Lightning stroke positioning method and system

Abstract

The invention discloses a lightning stroke positioning method and system, relates to the technical field of power system safety protection, and solves the problem of large lightning stroke positioning error in a general scheme. An initial lightning stroke positioning clue is provided through electromagnetic wave data, the Joule heating effect of a discharge point is captured through infrared thermal imaging, non-lightning stroke condition interference is eliminated through a vibration spectrum, and under three-mode physical quantity complementation, multi-dimensional characteristics such as electromagnetic radiation, energy release and mechanical shock when the power transmission line is struck by lightning can be represented; bayesian fusion probability calculation is carried out based on the characteristics, so that more accurate lightning stroke points can be obtained, and protection starting and first-aid repair of a subsequent power system are facilitated.

Description

Technical Field

[0001] This invention relates to the field of power system safety protection technology, and in particular to a lightning strike location method and system. Background Technology

[0002] Lightning is a significant factor affecting the safe and reliable operation of power systems, posing a serious threat to the normal operation of transmission and distribution lines. It can easily cause insulator flashover, line breaks, and line tripping. In the field of power system safety protection, lightning strike location is crucial for ensuring the stable operation of power facilities and reducing losses from lightning faults.

[0003] Traditional lightning location systems primarily rely on single electric field sensors or electromagnetic wave detection devices, typically employing location algorithms based on the Time Difference of Arrival (TOA) to calculate the coordinates of lightning strike points. This method involves deploying multiple detection stations to record the arrival time of the electromagnetic waves generated by the lightning strike at each station. The location of the lightning strike point is then determined through geometric calculations using the time difference and the electromagnetic wave propagation speed. However, severe thunderstorms are often accompanied by complex and variable electromagnetic interference. Single sensors are highly susceptible to noise when receiving electromagnetic wave signals, leading to significant errors in the acquired time data and a substantial decrease in the accuracy of the calculated lightning strike coordinates. With the continuous expansion of modern power grids and the increasing demands for precise protection of transmission lines, traditional lightning strike location methods, due to their large positioning errors, struggle to achieve accurate lightning strike location and cannot meet the practical needs of refined line protection and rapid fault diagnosis.

[0004] Therefore, a method and system for locating lightning strikes are needed. Summary of the Invention

[0005] To address the problem of large errors in lightning strike location in existing technologies, this invention provides a lightning strike location method and system that can more accurately locate the lightning strike position. The specific technical solution is as follows:

[0006] In a first aspect, embodiments of this application provide a lightning strike location method, including:

[0007] Multimodal sensing data of the transmission line is acquired, including electromagnetic wave data, infrared thermal imaging data, and vibration data; time-frequency domain features of the multimodal sensing data are extracted; Bayesian probability fusion calculation is performed based on the time-frequency domain features to obtain the coordinates of the lightning strike point.

[0008] Preferably, the time-frequency domain features of the electromagnetic wave data include the time of arrival (TOA); the time-frequency domain features of the infrared thermal imaging data include the temperature change rate; and the time-frequency domain features of the vibration data include a spectral matching degree weight, which is used to distinguish between lightning strike events and non-lightning strike events based on the matching degree between the vibration data and a preset lightning strike vibration template.

[0009] Preferably, the Bayesian probability fusion calculation based on the time-frequency domain features to obtain the lightning strike point coordinates includes: determining candidate lightning strike regions based on the TOA and dividing the candidate regions into grid cells; calculating the prior probability of lightning strike occurring in each grid cell based on the TOA; the formula for calculating the prior probability includes:

[0010]

[0011] Among them, L i P represents the event of a lightning strike occurring in grid cell i. prior (L i ) indicates that event L has occurred. i The prior probability, d i Let be the distance from grid cell i to the TOA location point, μ be the distance from the candidate region center to the TOA location point, σ be the initial error radius, and e be the base of the natural logarithm; the TOA location point is the lightning strike point calculated based on the TOA; using hotspots as conditional probability constraints, the intermediate probability of the grid cell being struck by lightning is calculated based on the prior probability; the hotspot is the point on the transmission line where the temperature change rate is greater than a preset first threshold; the formula for calculating the intermediate probability includes:

