Method for identifying lightning fault of transmission line and lightning detection device

Abstract

This application provides a method for identifying lightning strike faults in power transmission lines and a lightning detection device. The method includes: capturing lightning light signals within a preset time period using an optical sensing unit and converting them into a series of event data; processing the event data to identify target lightning events related to lightning strikes on power transmission lines; and determining whether the target lightning event has caused a fault in the power transmission equipment based on the spatial information of the target lightning event and the geographical information of the power transmission equipment. This allows for the assessment of the impact of lightning on power transmission equipment through real-time capture of light signals, improving the accuracy of lightning detection and thus enhancing the accuracy of detecting lightning-induced faults in power transmission equipment.

Description

Technical Field

[0001] This application relates to the field of lightning detection technology, and in particular to a method for identifying lightning strike faults in power transmission lines and a lightning detection device. Background Technology

[0002] In the environment of power transmission lines and substations, lightning activity can affect power transmission equipment and cause it to malfunction.

[0003] Currently, lightning is detected using predictive methods. Specifically, this involves analyzing cloud radar data, regional weather conditions, and historical lightning activity patterns to predict the probability of lightning occurrence and its potential impact range. Alternatively, lightning can be detected using traveling wave signals; specifically, the location of the lightning strike is determined by monitoring the traveling wave signals generated by lightning strikes in transmission lines.

[0004] However, both of the above methods suffer from low detection accuracy. Summary of the Invention

[0005] This application provides a method for identifying lightning strike faults in power transmission lines and a lightning detection device to improve the accuracy of lightning strike fault detection.

[0006] In a first aspect, embodiments of this application provide a method for identifying lightning strike faults in transmission lines, including:

[0007] The system uses an optical sensing unit to capture lightning signals within a preset time period and converts them into a series of event data.

[0008] The event data is processed to identify target lightning events related to lightning strikes on power transmission lines;

[0009] Based on the spatial information of the target lightning event and the geographical information of the power transmission equipment, determine whether the target lightning event causes the power transmission equipment to malfunction.

[0010] In one possible implementation, the optical sensing unit is an event camera, and the event data includes pixel coordinates and an event timestamp.

[0011] The process of processing the event data to identify target lightning events related to power transmission line lightning strikes includes:

[0012] Clustering events based on their timestamps and pixel coordinates yields at least one event cluster.

[0013] From the at least one event cluster, the event cluster whose morphological characteristics match those of a banded lightning is selected as the target lightning event.

[0014] In one possible implementation, the clustering of events based on event timestamps and pixel coordinates to obtain at least one event cluster includes:

[0015] Construct an event cluster using the first event corresponding to a series of event data as a seed;

[0016] Traverse the remaining events. For events to be clustered whose timestamp difference is less than the time clustering threshold, calculate the Euclidean distance between the event to be clustered and the seed event based on the pixel coordinates of the event to be clustered and the pixel coordinates of the seed event.

[0017] Wherein, the timestamp difference is the difference between the timestamp of the event to be clustered and the target timestamp of the existing event cluster, and the seed event includes the first event;

[0018] If the Euclidean distance is less than the spatial clustering threshold, the event to be clustered is assigned to the event cluster corresponding to the seed event, and the target timestamp of the event cluster is updated using the timestamp of the event to be clustered.

[0019] If the Euclidean distance is greater than or equal to the spatial clustering threshold, then a new event cluster is formed using the event to be clustered as the seed;

[0020] After traversing all remaining events, at least one event cluster is obtained.

[0021] In one possible implementation, selecting event clusters from the at least one event cluster whose morphological characteristics match those of banded lightning as the target lightning event includes:

[0022] Calculate the convex hull of each event cluster;

[0023] Calculate the morphological parameters of each convex hull, which are used to characterize the elongation or narrowness of the shape;

[0024] Event clusters whose morphological parameters meet preset conditions are identified as event clusters whose morphological characteristics conform to those of banded lightning, and these event clusters are identified as target lightning events.

[0025] In one possible implementation, after identifying the target lightning event associated with a lightning strike on a transmission line, the process includes:

[0026] Based on the pixel coordinates in the target lightning event, determine the feature vector corresponding to the target lightning event;

[0027] The linear equation of the band lightning is determined based on the feature vector and the pixel coordinates in the target lightning event.

[0028] In one possible implementation, the spatial information of the target lightning event is the linear equation of a band lightning, and the geographical information of the power transmission equipment is the linear equation of the equipment.

[0029] The step of determining whether the target lightning event causes a malfunction in the transmission equipment based on the spatial information of the target lightning event and the geographical information of the transmission equipment includes:

[0030] Acquire images, including those of power transmission equipment, using a visible light camera;

[0031] The image is analyzed to determine the linear equation of the power transmission equipment in the coordinate system of the visible light camera.

[0032] Based on the pre-stored transformation matrix, the linear equation of the ribbon lightning is converted into the linear equation of the lightning in the coordinate system of the visible light camera;

[0033] Based on the lightning linear equation and the equipment linear equation, determine whether the target lightning event causes the power transmission equipment to malfunction.

