Dynamic discharge channel three-dimensional adaptive reconstruction method based on multiple high-speed cameras and related device

Abstract

The invention provides a dynamic discharge channel three-dimensional adaptive reconstruction method based on multiple high-speed cameras and a related device, and the method comprises the steps: taking a discharge gap as a center, and determining shooting points of the multiple high-speed cameras; shooting a long air gap discharge dynamic image on each shooting point through a high-speed camera; processing the image shot by each shooting point, identifying a discharge channel in the image, and constructing a two-dimensional coordinate sequence of the discharge channel in the corresponding image; the three-dimensional coordinate position of each shooting point in a three-dimensional space coordinate system with the discharge gap as the center is determined; matching the discharge channel images shot by each discharge channel at different shooting points and at different moments, and constructing the discharge channels of three-dimensional spaces at different moments; and constructing a complete dynamic three-dimensional discharge channel according to the discharge channel of each discharge channel in the three-dimensional space at different moments. According to the invention, efficient and accurate three-dimensional reconstruction can be realized by using the position relationship between the plurality of high-speed cameras and the discharge channel.

Description

Technical Field

[0001] The invention belongs to the technical field of gas discharge observation and analysis, and in particular relates to a three-dimensional adaptive reconstruction method of a dynamic discharge channel based on multiple high-speed cameras and a related device. Background Art

[0002] With the rapid development of social economy and the continuous acceleration of urbanization, energy demand has been increasing year by year, prompting the continuous expansion of the scale of power transmission and distribution network. The mismatch between the distribution of energy resources and consumption areas in my country determines the necessity of long-distance power transmission to achieve energy balance and allocation. With the characteristics of high voltage level and low loss, UHV transmission lines can not only effectively reduce energy loss and environmental pollution, meet domestic energy demand, but also promote the optimal allocation of national power resources. Under the conditions of high voltage and high current operation, the external insulation design of UHV transmission system is very important. As the main form of external insulation, the discharge characteristics of long air gaps have become the core and key direction of the external insulation design of UHV transmission system.

[0003] At present, the observation of long air gap discharge characteristics in the field of gas discharge is mostly limited to two-dimensional observation, which makes it difficult to fully present the three-dimensional morphology of the discharge channel and its dynamic evolution process. Although the development of high-speed photography technology has made it possible to reconstruct the discharge channel in three dimensions by using multiple high-speed cameras to synchronously shoot discharge phenomena from different angles, the dynamic discharge channel has the characteristics of high-speed changes, uneven light intensity and complex morphology, which poses great challenges to traditional feature point detection and tracking algorithms. When the existing multi-view geometry principles are applied to the three-dimensional reconstruction of dynamic discharge channels, problems such as easy loss of feature points and unstable tracking often occur, which greatly reduces the accuracy and reliability of the three-dimensional reconstruction. How to achieve efficient and accurate three-dimensional reconstruction is still a hot and difficult problem that needs to be overcome in the current research field. Summary of the invention

[0004] In view of this, the present invention provides a three-dimensional adaptive reconstruction method and related devices for a dynamic discharge channel based on multiple high-speed cameras, aiming to achieve high-precision three-dimensional reconstruction of the discharge channel by optimizing the shooting layout and data processing algorithm, and provide a new technical means for the study of gas discharge phenomena.

[0005] In order to achieve the above object, the technical solution provided by the present invention is as follows:

[0006] In a first aspect, the present invention provides a three-dimensional adaptive reconstruction method of a dynamic discharge channel based on multiple high-speed cameras, comprising the following steps:

[0007] Taking the discharge gap as the center, determine the shooting points of multiple high-speed cameras;

[0008] At each shooting point, the long air gap discharge dynamic images are captured by a high-speed camera;

[0009] The images taken at each shooting point are processed to identify the discharge channels in the images and construct a two-dimensional coordinate sequence of the discharge channels in the corresponding images;

[0010] Determine the three-dimensional coordinate position of each shooting point in the three-dimensional space coordinate system centered on the discharge gap;

[0011] Matching the discharge channel images taken at different shooting points and at different times of each discharge channel, and constructing the discharge channel in three-dimensional space at different times according to the two-dimensional coordinate sequence of each discharge channel in the matched image and the three-dimensional coordinate position of the shooting point corresponding to the matched image;

[0012] A complete dynamic three-dimensional discharge channel is constructed according to the discharge channel of each discharge channel in three-dimensional space at different times.

[0013] Furthermore, the images captured at each shooting point are processed to identify the discharge channels in the images and construct a two-dimensional coordinate sequence of the discharge channels in the corresponding images, including:

[0014] Convert the images taken at each shooting point into grayscale images;

[0015] The grayscale image is processed by using a grayscale image processing method based on morphological filtering to obtain the upper and lower envelope surfaces of the grayscale image;

[0016] The upper and lower envelope surfaces are smoothed by using a mean filter to obtain smooth upper and lower envelope surfaces;

[0017] The characteristics of the discharge channel are identified according to the smooth upper and lower envelope surfaces, and the grayscale image is processed into a binary image on the basis of retaining the characteristics;

[0018] The discharge channel is identified in the binary image and a two-dimensional coordinate sequence of the discharge channel in the image is constructed.

[0019] Furthermore, the upper and lower envelope surfaces are determined according to the following formula:

[0020]

[0021]

[0022] In the formula, and The pixel positions are The upper and lower envelope surface values ​​at ; The pixel position centered The set of pixels in the window; is the original grayscale image At pixel position The gray value at ; ⊕ is the morphological dilation filter; is a morphological corrosion filter, and b is a binary characteristic function.

[0023] Furthermore, the smooth upper and lower envelope surfaces are determined according to the following formula:

[0024]

[0025]

[0026] In the formula, and The pixel positions are The upper and lower envelope surface values ​​after smoothing; and The pixel positions are The upper and lower envelope surface values ​​at .