[0012] P mid (L i ) = P prior (L i )·P(H|L i );

[0013]

[0014] Among them, P mid (L i ) indicates that event L has occurred. i The intermediate probability, H represents the condition for whether the grid contains a hotspot, P(H|L) i ) indicates that event L occurs under condition H. i The probability of a lightning strike in a grid cell is calculated by weighting the intermediate probability based on the spectral matching degree weight. The formula for calculating this corrected probability includes:

[0015] P final (L i ) = P mid (L i )·(0.5+0.5W vib );

[0016] Among them, W vib P represents the spectral matching weight. final (L i ) indicates that event L occurred in grid i. iThe correction probability is calculated; the coordinates of the grid cell with the highest correction probability are output as the coordinates of the lightning strike point.

[0017] Preferably, the spectral matching weight W vib The calculation method includes: extracting the energy proportion E of the vibration data in the 8-12kHz frequency band. high Calculate the cosine similarity S between the vibration data and the lightning strike vibration template. cos Based on this energy ratio E high And the cosine similarity S cos Calculate the spectral matching weight W vib The spectral matching weight W vib The calculation formulas include:

[0018] W vib =0.7×E high +0.3×S cos .

[0019] Preferably, the time-frequency domain characteristics of the electromagnetic wave data also include pulse leading edge characteristics and pulse waveform area, the pulse leading edge characteristics being used to determine whether a lightning strike event has occurred; the time-frequency domain characteristics of the vibration data also include the energy proportion in the 8-12kHz frequency band.

[0020] Preferably, after extracting the time-frequency domain features of the multimodal sensing data, the method further includes: calculating the peak lightning current based on the pulse waveform area, the energy ratio, and the temperature change rate; the formula for calculating the peak lightning current includes:

[0021]

[0022] Among them, I peak The peak value of the lightning current is represented by k1, k2, and k3, which are weighting coefficients calibrated experimentally. ∫E(t)dt represents the area of ​​the pulse waveform, ΔT represents the rate of temperature change, and E high The energy percentage is represented; the lightning strike intensity is calculated based on the peak lightning current; and the corresponding lightning strike defense action is executed based on the lightning strike intensity.

[0023] Preferably, after obtaining the coordinates of the lightning strike point, the method further includes: mapping the coordinates of the lightning strike point to the GIS topology database of the power grid geographic information system to obtain the latitude and longitude coordinates corresponding to the coordinates of the lightning strike point; determining the threatened equipment based on the line impedance matrix of the transmission line; and sending a control command to the threatened equipment so that the threatened equipment performs a protection operation based on the control command.

[0024] Secondly, embodiments of this application provide a lightning strike location system, applied to the method described in the first aspect, the system comprising:

[0025] The acquisition module is used to acquire multimodal sensing data of the transmission line, including electromagnetic wave data, infrared thermal imaging data and vibration data.

[0026] The extraction module is used to extract the time-frequency domain features of the multimodal sensing data;

[0027] The calculation module is used to perform Bayesian probability fusion calculation based on the time-frequency domain features to obtain the coordinates of the lightning strike point.

[0028] Thirdly, embodiments of this application provide a computing device, including: a memory for storing a program; and a processor for loading the program to execute the method as described in the first aspect.

[0029] Fourthly, embodiments of this application provide a computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the method described in the first aspect.

[0030] Compared with the prior art, the beneficial effects of the present invention are as follows: electromagnetic wave data provides initial location clues for lightning strikes, infrared thermal imaging captures the Joule heating effect of the discharge point, vibration spectrum is used to eliminate interference from non-lightning strike conditions such as wind vibration, and the complementary three-mode physical quantities can cover the full-dimensional characteristics of electromagnetic radiation, energy release and mechanical impact when a transmission line is struck by lightning. Based on these characteristics, Bayesian fusion probability calculation can be performed to obtain a more accurate lightning strike point, so as to facilitate the subsequent protection activation and emergency repair of the power system. Attached Figure Description

[0031] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0032] Figure 1 A flowchart illustrating a lightning strike location method provided in an embodiment of this application;

[0033] Figure 2 A schematic diagram of a lightning strike location system provided in an embodiment of this application;

[0034] Figure 3 This is a schematic diagram of the structure of a computing device provided in an embodiment of this application. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0037] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0038] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0039] To address the problem of large errors in lightning strike location using traditional methods, this invention provides a lightning strike location method and system that can more accurately locate the lightning strike position.