[0034] In one possible implementation, determining whether the target lightning event caused a failure in the power transmission equipment based on the lightning linear equation and the equipment linear equation includes:

[0035] Calculate the distance between the lightning straight-line equation and the device straight-line equation;

[0036] If the distance is less than a preset distance, it is determined that the target lightning event caused the power transmission equipment to malfunction, and the location of the malfunction in the power transmission equipment is determined.

[0037] In one possible implementation, the power transmission equipment includes power transmission lines and towers;

[0038] The preset distance includes a first preset distance corresponding to the transmission line and a second preset distance corresponding to the tower.

[0039] In one possible implementation, an optical sensing unit is used to capture lightning light signals within a preset time period and convert them into a series of event data, including:

[0040] Real-time detection of ambient light intensity;

[0041] When the detected ambient brightness value is greater than the brightness threshold, the optical sensing unit captures the lightning light signal within a preset time period and converts it into a series of event data.

[0042] Secondly, embodiments of this application provide a lightning monitoring device, comprising:

[0043] The event camera module is used to capture lightning light signals and output event data;

[0044] The processing unit is communicatively connected to the event camera module and is used to execute the transmission line lightning strike fault identification method as described in the first aspect and / or various possible embodiments of the first aspect.

[0045] In one possible implementation, the device further includes:

[0046] A visible light camera module, which is communicatively connected to the processing unit, is used to acquire visible light images containing power transmission equipment.

[0047] The processing unit is also used to determine the location information of the power transmission equipment based on the visible light image.

[0048] Thirdly, embodiments of this application provide a transmission line lightning strike monitoring and early warning system, including:

[0049] One or more lightning monitoring devices as described in the second aspect and / or various possible embodiments of the second aspect are deployed along the transmission line or at critical nodes;

[0050] The system server is communicatively connected to the lightning monitoring device and is used to receive and aggregate the processing results of each device for comprehensive analysis, data storage and visualization.

[0051] The client terminal communicates with the system server and is used to receive and display lightning strike fault alarms, location information, and system status.

[0052] Fourthly, embodiments of this application provide a transmission line lightning strike fault identification device, comprising:

[0053] The signal acquisition module is used to capture lightning light signals within a preset time period using an optical sensing unit and convert them into a series of event data;

[0054] The processing module is used to process the event data and identify target lightning events related to lightning strikes on transmission lines;

[0055] The fault determination module is used to determine whether the target lightning event causes a fault in the power transmission equipment based on the spatial information of the target lightning event and the geographical information of the power transmission equipment.

[0056] Fifthly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0057] The memory stores computer-executed instructions;

[0058] The processor executes computer execution instructions stored in the memory, causing the processor to perform the transmission line lightning strike fault identification method as described in the first aspect and / or various possible embodiments of the first aspect.

[0059] In a sixth aspect, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the transmission line lightning strike fault identification method as described in the first aspect and / or various possible embodiments of the first aspect.

[0060] In a seventh aspect, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the transmission line lightning strike fault identification method as described in the first aspect and / or various possible implementations of the first aspect.

[0061] The transmission line lightning strike fault identification method and lightning detection device provided in this application include: capturing lightning light signals within a preset time period using an optical sensing unit and converting them into a series of event data; processing the event data to identify target lightning events related to lightning strikes on transmission lines; and determining whether the target lightning event causes a fault in the transmission equipment based on the spatial information of the target lightning event and the geographical information of the transmission equipment. In this way, the optical sensing unit captures lightning light signals in real time and identifies target lightning signals related to lightning strikes based on a series of event data converted from the lightning light signals. Furthermore, considering that whether lightning will cause a fault in the transmission equipment is related to the distance between the lightning and the transmission equipment, the method determines whether the target lightning event causes a fault in the transmission equipment based on the spatial information of the target event and the geographical information of the transmission equipment. This achieves the goal of judging the impact of lightning on transmission equipment by capturing light signals in real time, improving the accuracy of lightning detection and thus improving the accuracy of lightning-induced fault detection in transmission equipment. Attached Figure Description

[0062] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0063] Figure 1 A flowchart illustrating a method for identifying lightning strike faults in transmission lines provided in this application;

[0064] Figure 2 A flowchart illustrating a method for determining a target lightning event provided in this application;

[0065] Figure 3 This application provides a flowchart illustrating a method for determining whether a power transmission equipment has malfunctioned.

[0066] Figure 4 A flowchart illustrating another method for identifying lightning strike faults in transmission lines provided in this application;

[0067] Figure 5 This application provides a schematic diagram of the structure of a lightning monitoring device;

[0068] Figure 6 This application provides a schematic diagram of a power transmission line lightning strike monitoring and early warning system;

[0069] Figure 7 A schematic diagram of the structure of a power transmission line lightning strike fault identification device provided in this application;

[0070] Figure 8 This is a schematic diagram of the structure of an electronic device provided in this application.

[0071] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0072] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application.

[0073] In transmission lines and substations, lightning activity is a major cause of equipment failure. The instantaneous high voltage and strong current generated by lightning discharge can directly break down insulating equipment or induce overvoltage through electromagnetic induction, leading to short circuits in transmission lines, damage to towers, or equipment failures in substations. Therefore, it is necessary to monitor lightning conditions on transmission lines to facilitate subsequent repairs of lightning-induced faults.