[0027] Furthermore, matching is performed on the discharge channel images taken at different shooting points of each discharge channel, including:

[0028] Extracting a point from the path of the discharge channel as a reference point and obtaining the two-dimensional coordinates of the reference point in each discharge channel image; the two-dimensional coordinates include horizontal coordinates and vertical coordinates;

[0029] According to the three-dimensional coordinate position of the shooting point corresponding to the discharge channel image and the two-dimensional coordinate of the reference point, the azimuth and elevation angle of the reference point observed at the shooting point are calculated;

[0030] In the same three-dimensional coordinate system, take any two shooting points and observe the vertical line where the common reference point is located according to the corresponding azimuth and elevation angles to obtain two observation points on the vertical line of the two shooting points; the common reference point is a point determined by projecting the two horizontal coordinates of the reference point on the horizontal plane in the discharge channel image taken by the two shooting points;

[0031] According to the distance difference between the two observation points, it is judged whether the discharge channel images taken by the two shooting points match. If so, they are divided into the image set of the corresponding discharge channel. If not, the shooting point is changed until all shooting points are traversed.

[0032] Furthermore, when judging whether the discharge channel images taken by the two shooting points match according to the distance difference between the two observation points, the distance difference between the two observation points is converted into an elevation error before judging. The elevation error is calculated according to the following formula:

[0033]

[0034] In the formula, is the elevation error; is the distance difference; First shooting point Distance from common reference point Vertical line The horizontal distance First shooting point Horizontal plane and vertical line The intersection of Second shooting point Distance from common reference point Vertical line The horizontal distance Second shooting point Horizontal plane and vertical line The intersection of

[0035] The distance difference is determined as follows:

[0036]

[0037]

[0038]

[0039]

[0040]

[0041] In the formula, and The first shooting point According to the corresponding azimuth and elevation And the second shooting point According to the corresponding azimuth and elevation On the vertical line Two observation points observed on the and Public Reference Points Distance between two observation points and distance; and are the distances between the two intersection points and the two observation points respectively; and The first shooting point And the second shooting point Height; and They are respectively the distances between the two shooting points projected onto the horizontal plane where the common reference point is located and the common reference point.

[0042] Furthermore, according to the two-dimensional coordinate sequence of each discharge channel in the matched image and the three-dimensional coordinate position of the shooting point corresponding to the matched image, the discharge channel in the three-dimensional space at different times is constructed, including:

[0043] For any reference point in the discharge channel , using the three-dimensional coordinate positions of at least two shooting points matched by the reference point to calculate the distances between the two shooting points and the corresponding two observation points and ;

[0044] Based on distance and Calculate reference point The distances to the two observation points are as follows:

[0045]

[0046]

[0047] In the formula, and The reference points The distances to the two observation points;

[0048] For reference point , its 3D reconstruction coordinates are determined according to the following formula:

[0049]

[0050]

[0051]

[0052] In the formula, , and Coordinates for three-dimensional reconstruction; and The reference points determined in the discharge channel images taken from the common reference point to the first shooting point and the second shooting point are The horizontal coordinate of

[0053] The three-dimensional reconstructed coordinates of all reference points are combined into the three-dimensional reconstructed coordinates of the discharge channel.

[0054] In a second aspect, the present invention provides a three-dimensional adaptive reconstruction device for a dynamic discharge channel based on multiple high-speed cameras, comprising:

[0055] The shooting point position determination module is used to determine the shooting points of multiple high-speed cameras with the discharge gap as the center;

[0056] An image acquisition module is used to capture dynamic images of long air gap discharge at various shooting points using a high-speed camera;

[0057] An image recognition module is used to process the images taken at each shooting point, identify the discharge channels in the images and construct a two-dimensional coordinate sequence of the discharge channels in the corresponding images;

[0058] A three-dimensional coordinate determination module, used to determine the three-dimensional coordinate position of each shooting point in a three-dimensional space coordinate system centered on the discharge gap;

[0059] An image matching and processing module is used to match the discharge channel images taken at different shooting points and at different times of each discharge channel, and to construct the discharge channel in three-dimensional space at different times according to the two-dimensional coordinate sequence of each discharge channel in the matched image and the three-dimensional coordinate position of the shooting point corresponding to the matched image;

[0060] The three-dimensional reconstruction module is used to construct a complete dynamic three-dimensional discharge channel according to the discharge channel of each discharge channel in three-dimensional space at different times.

[0061] In a third aspect, the present invention provides a computer device, the device comprising a processor and a memory:

[0062] The memory is used to store the computer program and send the instructions of the computer program to the processor;

[0063] The processor executes a three-dimensional adaptive reconstruction method of a dynamic discharge channel based on multiple high-speed cameras according to the instructions of the computer program as described in the first aspect.

[0064] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, a three-dimensional adaptive reconstruction method of a dynamic discharge channel based on multiple high-speed cameras as in the first aspect is implemented.

