Lightning protection intelligent control method and system based on multi-dimensional data

Abstract

The method and system for lightning protection intelligent control based on multi-dimensional data, a view construction unit constructs a three-dimensional panoramic view, a regional three-dimensional view and a device parameter view; an association unit establishes a bidirectional mapping relationship between the three-dimensional panoramic view and the regional three-dimensional view, associates a protection node of the three-dimensional panoramic view to a device model corresponding to the regional three-dimensional view through a risk type label, and associates the device model to the protection node of the three-dimensional panoramic view through a device type label; and an interactive display unit matches the protection node and / or real-time risk data and the device type label corresponding to the label in the three-dimensional panoramic view and the regional three-dimensional view and displays. The present application is deeply coupled with a meteorological big data platform and a smart emergency system, and constructs a lightning safety system in multiple directions: integrates data collection, analysis, control and visualization, realizes real-time monitoring, intelligent evaluation and rapid response to lightning activities, greatly improves the efficiency and effect of lightning protection, and guarantees the safe and stable operation of key infrastructure.

Description

Technical Field

[0001] This invention relates to the field of information and data fusion technology, and in particular to a lightning protection intelligent control method and system based on multi-dimensional data. Background Technology

[0002] Lightning, as a natural phenomenon, poses a serious threat to human life and various facilities due to its suddenness, randomness, and destructiveness. Lightning not only causes direct physical damage, such as destroying buildings and equipment or causing fires, but it can also affect the normal operation of critical infrastructure such as communications and power through electromagnetic interference, and even trigger broader socio-economic impacts.

[0003] With technological advancements and societal development, the requirements for lightning protection across various facilities are increasingly stringent. Modern society's critical infrastructure, including power, communications, transportation, and security systems, demands greater timeliness, accuracy, and intelligence in lightning protection. However, existing lightning protection technologies are insufficient to meet these needs and cannot provide comprehensive and reliable lightning protection for critical infrastructure.

[0004] Therefore, the existing technology has problems and needs further improvement and development. Summary of the Invention

[0005] (I) Purpose of the invention: In order to solve the problems existing in the prior art, the purpose of the present invention is to provide a lightning protection intelligent control method and system based on multi-dimensional data.

[0006] (II) Technical Solution: In order to solve the above technical problems, this technical solution provides a lightning protection intelligent control method based on multi-dimensional data, which constructs a three-dimensional panoramic view, a regional three-dimensional view and an equipment parameter view; the three-dimensional panoramic view is a three-dimensional panoramic model of the geographical area of ​​interest, and the protection nodes of the three-dimensional panoramic model include substations and transmission line towers, and each protection node is associated with a risk type label, a time label and a risk level label;

[0007] The three-dimensional view of the area includes a three-dimensional perspective view of the substation and a three-dimensional perspective view of the transmission line. The three-dimensional perspective view of the substation and the three-dimensional perspective view of the transmission line contain equipment models, and the equipment models are overlaid with real-time risk data and equipment type labels.

[0008] The equipment parameter view is a slice of the parameters of the target equipment in the substation and transmission line towers, and displays the parameter change curve of the target equipment along the time axis.

[0009] Establish a bidirectional mapping relationship between a 3D panoramic view and a regional 3D view. Associate the protection nodes of the 3D panoramic view with risk type labels to the corresponding equipment models in the regional 3D view. The equipment models are associated with the protection nodes of the 3D panoramic view with equipment type labels.

[0010] In response to management instructions, the corresponding tags are filtered, and the corresponding protection nodes and / or real-time risk data and equipment type tags are matched and displayed in the 3D panoramic view and regional 3D view.

[0011] The lightning protection intelligent control method based on multi-dimensional data, wherein the real-time risk data specifically includes:

[0012] Lightning physical parameters: lightning current amplitude, number of return strokes, and electric field strength;

[0013] Core indicators of the equipment model: grounding resistance, equipment temperature, and insulation resistance;

[0014] Meteorological multi-element coupling effect parameter: The coupling coefficient, calculated from humidity, wind speed, air pressure and precipitation probability, characterizes the amplification effect of lightning risk.

[0015] The lightning protection intelligent control method based on multidimensional data, wherein when the risk level label of the protection node in the three-dimensional panoramic view is red, the icon size of the red label is set to 1.5 times the normal size, and the spacing between adjacent nodes is increased by 20%.

[0016] The lightning protection intelligent control method based on multidimensional data, wherein multiple protection nodes in the three-dimensional panoramic view are projected and overlapped in three-dimensional space, and displayed in a weighted order according to risk level and equipment type.

[0017] The lightning protection intelligent control method based on multidimensional data, wherein the parameter slice of the target device is displayed along the time axis, and when the parameter curve of the target device exceeds the threshold range, the parameter curve of that period is highlighted in red and a warning label with a vertical offset of 5% is generated on the right side of the parameter slice.

[0018] The lightning protection intelligent control method based on multidimensional data, wherein when the time axis scaling ratio is >50%, the parameter slice plot automatically aggregates the maximum / minimum values ​​of adjacent data points, and marks the data fluctuation range value with a shaded area, the fluctuation range value The calculation formula is: , The values ​​are those of adjacent data points.

[0019] The lightning protection intelligent control method based on multi-dimensional data, wherein the device model of the three-dimensional view of the region is superimposed with real-time data animation of the particle effects of the lightning rod's current discharge, and the lightning current amplitude, grounding resistance and particle system and shader parameters of the rendering engine are bound together.