[0074] Currently, lightning is detected using predictive methods. Specifically, this involves analyzing cloud radar data, regional weather conditions, and historical lightning activity patterns to predict the probability of lightning occurrence and its potential impact range. Alternatively, lightning can be detected using traveling wave signals; specifically, the location of the lightning strike is determined by monitoring the traveling wave signals generated by lightning strikes in transmission lines.

[0075] However, the forecasting method is highly dependent on the accuracy of meteorological data and historical statistical models. Since the forecasting data used is not data from when lightning occurs, the accuracy of the forecast results is relatively poor.

[0076] The traveling wave detection method may lead to misjudgment because the traveling wave signal may be triggered by other factors (such as short circuit faults or equipment abnormalities). Furthermore, traveling wave detection can only reflect the indirect effects of lightning strikes and cannot record the trajectory of lightning, thus it cannot determine the faults of power transmission equipment caused by lightning strikes.

[0077] Therefore, neither of the existing methods can accurately detect faults in power transmission equipment.

[0078] Based on this, this application provides a method for identifying lightning strike faults in power transmission lines. It utilizes an optical sensing unit to detect lightning signals in real time, obtaining multiple event data. Further, the multiple event data are processed to identify target lightning events related to power transmission line lightning strikes, thereby achieving lightning strike detection. Moreover, considering that power transmission equipment faults caused by lightning strikes are mainly related to the location of both the lightning and the transmission equipment, the method determines whether the target lightning event has caused a power transmission equipment fault based on the spatial information of the target lightning event and the geographical information of the transmission equipment. In this way, it achieves lightning detection through real-time data and determines whether the target lightning event has caused a power transmission equipment fault based on location information, thus improving the accuracy of lightning-induced power transmission equipment fault detection.

[0079] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0080] Figure 1 This is a flowchart illustrating a method for identifying lightning strike faults in power transmission lines provided in this application. This method can be applied to inspection equipment for inspecting power transmission lines, or to a server. This application does not limit the application to this method.

[0081] Among them, inspection equipment refers to equipment that can move along the power transmission line.

[0082] like Figure 1 As shown, the method includes:

[0083] S101. Use an optical sensing unit to capture lightning light signals within a preset time period and convert them into a series of event data.

[0084] The optical sensing unit can be installed on the inspection equipment. It is an event-driven optical sensor capable of capturing pixel-level brightness changes in real time and outputting event stream data.

[0085] For example, the optical sensing unit may include an event camera, such as a Dynamic Vision Sensor (DVS) camera. The DVS camera records brightness change events of each pixel through event stream data, such as generating an event when the brightness of a pixel jumps from 100 lux to 200 lux at a certain moment.

[0086] A series of event data is an event sequence output by the optical sensing unit, including pixel coordinates, timestamps, and brightness changes.

[0087] For example, the event data includes events such as E1(100,150,10.0,ON) and E2(102,152,10.1,ON). The first two parameters are pixel coordinates, the third parameter is a timestamp, and the fourth parameter is the brightness change status. ON indicates that the pixel brightness has increased.

[0088] In this application, the ambient light brightness can be detected in real time by an ambient light detection device; when the detected ambient light brightness value is greater than the brightness threshold, the lightning light signal within a preset time period is captured by an optical sensing unit and converted into a series of event data.

[0089] This ambient light detection device is a sensor used to measure the ambient light in real time.

[0090] For example, a light intensity sensor measures the lux value of the current scene using a photodiode.

[0091] The brightness threshold can be a pre-set, relatively large value to avoid misidentifying light as lightning. The brightness threshold varies depending on the time of day, and can be determined based on the current moment. This application does not limit the brightness threshold in its embodiments.

[0092] The series of event data refers to data corresponding to a series of events, and this application embodiment does not limit this.

[0093] For example, a light sensor can be used to collect the current brightness value p, a fixed brightness increment value p0 can be set, and an initial brightness threshold p1 can be set according to... When the brightness exceeds the brightness threshold p1, the DVS camera records the current time t1 and records the preset time period. Pixel data within DVS camera acquisition Pixel data within a given time period.

[0094] The brightness threshold is a brightness judgment standard that is dynamically adjusted based on the ambient brightness.

[0095] For example, if the ambient brightness is 1000 lux and the brightness threshold is set to 2000 lux, when the light sensor detects that the brightness of a certain pixel suddenly increases to 2500 lux, it will trigger the event collection within a preset time period.

[0096] For example, in low-light nighttime scenarios, the brightness threshold can be appropriately lowered to capture weak lightning signals; in high-light interference scenarios, the brightness threshold can be increased to filter out non-lightning noise.

[0097] Since the likelihood of lightning is higher when the ambient light is bright, the optical sensor is used to capture lightning signals only when the ambient light is bright, thus avoiding the waste of resources caused by real-time detection by the optical sensor.

[0098] S102. Process the event data to identify target lightning events related to lightning strikes on power transmission lines.

[0099] For example, in the above embodiments, the DVS camera acquires... When analyzing pixel data within a given time period, it is also possible to obtain brightness changes within that time period. Calculate the rate of change in brightness Set a threshold r1 for the brightness change of lightning. At that time, a lightning warning signal was triggered.

[0100] The brightness change threshold can be preset based on actual conditions, and this application embodiment does not limit this.