[0065] In summary, the present invention provides a three-dimensional adaptive reconstruction method and related devices for dynamic discharge channels based on multiple high-speed cameras, including determining the shooting points of multiple high-speed cameras with the discharge gap as the center; shooting long air gap discharge dynamic images with high-speed cameras at each shooting point; processing the images shot at each shooting point, identifying the discharge channel in the image and constructing a two-dimensional coordinate sequence of the discharge channel in the corresponding image; determining the three-dimensional coordinate position of each shooting point in a three-dimensional space coordinate system centered on the discharge gap; matching the discharge channel images shot at different shooting points and at different times for each discharge channel, and constructing the discharge channels in three-dimensional space at different times according to the two-dimensional coordinate sequence of each discharge channel in the matched image and the three-dimensional coordinate position of the shooting point corresponding to the matched image; constructing a complete dynamic three-dimensional discharge channel according to the discharge channels in three-dimensional space at different times for each discharge channel. The present invention can achieve efficient and accurate three-dimensional reconstruction by utilizing the positional relationship between multiple high-speed cameras and the discharge channel. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0067] Figure 1 A flowchart of a method for three-dimensional adaptive reconstruction of a dynamic discharge channel based on multiple high-speed cameras provided in an embodiment of the present invention;

[0068] Figure 2 A schematic diagram of the arrangement of high-speed cameras provided in an embodiment of the present invention;

[0069] Figure 3 A schematic diagram of a discharge channel image before and after preprocessing provided by an embodiment of the present invention;

[0070] Figure 4 Schematic diagram of the front and side view of the discharge channel after image enhancement processing provided by an embodiment of the present invention;

[0071] Figure 5 A schematic diagram of the relative position relationship between the shooting point and the discharge channel provided in an embodiment of the present invention;

[0072] Figure 6 A reconstructed three-dimensional development path diagram of the leader discharge dynamics provided by an embodiment of the present invention;

[0073] Figure 7A block diagram of a three-dimensional adaptive reconstruction device for a dynamic discharge channel based on multiple high-speed cameras provided in an embodiment of the present invention;

[0074] Figure 8 A block diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0075] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0076] See also Figure 1 The embodiment of the present application provides a three-dimensional adaptive reconstruction method of a dynamic discharge channel based on multiple high-speed cameras, comprising the following steps:

[0077] S1: Taking the discharge gap as the center, determine the shooting points of multiple high-speed cameras.

[0078] It should be noted that this step can prepare for the subsequent comprehensive and multi-angle shooting of the long air gap discharge process. Reasonable determination of the shooting points is the basis for obtaining accurate three-dimensional information of the discharge channel.

[0079] The shooting points to be determined need to take into account factors such as the shape and size of the discharge area. For different types of discharge specimens (such as rod-plate, ring-plate, etc.), the location of the corona initiation point and the area where the discharge may occur are different. The location and number of shooting points should be determined according to the specific situation to ensure that the entire area where the discharge phenomenon may occur can be covered.

[0080] S2: At each shooting point, a high-speed camera is used to capture dynamic images of long air gap discharge.

[0081] It should be noted that this step can capture continuous dynamic images of the long air gap discharge process and provide raw data for subsequent image processing and three-dimensional reconstruction.

[0082] When implementing this step, a high-speed camera needs to be placed at each determined shooting point, and parameters need to be set, such as adjusting the frame rate, exposure time, resolution, etc., to adapt to the rapid changes in the discharge process. When the discharge occurs, all high-speed cameras are started synchronously to ensure that the complete dynamic process of the discharge is recorded. During the shooting process, the shooting environment should be kept as stable as possible to avoid external factors (such as vibration, light changes, etc.) affecting the image quality.

[0083] S3: Process the images captured at each shooting point, identify the discharge channels in the images, and construct a two-dimensional coordinate sequence of the discharge channels in the corresponding images.

[0084] It should be noted that, in this step, the information of the discharge channel can be extracted from the captured original image, and converted into a two-dimensional coordinate form that is convenient for subsequent three-dimensional reconstruction.

[0085] S4: Determine the three-dimensional coordinate position of each shooting point in the three-dimensional space coordinate system centered on the discharge gap.

[0086] It should be noted that this step can establish the positional relationship of all shooting points in a unified three-dimensional space, so as to facilitate subsequent three-dimensional reconstruction based on multi-view images.

[0087] During implementation, a three-dimensional space coordinate system is first established with the center of the discharge gap as the origin. For each shooting point, its coordinates (x, y, z) in the three-dimensional coordinate system can be measured by high-precision measuring equipment (such as total station, laser rangefinder, etc.). These coordinates will be used to determine the spatial geometric relationship between the images of the same discharge channel taken at different shooting points.

[0088] S5: Matching the discharge channel images taken at different shooting points and at different times for each discharge channel, and constructing the discharge channels in three-dimensional space at different times according to the two-dimensional coordinate sequence of each discharge channel in the matched image and the three-dimensional coordinate position of the shooting point corresponding to the matched image.

[0089] It should be noted that this step accurately selects images belonging to the same discharge channel from a large number of discharge channel images taken at many different shooting points and at different times, and constructs the three-dimensional spatial form of the discharge channel at different times based on these matching images and related coordinate information, gradually restoring the dynamic evolution process of the discharge channel.

[0090] Specifically, we first need to analyze the geometric relationship (such as angle, distance, etc.) between different shooting points when shooting the same discharge channel and possible error factors (such as camera installation deviation, measurement error, etc.). Based on these factors, use a suitable image matching algorithm (such as an algorithm based on feature point matching) to match images belonging to the same discharge channel by analyzing the positional relationship between feature points in the image (such as specific points on the discharge channel) in different images. For example, the relative position, grayscale value and other features of feature points in different images can be compared to determine whether they come from the same discharge channel.

[0091] At the same time, considering the images taken at different times, the time factor needs to be processed. It may be necessary to group the images taken at the same time or at a similar time into one group for matching based on information such as the timestamp or shooting frame rate of the image to ensure the accuracy of the matching.

[0092] After image matching is completed, for each successfully matched discharge channel, combined with its two-dimensional coordinate sequence in the matched image and the three-dimensional coordinate position of the shooting point corresponding to the matched image, the two-dimensional coordinates can be converted into three-dimensional coordinates through the triangulation principle or other three-dimensional reconstruction algorithms. Specifically, if the three-dimensional coordinates of two or more shooting points and the two-dimensional coordinates of the discharge channel in the images shot at these shooting points are known, the three-dimensional coordinates of the corresponding points on the discharge channel can be calculated through geometric relationships. By performing such processing on the images of each discharge channel at different times, the three-dimensional spatial form of the discharge channel at different times can be constructed.