[0020] The lightning protection intelligent control method based on multi-dimensional data, wherein the particle system of the rendering engine is:

[0021] First, the lightning rod model is sampled using sampling grid nodes to obtain the coordinates of the needle body vertices including the needle tip. The needle tip vertices are then perturbed and sampled based on a continuous Burmester noise map to generate particle emission positions. The noise map frequency is set to 0.5Hz to simulate random discharge trajectories.

[0022] Mapping lightning current amplitude to particle system parameters in real time:

[0023] When the lightning current amplitude is greater than 30kA, the particle emission rate is set to 500 particles / second, the particle lifetime is 2 seconds, and the particle color transitions linearly from blue to white.

[0024] When the lightning current amplitude is ≤30kA, the particle emission rate drops to 200 particles / second, the lifetime is 1 second, and the particle color is fixed as blue.

[0025] An initial velocity of 50-100 cm / s is applied to the particles along the normal direction of the needle tip. At the tip of the needle, attractive force and turbulent force are superimposed. The strength of the attractive force increases linearly with the amplitude of the lightning current, and the strength of the turbulent force is 0.2, simulating the divergence and convergence effect of the discharge particles.

[0026] Fourth: The particles adopt a semi-transparent superimposed blending mode and enable the self-illuminating shader. The intensity of the self-illuminating shader is positively correlated with the lightning current amplitude. For every 10kA increase in the lightning current amplitude, the intensity of the self-illuminating shader increases by 20%.

[0027] The lightning protection intelligent control method based on multidimensional data, wherein the parameters of the flickering animation of the grounding model in the three-dimensional perspective view of the substation in the regional three-dimensional view are connected to the rendering engine; the generation of the dissolving mask includes: using the texture coordinates of the grounding model to the tile noise map to generate a dynamic dissolving mask map, wherein the size of the tile noise map is 0.5m×0.5m, and the sampling frequency of the flickering period of the flickering animation is positively correlated with the grounding resistance value; when the grounding resistance is ≤4Ω, the sampling frequency is 0.5Hz and the flickering period is 2 seconds;

[0028] When 4Ω < grounding resistance ≤ 10Ω, the sampling frequency is 1Hz and the flashing period is 1 second.

[0029] When the grounding resistance is greater than 10Ω, the sampling frequency is 2Hz and the flashing period is 0.5 seconds.

[0030] The dissolved mask image is used as an opaque mask for the grounding grid model material. The mask threshold is dynamically adjusted according to the sampling results, and a flashing effect is achieved through self-illuminating color.

[0031] A lightning protection intelligent control system based on multi-dimensional data includes a view construction unit, an association unit, and an interactive display unit.

[0032] The view construction unit is configured to construct a three-dimensional panoramic view, a regional three-dimensional view, and a device parameter view; the three-dimensional panoramic view is a three-dimensional panoramic model of the geographic area of ​​interest, and the protection nodes of the three-dimensional panoramic model include substations and transmission line towers, with each protection node associated with a risk type label, a time label, and a risk level label;

[0033] The three-dimensional view of the area includes a three-dimensional perspective view of the substation and a three-dimensional perspective view of the transmission line. The three-dimensional perspective view of the substation and the three-dimensional perspective view of the transmission line contain equipment models, and the equipment models are overlaid with real-time risk data and equipment type labels.

[0034] The equipment parameter view is a slice of the parameters of the target equipment in the substation and transmission line towers, and displays the parameter change curve of the target equipment along the time axis.

[0035] The association unit is configured to establish a bidirectional mapping relationship between the three-dimensional panoramic view and the regional three-dimensional view, and to associate the protection nodes of the three-dimensional panoramic view with the corresponding equipment model of the regional three-dimensional view through risk type labels, and the equipment model with the protection nodes of the three-dimensional panoramic view through equipment type labels.

[0036] The interactive display unit is configured to filter corresponding tags in response to management instructions, and match and display the protection nodes and / or real-time risk data and equipment type tags corresponding to the tags in the three-dimensional panoramic view and the regional three-dimensional view.

[0037] (III) Beneficial effects: This invention provides a lightning protection intelligent control method and system based on multi-dimensional data, which is deeply coupled with meteorological big data platform and intelligent emergency system to build a multi-faceted collaborative lightning safety system. By integrating advanced data acquisition, analysis, control and visualization technologies, it realizes real-time monitoring, intelligent assessment and rapid response to lightning activities, which greatly improves the efficiency and effectiveness of lightning protection and ensures the safe and stable operation of critical infrastructure. Attached Figure Description

[0038] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0039] Figure 1 This is a schematic diagram of the steps of the lightning protection intelligent control method based on multidimensional data of the present invention;

[0040] Figure 2 This is a schematic diagram of the lightning protection intelligent control system based on multidimensional data according to the present invention. Detailed Implementation

[0041] The technical solutions of the present invention will now be described with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0042] Hereinafter, the terms "first," "second," etc., are used for descriptive convenience only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0043] In this invention, unless otherwise explicitly specified and limited, the term "connection" should be interpreted broadly. For example, "connection" can be a fixed mechanical connection, a detachable mechanical connection, or an integral part; or, "connection" can be a direct connection or an indirect connection through an intermediate medium. Furthermore, unless otherwise explicitly specified and limited, the term "coupling" should be interpreted broadly. For example, "coupling" can be a direct electrical connection, such as physical contact and electrical conduction between two components; it can also be understood as an electrical connection between different components in a circuit structure through physical lines capable of transmitting electrical signals, such as copper foil or wires on a printed circuit board (PCB), to transmit electrical signals; or, "coupling" can be an indirect electrical connection between two components through an intermediate medium; or, "coupling" can be an electrical connection between two components in a non-contact manner, such as an electrical connection between two components using capacitive coupling to transmit electrical signals.

