Floating object track predicting and tracing method and system based on WRF and HYSPLIT model

Abstract

The invention discloses a floating object track prediction and tracing method and system based on WRF and HYSPLIT models, and relates to the technical field of power system power transmission line operation and maintenance, and the method comprises five units: a data acquisition unit, a three-dimensional atmosphere model construction unit, a floating object track prediction unit, a floating object tracing unit and a result display unit. The data acquisition unit acquires meteorological data and floating object information. The three-dimensional atmosphere model construction unit constructs an applicable three-dimensional atmosphere model on the basis of a WRF weather forecast mode. The floater trajectory prediction unit predicts the future trajectory of the floater through an HYSPLIT mixed single-particle Lagrange comprehensive trajectory model in combination with weather forecast data. The floating object traceability unit inverts the historical motion trail and source of the floating object. And the result display unit displays the floating object track prediction and traceability result based on a geographic information system. According to the method, the safety and reliability of the power transmission line are improved, accidents such as line hanging and tripping of the floaters are reduced, and accurate trajectory prediction and source inversion of the floaters are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of operation and maintenance of transmission lines in power systems, and specifically to a method and system for predicting and tracing the trajectory of floating objects based on WRF and HYSPLIT models. Background Art

[0002] In the field of operation and maintenance management of transmission lines, power supply companies currently have relatively complete monitoring and maintenance systems for transmission lines, which can monitor the status of transmission lines in real time and take corresponding measures for operation and maintenance to ensure the safe and stable operation of the power grid. However, when facing potential hazards to transmission lines caused by floating objects such as plastic films, balloons, and kite strings, they still face severe challenges. Since the movement trajectory of floating objects is affected by various complex factors such as wind direction, wind speed, and air density, existing technical means can only monitor the current position of floating objects and it is difficult to accurately predict the future movement trajectory of floating objects. At the same time, for floating objects that have already affected transmission lines, in terms of tracing the source, after the floating objects have affected the transmission lines, it is very difficult for existing technical means to accurately trace their sources. This makes it difficult for the power department to take targeted measures from the root cause to reduce the threat of similar floating objects to transmission lines again. For some transmission line faults caused by lightweight items randomly discarded in the surrounding environment being blown up by the wind, since their specific sources cannot be determined, it is difficult to avoid the recurrence of such incidents by strengthening management and other means. Thus, it is difficult to judge their sources and possible propagation routes. Therefore, there is an urgent need for a system and method that can effectively predict the trajectory of floating objects and trace their sources to improve the safety and reliability of transmission lines. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and system for predicting and tracing the trajectory of floating objects based on WRF and HYSPLIT models. By collecting various types of information through a data collection unit and preprocessing them, a three-dimensional atmospheric model is constructed with the help of WRF, and the HYSPLIT model is used to predict the trajectory and trace the source of floating objects based on the atmospheric model and relevant data respectively. Finally, the results are presented on a GIS map through a result display unit to achieve accurate trajectory prediction and source inversion of floating objects and improve the safety and reliability of transmission lines.

[0004] To achieve the above purpose, the present invention provides the following technical solutions:

[0005] First, the data collection unit completes the input of floating object information and environmental information. This step includes collecting meteorological data along the transmission line: obtaining real-time and historical meteorological data such as wind direction, wind speed, temperature, humidity, and air pressure from meteorological observation stations, radars, and satellite data sources.

[0006] Terrain data: Obtaining high-resolution terrain data, including altitude, terrain undulation, and landform features.

[0007] Land use data: Collect land use type data, such as farmland, forest, city, water area, to reflect the surface coverage.

[0008] Floating object information: Record the location, time, and floating object type information of the occurred floating object wire hanging and tripping events, as well as the floating object location and status information obtained in real time through monitoring devices.

[0009] During the data collection process, it is also necessary to integrate and preprocess the collected data to ensure the accuracy and consistency of the data.

[0010] At the same time, the data collection unit also includes a visual warning function for transmission lines, which is used to monitor the floating objects taking off near the transmission lines and estimate their data.

[0011] Secondly, according to the collected environmental information, a three-dimensional atmospheric model suitable for the target area is constructed through the WRF model. This process combines high-resolution terrain and land use static data, and generates three-dimensional atmospheric field data through multi-level nesting, dynamic downscaling or statistical downscaling methods. To ensure the accuracy and reliability of the model, model verification and evaluation are also required.

[0012] Next, after the visual warning system for transmission lines detects the takeoff of a floating object, the relevant data of the floating object is input into the HYSPLIT model. Based on the forecast data of the constructed three-dimensional atmospheric model and the global weather forecast model, the HYSPLIT model can predict the future movement trajectory of the floating object. This step includes data preparation, input of floating object physical parameters, trajectory prediction and result output, and finally outputs the position of the floating object at future moments including longitude, latitude, and altitude and the corresponding time.