[0093] S6: Construct a complete dynamic three-dimensional discharge channel according to the discharge channel of each discharge channel in the three-dimensional space at different times.

[0094] It should be noted that, through this step, the three-dimensional spatial morphology of each discharge channel at different times is integrated to construct a complete three-dimensional model that can reflect the entire dynamic evolution process of the discharge channel, so as to study the discharge phenomenon more comprehensively and intuitively.

[0095] Specifically, according to the three-dimensional spatial form of each discharge channel constructed in the previous steps at different times, they are connected in chronological order. In the connection process, attention should be paid to maintaining the continuity of the discharge channel in time and space to avoid jumps or discontinuities. Appropriate interpolation algorithms (such as linear interpolation, spline interpolation, etc.) can be used to process the three-dimensional channels at adjacent times to fill the possible time intervals and make the entire dynamic three-dimensional discharge channel smoother and more natural. At the same time, the constructed dynamic three-dimensional discharge channel can also be further processed according to actual needs, such as rendering, annotation and other operations, so as to better display and analyze the discharge phenomenon.

[0096] This embodiment provides a three-dimensional adaptive reconstruction method of a dynamic discharge channel based on multiple high-speed cameras, by determining the shooting points of multiple high-speed cameras with the discharge gap as the center, shooting dynamic images of long air gap discharge at these shooting points, and then processing the shot images, identifying the discharge channel and constructing a two-dimensional coordinate sequence, while determining the three-dimensional coordinate position of the shooting point, matching images based on the three-dimensional coordinates of the shooting point and the error relationship of shooting the same discharge channel at different shooting points, and finally reconstructing the discharge channel in three dimensions by combining the two-dimensional coordinate sequence of the discharge channel and the three-dimensional coordinates of the shooting point. This method has many advantages. In terms of high precision, by reasonably arranging the shooting points and accurately calibrating, combined with advanced image processing algorithms, the three-dimensional morphology of the discharge channel at different times can be accurately captured. In terms of high efficiency, the synchronous shooting of multiple high-speed cameras is combined with efficient image processing and three-dimensional reconstruction algorithms, which greatly shortens the data processing time. In terms of comprehensiveness and dynamics, compared with traditional two-dimensional observation, it can record the discharge process in all directions and from multiple angles and construct a three-dimensional model, and can also capture the dynamic evolution of the discharge channel, providing reliable and intuitive and comprehensive data support for the study of dielectric breakdown phenomena.

[0097] In one embodiment, step S1 can be implemented by the following steps:

[0098] (1) Site investigation and planning: First, investigate the discharge experiment site to determine the specific location, size and shape of the discharge gap. At the same time, observe the environmental conditions on site, including lighting conditions, possible interference sources, etc., to provide a basis for the subsequent shooting point layout design.

[0099] (2) Shooting point layout design: The specific conditions of the discharge of different samples should be fully considered. With the discharge gap as the center, a reasonable shooting point layout should be designed according to the size and shape of the discharge area. Ensure that the discharge area is covered from multiple angles (such as front and back, left and right, up and down, etc.) to obtain sufficient three-dimensional information. Figure 2 As shown, if the test piece is a rod plate or a ball plate, considering that the starting point of this type of gap is at the top of the electrode, only two high-speed cameras are needed to shoot orthogonally; if the test piece is a ring plate, a ring combination gap, a double-ring combination gap, etc., considering that the starting point of the ring may be at any position between the horizontal tangent point and the vertical tangent point below the ring, and it will tilt due to wind force, it is necessary to arrange high-speed cameras in the four horizontal directions, and the cameras in the four directions should have a certain height difference to ensure that the discharge area is covered from multiple angles to obtain sufficient three-dimensional information.

[0100] (3) Shooting point calibration: Set markers at each shooting point or use high-precision measuring equipment to determine the precise coordinates of each shooting point in three-dimensional space. Place a special marker with known size and shape at each shooting point. Then, use a total station or laser rangefinder to measure each marker to determine its coordinates in three-dimensional space. Record these coordinates and input them into the data processing and analysis system for subsequent three-dimensional reconstruction. These coordinates will be used for subsequent three-dimensional reconstruction.

[0101] In one embodiment, step S2 can be implemented by the following steps:

[0102] (1) Equipment preparation and debugging: Check and debug to ensure that all high-speed cameras are working properly. First, perform an appearance inspection on each high-speed camera to check for damaged or loose parts. Then, connect the power and data cables, turn on the power switch of the high-speed camera, enter the setting interface, and adjust the viewfinder, lens focal length, exposure time and other parameters to meet the shooting requirements of the discharge process. By adjusting various parameters, ensure that the discharge moment can be clearly captured while the shooting process has the highest frame rate.

[0103] (2) Synchronous trigger setting: Through the synchronous control device, ensure that all high-speed cameras start shooting at the same time to ensure the time consistency of the image sequence. Use a synchronous controller to connect all high-speed cameras to the synchronous controller. Set the trigger signal source of the synchronous controller, which can be an external trigger signal (such as a pulse generator) or an internal trigger signal (such as a timer). When the trigger signal is issued, the synchronous controller sends a trigger signal to all high-speed cameras at the same time, so that they start shooting at the same time.

[0104] (3) Shooting execution: Start shooting and record the continuous image sequence during the discharge process. Pay attention to maintaining the stability of the shooting environment to avoid external interference on the image quality. A shock absorber can be used to reduce the impact of ground vibration on the high-speed camera. At the same time, turn off unnecessary light sources at the scene to avoid light interference. If possible, a lens hood can be used to further reduce the impact of external light.

