module, a warning line setting module, a real-time display module, a ship AIS information integration module and a decision support module, wherein the modules are electrically connected by signals; The data acquisition module is used to collect various data related to algae growth and marine environment, use satellite remote sensing technology to monitor the distribution and drift of algae in the sea area in real time, and provide real-time data of algae coverage areas; The FVCOM model module is used to simulate and predict the drift of algae using the hydrodynamic module and particle tracking module of the FVCOM model, wherein the hydrodynamic module provides a simulation of the three-dimensional tidal field in the prediction area, and the particle tracking module uses Lagrangian technology to simulate and predict the migration path of algae; The prediction and correction module is used to predict the algae drift path using the FVCOM model module, and to correct the particle drift trajectory of the next day predicted by the model through the remote sensing satellite images of the day; The warning line setting module is used to set warning lines of different radii around the water intake of the nuclear power plant to distinguish different disaster levels and provide a clear warning threshold for the alarm device, wherein the warning lines of different radii are 1000m, 500m, 200m and 100m respectively; The real-time display module is used to display the information of the ocean current flow arrow, the drift trajectory of the algae and the water intake warning line based on the GIS platform and in combination with satellite images, and to dynamically display the movement state of the algae in real time. When the algae enter the warning line, the alarm device triggers an alarm; The ship AIS information integration module is used to superimpose the ship AIS information into the alarm device, and combine it with the algae drift trajectory to display the real-time position and dynamics of the ship in the sea area; The decision support module is used to provide decision makers with preventive and response measures based on the output information of the alarm device and the ship's AIS information.

2. The early warning system for algae blocking water intake of a nuclear power plant according to claim 1, characterized in that: In the data acquisition module, the process of collecting algae growth and marine environment data is as follows: Determine the target sea area, use the remote sensing sensors carried by the satellite to scan the target sea area in real time, monitor the drift and distribution of algae in the sea area in real time, and obtain algae data and marine environment data; Transmit the collected remote sensing data to the alarm device and pre-process the received satellite remote sensing data; Analyze the preprocessed images, identify and classify algae, and extract geographic information of the algae coverage area; The various types of data collected are integrated to form a complete algae growth and marine environment data set, and stored in a data warehouse.

3. The early warning system for algae blocking water intake of a nuclear power plant according to claim 2, characterized in that: In the FVCOM model module, the process of simulating and predicting algae drift is as follows: Obtain and process the terrain data and shoreline data of the target area. The terrain data and shoreline data are the basis for model construction. According to the needs, the target area is gridded so that the grid resolution of the water intake of the nuclear power plant and its surrounding areas meets the needs. The grid resolution of the water intake is not less than 20m, and the grid resolution within a radius of 10km from the water inlet is not less than 100m. Configure the parameters of the FVCOM model, including the relevant settings of the hydrodynamic module and particle tracking module; The hydrodynamic module of the FVCOM model is used to simulate the three-dimensional tidal field in the prediction area. Based on the given initial flow field, initial conditions of the temperature field and boundary conditions of the current speed, direction, temperature and salinity, the three-dimensional tidal field in the study area is simulated. Lagrangian particle tracking technology is used to treat algae as particles and track them in the simulated three-dimensional tidal field. According to the movement trajectory of the particles, combined with the flow velocity, flow direction, and turbulent diffusion factors, the migration path and distribution range of the algae are predicted. Combined with the simulation results of the hydrodynamic module, the algae drift process is simulated in a refined manner to improve the prediction accuracy. The particles in the fluid are tracked according to the particle tracking equation, and the movement trajectory of the particles in the fluid is calculated; Visualization tools are used to display and analyze the simulation results, and the simulation results are compared and verified with the measured data.

4. The early warning system for algae blocking water intake of a nuclear power plant according to claim 3, characterized in that: Based on the Navier-Stokes equation, the fluid velocity field is calculated and calculated according to the continuity equation to ensure mass conservation, describe the change of fluid density with time and space, and the compressibility of the fluid. The specific expression is: ； ； Where u is the fluid velocity vector, p is the pressure, is the fluid density, is the dynamic viscosity coefficient, f is the body force, is the sea level, is the partial derivative of the fluid velocity with time, is the gradient tensor of the fluid velocity, is the Laplace operator; Through grid division and numerical simulation algorithm, the simulation results reflect the flow field characteristics of the water intake of the nuclear power plant and its surrounding areas. The heat transfer and conversion in the ocean are described according to the thermodynamic equation, including heat diffusion, convection and source / sink terms, to achieve the simulation of the ocean temperature field. The specific expression is: ； Where T is the temperature, is the specific heat capacity, a is the thermal diffusivity, and Q is the heat source / sink; The salinity equation is used to describe the diffusion and source / sink process of salinity in the ocean and analyze the distribution and change of ocean salinity. The specific expression is: ； Where S is the salinity, K is the salt diffusion coefficient, is a salinity source / sink; According to the turbulence model, turbulent diffusion is described and calculated, and the effective viscosity and diffusion coefficient are calculated. The specific expressions are: k transport equation: ; Transport equation: ; where k is the turbulent kinetic energy, is the turbulent dissipation rate, is the turbulent viscosity coefficient, is the turbulence generation rate, is a constant in the turbulence model, and is a constant in the turbulence model.