[0044] In this embodiment of the invention, directional terms such as "up," "down," "left," and "right" may be defined relative to the orientation of the components shown in the accompanying drawings. It should be understood that these directional terms can be relative concepts, used for relative description and clarification, and can change accordingly depending on the orientation of the components in the accompanying drawings.

[0045] Lightning protection intelligent control system based on multi-dimensional data, such as Figure 2 As shown, the system includes a view construction unit, an association unit, and an interactive display unit. The view construction unit is configured to construct a 3D panoramic view, a regional 3D view, and a device parameter view. The association unit is configured to establish a bidirectional mapping relationship between the 3D panoramic view and the regional 3D view. The interactive display unit is configured to respond to management commands by filtering corresponding tags, matching and displaying the corresponding protection nodes and / or real-time risk data and device type tags in the 3D panoramic view and the regional 3D view.

[0046] Lightning protection intelligent control methods based on multidimensional data, such as Figure 1 As shown, it includes the following steps:

[0047] Step 101: Construct a 3D panoramic view, a regional 3D view, and a device parameter view;

[0048] Step 102: Establish a two-way mapping relationship between the 3D panoramic view and the regional 3D view;

[0049] Step 103: In response to the management instruction, filter the corresponding tags, match the protection nodes and / or real-time risk data and equipment type tags corresponding to the tags in the 3D panoramic view and the regional 3D view, and display them.

[0050] The three-dimensional panoramic view is a three-dimensional panoramic model of the geographic area of ​​interest. The protection nodes of the three-dimensional panoramic model include substations and transmission line towers. Each protection node is associated with a risk type label, a time label, and a risk level label.

[0051] The 3D panoramic view is a 3D panoramic model of a region of interest (such as the area under the jurisdiction of a substation) constructed based on data from a Geographic Information System (GIS). Specifically, a 3D mesh of terrain, buildings, and power facilities is generated through oblique photogrammetry or BIM modeling. The protection nodes are bound to their corresponding positions in the 3D panoramic model via coordinate matching. The label data associated with each protection node can be stored in a relational database, such as MySQL, and the label data is associated with the identifier of the protection node.

[0052] The regional 3D view includes a 3D perspective view of the substation and a 3D perspective view of the transmission line. These views contain equipment models, which are overlaid with real-time risk data and equipment type labels. Specifically, the regional 3D view generates a refined 3D perspective view of the substation / transmission line towers with an accuracy of 0.1m. The equipment models include lightning rods, grounding grids, etc., and can be created using 3D modeling software, such as Blende. The real-time risk data for these equipment models is obtained from the monitoring system via an application programming interface and overlaid onto the surface of the equipment models; this data can be a texture map or floating text labels. The monitoring system can be a Supervisory Control and Data Acquisition (SCADA) system.

[0053] The equipment parameter view is a slice of parameters for target equipment in substations and transmission line towers, displaying parameter change curves along a time axis. Specifically, the equipment parameter view uses data visualization libraries such as ECharts or D3.js to draw time-series line charts, with the X-axis representing time and the Y-axis representing parameter values ​​(such as grounding resistance and lightning current). The data source for the equipment parameter view can be a historical database.

[0054] Establishing a bidirectional mapping relationship between the 3D panoramic view and the regional 3D view involves associating the protection nodes of the 3D panoramic view with the corresponding equipment models in the regional 3D view through risk type labels, and vice versa. For example, a risk type label-equipment type label mapping table can be used: the "thunderstorm" risk label is associated with "lightning rod" and "surge arrester" equipment models, and the "grounding anomaly" label is associated with "grounding grid" and "cable joint" models. This mapping table can be input or modified via an input unit. When the 3D panoramic view filters labels, it automatically sends associated equipment identifiers to the regional 3D view, triggering highlighted rendering of the equipment models; conversely, when the regional view selects a equipment model, it sends node identifiers to the panoramic view, triggering node positioning and zooming.

[0055] In response to management commands, the system filters corresponding tags, matches and displays the protection nodes and / or real-time risk data and equipment type tags corresponding to the tags in the 3D panoramic view and the regional 3D view. Management commands include mouse clicks, keyboard shortcuts, or voice input on the input unit.

[0056] The real-time risk data specifically includes:

[0057] Lightning physical parameters: lightning current amplitude, number of return strokes, and electric field strength; lightning current amplitude and number of return strokes are collected by lightning monitoring stations, and electric field strength is monitored in real time by an electric field meter;

[0058] The core indicators of the equipment model are: grounding resistance, equipment temperature, and insulation resistance. Grounding resistance is measured regularly by a grounding resistance tester, which can be once a day. Equipment temperature is collected by an infrared sensor, and insulation resistance is measured by a megohmmeter, which can be measured once a week.

[0059] Meteorological multi-element coupling effect parameter: The coupling coefficient, calculated from humidity, wind speed, air pressure, and precipitation probability, characterizes the amplification effect of lightning risk. Specifically, humidity, wind speed, air pressure, and precipitation probability data are obtained from the meteorological department's API, and the coupling coefficient K is calculated using the following formula: K = 0.4H + 0.3V + 0.2P + 0.1Q, where H is humidity, V is wind speed, P is air pressure, and Q is precipitation probability. Humidity, wind speed, air pressure, and precipitation probability are all normalized to 0-1, and the K value ranges from 0 to 1. A larger value indicates a stronger risk amplification effect.