[0105] In one embodiment, step S3 can be implemented by the following steps:

[0106] (1) Image preprocessing: Perform preprocessing operations such as denoising and contrast enhancement on the images taken by each camera to improve image quality. Use a median filter or a Gaussian filter to denoise the image and remove noise points in the image. Use methods such as histogram equalization or contrast stretching to enhance the contrast of the image so that the discharge channel is more clearly visible in the image.

[0107] (2) Discharge channel identification: Use image processing algorithms (such as edge detection, threshold segmentation, etc.) to identify the discharge channels at different times and extract their contours. The Canny edge detection algorithm can be used to perform edge detection on the image to find the edge of the discharge channel. Then, the threshold segmentation algorithm is used to separate the discharge channel from the background and extract its contour.

[0108] Furthermore, a morphological algorithm can be used to identify the discharge channel so as to construct a two-dimensional coordinate sequence of the discharge channel in the corresponding image. The process of identifying the discharge channel is as follows:

[0109] 1) Using morphological algorithms to identify discharge channels

[0110] The calculation formula of the upper and lower envelope surfaces of the grayscale image I with a size of W×H based on BEMD of morphological filtering is as follows:

[0111]

[0112]

[0113] where ⊕ represents the morphological dilation filter, represents the morphological corrosion filter, Zxy represents the pixel set in the w×w window centered on the pixel (x, y), b is the binary characteristic function on Zxy, and w is the average extreme value distance of the grayscale image I, which is calculated as follows:

[0114]

[0115] Where N represents the average number of local maxima and minima in image I.

[0116] 2) Smoothing the upper and lower envelopes with the following mean filter can obtain a smoother envelope.

[0117]

[0118]

[0119] By directly determining the envelope surface in the BEMD calculation, a multi-level spatial feature decomposition of the image from details to the whole can be obtained. This method is similar to BEMD based on order statistics, which can reduce the problem of over-expansion or under-expansion that may occur during the envelope construction process and effectively capture the characteristics of the image at all scales. Importantly, the morphological and mean filtering techniques it uses can be executed quickly and have high computational efficiency.

[0120] 3) For the original image (i.e. Figure 3(a)) is preprocessed to read the image as a two-dimensional grayscale value array with a grayscale variation range between [0, 255]. The preprocessed image is as follows Figure 3 As shown. Secondly, the photo is enhanced, the array matrix is ​​scanned row by row, and the position with a gray value of 255 in the array is identified, and the position of the discharge channel can be identified. Then, the coordinates are set to (5, 5, 10) with the discharge start position as the center; the discharge end position is set to (x, y, 0), and the image is cropped in equal proportion. The enhanced discharge channel image is shown as follows Figure 4 shown.

[0121] (3) Two-dimensional coordinate construction: According to the image coordinate system and camera parameters (such as focal length, pixel size, etc.), the contour of the discharge channel is converted into a two-dimensional coordinate sequence. The origin and coordinate axis direction of the image coordinate system are determined, and the actual physical size corresponding to each pixel in the image is calculated according to the focal length and pixel size of the camera. Finally, the coordinates of each point on the contour of the discharge channel in the image coordinate system are converted into actual physical coordinates to obtain the two-dimensional coordinate sequence of the discharge channel.

[0122] In one embodiment, step S4 can be implemented by the following steps:

[0123] (1) Establish a three-dimensional coordinate system: Take the geometric center of the discharge gap as the origin and establish a three-dimensional rectangular coordinate system. Determine the direction and scale of the coordinate axis based on the on-site survey and shooting point calibration results;

[0124] (2) Camera position calibration: Input the coordinates of each shooting point in the three-dimensional coordinate system determined previously into the system.

[0125] In one embodiment, step S5 includes matching images at different shooting points and matching images at different moments.

[0126] The matching of images at different times can be achieved through the following steps:

[0127] (1) Adaptive threshold setting: According to the light intensity distribution characteristics of the discharge channel, the threshold of feature point detection is dynamically adjusted. The local contrast analysis method is used to achieve adaptive recognition of different light intensity areas. First, the light intensity distribution of the discharge channel is analyzed using histogram analysis or local contrast calculation. Then, according to the characteristics of the light intensity distribution, the threshold of feature point detection is dynamically adjusted. If the light intensity of the discharge channel is high, the threshold can be appropriately lowered to improve the sensitivity of feature point detection; if the light intensity is low, the threshold can be appropriately increased to reduce false detection.

[0128] (2) Pre-screening of optical feature points: Using morphological filtering or edge detection algorithms, possible highlight areas and edges on the discharge channel are preliminarily screened as candidate feature points;

[0129] (3) Optical feature point quality assessment: A set of feature point quality assessment mechanisms is used to comprehensively consider factors such as the stability, significance, and distribution uniformity of feature points, and select high-quality feature points from candidate feature points;

[0130] The stability of feature points is evaluated by matching feature points in multiple frames. Stable feature points should maintain a high matching rate in different frames. Feature point detection is performed on multiple frames. After obtaining candidate feature points in different frames, the feature points in different frames are matched using nearest neighbor matching or random sampling consensus (RANSAC) matching. The matching rate of each feature point in different frames is calculated, and feature points with higher matching rates are selected as stable feature points.

[0131] Consider factors such as brightness and contrast in the area where the feature points are located to evaluate the significance of the feature points. High-brightness and high-contrast areas usually contain more valuable feature points. Use local contrast calculation or brightness statistics to analyze the brightness and contrast of the area where the feature points are located. Evaluate the significance of the feature points based on the brightness and contrast. Select feature points with higher brightness and contrast as significant feature points.