[0101] Lightning warning signals can be sent through inspection equipment and / or servers, but this application embodiment does not limit this.

[0102] When the rate of change in brightness within a preset time period exceeds the brightness change threshold, a process is executed to identify target lightning events related to lightning strikes on transmission lines.

[0103] Processing event data to identify target lightning events related to lightning strikes on transmission lines may include: clustering the event data and identifying target lightning events related to lightning strikes on transmission lines based on the clustering results. See the following embodiments for details.

[0104] S103. Based on the spatial information of the target lightning event and the geographical information of the power transmission equipment, determine whether the target lightning event caused a malfunction in the power transmission equipment.

[0105] The spatial information of the target lightning event can include the location where the lightning occurred, and the geographical information of the power transmission equipment can include the location of the power transmission equipment.

[0106] The transmission line lightning strike fault identification method provided in this application utilizes an optical sensing unit to detect lightning signals in real time, obtaining multiple event data. Further, the multiple event data are processed to identify target lightning events related to transmission line lightning strikes, thereby achieving lightning detection. Moreover, considering that lightning-induced transmission equipment faults are mainly related to the location of both the lightning and the transmission equipment, the method determines whether the target lightning event has caused a transmission equipment fault based on the spatial information of the target lightning event and the geographical information of the transmission equipment. In this way, it achieves the identification of target lightning events through real-time detection data to determine the presence of lightning, and the determination of whether the target lightning event has caused a transmission equipment fault based on location information, thus improving the accuracy of lightning-induced transmission equipment fault detection.

[0107] Figure 2 This application provides a flowchart illustrating a method for determining a target lightning event, as shown below. Figure 2 As shown, in this embodiment... Figure 1 Based on the embodiments, the method for targeting lightning events is described in detail.

[0108] It should be understood that the event data in the above embodiments includes pixel coordinates and event timestamps.

[0109] like Figure 2 As shown, the method includes:

[0110] S201. Cluster the events based on their timestamps and pixel coordinates to obtain at least one event cluster.

[0111] Pixel coordinates are the coordinate information of the location where the lightning signal occurred, recorded in the event data.

[0112] For example, if the pixel coordinates in the event data are (100, 150), it means that the lightning signal occurred in the 100th column and 150th row of the image.

[0113] The timestamp is the time when the event was captured.

[0114] In this application, clustering events based on their timestamps and pixel coordinates to obtain at least one event cluster may include: constructing an event cluster using the first event corresponding to a series of event data as a seed; traversing the remaining events, for events to be clustered whose timestamp difference is less than a time clustering threshold, calculating the Euclidean distance between the event to be clustered and the seed event based on the pixel coordinates of the event to be clustered and the pixel coordinates of the seed event; wherein, the timestamp difference is the difference between the timestamp of the event to be clustered and the target timestamp of an existing event cluster, and the seed event includes the first event; if the Euclidean distance is less than a spatial clustering threshold, then the event to be clustered is assigned to the event cluster corresponding to the seed event, and the target timestamp of the event cluster is updated using the timestamp of the event to be clustered; if the Euclidean distance is greater than or equal to the spatial clustering threshold, then a new event cluster is constructed using the event to be clustered as a seed; after traversing all remaining events, at least one event cluster is obtained.

[0115] The temporal clustering threshold and spatial clustering threshold can be preset, and this application embodiment does not limit this.

[0116] Optionally, updating the target timestamp of an event cluster using the timestamp of the event to be clustered may include updating the timestamp of the event to be clustered into an existing event cluster to the target timestamp corresponding to that event cluster.

[0117] For example, a temporal clustering threshold T and a spatial clustering threshold R are pre-set, with the first event... Create event cluster A as a seed. For each subsequent new event... That is, for events to be clustered, traverse the known event clusters A and calculate the time difference between the new event and event cluster A. ,like If so, skip that event cluster. pass Calculate the Euclidean distance between two events (the current new event and the first event), and further if... If so, the event is placed into event cluster A, and the timestamp in event cluster A is updated.

[0118] If an event If it does not belong to any cluster, then the event is considered as such. A new event cluster is created for the seed. If no new events are added to an event cluster within 2T time, the event cluster is considered to have been generated.

[0119] In this way, multiple events are divided into at least one event cluster based on pixel coordinates and timestamps, so as to group events with similar features into the same event cluster, so as to facilitate subsequent filtering of target lightning events based on event clusters.

[0120] S202. Select the event clusters whose morphological characteristics match those of banded lightning from at least one event cluster as target lightning events.

[0121] In this application, the process of screening target lightning events may include: calculating the convex hull of each event cluster; calculating the morphological parameters of each convex hull, the morphological parameters being used to characterize the elongation of the shape; determining the event cluster whose morphological parameters meet preset conditions as an event cluster whose morphological characteristics conform to those of band lightning, and identifying the event cluster as the target lightning event.

[0122] The morphological parameter can be the compactness of the convex hull, which can be determined based on the area and perimeter of the convex hull. The smaller the compactness, the closer the convex hull is to a band shape.

[0123] The preset conditions can be conditions related to the tightness of the convex hull, but this application embodiment does not limit this.

[0124] For example, for any event cluster, the Graham Scan algorithm is used to calculate the convex hull of the event cluster and determine the vertex coordinates of the convex hull. Using the shoelace formula Calculate the area of ​​the convex hull. .