[0013] The calculation basis for simulating the trajectory of the HYSPLIT model includes the meteorological data basis and the advection calculation basis. The basis of any Lagrangian model is to calculate the diffusion according to particles or air masses. That is to say, the horizontal advection calculation of particles is independent of the diffusion calculation. The horizontal advection integral of each particle in time can be regarded as a simple trajectory, which only requires a three-dimensional velocity field. The meteorological data used for trajectory and diffusion calculations is output from meteorological model simulations, and usually these fields are used by HYSPLIT after preprocessing. In order to be able to use different meteorological data sources for input, the meteorological data profile at each horizontal grid point is linearly interpolated into the terrain-following σ coordinate system:

[0014]

[0015] where z is the height relative to the terrain, Z topis the top height of the HYSPLIT coordinate system. The grid fields of the meteorological variables are set at fixed time intervals, available every 3 hours for some regional grids and every 6 hours for coarser global grids;

[0016] The input elements for HYSPLIT meteorological simulations include horizontal wind components, temperature, height or pressure, and surface pressure. If the wet deposition process is to be included, the model also requires an input rainfall field. In most cases, the meteorological data will include a vertical motion field, usually expressed in pressure units, and these data fields can be directly used for the calculation of the trajectory diffusion model. When the vertical motion field is missing, or when special conditions need to be set for the simulation, HYSPLIT can choose to replace these fields with a vertical velocity, which is calculated based on the assumption of pollutant parcel transport on other surfaces. The vertical velocity calculation for a specific air mass surface is as follows:

[0017]

[0018] where t is time, u is the horizontal x-direction velocity, ν is the horizontal y-direction velocity, and z is the vertical direction;

[0019] After the basic meteorological data is processed and interpolated into the grid inside the HYSPLIT model,

[0020] the horizontal advection component of the trajectory can be calculated. The key in advection calculation is to directly incorporate the time interpolation of the meteorological field

[0021] into the horizontal algorithm. Assuming that a particle or air mass moves with the wind field, its trajectory is the integral of the mass point in space and time. The horizontal displacement of a particle or air mass is calculated from the average of the three-dimensional velocity vectors at the initial position P(t) and the first predicted position P(t + Δt). The velocity vectors are linearly interpolated in space and time, and the first predicted position is as shown in the following formula:

[0022] P(t + Δt) = P(t) + V(P, t)Δt

[0023] The calculation of the new predicted position at time step t + Δt is affected by the average horizontal advection of the wind, which determines the movement trajectory that a particle or air mass will follow. Then the final position is:

[0024]

[0025] In other words, the change of the position vector P mean over time is calculated from the average of the three-dimensional velocity vector V at its initial position and the first guessed position. Substituting it into the final position, the formula can be obtained:

[0026]

[0027] where Δt is the time step, P(t) is the initial position of the air mass, V(P,t) is the three-dimensional velocity vector at the initial position, P(t+Δt) is the initial hypothetical position of the air mass, V(P′,t+Δt) is the three-dimensional velocity vector at the initial hypothetical position, and P′(t+Δt) is the final position of the air mass;

[0028] The above equation is the basis for calculating the trajectory in HYSPLIT. Only the horizontal advection component is considered when running the trajectory. The turbulent diffusion component is only used to describe the atmospheric transport and mixing processes of three-dimensional particles and plumes. The position of the particle at the next moment is obtained by multiplying the average velocity at the previous moment and the average velocity at the point of the first guess value by the time step.

[0029] Output the predicted trajectory results of the floating object, including the position of the floating object at future moments, including longitude, latitude, and altitude, and the corresponding time.

[0030] Meanwhile, in order to trace the source of the floating object that has affected the transmission line, the present invention also uses the HYSPLIT model to trace the source of the floating object. This process is also based on a three-dimensional atmospheric model, but combined with reanalysis meteorological data. Through backward time derivation, the HYSPLIT model can invert the historical movement trajectory and source of the floating object. This step includes data preparation, event selection, trajectory inversion, and result output, and finally outputs the inverted trajectory and source results of the floating object for analyzing the source and propagation path of the floating object.

[0031] Finally, the result display unit visually displays the floating object trajectory prediction and source tracing results on the map. This step is based on the Geographic Information System (GIS). Integrate the predicted floating object trajectory, the inverted floating object trajectory and source results into the GIS system, and display the movement trajectory of the floating object and its potential threat to the transmission line in a three-dimensional atmospheric environment. This helps the operation and maintenance personnel to intuitively understand the dynamic changes of the floating object and its impact on the transmission line, so as to take corresponding operation and maintenance measures.

[0032] A floating object trajectory prediction and source tracing system based on WRF and HYSPLIT models, including a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that it includes a data acquisition unit, a three-dimensional atmospheric model construction unit, a floating object trajectory prediction unit, a floating object source tracing unit, and a result display unit. When the computer program is loaded into the processor, it realizes the steps of the processing method according to any one of claims 1-7 on each unit.

[0033] The data acquisition unit collects meteorological data, terrain data, land use data, and floating object information along the transmission line, including obtaining real-time and historical meteorological data from data sources such as meteorological observation stations, radars, and satellites, as well as high-resolution terrain data and land use type data, and integrates and preprocesses the collected data to ensure the accuracy and consistency of the data.