[0132] Ensure that the selected feature points are evenly distributed on the discharge channel to avoid being too dense in some areas and sparse in other areas. Use spatial distribution statistics or cluster analysis to calculate the position distribution of each feature point on the discharge channel. According to the position distribution, evaluate the distribution uniformity of the feature points. If the feature points in some areas are too dense, some redundant feature points can be deleted; if the feature points in some areas are too sparse, some new feature points can be added to ensure that the feature points are evenly distributed on the discharge channel.

[0133] (4) Dynamic tracking of optical feature points: Based on the Kalman filter tracking method and combined with the motion characteristics of the discharge channel, the selected feature points are stably tracked. During the tracking process, the feature point descriptors are updated in real time to adapt to the dynamic changes of the discharge channel.

[0134] The Kalman filter is used to predict the position of the feature point in the next frame and is updated in combination with the actual detected position. This helps maintain tracking stability when the image is blurred or occluded. During tracking, the descriptors of the feature points (such as SIFT, SURF, or ORB descriptors) are updated in real time to reflect the dynamic changes of the discharge channel. Efficient matching algorithms such as FLANN (Fast Nearest Neighbor Search Library) are used to match feature points between adjacent frames.

[0135] The Kalman filter is used to predict the position of the feature point in the next frame and update it in combination with the actual detected position. This helps to maintain the stability of tracking when the image is blurred or occluded. First, the state equation and observation equation of the Kalman filter are established to describe the motion state and observation model of the feature point. Then, based on the position and velocity of the feature point in the current frame, the position of the feature point in the next frame is predicted. When the next frame of the image is actually detected, the predicted position is compared with the actual detected position, and the state estimate of the Kalman filter is updated based on the difference between the two. Through continuous prediction and updating, stable tracking of feature points can be achieved.

[0136] During the tracking process, the descriptors of the feature points (such as SIFT, SURF or ORB descriptors) are updated in real time to reflect the dynamic changes of the discharge channel. Select an appropriate feature point descriptor, such as SIFT descriptor. During the tracking process, the descriptors of the feature points are updated in real time according to the dynamic changes of the discharge channel. If the shape of the discharge channel changes, the SIFT descriptors of the feature points can be recalculated to reflect the new shape characteristics.

[0137] Use efficient matching algorithms such as FLANN (Fast Nearest Neighbor Search Library) to match feature points between adjacent frames. Use the FLANN algorithm to match feature points in adjacent frames. First, establish a descriptor database of feature points, and then use the FLANN algorithm to quickly search the database for feature points that are most similar to the feature points in the current frame. By matching feature points, the corresponding relationship between feature points in different frames can be determined, thereby achieving tracking of feature points and matching of discharge channel images at different times.

[0138] For the matching of images at different shooting points, the following process is adopted:

[0139] (1) A point is extracted from the path of the discharge channel as a reference point and the two-dimensional coordinates of the reference point in each discharge channel image are obtained; the two-dimensional coordinates include horizontal coordinates and vertical coordinates.

[0140] First, determine the reference position to measure the elevation and azimuth. In field tests, the camera's "optical axis" is difficult to measure and the horizontal direction of the image is not always parallel to the ground, so the image angle coordinates must be initialized. The vertex can be used as a reference point for the rotated image to calibrate the horizontal direction. The elevation and azimuth can be calculated using the observation point and the known geographic location reference point to obtain the actual difference. Usually the angle difference measured in the image is different from the actual value. By rotating the image and using the least squares method, the difference can be made close to the actual value, and a coordinate transformation relationship can be established. The vertex of the building is selected as the reference point in the rotated image. The reference point in the actual space has an azimuth angle α relative to the observation station. real and elevation angle β real , the reference point in the image is α relative to the center point image and βimage , the angle coordinates of a single pixel can be calculated. The initialization coordinate sequence can be obtained by processing the two observation stations.

[0141] like Figure 5 As shown, let A be the main observation station, which is located directly above the X-axis. A' is the projection point of the main observation station on the Z=0 plane, and h1 represents the height of the camera in the main observation station. A set of azimuth and elevation coordinates are selected from the lightning channel photographed by the main observation station, denoted as α1 and β1. B is the secondary observation station, which is located directly above the Y-axis. B' is the projection point of the secondary observation station on the Z=0 plane, and h2 is the height of the camera in the secondary observation station. A set of azimuth and elevation coordinates are selected from the lightning channel photographed by the secondary observation station, denoted as α2 and β2. In the Z=0 plane, the ray with A' as the vertex and azimuth angle α1 intersects with the ray with B' as the vertex and azimuth angle α2, and the intersection point is P. In the Z=h1 plane, the ray with A as the vertex and azimuth angle α1 intersects with the ray with P as the vertex and perpendicular to the Z=0 plane, and the intersection point is P1. In the Z=h2 plane, the ray with B as the vertex and azimuth angle α2 intersects the vertical line with P as the vertex, and the intersection point is P2.

[0142] (2) According to the three-dimensional coordinate position of the shooting point corresponding to the discharge channel image and the two-dimensional coordinate of the reference point, calculate the azimuth and elevation angle of the reference point observed at the shooting point, that is, and .

[0143] (3) In the same three-dimensional coordinate system, take any two shooting points and observe the vertical line where the common reference point is located according to the corresponding azimuth and elevation angles to obtain two observation points on the vertical line of the two shooting points; the common reference point is the point determined by projecting the two horizontal coordinates of the reference point onto the horizontal plane in the discharge channel image taken by the two shooting points.

[0144] according to Figure 5 It is known that there are , , ,and:

[0145]

[0146]

[0147]

[0148] , , ,and:

[0149]

[0150]

[0151]

[0152] is the horizontal distance from the camera in the main observation station to the coordinate origin, is the horizontal distance from the camera in the secondary observation station to the origin of the coordinate system. By calculation, we can get , and .