[0060] When the risk level label of a protective node in the 3D panoramic view is red, the icon size of the red label is set to 1.5 times the normal size, and the spacing between adjacent nodes is increased by 20%. When the risk level label of a protective node is updated to red, if the lightning current amplitude is >30kA or the grounding resistance is >10Ω, the rendering engine triggers a display adjustment event, modifies the scaling matrix of the node model, with the scaling center being the geometric center of the node, and sets the icon size of the red label to 1.5 times the normal size. After the red label node is scaled, the repulsion coefficient of adjacent nodes is increased by 20%, increasing the spacing between adjacent nodes by 20% to avoid node overlap and maintain view clarity.

[0061] In the 3D panoramic view, multiple protective nodes are projected and overlapped in 3D space, and displayed in order of risk level and equipment type weight. Specifically, the projection coordinates of the nodes on the 2D screen are detected by the depth buffer of the 3D scene. When the overlapping area of ​​the projection rectangles of two nodes is greater than 50%, it is determined to be a projection overlap. The priority calculation formula is P: P = 0.7R + 0.3W, where R is the risk level weight (red = 3, yellow = 2, green = 1) and W is the equipment type weight (substation = 2, tower = 1). Nodes are arranged in descending order of P value, with nodes having higher P values ​​displayed at the top (i.e., larger Z-axis coordinates). Nodes with the same P value are arranged in ascending order of equipment number, such as substation A being prioritized over substation B. Top-level nodes are fully displayed, while bottom-level nodes are semi-transparent (50% transparency) and marked with a prompt indicating X overlapping nodes, where X is the number of overlapping nodes.

[0062] The parameter slices of the target device are displayed along the time axis. When the parameter curve of the target device exceeds the threshold range, the parameter curve for that period is highlighted in red, and a warning label with a vertical offset of 5% is generated on the right side of the parameter slice. Specifically, a line graph of the parameter curve is drawn, and the threshold range is read from the device parameter configuration table stored in a relational database. For example, the normal range of grounding resistance is ≤4Ω. The current parameter value is compared with the threshold in real time, and an anomaly label is triggered when it exceeds the threshold. When the parameter is abnormal, a label is generated on the right side of the curve. The label can be red with white text, and the text content is "Parameter Exceeds Standard: XXΩ (Threshold ≤4Ω)". The vertical offset of the label is set to 5% by calculating the Y-axis coordinate of the corresponding time point of the curve.

[0063] When the timeline scaling factor is greater than 50%, the parametric slice automatically aggregates the maximum / minimum values ​​of adjacent data points and marks the data fluctuation range with a shaded area. The formula for calculating the fluctuation range value is: where is the value of the adjacent data point. For example, by listening to the scaling event of the timeline control, such as mouse wheel or touch scaling, the current scaling factor is calculated, i.e., the current time window width / the original window width. Aggregation is triggered when the factor is greater than 50%. A sliding window aggregation is used, where the window size dynamically adjusts with the scaling factor; the larger the scaling factor, the larger the window. The maximum and minimum values ​​of adjacent data points within the window are taken to form a maximum-minimum value range. On the aggregated curve, a semi-transparent shaded area is used to fill the area between the maximum and minimum values, with the shaded boundary being the maximum and minimum value curves. The semi-transparent shaded area can be 30% transparent with the color of the curve.

[0064] The device model of the three-dimensional view of the area is superimposed with the real-time data animation of the particle effects of the lightning rod's current discharge, which binds the lightning current amplitude, grounding resistance, and particle system and shader parameters of the rendering engine.

[0065] The particle system of the rendering engine:

[0066] First, the lightning rod model is sampled using sampling mesh nodes to obtain the coordinates of the vertices of the lightning rod body, including the tip. Then, the tip vertex coordinates are perturbed and sampled based on a continuous Burmester noise map to generate particle emission positions. The noise map frequency is set to 0.5Hz to simulate random discharge trajectories. For example, a particle system is created in the rendering engine, and the lightning rod model vertices are sampled using sampling mesh nodes to obtain the tip coordinates, such as vertex number 0 representing the tip. Random perturbations are added to the tip coordinates using a continuous Burmester noise map, with ±0.1m on each of the X / Y / Z axes, to simulate the randomness of the discharge trajectory.

[0067] Second, the lightning current amplitude is mapped to particle system parameters in real time:

[0068] When the lightning current amplitude is greater than 30kA, the particle emission rate is set to 500 particles / second, the particle lifetime is 2 seconds, and the particle color transitions linearly from blue to white.

[0069] When the lightning current amplitude is ≤30kA, the particle emission rate drops to 200 particles / second, the lifetime is 1 second, and the particle color is fixed as blue.

[0070] Third, an initial velocity of 50-100 cm / s is applied to the particles along the normal direction of the needle tip. At the tip of the needle, attractive force and turbulent force are superimposed. The strength of the attractive force increases linearly with the amplitude of the lightning current, and the strength of the turbulent force is 0.2, simulating the divergence and convergence effect of the discharge particles.

[0071] Fourth: The particles adopt a semi-transparent overlay and blending mode, and the self-illuminating shader is enabled. The intensity of the self-illuminating shader is positively correlated with the lightning current amplitude. The self-illuminating intensity = 1 + 0.2*(lightning current amplitude / 10), that is, for every 10kA increase in the lightning current amplitude, the intensity of the self-illuminating shader increases by 20%.

[0072] The parameters of the flashing animation of the grounding model in the three-dimensional perspective view of the substation in the three-dimensional view of the region are connected to the rendering engine; the generation of the dissolving mask includes: taking the texture coordinates of the grounding model and applying them to the tile noise map to generate a dynamic dissolving mask map, wherein the size of the tile noise map is 0.5m×0.5m, and the sampling frequency of the flashing period of the flashing animation is positively correlated with the grounding resistance value; when the grounding resistance is ≤4Ω, the sampling frequency is 0.5Hz and the flashing period is 2 seconds;

[0073] When 4Ω < grounding resistance ≤ 10Ω, the sampling frequency is 1Hz and the flashing period is 1 second.