[0040] Please see Figure 1 , Figure 1 This application provides a flowchart illustrating a lightning strike location method, which is applied to a computing device. Figure 1 As shown, the method includes:

[0041] Step 101: The computing device acquires multimodal sensing data of the transmission line.

[0042] The computing device can be a computing module or control module deployed on the transmission line, or it can be a server, or a smart terminal such as a personal computer or tablet directly operated by power system managers or maintenance personnel. The computing device can communicate with various sensors deployed around the transmission line via wired or wireless means and acquire multimodal sensing data collected by these sensors in real time.

[0043] The multimodal sensing data includes electromagnetic wave data, infrared thermal imaging data, and vibration data.

[0044] Specifically, the computing device can use a loop antenna array with a sampling rate of 10MHz to acquire electromagnetic wave data and capture electromagnetic waveforms in the 10kHz-1MHz frequency band; it can use an uncooled focal plane detector with a frame rate greater than or equal to 30Hz to acquire infrared thermal imaging signals of wire joints and measure the temperature change of wire joints; it can use a triaxial piezoelectric accelerometer to acquire vibration signals and monitor the vibration spectrum of towers in the 0.1-50Hz frequency band; the multimodal sensing data is time-synchronized through GPS or Beidou dual-mode clocks, with a synchronization error of less than or equal to 1μs.

[0045] For example, the electromagnetic wave sensor can be deployed at the top of the tower, using a loop antenna array with a diameter of 1m; the infrared thermal imager can be deployed 3m below the transmission line, using a 640×480 resolution uncooled focal plane detector with a temperature measurement range of -20℃ to 300℃; the vibration sensor is a piezoelectric accelerometer with a frequency response of 0.1-500Hz, installed at the suspension point of the transmission line, and measures vibration acceleration through triaxial measurement with a range of ±50g.

[0046] Step 102: The computing device extracts the time-frequency domain features of the multimodal sensing data.

[0047] For data of different modalities, the computing device can use different computing methods to extract the corresponding time-frequency domain features.

[0048] Preferably, the time-frequency domain features of the electromagnetic wave data include the electromagnetic wave arrival time (TOA); the time-frequency domain features of the infrared thermal imaging data include the temperature change rate; and the time-frequency domain features of the vibration data include the spectral matching weight between the vibration data and a preset lightning strike vibration template.

[0049] The computing device can collect broadband electromagnetic waves generated by lightning strikes based on multiple electromagnetic wave sensors installed on the transmission line; and calculate the time of arrival (TOA) of the broadband electromagnetic waves at each electromagnetic wave sensor based on the waveform characteristics of the broadband electromagnetic waves.

[0050] By combining the TOA (Time of Arrival), the speed of electromagnetic waves, and the positions of various electromagnetic wave sensors, the location of the lightning strike point can be calculated. This location can also be called the TOA positioning point. It is understandable that because the speed of electromagnetic waves is close to the speed of light, and the speed of electromagnetic waves is affected by environmental and medium factors, errors can occur. Furthermore, time synchronization and measurement accuracy also affect positioning accuracy. Therefore, the error between the TOA positioning point and the actual lightning strike point often exceeds 500 meters.

[0051] Therefore, the computing device can perform coarse positioning of the lightning strike point based on the TOA positioning point to obtain a certain candidate area range, and then combine it with other modal data to perform precise positioning of the lightning strike point.

[0052] The computing equipment primarily acquires infrared thermal imaging data of conductor joints to measure their temperature change rate. Conductor joints are the connection points between different conductor segments in a transmission line. Due to contact resistance, heat is generated at these joints when current flows. According to Joule's law, even with the same current and time, joints with higher contact resistance will generate more heat than other parts, leading to a temperature increase. Therefore, the heat generation in the transmission line can be observed by monitoring the temperature change rate of the conductor joints.