[0125] Use the Euclidean distance between any two vertices Calculate the perimeter of the convex hull by... Calculate the tightness of the convex hull and pre-set a tightness threshold. ,Should It can be a value close to 0, if Then it can be determined that the event clusters within the convex hull are banded lightning.

[0126] In this way, by calculating the convex hull of each event cluster, the shape of time within the event cluster can be determined. If the elongation of the convex hull corresponding to the event cluster meets the preset conditions, it can be determined that the events within the event cluster constitute lightning.

[0127] The method for determining target lightning events provided in this application clusters events, grouping similar events into a single category to obtain event clusters. Event clusters with morphological characteristics matching banded lightning are then identified to more accurately determine the target lightning event.

[0128] The following examples illustrate the method for identifying target lightning events.

[0129] The optical sensing unit has a dynamic range of 120dB and a resolution of 1280. A 720-pixel DVS camera. The visible light camera can be a combination of an 8-megapixel white-vision camera and a 4-megapixel night-vision camera.

[0130] The overall process of identifying lightning faults in transmission lines includes:

[0131] Obtain the ambient brightness p in real time through an ambient brightness sensor, add 1000 lux to the ambient brightness p to obtain the ambient brightness threshold p1. The DVS camera continuously collects the brightness around the transmission line. When the surrounding brightness is greater than p1, record this moment as t1 and record the DVS pixel data within 100 ms. The DVS camera records the pixel data and brightness changes within 100 ms. Calculate the brightness change rate. Set the brightness change threshold r1 for lightning. When it is satisfied, trigger a lightning warning signal.

[0132] Cluster the events within 100 ms. The preset time clustering threshold T = 5 ms and the spatial clustering threshold R = 5 pixels. The 5 recorded events are: E1:(100,150,10.0,ON), E2:(102,152,10.1,ON), E3:(200,50,10.2,ON), E4:(105,155,10.5,ON), E5:(101,149,11.0,ON), E6:(205,55,20.0,ON).

[0133] Create an event cluster C1 with the first event E1 as the seed and read the next event E2. Calculate the time difference between E2 and all events in C1 (currently only E1): 10.1 - 10.0 = 0.1 ms < T(5 ms).

[0134] Calculate the spatial distance: ≈2.8 pixels < R(5 pixels). Both meet the thresholds, so E2 is included in C1. The time difference between E3 and the events in C1 (such as with E1: 0.2 ms) is satisfied, but the spatial distance ≈141 pixels, which is much greater than R. Therefore, E3 cannot be added to C1. Since it does not belong to other existing event clusters either, create a new event cluster C2 with E3 as the seed. The spatio-temporal distances between E4 and E1 / E2 in C1 are very close, so E4 is added to C1. E5 is also added to C1. The time difference between E6 and C1 (10 ms) has exceeded T, and the spatial distance is also far. The time difference between E6 and C2 (9.8 ms) has also exceeded T. Therefore, create a new event cluster C3 with E6 as the seed.

[0135] In this way, three independent event clusters can be obtained: C1 = {E1, E2, E4, E5} (possibly a part of a lightning flash), C2 = {E3} (an isolated flash point), C3 = {E6} (another event at a later time). Therefore, it can be determined that the events in event cluster C1 are target lightning events.

[0136] In this application, a method for calculating the linear lightning corresponding to a band lightning strike can be used after identifying the target lightning event associated with the lightning strike on the transmission line.

[0137] Optionally, the feature vector corresponding to the target lightning event is determined based on the pixel coordinates in the target lightning event; the linear equation of the band lightning is determined based on the feature vector and the pixel coordinates in the target lightning event.

[0138] For example, the coordinates of the selected points form a set of points that are filtered to resemble a band of lightning clusters:

[0139]

[0140] pass , Find the coordinates of the center point of the event cluster. Where n is the number of events in the event cluster.

[0141] Subtracting the coordinates of the center point from each point yields:

[0142]

[0143] Calculate the covariance matrix of point set P1

[0144] in, , ,

[0145] .

[0146] use , Given a unit vector, obtain the eigenvalues. , eigenvalue Bring back Where W is the eigenvector to be solved. Thus, the corresponding unit eigenvector can be obtained. That is, we obtain the two components a and b of the unit eigenvector.

[0147] Given the coordinates of the center point The linear equation of the target lightning event is obtained. .

[0148] In this way, after identifying the target lightning event, the linear equation corresponding to the target lightning event is further determined based on the characteristics of the target lightning event, so as to determine whether the lightning will cause the power transmission equipment to fail based on the linear equation.

[0149] Figure 3 This application provides a flowchart illustrating a method for determining whether a power transmission equipment has malfunctioned. Figure 3 As shown, in this embodiment... Figure 1 Based on the embodiments, a detailed explanation is provided of the method for determining whether a target lightning event causes a power transmission equipment malfunction.

[0150] It should be understood that the spatial information of the target lightning event in the above embodiments is the linear equation of the band lightning, and the geographical information of the power transmission equipment is the linear equation of the power transmission equipment.

[0151] like Figure 3 As shown, the method includes:

[0152] S301. Acquire images, including those of power transmission equipment, using a visible light camera.