[0034] The three-dimensional atmospheric model construction unit constructs a three-dimensional atmospheric model applicable to the target area based on the WRF model, combined with static data such as high-resolution terrain and land use, through methods such as multi-level nesting, dynamic downscaling, or statistical downscaling. The specific steps include model setup, data input, model operation, and model verification and evaluation to ensure the accuracy and reliability of the generated three-dimensional atmospheric field data.

[0035] The floating object trajectory prediction unit predicts the future movement trajectory of floating objects through the HYSPLIT model based on the three-dimensional atmospheric model and combined with the forecast data of the global weather forecast model. The specific steps are that the transmission line visualization warning platform discovers warning floating objects, then completes data preparation, inputs the physical parameters of the floating objects into the HYSPLIT model, and finally completes trajectory prediction and result output, and outputs the predicted floating object trajectory results, including the position of the floating object at future times, including longitude, latitude, and altitude, and the corresponding time.

[0036] The floating object traceability unit also inversely calculates the historical movement trajectory and source of floating objects through the HYSPLIT model based on the three-dimensional atmospheric model and combined with reanalysis meteorological data. The specific steps include data preparation, event selection, trajectory inversion, and result output, and outputs the inversed floating object trajectory and source results for analyzing the source and propagation path of floating objects. This step can also be used for analyzing the source of historical line tripping and hanging line events.

[0037] The result display unit intuitively displays the floating object trajectory prediction and traceability results on a map containing the transmission line model based on the geographic information system GIS. The specific steps include data integration, map display, and three-dimensional display, and display the movement trajectory of floating objects and their potential threats to the transmission line in a three-dimensional atmospheric environment to help operation and maintenance personnel intuitively understand the dynamic changes of floating objects and their impacts on the transmission line.

[0038] The relationship between the various units is as follows: First, the floating object information and environmental information are entered through the data acquisition unit. Then, according to the environmental information, a three-dimensional atmospheric model of the region is constructed through WRF. After the transmission line visualization warning system detects the takeoff of a floating object, the floating object data is input into the HYSPLIT model to complete trajectory prediction and traceability analysis. Finally, combined with the transmission line map, the floating object threat assessment is completed to assist the power grid management unit in operating and maintaining the transmission line level.

[0039] The data acquisition unit further includes a visual warning module for transmission lines, which is used to monitor floating objects taking off near the transmission lines and estimate their data. The three-dimensional atmospheric model construction unit further includes a model verification and evaluation unit, which is used to verify the accuracy and evaluate the performance of the constructed three-dimensional atmospheric model to ensure the accuracy and reliability of the model.

[0040] The data acquisition unit further includes the function of integrating and preprocessing data from data sources such as meteorological observation stations, radars, and satellites along the transmission line to ensure the accuracy and consistency of the data.

[0041] The floating object trajectory prediction unit further includes a physical parameter input module for floating objects, which is used to input physical parameters of the floating objects such as shape, size, mass, initial position, and initial velocity collected to improve the accuracy of trajectory prediction.

[0042] The floating object traceability unit further includes a ground hazard source marking module, which identifies and marks potential ground hazard sources according to the floating object traceability results and provides targeted treatment suggestions for operation and maintenance personnel.

[0043] The result display unit further includes a three-dimensional atmospheric environment display function, which displays the movement trajectory of the floating object and its potential threat to the transmission line in three-dimensional space, enhancing the intuitive understanding of operation and maintenance personnel on the dynamic changes of the floating object.

[0044] In summary, through steps of data acquisition, three-dimensional atmospheric model construction, floating object trajectory prediction, floating object traceability, and result display, the present invention realizes accurate trajectory prediction and source inversion of floating objects, providing strong support for the safe operation and maintenance of transmission lines.

[0045] First, the floating object information and environmental information are input through the data acquisition unit, and then according to the environmental information, a regional three-dimensional atmospheric model is constructed by WRF. After the visual warning system for transmission lines detects the takeoff of the floating object, the floating object data is input into the HYSPLIT model to complete trajectory prediction and traceability analysis. Finally, combined with the transmission line map, the threat assessment of the floating object is completed to assist the power grid management unit in maintaining the operation level of the transmission line.

[0046] Compared with the prior art, the beneficial effects of the present invention are:

[0047] Achieved the deep integration and fine preprocessing of multi-source data, enhancing the integrity and accuracy of the data, providing a solid and reliable data foundation for the prediction and tracing of the trajectory of floating objects, and significantly enhancing the credibility of the analysis results. Significantly improved the safety and reliability of transmission lines, reduced the occurrence of accidents such as floating objects hanging on the lines and tripping, and brought significant economic and social benefits to the power industry. At the same time, this achievement can also be extended and applied to fields such as environmental protection and meteorology, providing new ideas and methods for research on the diffusion of atmospheric pollutants and climate change. In addition, through cooperation and exchanges with industries such as power and meteorology, this project will promote technological innovation and industrial upgrading, facilitate the transformation and application of research results, and inject new vitality into the development of related industries.