[0153]

[0154]

[0155]

[0156] exist , using the law of sines we obtain:

[0157]

[0158]

[0159] With A as the vertex, the ray with azimuth and elevation angles of α1 and β1 respectively and the vertical line PL intersect at point L1; with B as the vertex, the ray with azimuth and elevation angles of α2 and β2 respectively and PL intersect at point L2.

[0160] (4) Determine whether the discharge channel images taken at the two shooting points match based on the distance difference between the two observation points. If so, divide them into the image set of the corresponding discharge channel. If not, change the shooting point until all shooting points are traversed.

[0161] The height error (i.e., distance difference) between L1 and L2 is as follows:

[0162]

[0163] In a further embodiment, the distance difference may be converted into the elevation angle error of AL1 and BL2 and then the matching judgment is performed as follows:

[0164]

[0165] Through the above calculation process, the elevation angle difference between any set of lightning channel angle coordinates obtained from a specific site and the entire lightning channel angle coordinates obtained from another observation station can be determined. The two sets of angle coordinates with the smallest values ​​are very likely to meet the matching conditions. Usually, in the actual lightning channel reconstruction process, the minimum elevation angle difference (Δβmin ) is not zero. Define δ as the acceptable error range. When Δβ min When it is less than δ, it means that a matching angle combination has been found; and when Δβ min When it is greater than δ, it can be determined that there is no coordinate sequence in the image of the secondary observation station that matches the group of angles of the primary observation station.

[0166] So far, the matching of images at different times and different shooting points can be completed in the above manner, and the rest of step S5 can be implemented by the following steps:

[0167] (5) Three-dimensional coordinate conversion: According to the internal and external parameters of the camera (such as rotation matrix, translation vector, etc.) and the feature point matching results, the two-dimensional coordinate sequence is converted into a three-dimensional coordinate sequence;

[0168] First, calibrate the camera to obtain the camera's internal and external parameters (rotation matrix, translation vector, focal length, etc.). Using the camera's internal and external parameters and the two-dimensional coordinates of the feature points, the three-dimensional coordinates of the feature points are calculated through the inverse process of perspective projection. Considering the camera calibration error and image processing error, the calculated three-dimensional coordinates are corrected and filtered as necessary.

[0169] First, calibrate the camera to obtain the camera's internal and external parameters (rotation matrix, translation vector, focal length, etc.). Use a camera calibration plate or an object of known size to calibrate the camera. By taking multiple images of the calibration plate at different angles, use the Zhang Zhengyou calibration method to calculate the camera's internal and external parameters. Record these parameters and input them into the data processing and analysis system.

[0170] Using the internal and external parameters of the camera and the two-dimensional coordinates of the feature points, the three-dimensional coordinates of the feature points are calculated through the inverse process of perspective projection. According to the internal and external parameters of the camera and the two-dimensional coordinates of the feature points, the perspective projection equation is established. Then, the three-dimensional coordinates of the feature points are calculated by solving the inverse process of the perspective projection equation. In the calculation process, it is necessary to consider the camera calibration error and image processing error, and perform necessary correction and filtering on the calculated three-dimensional coordinates.

[0171] (6) Three-dimensional channel construction: Connect the converted three-dimensional coordinate points into lines or surfaces to form a three-dimensional spatial discharge channel. Connect the converted three-dimensional coordinate points into lines or surfaces in a certain order. Use three-dimensional modeling software or programming languages ​​(such as Python) to realize the construction of three-dimensional channels. When connecting coordinate points, it is necessary to consider the shape and continuity of the discharge channel to ensure that the constructed three-dimensional channel conforms to the actual discharge situation.

[0172] Knowing that the vertical distance between the discharge start position and the discharge end position is 10m, the actual length corresponding to each grid in the matrix can be converted. Referring to the coordinates of the starting point of the leader discharge, the coordinates of each point in the leader channel can be converted. Combined with the vertical distance of the leader over time acquired by the high-speed camera, the three-dimensional dynamic evolution path of the leader can be reconstructed, such as Figure 6 shown.

[0173] Combination Figure 5 The above three-dimensional reconstruction process is introduced as follows:

[0174] For the matching angle combinations (α1, β1) and (α2, β2), let L be the corresponding lightning channel point, and its three-dimensional coordinates are (L X , L Y , L Z ). Easy to get:

[0175]

[0176]

[0177] For optical observation, the longer the observation distance, the greater the observation error. Therefore, the final 3D reconstruction point L on the line segment L1L2 is located close to the end with the shortest observation distance.

[0178]

[0179]

[0180]

[0181] P is the projection point of the 3D reconstruction point L on the Z=0 plane.

[0182]

[0183]

[0184]

[0185] You can get:

[0186]

[0187]

[0188] Where L X , L Y and L Z is the 3D reconstructed coordinate of L. According to the above process, all matching angle combinations are reconstructed to obtain a set of 3D point coordinate sequences, which are connected to form the reconstructed 3D lightning channel.

[0189] In one embodiment, step S6 can be implemented by the following process:

[0190] (1) Time synchronization and interpolation: According to the shooting frame rate of the high-speed camera, the three-dimensional discharge channels at adjacent moments are time synchronized and interpolated to construct a smooth dynamic three-dimensional discharge channel;

[0191] (2) Result output and display: The constructed dynamic three-dimensional discharge channel is output and displayed in the form of a three-dimensional model or animation to facilitate subsequent analysis and research.

[0192] Based on the same inventive concept, the embodiment of the present application also provides a three-dimensional adaptive reconstruction device for a dynamic discharge channel based on multiple high-speed cameras for implementing the three-dimensional adaptive reconstruction method for a dynamic discharge channel based on multiple high-speed cameras involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiment of the three-dimensional adaptive reconstruction device for a dynamic discharge channel based on multiple high-speed cameras provided below can be referred to the limitations of the three-dimensional adaptive reconstruction method for a dynamic discharge channel based on multiple high-speed cameras above, and will not be repeated here.