[0153] For example, power transmission equipment may include power transmission lines and towers, and may also include other equipment, which is not limited in this application embodiment.

[0154] For example, while using an optical sensing unit to capture lightning signals within a preset time period and convert them into a series of event data, an image captured by a visible light camera, including images of power transmission equipment, is obtained.

[0155] S302. Analyze the image to determine the linear equation of the power transmission equipment in the coordinate system of the visible light camera.

[0156] For example, by using image edge detection and Hough transform, straight line segments corresponding to power transmission equipment are detected. Pixels belonging to the same physical target, such as pixels belonging to power transmission lines, are fitted into multiple straight line equations using the least squares method. .

[0157] S303. Based on the pre-stored transformation matrix, convert the linear equation of the ribbon lightning into the linear equation of the lightning in the coordinate system of the visible light camera.

[0158] For example, the linear coefficient B of the determined linear equation of the band lightning. pass The linear coefficients of the linear equation of the band lightning in the visible light camera coordinate system were obtained. .

[0159] Where B is the coefficient matrix of the straight line equation obtained in the DVS camera, and H is the transformation matrix between the DVS camera coordinate system and the visible light camera coordinate system, that is, the transformation matrix pre-stored in this application. This is the transpose operator. is the inverse of matrix H. C is the coefficient matrix of the equation of the line in the visible light camera coordinate system.

[0160] Using the above method, the equation of the linear lightning in the visible light camera coordinate system can be obtained as follows: .

[0161] The method for obtaining the pre-stored transformation matrix may include: A DVS camera and a visible light camera are rigidly connected. Using a calibration board with a known pattern (such as a checkerboard), the calibration board is moved in different orientations within the shared field of view of both cameras. Based on synchronously acquired data, the internal parameters (including focal length, principal point, and distortion coefficients) of the DVS camera and the visible light camera are calculated separately. Through the correspondence between the calibration board pattern and the two sets of data, a homography transformation matrix H from the DVS module pixel coordinate system to the optical module pixel coordinate system is calculated.

[0162] S304. Based on the lightning linear equation and the equipment linear equation, determine whether the target lightning event caused a failure in the power transmission equipment.

[0163] In this application, the distance between the lightning straight-line equation and the equipment straight-line equation can be calculated; if the distance is less than a preset distance, it is determined that the target lightning event caused the power transmission equipment to malfunction, and the location of the malfunction in the power transmission equipment is determined.

[0164] The preset distance can be the unsafe distance for lightning, but this application embodiment does not limit this.

[0165] When the power transmission equipment includes transmission lines and towers, the preset distance includes a first preset distance corresponding to the transmission lines and a second preset distance corresponding to the towers. The first preset distance and the second preset distance may be the same or different, and this application embodiment does not limit this.

[0166] For example, in and When parallel, through the formula Calculate the distance between two lines. Specifically, and Substituting into the formula, we can get ,in, for For any point, set a preset distance of M, when It is believed that if a band lightning strikes a power transmission tower or line, a lightning warning signal can be issued again.

[0167] It should be understood that the location of a fault in a power transmission device can be determined based on the intersection of two straight lines or a location that is relatively close to it.

[0168] Thus, considering that lightning can cause power transmission equipment to malfunction when the distance between the lightning and the power transmission equipment is small, the target lightning event is determined to cause the power transmission equipment to malfunction when the distance between the two straight line equations is less than the preset distance.

[0169] Therefore, the method for determining whether a power transmission equipment has malfunctioned, provided in this application embodiment, transforms the linear equation of the lightning event and the linear equation of the power transmission equipment to the same coordinate system, so that it is possible to determine whether the power transmission equipment has malfunctioned based on the linear equation, resulting in a higher accuracy of the determination result.

[0170] In conclusion, Figure 4 A flowchart illustrating another method for identifying lightning strike faults in transmission lines provided in this application.

[0171] like Figure 4 As shown, the method for identifying lightning strike faults on transmission lines includes the following steps:

[0172] The DVS camera acquires a real-time event stream of the surrounding environment and determines whether the ambient brightness exceeds a brightness threshold. If not, it returns to the step of acquiring the real-time event stream of the surrounding environment using the DVS camera. If so, it takes the pixel data and brightness change Δp within the time interval Δt, and calculates the brightness change rate based on r = Δp / Δt.

[0173] Determine if the brightness change rate is greater than the brightness change threshold. If not, return to the step of real-time acquisition of surrounding environmental event streams by the DVS camera. If so, trigger the first radar warning signal, cluster the event streams, and obtain event clusters.

[0174] Convex hull analysis is performed on the event clusters to calculate the area-to-perimeter ratio, thus obtaining the compactness of the convex hull. It is then determined whether the compactness of the convex hull is less than a compactness threshold. If not, the event cluster is identified as an interfering event cluster and not a banded lightning cluster. If it is, the eigenvectors of the banded lightning are determined, and the linear equation of the current lightning is calculated.

[0175] Furthermore, visible light images are acquired, and the linear equations of the transmission lines and towers are obtained through edge detection and the least squares method. The linear equation of the banded lightning is then transformed into the linear equation of the visible light image through matrix transformation, and the distance between the two lines is calculated. That is, the distance between the linear equation of the banded lightning and the linear equation of the transmission line, and the distance between the linear equation of the banded lightning and the linear equation of the tower are calculated separately.