[0053] Specifically, the computing device can use the adjacent frame difference method to detect areas of sudden temperature rise. When the rate of temperature change exceeds a preset first threshold, the computing device can designate the area or point as a hotspot. For example, the first threshold is 50°C / ms. The computing device can then use the hotspot situation on the transmission line to assist in determining lightning strike points within the candidate area.

[0054] The spectral matching weight is primarily used to distinguish between lightning strikes and non-lightning strikes. Vibration sensors are fixedly installed at conductor suspension points or towers, and the vibration signals collected during a single lightning strike reflect the overall mechanical impact effect. Therefore, the parameters involved in the spectral matching weight are calculated based on the full waveform data of a single vibration event, characterizing the overall vibration characteristics of that event, and are independent of the local location of the transmission line.

[0055] Preferably, the spectral matching weight W vib The calculation method includes: the calculation device extracts the energy proportion E of the vibration data in the 8-12kHz frequency band. high Calculate the cosine similarity S between the vibration data and the lightning strike vibration template. cos Based on this energy ratio E high And the cosine similarity S cos Calculate the spectral matching weight W vib The spectral matching weight W vib The calculation formulas include:

[0056] W vib =0.7×E high +0.3×S cos .

[0057] The lightning strike vibration template is either a pre-collected vibration dataset of the transmission line under lightning strike conditions, or vibration characteristics of the transmission line under lightning strike conditions extracted based on this dataset. The computing device can perform Fourier transform analysis on the vibration data and then match the analyzed features with the lightning strike vibration template.

[0058] By extracting the high-frequency features of vibration data, low-frequency interference from events such as bird collisions can be eliminated.

[0059] In this embodiment, vibration data is used to verify the authenticity of the event, i.e., whether it was a lightning strike, while infrared and electromagnetic data are responsible for spatial positioning. If the spectral matching weight W... vib A value of 0 indicates a non-lightning strike event, thus suppressing the lightning strike probability for all subsequently calculated regions; if the spectral matching weight W... vib If the value is 1, then the enhancement effect of vibration data on high-probability regions is maximized.

[0060] Preferably, the time-frequency domain characteristics of the electromagnetic wave data also include pulse leading edge characteristics and pulse waveform area, and the time-frequency domain characteristics of the vibration data also include the energy proportion in the 8-12kHz frequency band.

[0061] The computing device can perform wavelet transform on the electromagnetic wave data to extract pulse leading-edge features, which are used to determine whether a lightning strike has occurred. For example, if the rise time of the pulse leading edge is less than 2 μs, the computing device can determine that a lightning strike has occurred.

[0062] Step 103: The computing device performs Bayesian probability fusion calculation based on the time-frequency domain features to obtain the coordinates of the lightning strike point.

[0063] In this context, the computing device can perform fusion calculations based on the multiple features corresponding to the multimodal sensing data after acquiring them.

[0064] Preferably, the computing device can determine the candidate region where the lightning strike event occurred based on the TOA and divide the candidate region into grid cells.

[0065] For example, the size of the grid cell can be 10m*10m, and the TOA positioning point obtained based on the TOA can be the center of the candidate area.

[0066] Based on the TOA, the prior probability of a lightning strike occurring in each grid cell is calculated; the formula for calculating this prior probability includes:

[0067]

[0068] Among them, L i P represents the event of a lightning strike occurring in grid cell i. prior (L i ) indicates that event L has occurred. i The prior probability, d i Let be the distance from grid cell i to the TOA location point, μ be the distance from the center of the candidate region to the TOA location point, σ be the initial error radius, and e be the base of the natural logarithm; the TOA location point is the lightning strike point calculated based on this TOA. It is understandable that if the TOA location point can be the center of the candidate region, μ is 0.

[0069] For example, the initial error radius σ is 500 meters.