[0048] Using the WRF model to construct a high-precision three-dimensional atmospheric model, compared with simple atmospheric simulation methods, it can accurately depict the complex and changeable atmospheric conditions in the target area, taking into account the influence of multiple factors such as terrain and land use on atmospheric motion, providing a very realistic atmospheric environment simulation for the subsequent HYSPLIT model to analyze the trajectory of floating objects, and greatly improving the accuracy of trajectory prediction and tracing.

[0049] With the help of the HYSPLIT model, two-way analysis is realized on the basis of an advanced atmospheric model. It can not only prospectively predict the future movement trajectory of floating objects and provide early warnings for maintenance personnel in a timely manner, but also trace back the sources of floating objects that have affected the transmission lines. This unique two-way function is lacking in the existing technologies and provides a powerful tool for comprehensively understanding the behavior of floating objects.

[0050] Based on the result display method of the GIS system, breaking through the limitations of traditional two-dimensional or single-information display, combining the trajectory prediction and tracing results with the transmission line model, and stereoscopically presenting the potential threats of floating objects to the transmission lines in a three-dimensional atmospheric environment, providing intuitive and comprehensive information for maintenance personnel, greatly improving the scientificity and timeliness of maintenance decisions, and effectively reducing the failure rate of transmission lines caused by floating objects. Brief Description of the Drawings

[0051] Figure 1 It is a system diagram of a floating object trajectory prediction and tracing system based on the WRF and HYSPLIT models of the present invention;

[0052] Figure 2 It is a flowchart of a floating object trajectory prediction and tracing method based on the WRF and HYSPLIT models of the present invention. Specific Implementation Method

[0054] Next, the technical solutions in the embodiments of the present invention will be completely described in conjunction with the drawings in the embodiments of the present invention.

[0055] Such as Figure 1-2As shown in the figure, a method for predicting the trajectory and tracing the source of floating objects based on the WRF and HYSPLIT models is characterized by including the following steps:

[0056] S1: Data collection;

[0057] S2: Construct a three-dimensional atmospheric model;

[0058] S3: Predict the trajectory of floating objects;

[0059] S4: Trace the source of floating objects;

[0060] S5: Result display.

[0061] Specifically, in step S1, the data collection is the meteorological data, terrain data, land use data and floating object information along the transmission line, including obtaining real-time and historical meteorological data from meteorological observation stations, radars, satellite data sources, as well as high-resolution terrain data and land use type data, and integrating and preprocessing the collected data to ensure the accuracy and consistency of the data.

[0062] Based on the WRF model and combined with high-resolution terrain and land use static data, step S2 constructs a three-dimensional atmospheric model suitable for the target area. The specific steps are as follows:

[0063] S21: Model setting. According to the characteristics of the research area, set the grid resolution, nesting layer number, and physical parameterization scheme parameters of the WRF model;

[0064] S22: Data input. Input the preprocessed meteorological data, terrain data, land use data, etc. into the WRF model;

[0065] S23: Model operation. Run the WRF model to generate three-dimensional atmospheric field data for the target area, including the spatio-temporal distribution of meteorological elements such as wind speed, wind direction, temperature, and humidity;

[0066] S24: Model verification and evaluation. Use actual observation data to verify and evaluate the generated three-dimensional atmospheric field data to ensure the accuracy and reliability of the model.

[0067] Based on the three-dimensional atmospheric model and combined with the forecast data of the global weather forecast model, step S3 predicts the future movement trajectory of floating objects through the HYSPLIT model. The specific steps are as follows:

[0068] S31: Data preparation. Input the forecast data of the global weather forecast model into the HYSPLIT model;

[0069] S32: Input of physical parameters of floating objects. According to the information of floating objects obtained by monitoring equipment, input the physical parameters of floating objects, such as shape, size, mass, initial position, initial velocity, etc.;

[0070] S33: Trajectory prediction. In the HYSPLIT model, using the input meteorological data and physical parameters of the floating objects, calculate the future movement trajectories of the floating objects through the motion equations.

[0071] The specific trajectory prediction in step S33 is to calculate by simulating the trajectory through the HYSPLIT model. The specific steps are as follows:

[0072] Output meteorological data for trajectory and diffusion calculations from the meteorological model simulation, and linearly interpolate the meteorological data profile of each horizontal grid point to the terrain-following σ coordinate system:

[0073]

[0074] where z is the height relative to the terrain, and Z top is the top height of the HYSPLIT coordinate system. The grid fields of the meteorological variables are set at fixed time intervals, which are available every 3 hours for some regional grids and every 6 hours for coarser global grids;

[0075] When the vertical motion field is missing, or when the simulation requires setting special conditions, HYSPLIT chooses to replace these fields with vertical velocities, which are calculated based on the assumption of the transport of pollutant parcels on other surfaces. The vertical velocity of a specific air mass surface is calculated as follows:

[0076]

[0077] where t is time, u is the horizontal x-direction velocity, ν is the horizontal y-direction velocity, and z is the vertical direction;