[0176] If the distance is less than a preset distance, the device's location information is obtained and uploaded to the monitoring platform along with the captured image and the shape of the lightning. If not, no lightning warning is issued.

[0177] It should be understood that the specific execution method of each step in the above process can be found in the relevant description of the above embodiments, and will not be repeated here.

[0178] Figure 5 This application provides a schematic diagram of the structure of a lightning monitoring device.

[0179] like Figure 5As shown, the lightning monitoring device includes an event camera module, a visible light camera module, and a processing unit.

[0180] The event camera module is used to capture lightning light signals and output event data.

[0181] For example, the event camera module may include a DVS camera, which collects event information in the transmission line channel in real time.

[0182] The processing unit is communicatively connected to the event camera module and is used to execute the transmission line lightning strike fault identification method described in the above embodiments.

[0183] The visible light camera module, which communicates with the processing unit, is used to acquire visible light images containing power transmission equipment. For example, the visible light camera module records images within a power transmission line corridor.

[0184] For example, images containing power transmission equipment can be captured.

[0185] The processing unit is also used to determine the location information of the power transmission equipment based on the visible light image. For details, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0186] Lightning monitoring devices may also include a power supply module for powering the equipment.

[0187] This application also provides a lightning strike monitoring and early warning system for power transmission lines, which includes: a lightning monitoring device, a system server, and a client terminal.

[0188] The number of lightning monitoring devices can be one or more, and this application embodiment does not limit this.

[0189] Lightning monitoring devices are deployed along power transmission lines or at key nodes.

[0190] The system server communicates with the lightning monitoring devices to receive and aggregate the processing results from each device, and performs comprehensive analysis, data storage, and visualization.

[0191] The client terminal communicates with the system server to receive and display lightning strike alarms, location information, and system status.

[0192] For example, a lightning strike fault alarm may include the lightning warning signal in the above embodiments.

[0193] Figure 6 This application provides a schematic diagram of a power transmission line lightning strike monitoring and early warning system.

[0194] like Figure 6As shown, the lightning monitoring device includes a light intensity sensor, a DVS camera, a visible light camera, a positioning module, a control module, and a wireless communication module.

[0195] The light intensity sensor, DVS camera, visible light camera, and positioning module transmit the collected data to the control module. The control module can communicate with the server via a wireless communication module, either directly transmitting the collected data to the server for processing or processing the data and transmitting the processed data back to the server. The server processes the received data and transmits the processing results to the client terminal. The light intensity sensor is used by the user to detect the ambient light level.

[0196] For example, the control module acquires the current location information and transmits the location information (acquired by the positioning module), image or image analysis results to the server via a wireless module. The server processes the data and displays it through a monitoring platform (such as a client terminal).

[0197] Figure 7 This application provides a schematic diagram of the structure of a transmission line lightning strike fault identification device, as shown below. Figure 7 As shown, the transmission line lightning strike fault identification device 70 provided in this embodiment includes:

[0198] The signal acquisition module 701 is used to capture lightning light signals within a preset time period using an optical sensing unit and convert them into a series of event data.

[0199] The processing module 702 is used to process event data and identify target lightning events related to lightning strikes on power transmission lines.

[0200] The fault determination module 703 is used to determine whether the target lightning event has caused a fault in the power transmission equipment based on the spatial information of the target lightning event and the geographical information of the power transmission equipment.

[0201] The transmission line lightning fault identification device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0202] Figure 8 This is a schematic diagram of the structure of an electronic device provided in this application. Figure 8 As shown, the electronic device 80 provided in this embodiment includes at least one processor 801 and a memory 802. Optionally, the device 80 further includes a communication component 803. The processor 801, memory 802, and communication component 803 are connected via a bus 804.

[0203] In a specific implementation, at least one processor 801 executes computer execution instructions stored in memory 802, causing at least one processor 801 to perform the above-described method.

[0204] The specific implementation process of processor 801 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0205] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0206] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0207] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0208] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0209] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0210] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0211] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0212] The division of units is merely a logical functional division; 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 coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0213] 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.

[0214] In addition, 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.

[0215] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a 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 of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0216] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0217] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope.

Claims

1. A method for identifying lightning strike faults in power transmission lines, characterized in that, include: The system uses an optical sensing unit to capture lightning signals within a preset time period and converts them into a series of event data. The event data is processed to identify target lightning events related to lightning strikes on power transmission lines; Based on the spatial information of the target lightning event and the geographical information of the power transmission equipment, it is determined whether the target lightning event caused the power transmission equipment to malfunction. The spatial information of the target lightning event is the linear equation of the band lightning, and the geographical information of the power transmission equipment is the linear equation of the power transmission equipment. The step of determining whether the target lightning event causes a malfunction in the transmission equipment based on the spatial information of the target lightning event and the geographical information of the transmission equipment includes: Acquire images, including those of power transmission equipment, using a visible light camera; The image is analyzed to determine the linear equation of the power transmission equipment in the coordinate system of the visible light camera. Based on the pre-stored transformation matrix, the linear equation of the ribbon lightning is converted into the linear equation of the lightning in the coordinate system of the visible light camera; Based on the lightning linear equation and the equipment linear equation, determine whether the target lightning event causes the power transmission equipment to malfunction; The step of determining whether the target lightning event causes a malfunction in the power transmission equipment based on the lightning linear equation and the equipment linear equation includes: Calculate the distance between the lightning straight-line equation and the device straight-line equation; If the distance is less than a preset distance, it is determined that the target lightning event caused the power transmission equipment to malfunction, and the location of the malfunction in the power transmission equipment is determined.