[0070] Using hotspots as conditional probability constraints, the intermediate probability of a lightning strike occurring in a grid cell is calculated based on this prior probability. A hotspot is a point on the transmission line where the rate of temperature change exceeds a preset first threshold. The formula for calculating this intermediate probability includes:

[0071] P mid (L i ) = P prior (L i )·P(H|L i );

[0072]

[0073] Among them, P mid (L i ) indicates that event L has occurred. i The intermediate probability, H represents the condition for whether the grid contains a hotspot, P(H|L) i ) indicates that event L occurs under condition H. i The probability of a lightning strike in a grid cell is calculated by weighting the intermediate probability based on the spectral matching degree weight. The formula for calculating this corrected probability includes:

[0074] P final (L i ) = P mid (L i )·(0.5+0.5W vib );

[0075] Among them, W vib P represents the global spectral matching weight. final (L i ) indicates that event L occurred in grid i. i The correction probability is calculated; the coordinates of the grid cell with the highest correction probability are output as the coordinates of the lightning strike point.

[0076] It is understandable that the calculation process of the above-mentioned lightning strike point coordinates is also an iterative process: in the first iteration, the computing device calculates the prior probability distribution based only on the electromagnetic wave TOA; in the second iteration, the computing device introduces the coordinates of the infrared hotspot and concentrates the probability on the grid around the hotspot; in the third iteration, the computing device superimposes the vibration matching degree weight to further suppress the probability value of non-lightning strike areas.

[0077] Preferably, after calculating the correction probability of each grid cell, the computing device can normalize the correction probabilities of all grid cells and output them. The calculation formula for the normalization calculation includes:

[0078]

[0079] Where j is the index of the grid cell, N is the total number of grid cells, and P(L) i ) represents the event L occurring in the normalized mesh i. i The probability of.

[0080] For example, in this iteration process, the iteration terminates when a grid with a lightning strike probability (including prior probability, intermediate probability and corrected probability) greater than or equal to 0.95 appears, or after the third iteration is completed.

[0081] In one possible implementation, if the spectral matching weight is greater than the second threshold and the maximum lightning strike probability obtained in the first iteration is less than the preset third threshold, the computing device can initiate secondary grid partitioning around the highest probability grid and recalculate the probability distribution. The secondary grid is smaller than the original grid cells.

[0082] In another possible implementation, if the spectral matching weight is greater than the second threshold and the maximum lightning strike probability obtained in the third iteration is less than the preset fourth threshold, the computing device can divide the candidate region into a finer-grained grid and restart the calculation of the first iteration.

[0083] For example, the second threshold can be 0.95, and the third and fourth thresholds can be 0.8.

[0084] Preferably, after extracting the time-frequency domain features of the multimodal sensing data, the method further includes: calculating the peak lightning current based on the pulse waveform area, the energy ratio, and the temperature change rate; the formula for calculating the peak lightning current includes:

[0085]

[0086] Among them, I peak The peak value of the lightning current is represented by k1, k2, and k3, which are weighting coefficients calibrated experimentally. ∫E(t)dt represents the area of ​​the pulse waveform, ΔT represents the rate of temperature change, and E high This indicates the percentage of energy used.

[0087] Specifically, based on the IEC 62305 standard, the pulse waveform area in electromagnetic wave data can be directly correlated with the lightning current amplitude; the rate of temperature change can reflect the generation of Joule thermal energy; and the proportion of high-frequency vibration energy is positively correlated with the mechanical impact force of lightning strikes. Based on the above characteristics and the relationship between the transmission line status under lightning strikes, the above formula can be used to calculate the peak lightning current.

[0088] Preferably, the computing device can assess the intensity of the lightning strike based on the peak lightning current.

[0089] The calculation device can directly represent the lightning strike intensity with the peak value of the lightning current, or it can further calculate the lightning current steepness, lightning strike duration and total charge, and then calculate the lightning strike intensity based on these parameters.

[0090] Preferably, when the peak lightning current is less than 10kA, the computing device can only record event data; when the peak lightning current is in the range of 10-100kA, the computing device triggers the surge arrester of the tower adjacent to the lightning strike point to perform protective action; when the peak lightning current is greater than 100kA, the computing device can activate the line differential protection pre-charging and the emergency alarm for maintenance personnel.

[0091] Pre-charging refers to the process by which the differential protection device charges certain capacitors or energy storage elements within itself during normal operation to store sufficient energy. This allows the protection device to quickly activate using the pre-charged energy when a line fault occurs, rapidly detect and assess the fault, and issue a trip command, thus providing rapid protection for the line.