[0074] When the grounding resistance is greater than 10Ω, the sampling frequency is 2Hz and the flashing period is 0.5 seconds.

[0075] The dissolved mask image is used as an opaque mask for the grounding grid model material. The mask threshold is dynamically adjusted according to the sampling results, and a flashing effect is achieved through self-illuminating color.

[0076] The dissolving mask controls the transparency of the model surface through a noise map. Areas with noise values ​​greater than a threshold are transparent, while areas with values ​​less than the threshold are opaque, thus achieving a dissolving or flickering effect for the model.

[0077] The bidirectional mapping relationship between the 3D panoramic view and the regional 3D view can be dynamically associated through a risk-equipment mirror list:

[0078] Risk - Building the Device Image List:

[0079] Establish a risk mirror list for each protection node in the 3D panoramic view, and record the associated regional 3D view equipment model labels and risk type labels, such as associating the "thunderstorm" risk label with the lightning rod model, and the "grounding anomaly" risk label with the grounding grid model;

[0080] The regional 3D view equipment model is used to create a mirror list of equipment, which is then linked to the panoramic view protection node identifiers and equipment type labels.

[0081] Dynamic update mechanism for dynamic associations:

[0082] When the risk level of the protection node in the panoramic view is upgraded to red, for example, when the lightning current is >30kA, the associated equipment model is automatically added to the high-risk rendering queue of the area view, the particle effects are updated first, and the lightning rod discharge frequency is increased to 5Hz.

[0083] When the parameters of the device model in the area view return to normal, such as when the grounding resistance is ≤4Ω, the panoramic view node label is downgraded, the red color turns green, and the temporary associated record is removed from the mirror list.

[0084] The bidirectional mapping relationship enables dynamic scheduling across views through a view resource pool, which includes a core resource pool and a buffer resource pool. The core resource pool accounts for 70% of the CPU / GPU memory and is used for rendering the device model of the currently active view, such as the lightning rod particle effect in a regional 3D view. The buffer resource pool accounts for 30% of the CPU / GPU memory and is used for caching static data of inactive views, such as the coordinates of protection nodes in a panoramic view.

[0085] The cross-view dynamic scheduling rule is that when the regional 3D view is activated, the rendering resolution of the panoramic view is reduced from 1080P to 720P to release video memory resources; the device models in the high-risk mirror list, i.e. the device models with red labels, are given priority in the particle effect rendering channel, and the rendering priority is increased by 2 for each frame.

[0086] Mirror list data that has not been updated for more than 5 minutes is automatically compressed into the lossless LZ4 format for storage. When the view switches back to the panoramic view, high-precision rendered data is restored from the buffer pool within 2 seconds, during which low-precision transition frames are displayed, showing a gradual transition from blurry to clear.

[0087] Rendering resource scheduling uses a risk-type two-dimensional priority matrix.

[0088] The priority levels are as follows:

[0089]

[0090] The rendering resource scheduling adjustment rules are as follows: when the GPU utilization rate is >85%, the texture resolution of P2 and below devices is reduced by 50%; high-risk devices P0 / P1 are given priority in VRAM graphics card memory allocation, with 20% buffer space reserved; device models removed from the image list release their rendering resources within 5 seconds, that is, release texture and vertex caches.

[0091] The risk-based partitioning of the rendering resource pool for the device image list includes the following steps:

[0092] First, resource pre-allocation: The core-buffer two-level pool is initialized. This is used during system startup to divide the resource pool according to hardware configurations, such as GPU memory and CPU core count. This ensures that the core pool prioritizes rendering on high-risk devices, while the buffer pool stores low-priority data. Specifically...

[0093] Hardware resource detection and allocation:

[0094] Memory allocation is performed by obtaining the total memory capacity through the GPU driver interface and dividing it in a 7:3 ratio: Core resource pool: 70%, used for dynamic rendering resources, including particle effects, real-time textures, and shader parameters; Buffer resource pool: 30%, used for static data caching, including device model base mesh and historical logs.

[0095] CPU thread allocation: the core pool is bound to high-priority rendering threads, and the buffer pool is bound to low-priority background threads.

[0096] Resource pool content initialization:

[0097] The core pool is preloaded with a default high-risk equipment model library, such as high-precision meshes for lightning rods and grounding grids, with a face count > 1000; the particle effects system is initialized with 5 preset rendering channels, supporting simultaneous rendering of 10 sets of discharge effects; and a real-time risk data receiving buffer is cached.

[0098] The buffer pool is preloaded to load low-precision models of the panoramic view protection nodes; the compressed storage module is initialized, which can specifically use the LZ4 algorithm to store historical mirror list data exceeding 24 hours.

[0099] Second, the tag mapping rule: risk-device dual-dimensional resource pool binding, used to map the tags of the risk-device image list to the resource pool allocation strategy, clarifying which devices enter the core pool / buffer pool, specifically including the following steps.

[0100] Risk level labels are mapped according to the following table:

[0101]

[0102] Device type label mapping:

[0103] Substation equipment, such as transformers and lightning rods, has a resource pool priority of +2 and is given priority to enter the core pool under the same risk level; transmission line towers have a resource pool priority of -1 and are given priority to enter the buffer pool under the same risk level.

[0104] The specific mapping of compound tags can be as follows:

[0105] Red+ Substation: Core pool, allocated particle effect channel + dynamic texture 2048×2048;

[0106] Yellow + Tower: Buffer pool, retaining only static mesh + low-precision texture 1024×1024;

[0107] Green+ Substation: Buffer pool, compressed storage in LZ4 format, decompressed to the core pool when needed.