2. The method according to claim 1, characterized in that, The optical sensing unit is an event camera, and the event data includes pixel coordinates and event timestamps. The process of processing the event data to identify target lightning events related to power transmission line lightning strikes includes: Clustering events based on their timestamps and pixel coordinates yields at least one event cluster. From the at least one event cluster, the event cluster whose morphological characteristics match those of a banded lightning is selected as the target lightning event.

3. The method according to claim 2, characterized in that, The event clustering based on event timestamps and pixel coordinates yields at least one event cluster, including: Construct an event cluster using the first event corresponding to a series of event data as a seed; Traverse the remaining events. For events to be clustered whose timestamp difference is less than the time clustering threshold, calculate the Euclidean distance between the event to be clustered and the seed event based on the pixel coordinates of the event to be clustered and the pixel coordinates of the seed event. Wherein, the timestamp difference is the difference between the timestamp of the event to be clustered and the target timestamp of the existing event cluster, and the seed event includes the first event; If the Euclidean distance is less than the spatial clustering threshold, the event to be clustered is assigned to the event cluster corresponding to the seed event, and the target timestamp of the event cluster is updated using the timestamp of the event to be clustered. If the Euclidean distance is greater than or equal to the spatial clustering threshold, then a new event cluster is formed using the event to be clustered as the seed; After traversing all remaining events, at least one event cluster is obtained.

4. The method according to claim 3, characterized in that, The step of selecting event clusters whose morphological characteristics match those of banded lightning from the at least one event cluster as the target lightning event includes: Calculate the convex hull of each event cluster; Calculate the morphological parameters of each convex hull, which are used to characterize the elongation or narrowness of the shape; Event clusters whose morphological parameters meet preset conditions are identified as event clusters whose morphological characteristics conform to those of banded lightning, and these event clusters are determined as target lightning events.

5. The method according to any one of claims 1-4, characterized in that, After identifying the target lightning event related to the lightning strike on the transmission line, the process includes: Based on the pixel coordinates in the target lightning event, determine the feature vector corresponding to the target lightning event; The linear equation of the band lightning is determined based on the feature vector and the pixel coordinates in the target lightning event.

6. The method according to claim 1, characterized in that, The power transmission equipment includes power transmission lines and towers; The preset distance includes a first preset distance corresponding to the transmission line and a second preset distance corresponding to the tower.

7. The method according to claim 1, characterized in that, The system uses an optical sensing unit to capture lightning signals within a preset time period and converts them into a series of event data, including: Real-time detection of ambient light intensity; When the detected ambient brightness value is greater than the brightness threshold, the optical sensing unit captures the lightning light signal within a preset time period and converts it into a series of event data.

8. A lightning monitoring device, characterized in that, include: The event camera module is used to capture lightning light signals and output event data; The processing unit is communicatively connected to the event camera module and is used to execute the transmission line lightning strike fault identification method as described in any one of claims 1-7.

9. The apparatus according to claim 8, characterized in that, Also includes: A visible light camera module, which is communicatively connected to the processing unit, is used to acquire visible light images containing power transmission equipment. The processing unit is also used to determine the location information of the power transmission equipment based on the visible light image.

10. A lightning strike monitoring and early warning system for power transmission lines, characterized in that, include: One or more lightning monitoring devices as described in claim 8 or 9 are deployed along the transmission line or at key nodes; The system server is communicatively connected to the lightning monitoring device and is used to receive and aggregate the processing results of each device for comprehensive analysis, data storage and visualization. The client terminal communicates with the system server and is used to receive and display lightning strike fault alarms, location information, and system status.

11. A device for identifying lightning strike faults in power transmission lines, characterized in that, include: The signal acquisition module is used to capture lightning light signals within a preset time period using an optical sensing unit and convert them into a series of event data; The processing module is used to process the event data and identify target lightning events related to lightning strikes on transmission lines; The fault determination module is used to determine whether the target lightning event causes the transmission equipment to malfunction based on the spatial information of the target lightning event and the geographical information of the transmission equipment. The spatial information of the target lightning event is the linear equation of the band lightning, and the geographical information of the power transmission equipment is the linear equation of the power transmission equipment. The fault determination module is specifically used to acquire images including power transmission equipment collected by a visible light camera; analyze the images to determine the straight line equation of the power transmission equipment in the coordinate system of the visible light camera; and convert the straight line equation of the band lightning into the lightning straight line equation in the coordinate system of the visible light camera according to a pre-stored transformation matrix. Calculate the distance between the lightning straight-line equation and the equipment straight-line equation; if the distance is less than a preset distance, determine that the target lightning event caused the power transmission equipment to malfunction, and determine the location of the malfunction in the power transmission equipment.

12. An electronic device, characterized in that, Including memory and processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-7.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7.

14. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-7.

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