[0092] Preferably, after obtaining the coordinates of the lightning strike point, the computing device can map the coordinates of the lightning strike point to the topology database of the power grid geographic information system (GIS) to obtain the latitude and longitude coordinates corresponding to the lightning strike point coordinates; determine the threatened equipment based on the line impedance matrix of the transmission line; and send control commands to the threatened equipment so that the threatened equipment can perform protection operations based on the control commands.

[0093] The computing device can overlay the coordinates of the lightning strike point onto a GIS map to obtain the latitude and longitude corresponding to the lightning strike point, and mark the threatened equipment near that latitude and longitude. Then, it can send a generic object-oriented substation event (GOOSE) message to the station monitoring system through the IEC 61850 protocol, and send control commands to the threatened equipment through the main control system. The threatened equipment then performs protection operations based on the control commands.

[0094] For example, when a lightning strike occurs in the middle of the #45-#46 span of a 500kV line: the electromagnetic sensor detects an 87kA characteristic waveform at time t0; the infrared thermal imaging detects a sudden temperature rise of 82℃ in the conductor splice tube at t0+15ms; the vibration sensor captures a 12kHz impact vibration (92% similarity to the lightning strike template); the computing device performs fusion calculation to locate and output coordinates (error circle radius 28m); the main control system triggers the parallel gap protection of tower #45 and simultaneously pushes precise location information to the operation and maintenance center.

[0095] In this embodiment, electromagnetic wave data provides initial location clues for lightning strikes, infrared thermal imaging captures the Joule heating effect at the discharge point, and vibration spectrum is used to eliminate interference from non-lightning conditions such as wind vibration. With the complementary physical quantities of the three modes, the full-dimensional characteristics of electromagnetic radiation, energy release, and mechanical impact when a transmission line is struck by lightning can be covered. Based on these characteristics, Bayesian fusion probability calculation can be performed to obtain a more accurate lightning strike point, so as to facilitate the subsequent protection activation and emergency repair of the power system.

[0096] The method provided in the embodiments of this application has been described above. The system provided in the embodiments of this application will be described below.

[0097] Please see Figure 2 , Figure 2 This is a schematic diagram of a lightning strike location system provided in an embodiment of this application, as shown below. Figure 2 As shown, the system 20 includes:

[0098] The acquisition module 201 is used to acquire multimodal sensing data of the transmission line, including electromagnetic wave data, infrared thermal imaging data and vibration data.

[0099] Extraction module 202 is used to extract the time-frequency domain features of the multimodal sensing data;

[0100] The calculation module 203 is used to perform Bayesian probability fusion calculation based on the time-frequency domain features to obtain the coordinates of the lightning strike point.

[0101] Preferably, the time-frequency domain features of the electromagnetic wave data include the time of arrival (TOA); the time-frequency domain features of the infrared thermal imaging data include the temperature change rate; and the time-frequency domain features of the vibration data include a spectral matching degree weight, which is used to distinguish between lightning strike events and non-lightning strike events based on the matching degree between the vibration data and a preset lightning strike vibration template.

[0102] Preferably, the calculation module 203 is specifically used to determine the candidate lightning strike area based on the TOA, and divide the candidate area into grid cells; calculate the prior probability of lightning strike occurring in each grid cell based on the TOA; the formula for calculating the prior probability includes:

[0103]

[0104] Among them, L i P represents the event of a lightning strike occurring in grid cell i. prior (L i ) indicates that event L has occurred. i The prior probability, d iLet be the distance from grid cell i to the TOA location point, μ be the distance from the candidate region center to the TOA location point, σ be the initial error radius, and e be the base of the natural logarithm; the TOA location point is the lightning strike point calculated based on the TOA; using hotspots as conditional probability constraints, the intermediate probability of the grid cell being struck by lightning is calculated based on the prior probability; the hotspot is the point on the transmission line where the temperature change rate is greater than a preset first threshold; the formula for calculating the intermediate probability includes:

[0105] P mid (L i ) = P prior (L i )·P(H|L i );

[0106]

[0107] Among them, P mid (L i ) indicates that event L has occurred. i The intermediate probability, H represents the condition for whether the grid contains a hotspot, P(H|L) i ) indicates that event L occurs under condition H. i The probability of a lightning strike in a grid cell is calculated by weighting the intermediate probability based on the spectral matching degree weight. The formula for calculating this corrected probability includes:

[0108] P final (L i ) = P mid (L i )·(0.5+0.5W vib );

[0109] Among them, W vib P represents the global spectral matching weight. final (L i ) indicates that event L occurred in grid i. i The correction probability is calculated; the coordinates of the grid cell with the highest correction probability are output as the coordinates of the lightning strike point.