[0078] After the basic meteorological data is processed and interpolated into the grids inside the HYSPLIT model, calculate the horizontal convective component of the trajectory; the horizontal displacement of a particle or air mass is calculated by the average value of the three-dimensional velocity vectors at the initial position P(t) and the first predicted position P(t + Δt); the velocity vectors are linearly interpolated in space and time, and the first predicted position is as shown in the following formula:

[0079] P(t + Δt) = P(t) + V(P, t)Δt

[0080] The calculation of the new predicted position at the time step t + Δt is affected by the average horizontal convection of the wind, which determines the movement trajectory that a particle or air mass will follow. Then the final position is:

[0081]

[0082] Position vector P meanThe change over time is calculated from the average of the three-dimensional velocity vector V at its initial position and the first guessed position, and substituting it into the final position, the formula can be obtained:

[0083]

[0084] where Δt is the time step, P(t) is the initial position of the air mass, V(P,t) is the three-dimensional velocity vector at the initial position, P(t + Δt) is the initial hypothetical position of the air mass, V(P′,t + Δt) is the three-dimensional velocity vector at the initial hypothetical position, and P′(t + Δt) is the final position of the air mass;

[0085] The above formula is the basis for calculating the trajectory in HYSPLIT. Only the horizontal convection component is considered when running the trajectory; the position of the particle at the next moment is obtained by multiplying the average of the average velocity at the previous moment and the velocity at the point of the first guess value by the time step;

[0086] Output the predicted trajectory results of the floating object, including the position of the floating object at future moments, including longitude, latitude, altitude and the corresponding time.

[0087] Step S4 is based on the three-dimensional atmospheric model, combined with the reanalysis meteorological data, and inversely calculates the historical movement trajectory and source of the floating object through the HYSPLIT model. The specific steps are as follows:

[0088] S41: Data preparation, input the reanalysis meteorological data, including historical wind speed, wind direction, and temperature, into the HYSPLIT model;

[0089] S42: Event selection, select the occurred floating object hanging wire and tripping events, and determine the time point and position for tracing the source;

[0090] S43: Trajectory inversion, in the HYSPLIT model, use the input meteorological data and event information to calculate the historical movement trajectory and source of the floating object through reverse time derivation;

[0091] S44: Result output, output the inverted trajectory and source results of the floating object.

[0092] Step S5 is based on the Geographic Information System (GIS) to display the floating object trajectory prediction and tracing results on the map. The specific steps are as follows:

[0093] S51: Data integration, integrate the predicted floating object trajectory, the inverted floating object trajectory and source results into the GIS system;

[0094] S52: Map display, on the GIS map, mark the position of the transmission line, the predicted floating object trajectory, the inverted floating object trajectory and source information;

[0095] S53: Three-dimensional display, showing the movement trajectory of floating objects and their potential threats to transmission lines in a three-dimensional atmospheric environment, helping operation and maintenance personnel intuitively understand the dynamic changes of floating objects and their impacts on transmission lines.

[0096] A floating object trajectory prediction and traceability system based on WRF and HYSPLIT models, including a memory, a processor, and a computer program stored on the memory and executable on the processor, including a data acquisition unit, a three-dimensional atmospheric model construction unit, a floating object trajectory prediction unit, a floating object traceability unit, and a result display unit. When the computer program is loaded into the processor, it realizes the steps of the processing method according to any one of claims 1-7 on each unit.

[0097] The relationship between the various units is as follows: First, the data acquisition unit completes the input of floating object information and environmental information. Then, according to the environmental information, a three-dimensional atmospheric model of the region is constructed through WRF. After the transmission line visualization warning system detects the takeoff of a floating object, the floating object data is input into the HYSPLIT model to complete trajectory prediction and traceability analysis. Finally, in combination with the transmission line map, a floating object threat assessment is completed to assist the power grid management unit in maintaining the level of transmission lines.

[0098] The data acquisition unit further includes a transmission line visualization warning module for monitoring floating objects taking off near the transmission line and estimating their data. The three-dimensional atmospheric model construction unit further includes a model verification and evaluation unit for verifying the accuracy and evaluating the performance of the constructed three-dimensional atmospheric model to ensure the accuracy and reliability of the model.

[0099] As Figure 1 shown, this embodiment provides a floating object trajectory prediction and traceability system and method, including a data acquisition unit, a three-dimensional atmospheric model construction unit, a floating object trajectory prediction unit, a floating object traceability unit, and a result display unit. The data acquisition unit is used to obtain meteorological data, terrain data, land use data, and floating object information along the transmission line; the three-dimensional atmospheric model construction unit is based on the WRF model, combines static data such as high-resolution terrain and land use, and constructs a three-dimensional atmospheric model applicable to the target area through methods such as multi-level nesting, dynamic downscaling, or statistical downscaling; the floating object traceability unit is based on the three-dimensional atmospheric model, combines reanalysis meteorological data, and inversely calculates the historical movement trajectory and source of the floating object through the HYSPLIT model; the result display unit is based on the geographic information system and intuitively displays the floating object trajectory prediction and traceability results on the map to guide the operation and maintenance work of the transmission line.