[0108] Third, the dynamic monitoring and adjustment process: resource reallocation based on mirror list updates is used to monitor changes in risk level and resource pool occupancy in the mirror list in real time, triggering dynamic migration of resources between the core / buffer pool. This specifically includes the following steps:

[0109] Real-time monitoring metrics: Risk status monitoring, scanning the risk-device image list every 500ms to detect changes in risk level labels, such as from red to green; Resource usage monitoring, obtaining the core pool memory usage rate U through the GPU driver interface, with a threshold set to 90%, and the frame rate F threshold set to 30FPS.

[0110] The triggering conditions and actions for resource adjustments are shown in the table below:

[0111]

[0112] Recovery mechanism, i.e. reset after an anomaly: resource overflow recovery, when a video memory overflow triggers a GPU driver reset, the resource pool initialization process is automatically restarted, and devices with red tags in the current image list are loaded first; view switching recovery, within 2 seconds after the switch is completed, the core pool resource precision is restored from the buffer pool (e.g., texture resolution is restored from 720P to 1080P), during which the frame rate is maintained at ≥25FPS.

[0113] By following the steps above, a deep binding between the risk-device image list and the resource pool is achieved, ensuring that high-risk devices receive rendering resources first, while maximizing the utilization of hardware performance.

[0114] The viewing angle parameters of the 3D panoramic view can be dynamically adjusted according to the risk level of the protected node, specifically including:

[0115] When the risk level label of a protected node is detected to be upgraded from yellow to red, for example, when the lightning current amplitude is greater than 30kA, the perspective correction is activated.

[0116] Corrected parameters: Pitch angle, gradually adjusted from the default 30° to 45°, with a correction rate of 0.5° / frame, calculated based on the incremental time of the rendering frame rate, to expand the vertical field of view in risk areas; Roll angle, rotated 15° around the risk node to ensure the node is centered in the view, the correction formula is: Roll angle 目标 =Switch angle 当前 +15° × Incremental Time × 0.8; Stop condition: Stop correction when the viewpoint parameter reaches the target value or the risk level is downgraded to yellow.

[0117] The dynamic correction triggering conditions for the 3D panoramic view view parameters also include complex risk scenarios:

[0118] Multi-node collaborative triggering: When the risk level labels of ≥3 protection nodes in the same area are detected to upgrade from yellow to red within 10 seconds, for example, the lightning current amplitude is all >30kA, or the lightning current amplitude of a single red node is >50kA, the emergency correction mode is activated.

[0119] Parameter linkage trigger: Combined with meteorological parameter thresholds, such as wind speed > 15m / s and humidity > 85%, if the risk level is upgraded and the meteorological conditions are met, the correction speed is increased to 0.8° / frame, the default is 0.5° / frame, and priority is given to focusing on the protection nodes in front of the thunderstorm's movement path.

[0120] The viewpoint parameter correction also includes the coordinated adjustment of zoom level and field of view:

[0121] The zoom is synchronized; as the tilt angle is adjusted from 30° to 45°, the zoom ratio of the 3D panoramic view increases synchronously from 1.0× to 1.5×. The zoom speed formula is: zoom ratio 目标 =1.0 + 0.5 × (current pitch angle - 30°) / 15°;

[0122] Field of view compensation: When rotating by the roll angle, the horizontal field of view is expanded, for example, from 90° to 120°, to prevent risk nodes from moving out of the view boundary. The compensation coefficient = 1.0 + 0.02° × roll angle adjustment amount.

[0123] Dynamic blurring is applied to non-risk areas, such as those more than 5km away from the red node, with a radial blur effect. The blur intensity is 0.3 + 0.01 × correction progress, highlighting the risk focus area.

[0124] A lightning protection intelligent control method and system based on multidimensional data transforms the data of each protection node into a dynamic visual view by constructing a multidimensional visualization view, establishing a cross-view bidirectional mapping mechanism and a dynamic resource scheduling strategy, thereby realizing intelligent, precise and efficient lightning protection management.

[0125] I. Multi-dimensional view construction: Achieving full-chain visualization of risk status from global to local to parameter levels;

[0126] The 3D panoramic view provides macro-risk monitoring: the 3D panoramic model associates protection nodes such as substations and towers with risk type labels, and intuitively distinguishes the risk level through label color. Red high-risk nodes are automatically magnified by 1.5 times and the spacing is increased by 20%, which solves the problem of the lack of global perspective in traditional 2D monitoring, enabling operation and maintenance personnel to quickly locate high-risk areas.

[0127] The regional 3D view enables refined monitoring at the equipment level: high-precision perspective views are generated for substations / towers, and real-time risk data animations are superimposed on equipment models. For example, lightning rods simulate lightning current discharge through particle effects. When the lightning current is >30kA, the emission rate is 500 particles / second, and the color gradually changes from blue to white. The grounding grid reflects the grounding resistance through the flashing frequency of the dissolving shield. The higher the resistance, the slower the flashing. Abstract parameters are transformed into intuitive dynamic effects, improving the efficiency of risk identification.

[0128] The device parameter view supports historical trend analysis: the time axis parameter slice can display curves such as grounding resistance and lightning current along the time axis. Abnormal periods are automatically highlighted in red and bolded and warning labels are generated. When the time axis is zoomed, the maximum / minimum values ​​of data points are automatically aggregated and the fluctuation range is marked, which helps maintenance personnel to trace the pattern of parameter changes and predict the trend of equipment degradation.