5. The early warning system for algae blocking water intake of a nuclear power plant according to claim 4, characterized in that: In the prediction and correction module, the process of correcting the particle drift trajectory predicted by the model on the second day is: According to the collected historical data, the initial conditions of the FVCOM model are set, including ocean current field, temperature, salinity, and density. The FVCOM model is used to predict the drift path of algae and simulate the movement trajectory of algae particles in the ocean. Output the predicted algae drift trajectory data for the next day, and process the remote sensing satellite data of the day to extract the algae distribution information; Compare the algae drift trajectory predicted by the FVCOM model with the algae distribution in the remote sensing data, identify the difference areas, adjust the model parameters, adjust the flow field and wind field parameters of the FVCOM model according to the difference areas, and re-run the model for correction; The above prediction and correction process is repeated until the preset accuracy or number of cycles is reached, and the corrected algae drift trajectory is output.

6. The early warning system for water inlet of a nuclear power plant blocked by algae according to claim 5, characterized in that: The model correction includes position correction, drift speed correction and direction correction; The position correction adjusts the particle position to match the actual position of the algae in the remote sensing data, and its expression is: ； ； in, is the position correction, is the position predicted by the model, is the observation location, It is the position difference; The drift velocity correction is performed by adjusting the particle drift velocity to reflect the actual observed algae drift velocity, and its expression is: ； in, is the speed correction, is the speed predicted by the model, is the observed velocity, k is the adjustment factor; The direction correction is achieved by adjusting the particle drift direction to match the actual observed algae drift direction, and its expression is: ; ； in, is the direction correction, is the predicted direction, is the observation direction, It is a directional difference.

7. The early warning system for water inlet of a nuclear power plant blocked by algae according to claim 6, characterized in that: In the warning line setting module, the process of dividing warning lines of different radii is as follows: Determine the sea area where the cordon needs to be set up based on the geographical location and operational requirements of the nuclear power plant's water intake; According to the actual situation and potential disaster risks of the water intake of the nuclear power plant, based on the historical disaster data, topography, the importance of the water intake and the comprehensive analysis of the surrounding environmental factors, four warning lines with different radii are set, namely 1000m, 500m, 200m and 100m, and the disaster levels represented by the warning lines with different radii are defined, among which the 1000m radius represents the low risk warning level, the 500m radius represents the medium risk warning level, the 200m radius represents the high risk warning level, and the 100m radius represents the extremely high risk warning level; On the GIS platform, according to the defined disaster levels, warning lines with radii of 1000m, 500m, 200m and 100m were drawn around the water intake of the nuclear power plant, and the boundaries of each warning area were marked.

8. The early warning system for algae blocking water intake of a nuclear power plant according to claim 7, characterized in that: In the real-time display module, the process of real-time dynamic display of the movement state of algae is: Integrate high-resolution satellite image data as a background layer, and obtain real-time ocean current data. Generate ocean current arrows through model calculation or measured data to display the direction and speed of water flow in the sea area. At the same time, based on ocean current data and algae characteristics, establish an algae drift trajectory model to simulate and display the movement status of algae in real time; Overlay satellite images and ocean current data with warning lines, track the drifting trajectory of algae in real time, and compare and analyze it with the warning line. When the algae trajectory is predicted to enter or has entered the warning line area, the early warning mechanism is automatically triggered. Once algae enters the cordon area, the alarm device will send out an alarm signal through sound alarms, flashing lights, and text message notifications to remind relevant personnel to pay attention and take necessary preventive measures.

9. The early warning system for water inlet of a nuclear power plant blocked by algae according to claim 8, characterized in that: In the ship AIS information integration module, the process of displaying the real-time position and dynamics of the ship in the sea area is as follows: Through AIS receiving equipment, AIS information of ships in nearby waters can be captured in real time; Parse and pre-process the received AIS information to extract key information, including the real-time position, speed and heading of the ship; The pre-processed AIS data is fused with the algae drift trajectory, and the AIS data is integrated on the GIS platform to intuitively display the real-time position and dynamics of the ship, as well as the distribution and drift trend of the algae in the form of maps and charts; The integrated information is connected to the alarm device to analyze the relationship between the ship's position and the drift trajectory of the algae, and to evaluate the risk of conflict between the ship and the algae blockage area. When the ship approaches or enters the algae blockage area, the alarm device automatically triggers an alarm signal to remind people to pay attention and take corresponding preventive measures, adjust the ship's route or issue a navigation warning.

Images