[0100] In the data collection stage, through the data collection unit, real-time and historical meteorological data along the transmission line are comprehensively collected from data sources such as meteorological observation stations, radars, and satellites, covering information such as wind direction, wind speed, temperature, humidity, and air pressure. At the same time, high-resolution terrain data are obtained, including altitude, terrain undulation, geomorphic features, and land use type data. For floating object information, the locations, times, and types of floating object hanging on the line and tripping events that have occurred are detailedly recorded, and the positions and status information of floating objects are obtained in real time with the aid of monitoring equipment. In this process, data integration and preprocessing technologies are used to ensure the accuracy and consistency of various data. In addition, the transmission line visualization warning module is used to monitor in real time the floating objects taking off near the transmission line and estimate their relevant data.

[0101] When constructing the three-dimensional atmospheric model, the WRF model is taken as the core. First, model settings are carried out. According to the geographical characteristics of the research area, parameters such as grid resolution, nesting level, and physical parameterization scheme are finely set to ensure that the model can accurately simulate the atmospheric environment of the target area. Then, the preprocessed meteorological, terrain, land use, etc. data are input into the WRF model. After the model runs, detailed three-dimensional atmospheric field data of the target area are generated, clearly presenting the spatio-temporal distribution of meteorological elements such as wind speed, wind direction, temperature, and humidity. Subsequently, using the actual observation data, the generated three-dimensional atmospheric field data are verified and evaluated through the model verification and evaluation unit to ensure the accuracy and reliability of the model.

[0102] The calculation of the trajectory is simulated through the HYSPLIT model. The specific steps are as follows:

[0103] The calculation basis of the trajectory simulated by the HYSPLIT model includes the meteorological data basis and the advection calculation basis. The basis of any Lagrangian model is to calculate diffusion according to particles or air masses. That is to say, the horizontal advection calculation of particles is independent of the diffusion calculation. The horizontal advection integral of each particle over time can be regarded as a simple trajectory, which only requires a three-dimensional velocity field. The meteorological data used for trajectory and diffusion calculations are output from meteorological model simulations. Usually, these fields are used by HYSPLIT after preprocessing. In order to be able to use different meteorological data sources for input, the meteorological data profiles at each horizontal grid point are linearly interpolated into the terrain-following σ coordinate system:

[0104]

[0105] where z is the height relative to the terrain, and Z top is the top height of the HYSPLIT coordinate system. The grid fields of the meteorological variables are set at fixed time intervals. For some regional grids, they are available every 3 hours, and for coarser global grids, they are available every 6 hours;

[0106] The meteorological simulation input elements of HYSPLIT include horizontal wind components, temperature, altitude or pressure, and surface pressure. If the wet deposition process is to be included, the model also requires an input of the rainfall field. In most cases, the meteorological data will include a vertical motion field, usually expressed in pressure units, and these data fields can be directly used in the calculation of the trajectory diffusion model. When the vertical motion field is missing, or when special conditions need to be set for the simulation, HYSPLIT can choose to replace these fields with the vertical velocity, which is calculated based on the assumption of the transport of pollutant parcels on other surfaces. The vertical velocity of a specific air mass surface is calculated as follows:

[0107]

[0108] where t is time, u is the velocity in the horizontal x - direction, ν is the velocity in the horizontal y - direction, and z is the vertical direction;

[0109] After the basic meteorological data is processed and interpolated into the grid inside the HYSPLIT model,

[0110] the horizontal advection component of the trajectory can be calculated. The key in the advection calculation is to directly incorporate the temporal interpolation of the meteorological field

[0111] into the horizontal algorithm. Assuming that a particle or air mass moves with the wind field, its trajectory is the integral of the mass point in space and time. The horizontal displacement of a particle or air mass is calculated from the average of the three - dimensional velocity vectors at the initial position P(t) and the first predicted position P(t + Δt). The velocity vectors are linearly interpolated in space and time, and the first predicted position is given by the following equation:

[0112] P(t + Δt) = P(t)+V(P,t)Δt

[0113] The calculation of the new predicted position at the time step t + Δt is affected by the mean horizontal advection of the wind, which determines the movement trajectory that a particle or air mass will follow. Then the final position is:

[0114]

[0115] In other words, the change of the position vector P mean with time is calculated from the average of the three - dimensional velocity vector V at its initial position and the first guessed position. Substituting it into the final position, the formula can be obtained:

[0116]

[0117] where Δt is the time step, P(t) is the initial position of the air mass, V(P,t) is the three-dimensional velocity vector at the initial position, P(t+Δt) is the initial hypothetical position of the air mass, V(P′,t+Δt) is the three-dimensional velocity vector at the initial hypothetical position, and P′(t+Δt) is the final position of the air mass;

[0118] The above equation is the basis for calculating trajectories in HYSPLIT. Only the horizontal advection component is considered when running the trajectory. The turbulent diffusion component is only used to describe the atmospheric transport and mixing processes of three-dimensional particles and plumes. The position of the particle at the next moment is obtained by multiplying the average velocity at the previous moment and the average velocity at the point of the first guess value by the time step.