[0129] II. Two-way mapping mechanism: Breaking down view barriers and enabling cross-level data linkage;

[0130] Risk-equipment tag bidirectional association: A dynamic binding is established between the protection nodes in the 3D panoramic view and the equipment models in the regional 3D view through a mirror list. When the panoramic view filters red risk nodes, the regional view automatically highlights the associated equipment and updates the particle effects; conversely, when the regional view selects a device, the panoramic view automatically locates the corresponding node, realizing a penetrating operation of global filtering, local positioning, and parameter viewing, reducing the operation steps by 70% compared to traditional systems.

[0131] Real-time cross-view data synchronization: Changes in risk level trigger bidirectional data push, panoramic view node labels are downgraded / upgraded in real time, and regional view device animation parameters are updated synchronously, ensuring data consistency across multiple views.

[0132] III. Dynamic resource scheduling: Optimize system performance and ensure real-time response of high-risk equipment;

[0133] Resource pool hierarchical allocation strategy: The core resource pool prioritizes rendering on high-risk devices, while the buffer resource pool stores static data. Combined with the risk-device priority matrix, this ensures that the particle effect frame rate is stable at ≥30FPS in extreme scenarios, reducing rendering latency on high-risk devices with fixed resource allocation.

[0134] Adaptive resource adjustment mechanism: Real-time monitoring of GPU memory usage and risk level changes. When core pool resources are insufficient, the texture resolution of low-priority devices is automatically reduced. After risk downgrade, dynamic rendering resources are released and compressed and stored in the buffer pool to improve system resource utilization and avoid low-risk devices from consuming too many resources.

[0135] IV. Overall Benefits: Enhance the level of intelligent management of lightning protection and ensure the safety of critical infrastructure.

[0136] Maintenance personnel can quickly locate high-risk equipment through multi-dimensional views, and use a two-way mapping mechanism to view parameter details in a penetrating manner. Dynamic resource scheduling ensures uninterrupted monitoring under extreme risks. In practical applications, it can reduce thunderstorm risk response time by 60% and ground fault investigation time by 50%, significantly improving the lightning protection capabilities of critical infrastructure such as power and communications, and reducing the incidence of equipment damage and power outages caused by lightning.

[0137] The above description illustrates preferred embodiments of the present invention and helps those skilled in the art to more fully understand the technical solution of the present invention. However, these embodiments are merely illustrative and should not be construed as limiting the specific implementation of the present invention to these embodiments. For those skilled in the art, several simple deductions and modifications can be made without departing from the inventive concept, and all such modifications should be considered within the protection scope of the present invention.

Claims

1. A lightning protection intelligent control method based on multi-dimensional data, characterized in that, Construct a 3D panoramic view, a regional 3D view, and an equipment parameter view; the 3D panoramic view is a 3D panoramic model of the geographic area of ​​interest, and the protection nodes of the 3D panoramic model include substations and transmission line towers, with each protection node associated with a risk type label, a time label, and a risk level label; The three-dimensional view of the area includes a three-dimensional perspective view of the substation and a three-dimensional perspective view of the transmission line. The three-dimensional perspective view of the substation and the three-dimensional perspective view of the transmission line contain equipment models, and the equipment models are overlaid with real-time risk data and equipment type labels. The equipment parameter view is a slice of the parameters of the target equipment in the substation and transmission line towers, and displays the parameter change curve of the target equipment along the time axis. Establish a bidirectional mapping relationship between a 3D panoramic view and a regional 3D view. Associate the protection nodes of the 3D panoramic view with risk type labels to the corresponding equipment models in the regional 3D view. The equipment models are associated with the protection nodes of the 3D panoramic view with equipment type labels. In response to management instructions, filter the corresponding tags, match and display the protection nodes and / or real-time risk data and equipment type tags corresponding to the tags in the 3D panoramic view and the regional 3D view; The bidirectional mapping relationship between the 3D panoramic view and the regional 3D view is dynamically associated through a risk-equipment mirror list: The risk-equipment mirror list is constructed by creating a risk mirror list for each protection node in the 3D panoramic view, and recording the associated area 3D view equipment model labels and risk type labels; The regional 3D view equipment model is used to create a mirror list of equipment, which is then linked to the panoramic view protection node identifiers and equipment type labels. The dynamic update mechanism of dynamic association automatically adds the associated device model to the high-risk rendering queue of the area view when the risk level of the protection node in the panoramic view is upgraded to red, prioritizes the updating of particle effects, and increases the lightning rod discharge frequency to 5Hz; when the parameters of the device model in the area view return to normal, it triggers the downgrading of the panoramic view node label, turns red into green, and removes the temporary association record from the mirror list.

2. The lightning protection intelligent control method based on multi-dimensional data according to claim 1, characterized in that, The real-time risk data specifically includes: Lightning physical parameters: lightning current amplitude, number of return strokes, and electric field strength; Core indicators of the equipment model: grounding resistance, equipment temperature, and insulation resistance; Meteorological multi-element coupling effect parameter: The coupling coefficient, calculated from humidity, wind speed, air pressure and precipitation probability, characterizes the amplification effect of lightning risk.

3. The lightning protection intelligent control method based on multi-dimensional data according to claim 1, characterized in that, When the risk level label of the protection node in the three-dimensional panoramic view is red, the icon size of the red label is set to 1.5 times the normal size, and the spacing between adjacent nodes is increased by 20%.

4. The lightning protection intelligent control method based on multi-dimensional data according to claim 1, characterized in that, In the three-dimensional panoramic view, multiple protective nodes are projected and overlapped in three-dimensional space, and displayed in a weighted order according to risk level and equipment type.