[0110] Preferably, the calculation module 203 is specifically used to extract the energy proportion E of the vibration data in the 8-12kHz frequency band. high Calculate the cosine similarity S between the vibration data and the lightning strike vibration template. cos Based on this energy ratio E high And the cosine similarity S cos Calculate the spectral matching weight W vib The spectral matching weight W vib The calculation formulas include:

[0111] Wvib =0.7×E high +0.3×S cos .

[0112] Preferably, the time-frequency domain characteristics of the electromagnetic wave data also include pulse leading edge characteristics and pulse waveform area, the pulse leading edge characteristics being used to determine whether a lightning strike event has occurred; the time-frequency domain characteristics of the vibration data also include the energy proportion in the 8-12kHz frequency band.

[0113] Preferably, the calculation module 203 is specifically used to calculate the peak lightning current based on the pulse waveform area, the energy ratio, and the temperature change rate; the calculation formula for the peak lightning current includes:

[0114]

[0115] Among them, I peak The peak value of the lightning current is represented by k1, k2, and k3, which are weighting coefficients calibrated experimentally. ∫E(t)dt represents the area of ​​the pulse waveform, ΔT represents the rate of temperature change, and E high The system represents the energy percentage; it calculates the lightning strike intensity based on the peak lightning current; the system also includes a protection module 204, which performs corresponding lightning strike defense actions based on the lightning strike intensity.

[0116] Preferably, the protection module 204 is further configured to map the coordinates of the lightning strike point to the GIS topology database of the power grid geographic information system to obtain the latitude and longitude coordinates corresponding to the lightning strike point; determine the threatened equipment based on the line impedance matrix of the transmission line; and send control commands to the threatened equipment so that the threatened equipment performs protection operations based on the control commands.

[0117] The lightning strike location system provided in this application can be understood by referring to the relevant content in the foregoing method embodiment section, and will not be repeated here.

[0118] like Figure 3 As shown, Figure 3 This is a schematic diagram of a possible logical structure of a computing device provided in an embodiment of this application. The computing device 30 includes a processor 301, a communication interface 302, a memory 303, and a bus 304. The processor 301, the communication interface 302, and the memory 303 are interconnected via the bus 304. In an embodiment of this application, the processor 301 is used to control and manage the operation of the computing device 30. For example, the processor 301 is used to execute... Figure 1 The steps in the embodiments and / or other processes used in the techniques described herein. Communication interface 302 is used to support communication by computing device 30. Memory 303 is used to store program code and data of computing device 30.

[0119] The processor 301 can be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a digital signal processor and a microprocessor, etc. The bus 304 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0120] In another embodiment of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including instructions that, when executed on a computer, cause the computer to perform the above-described... Figure 1 The method described in the embodiments.

[0121] Those skilled in the art will recognize that the units of the various examples described in connection with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of the invention.

[0122] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0123] In the embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0124] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0125] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0126] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A method for locating lightning strikes, characterized in that, include: Acquire multimodal sensing data of the transmission line, including electromagnetic wave data, infrared thermal imaging data, and vibration data; Extract the time-frequency domain features of the multimodal sensing data; Based on the aforementioned time-frequency domain features, Bayesian probability fusion calculation is performed to obtain the coordinates of the lightning strike point.

2. The method according to claim 1, characterized in that, The time-frequency domain features of the electromagnetic wave data include the time of arrival (TOA); the time-frequency domain features of the infrared thermal imaging data include the temperature change rate; the time-frequency domain features of the vibration data include a spectral matching weight, which is used to distinguish between lightning strike events and non-lightning strike events based on the matching degree between the vibration data and a preset lightning strike vibration template.