[0119] Output the predicted trajectory results of the floating object, including the position of the floating object at future times, including longitude, latitude, altitude, and the corresponding time.

[0120] In the floating object trajectory prediction section, based on the established three-dimensional atmospheric model, the forecast data of the global weather forecast model is input into the HYSPLIT model for data preparation. At the same time, according to the information of the floating object obtained by the monitoring equipment, physical parameters such as the shape, size, mass, initial position, and initial velocity of the floating object are input into the HYSPLIT model. Inside the model, meteorological data for trajectory and diffusion calculations are simulated and output from the meteorological model, and the meteorological data profile at each horizontal grid point is linearly interpolated into the terrain-following coordinate system. When the vertical motion field is missing or there are special requirements for the simulation, the vertical velocity is calculated according to a specific formula. The processed and interpolated meteorological data is used to calculate the horizontal advection component of the trajectory. By calculating the horizontal displacement of the particle or air mass, the future motion trajectory of the floating object is finally obtained, and its longitude, latitude, altitude, and the corresponding time at future times are output.

[0121] When tracing the source of the floating object, also based on the three-dimensional atmospheric model, reanalysis meteorological data such as historical wind speed, wind direction, temperature, etc. are input into the HYSPLIT model for data preparation. Select the floating object hanging wire and tripping events that have occurred, and clarify the time point and location of the source tracing. In the HYSPLIT model, using the input meteorological data and event information, the historical motion trajectory and source of the floating object are calculated by reverse time derivation, and the inversion results are output.

[0122] Finally, in the result display stage, based on the Geographic Information System (GIS), the predicted trajectories of floating objects, the inverted trajectories of floating objects, and the source results are integrated into the GIS system. On the GIS map, the positions of transmission lines, the predicted and inverted trajectories of floating objects, and the source information are clearly marked. Through the 3D display function, the movement trajectories of floating objects and their potential threats to transmission lines are visually presented in the 3D atmospheric environment, helping operation and maintenance personnel comprehensively and intuitively understand the dynamic changes of floating objects and their impacts on transmission lines, thereby assisting the power grid management unit to effectively improve the operation and maintenance level of transmission lines.

Claims

1. A method for predicting the trajectory and tracing the source of floating objects based on the WRF and HYSPLIT models, characterized in that It includes the following steps: S1: Data collection; S2: Construct a three-dimensional atmospheric model; S3: Prediction of the trajectory of floating objects; S4: Tracing the origin of floating objects; S5: Result display.

2. The method for predicting and tracing the trajectory of floating objects based on the WRF and HYSPLIT models according to claim 1, wherein, Specifically, the data collection in step S1 is meteorological data, terrain data, land use data and floating object information along the transmission line, including obtaining real-time and historical meteorological data from meteorological observation stations, radars, satellite data sources, as well as high-resolution terrain data and land use type data, and integrating and preprocessing the collected data to ensure the accuracy and consistency of the data.

3. A method for predicting the trajectory and tracing the source of floating objects based on the WRF and HYSPLIT models according to claim 1, characterized in that, Based on the WRF model and combined with high-resolution terrain and land use static data, step S2 constructs a three-dimensional atmospheric model suitable for the target area. The specific steps are as follows: S21: Model setup. According to the characteristics of the study area, set the grid resolution, nesting level, and physical parameterization scheme parameters of the WRF model; S22: Data input. Input the preprocessed meteorological data, terrain data, land use data, etc. into the WRF model; S23: Model run. Run the WRF model to generate three-dimensional atmospheric field data for the target area, including the spatio-temporal distribution of meteorological elements such as wind speed, wind direction, temperature, and humidity; S24, Model verification and evaluation. Use actual observation data to verify and evaluate the generated three-dimensional atmospheric field data to ensure the accuracy and reliability of the model.

4. A method for predicting the trajectory and tracing the source of floating objects based on the WRF and HYSPLIT models according to claim 1, characterized in that, Based on the three-dimensional atmospheric model and combined with the forecast data of the global weather forecast model, step S3 predicts the future movement trajectory of floating objects through the HYSPLIT model. The specific steps are as follows: S31: Data preparation. Input the forecast data of the global weather forecast model into the HYSPLIT model; S32: Input of physical parameters of floating objects. According to the information of floating objects obtained by monitoring equipment, input the physical parameters of floating objects, such as shape, size, mass, initial position, initial velocity, etc.; S33: Trajectory prediction. In the HYSPLIT model, use the input meteorological data and physical parameters of floating objects to calculate the future movement trajectory of floating objects through the motion equation.