5. The lightning protection intelligent control method based on multi-dimensional data according to claim 1, characterized in that, The parameter slice of the target device is displayed along the time axis. When the parameter curve of the target device exceeds the threshold range, the parameter curve that exceeds the threshold range is highlighted in red and a warning label with a vertical offset of 5% is generated on the right side of the parameter slice.

6. The lightning protection intelligent control method based on multi-dimensional data according to claim 1, characterized in that, When the time axis scaling ratio is greater than 50%, the parametric slice plot automatically aggregates the maximum / minimum values ​​of adjacent data points and marks the data fluctuation range with a shaded area. The calculation formula is , The values ​​are those of adjacent data points.

7. The lightning protection intelligent control method based on multi-dimensional data according to claim 1, characterized in that, The device model of the three-dimensional view of the area is superimposed with the real-time data animation of the particle effects of the lightning rod's current discharge, which binds the lightning current amplitude, grounding resistance, and particle system and shader parameters of the rendering engine.

8. The lightning protection intelligent control method based on multidimensional data according to claim 7, characterized in that, The particle system of the rendering engine: First, the lightning rod model is sampled using sampling grid nodes to obtain the coordinates of the needle body vertices including the needle tip. The needle tip vertices are then perturbed and sampled based on a continuous Burmester noise map to generate particle emission positions. The noise map frequency is set to 0.5Hz to simulate random discharge trajectories. Second, the lightning current amplitude is mapped to particle system parameters in real time: When the lightning current amplitude is greater than 30kA, the particle emission rate is set to 500 particles / second, the particle lifetime is 2 seconds, and the particle color transitions linearly from blue to white. When the lightning current amplitude is ≤30kA, the particle emission rate drops to 200 particles / second, the lifetime is 1 second, and the particle color is fixed as blue. Third, an initial velocity of 50-100 cm / s is applied to the particles along the normal direction of the needle tip. At the tip of the needle, attractive force and turbulent force are superimposed. The strength of the attractive force increases linearly with the amplitude of the lightning current, and the strength of the turbulent force is 0.2, simulating the divergence and convergence effect of the discharge particles. Fourth: The particles adopt a semi-transparent superimposed blending mode and enable the self-illuminating shader. The intensity of the self-illuminating shader is positively correlated with the lightning current amplitude. For every 10kA increase in the lightning current amplitude, the intensity of the self-illuminating shader increases by 20%.

9. The lightning protection intelligent control method based on multi-dimensional data according to claim 1, characterized in that, The parameters of the flashing animation of the grounding model in the three-dimensional perspective view of the substation in the three-dimensional view of the region are connected to the rendering engine; the generation of the dissolving mask includes: sampling the texture coordinates of the grounding model to the tile noise map to generate a dynamic dissolving mask map, wherein the size of the tile noise map is 0.5m×0.5m, and the sampling frequency of the flashing period of the flashing animation is positively correlated with the grounding resistance value; when the grounding resistance is ≤4Ω, the sampling frequency is 0.5Hz and the flashing period is 2 seconds; When 4Ω < grounding resistance ≤ 10Ω, the sampling frequency is 1Hz and the flashing period is 1 second. When the grounding resistance is greater than 10Ω, the sampling frequency is 2Hz and the flashing period is 0.5 seconds. The dissolved mask image is used as an opaque mask for the grounding grid model material. The mask threshold is dynamically adjusted according to the sampling results, and a flashing effect is achieved through self-illuminating color.

10. A lightning protection intelligent control system based on multi-dimensional data, characterized in that, It includes view building units, association units, and interactive display units. The view construction unit is configured to construct a three-dimensional panoramic view, a regional three-dimensional view, and a device parameter view; The three-dimensional panoramic view is a three-dimensional panoramic model of the geographic area of ​​interest. The protection nodes of the three-dimensional panoramic model include substations and transmission line towers. Each protection node is associated with a risk type label, a time label, and a risk level label. The three-dimensional view of the area includes a three-dimensional perspective view of the substation and a three-dimensional perspective view of the transmission line. The three-dimensional perspective view of the substation and the three-dimensional perspective view of the transmission line contain equipment models, and the equipment models are overlaid with real-time risk data and equipment type labels. The equipment parameter view is a slice of the parameters of the target equipment in the substation and transmission line towers, and displays the parameter change curve of the target equipment along the time axis. The association unit is configured to establish a bidirectional mapping relationship between the three-dimensional panoramic view and the regional three-dimensional view, and to associate the protection nodes of the three-dimensional panoramic view with the corresponding equipment model of the regional three-dimensional view through risk type labels, and the equipment model with the protection nodes of the three-dimensional panoramic view through equipment type labels. The interactive display unit is configured to filter corresponding tags in response to management instructions, and match and display the protection nodes and / or real-time risk data and equipment type tags corresponding to the tags in the three-dimensional panoramic view and the regional three-dimensional view; The bidirectional mapping relationship between the 3D panoramic view and the regional 3D view is dynamically associated through a risk-equipment mirror list: The risk-equipment mirror list is constructed by creating a risk mirror list for each protection node in the 3D panoramic view, and recording the associated area 3D view equipment model labels and risk type labels; The regional 3D view equipment model is used to create a mirror list of equipment, which is then linked to the panoramic view protection node identifiers and equipment type labels. The dynamic update mechanism of dynamic association automatically adds the associated device model to the high-risk rendering queue of the area view when the risk level of the protection node in the panoramic view is upgraded to red, prioritizes the updating of particle effects, and increases the lightning rod discharge frequency to 5Hz; when the parameters of the device model in the area view return to normal, it triggers the downgrading of the panoramic view node label, turns red into green, and removes the temporary association record from the mirror list.

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