3. The method according to claim 2, characterized in that, The step of performing Bayesian probability fusion calculation based on the time-frequency domain features to obtain the coordinates of the lightning strike point includes: Based on the TOA, candidate areas for lightning strikes are determined, and these candidate areas are divided into grid cells. The prior probability of a lightning strike for each of the grid cells is calculated based on the TOA; the formula for calculating the prior probability includes: Among them, L i P represents the event of a lightning strike occurring in grid cell i. prior (L i ) indicates that event L has occurred. i The prior probability, d i σ is the distance from grid cell i to the TOA location point, μ is the distance between the candidate region center and the TOA location point, σ is the initial error radius, and e is the base of the natural logarithm; the TOA location point is the lightning strike point calculated based on the TOA. Using hotspots as conditional probability constraints, the intermediate probability of a lightning strike occurring in the grid cell is calculated based on the prior probability. The hotspot is a point on the transmission line where the rate of temperature change exceeds a preset first threshold. The formula for calculating the intermediate probability includes: P mid (L i )=P prior (L i )·P(H|L i ); Among them, P mid (L i ) indicates that event L has occurred. i The intermediate probability, H represents the condition for whether the grid contains a hotspot, P(H|L) i ) indicates that event L occurs under condition H. i The probability of; Based on the aforementioned spectral matching degree weights, a weighted correction calculation is performed on the intermediate probability to obtain the corrected probability of the grid cell being struck by lightning; the formula for calculating the corrected probability includes: P final (L i )=P mid (L i )·(0.5+0.5W vib ); Among them, W vib P represents the spectral matching weight. final (L i ) indicates that event L occurred in grid i. i The correction probability; The coordinates of the grid cell with the highest correction probability are output as the coordinates of the lightning strike point.

4. The method according to claim 3, characterized in that, The spectrum matching weight W vib The calculation methods include: Extract the energy percentage E of the vibration data in the 8-12kHz frequency band. high ; Calculate the cosine similarity S between the vibration data and the lightning strike vibration template. cos ; Based on the energy percentage E high And the cosine similarity S cos Calculate the spectral matching weight W vib The spectral matching weight W vib The calculation formulas include: IN vib =0.7×E high +0.3×S cos 。 5. The method according to any one of claims 1-4, characterized in that, The time-frequency domain features of the electromagnetic wave data also include pulse leading edge features and pulse waveform area. The pulse leading edge features are used to determine whether a lightning strike event has occurred. The time-frequency domain features of the vibration data also include the energy proportion in the 8-12kHz frequency band.

6. The method according to claim 5, characterized in that, After extracting the time-frequency domain features of the multimodal sensing data, the method further includes: The peak lightning current is calculated based on the pulse waveform area, the energy percentage, and the temperature change rate; the formula for calculating the peak lightning current includes: Among them, I peak The peak value of the lightning current is represented by k1, k2, and k3, which are weighting coefficients calibrated experimentally. ∫E(t)dt represents the area of ​​the pulse waveform, ΔT represents the rate of temperature change, and E high Indicates the percentage of energy; Calculate the lightning strike intensity based on the peak lightning current; Based on the intensity of the lightning strike, execute the corresponding lightning protection action.

7. The method according to any one of claims 1-4, characterized in that, After obtaining the coordinates of the lightning strike point, the method further includes: The coordinates of the lightning strike point are mapped to the GIS topology database of the power grid geographic information system to obtain the latitude and longitude coordinates corresponding to the lightning strike point. The threatened equipment is determined based on the line impedance matrix of the transmission line; Send control commands to the threatened device so that the threatened device performs protective operations based on the control commands.

8. A lightning strike location system, characterized in that, The system, applied to the method of any one of claims 1-7, comprises: The acquisition module is used to acquire multimodal sensing data of the transmission line, including electromagnetic wave data, infrared thermal imaging data, and vibration data. The extraction module is used to extract the time-frequency domain features of the multimodal sensing data; The calculation module is used to perform Bayesian probability fusion calculation based on the time-frequency domain features to obtain the coordinates of the lightning strike point.

9. A computing device, characterized in that, include: Memory, used to store programs; A processor for loading the program to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the method of any one of claims 1-7.

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