5. A method for predicting and tracing the trajectory of floating objects based on the WRF and HYSPLIT models according to claim 4, characterized in that, Specifically, the trajectory prediction in step S33 is calculated by simulating the trajectory through the HYSPLIT model. The specific steps are: Interpolate the meteorological data output from the meteorological model for trajectory and dispersion calculations linearly to the terrain-following σ coordinate system for each horizontal grid point; where z is the height relative to the terrain, and Z top is the top height of the HYSPLIT coordinate system. The grid fields of the meteorological variables are set at fixed time intervals, available every 3 hours for the grid of some regions and every 6 hours for the coarser global grid; When the vertical motion field is missing, or when the simulation requires setting special conditions, HYSPLIT chooses to use the vertical velocity to replace these fields. This vertical velocity is calculated based on the assumption of the transport of pollutant parcels on other surfaces. The vertical velocity of a specific air mass surface is calculated as follows: Where t is time, u is the horizontal x-direction velocity, ν is the horizontal y-direction velocity, and z is the vertical direction; After the basic meteorological data is processed and interpolated into the grid inside the HYSPLIT model, calculate the horizontal advection component of the trajectory; the horizontal displacement of particles or air masses is calculated by the average value of the three-dimensional velocity vectors of the initial position P(t) and the first predicted position P(t + Δt); the velocity vector is linearly interpolated in space and time, and the first predicted position is shown as follows: P(t + Δt) = P(t) + V(P, t)Δt The calculation of the new predicted position at time step t + Δt is affected by the average horizontal convection of the wind, which determines the movement trajectory that a particle or air mass will follow. Then the final position is: Position vector P mean The change over time is calculated from the average of the three-dimensional velocity vector V at its initial position and the first guessed position and substituted into the final position, resulting in the formula: where Δt is the time step, P(t) is the initial position of the air mass, V(P, t) is the three-dimensional velocity vector at the initial position, P(t + Δt) is the initial hypothetical position of the air mass, V(P′, t + Δt) is the three-dimensional velocity vector at the initial hypothetical position, and P′(t + Δt) is the final position of the air mass; The above equation is the basis for calculating the trajectory in HYSPLIT, and only the horizontal convection component is considered when running the trajectory; the position of the particle at the next moment is obtained by multiplying the average of the average velocity at the previous moment and the velocity at the first guess point by the time step; Output the predicted trajectory results of the floating object, including the position of the floating object at future moments, including longitude, latitude, altitude, and the corresponding time.

6. A method for predicting the trajectory and tracing the source of floating objects based on the WRF and HYSPLIT models according to claim 1, characterized in that, Step S4, based on the three-dimensional atmospheric model, combines the reanalysis meteorological data, and inversely analyzes the historical movement trajectory and source of the floating object through the HYSPLIT model. The specific steps are as follows: S41: Data preparation, input the reanalysis meteorological data, including historical wind speed, wind direction, and temperature, into the HYSPLIT model; S42: Event selection, select the occurred events of the floating object hanging wire and tripping, and determine the time point and position for tracing the source; S43: Trajectory inversion, in the HYSPLIT model, use the input meteorological data and event information to calculate the historical movement trajectory and source of the floating object through backward time derivation; S44: Result output, output the results of the inversed trajectory and source of the floating object.

7. A method for predicting the trajectory and tracing the source of floating objects based on the WRF and HYSPLIT models according to claim 1, characterized in that, Step S5, based on the Geographic Information System (GIS), displays the floating object trajectory prediction and tracing results on the map. The specific steps are as follows: S51: Data integration, integrate the predicted floating object trajectory, the inversed floating object trajectory and source results into the GIS system; S52: Map display, on the GIS map, mark the position of the transmission line, the predicted floating object trajectory, the inversed floating object trajectory, and the source information; S53: Three-dimensional display, display the movement trajectory of the floating object and its potential threat to the transmission line in the three-dimensional atmospheric environment, helping the operation and maintenance personnel to intuitively understand the dynamic changes of the floating object and its impact on the transmission line.

8. A floating object trajectory prediction and tracing system based on WRF and HYSPLIT models, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, It includes a data acquisition unit, a three-dimensional atmospheric model construction unit, a floating object trajectory prediction unit, a floating object tracing unit, and a result display unit. When the computer program is loaded into the processor, it realizes the steps of the processing method according to any one of claims 1 - 7 on each unit.

9. A floating object trajectory prediction and traceability system based on the WRF and HYSPLIT models according to claim 8, characterized in that, The relationship between the various units is as follows: First, the data acquisition unit completes the input of the floating object information and environmental information. Then, according to the environmental information, a three-dimensional atmospheric model of the region is constructed through WRF. After the transmission line visualization warning system detects the takeoff of the floating object, the floating object data is input into the HYSPLIT model to complete the trajectory prediction and tracing analysis. Finally, combined with the transmission line map, the threat assessment of the floating object is completed to assist the power grid management unit in maintaining the operation level of the transmission line.

10. A floating object trajectory prediction and traceability system based on the WRF and HYSPLIT models according to claim 8, characterized in that, The data acquisition unit further includes a visual warning module for transmission lines, which is used to monitor floating objects taking off near the transmission lines and estimate their data. The three-dimensional atmospheric model construction unit further includes a model verification and evaluation unit, which is used to verify the accuracy and evaluate the performance of the constructed three-dimensional atmospheric model to ensure the accuracy and reliability of the model.

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