[0193] See also Figure 7 The embodiment of the present invention provides a three-dimensional adaptive reconstruction device of a dynamic discharge channel based on multiple high-speed cameras, comprising:

[0194] The shooting point position determination module is used to determine the shooting points of multiple high-speed cameras with the discharge gap as the center;

[0195] An image acquisition module is used to capture dynamic images of long air gap discharge at various shooting points using a high-speed camera;

[0196] An image recognition module is used to process the images taken at each shooting point, identify the discharge channels in the images and construct a two-dimensional coordinate sequence of the discharge channels in the corresponding images;

[0197] A three-dimensional coordinate determination module is used to determine the three-dimensional coordinate position of each shooting point in a three-dimensional space coordinate system centered on the discharge gap;

[0198] An image matching and processing module is used to match the discharge channel images taken at different shooting points and at different times of each discharge channel, and to construct the discharge channel in three-dimensional space at different times according to the two-dimensional coordinate sequence of each discharge channel in the matched image and the three-dimensional coordinate position of the shooting point corresponding to the matched image;

[0199] The three-dimensional reconstruction module is used to construct a complete dynamic three-dimensional discharge channel according to the discharge channel of each discharge channel in three-dimensional space at different times.

[0200] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0201] Reference Figure 8 An embodiment of the present invention further provides a computer device, comprising: a memory and a processor and a computer program stored in the memory. When the computer program is executed on the processor, a three-dimensional adaptive reconstruction method of a dynamic discharge channel based on multiple high-speed cameras as described in any one of the above methods is implemented.

[0202] The computer device may be a desktop computer, a notebook, a PDA, a cloud server or other computing device. The computer device may include, but is not limited to, a processor and a memory. Those skilled in the art will understand that Figure 8 It is only an example of a computer device and does not constitute a limitation of the computer device. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include input and output devices, network access devices, etc.

[0203] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0204] In some embodiments, the memory may be an internal storage unit of the computer device, such as a hard disk or memory of the computer device. In other embodiments, the memory may also be an external storage device of the computer device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device. Further, the memory may include both an internal storage unit and an external storage device of the computer device. The memory is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory may also be used to temporarily store data that has been output or is to be output.

[0205] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for three-dimensional adaptive reconstruction of a dynamic discharge channel based on multiple high-speed cameras as described in any one of the above methods is implemented.

[0206] In this embodiment, if the integrated unit is implemented in the form of 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 present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, USB flash drive, mobile hard disk, disk or optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0207] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0208] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0209] In the embodiments disclosed in the present application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0210] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A three-dimensional adaptive reconstruction method of a dynamic discharge channel based on multiple high-speed cameras, characterized in that: The steps include: Taking the discharge gap as the center, determine the shooting points of multiple high-speed cameras; At each of the shooting points, a long air gap discharge dynamic image is shot by the high-speed camera; Processing the images taken at each of the shooting points, identifying the discharge channels in the images and constructing a two-dimensional coordinate sequence of the discharge channels in the corresponding images; Determining the three-dimensional coordinate position of each of the shooting points in a three-dimensional space coordinate system centered on the discharge gap; Matching the discharge channel images of each discharge channel taken at different shooting points and at different times, and constructing the discharge channel in three-dimensional space at different times according to the two-dimensional coordinate sequence of each discharge channel in the matched image and the three-dimensional coordinate position of the shooting point corresponding to the matched image; A complete dynamic three-dimensional discharge channel is constructed according to the discharge channel of each discharge channel in the three-dimensional space at different times.

2. The method for three-dimensional adaptive reconstruction of dynamic discharge channels based on multiple high-speed cameras according to claim 1, characterized in that: The images captured at each of the shooting points are processed to identify the discharge channels in the images and construct a two-dimensional coordinate sequence of the discharge channels in the corresponding images, including: Convert the images captured at each of the shooting points into grayscale images; Processing the grayscale image using a grayscale image processing method based on morphological filtering to obtain upper and lower envelope surfaces of the grayscale image; Using a mean filter to smooth the upper and lower envelope curved surfaces to obtain smooth upper and lower envelope curved surfaces; Identifying the features of the discharge channel according to the smooth upper and lower envelope surfaces, and processing the grayscale image into a binary image on the basis of retaining the features; The discharge channel is identified in the binary image and a two-dimensional coordinate sequence of the discharge channel in the image is constructed.

3. The method for three-dimensional adaptive reconstruction of dynamic discharge channels based on multiple high-speed cameras according to claim 2, characterized in that: The upper and lower envelope surfaces are determined according to the following formula: In the formula, and The pixel positions are The upper and lower envelope surface values ​​at ; The pixel position centered The set of pixels in the window; is the original grayscale image At pixel position The gray value at ; ⊕ is the morphological dilation filter; is a morphological corrosion filter, and b is a binary characteristic function.

4. The method for three-dimensional adaptive reconstruction of dynamic discharge channels based on multiple high-speed cameras according to claim 3, characterized in that: The smooth upper and lower envelope surfaces are determined according to the following formula: In the formula, and The pixel positions are The upper and lower envelope surface values ​​after smoothing; and The pixel positions are The upper and lower envelope surface values ​​at .

5. The method for three-dimensional adaptive reconstruction of dynamic discharge channels based on multiple high-speed cameras according to claim 1, characterized in that: Matching the discharge channel images of each discharge channel taken at different shooting points includes: Extracting a point from the path of the discharge channel as a reference point and obtaining the two-dimensional coordinates of the reference point in each of the discharge channel images; the two-dimensional coordinates include a horizontal coordinate and a vertical coordinate; Calculate the azimuth and elevation angles of the reference point observed at the shooting point according to the three-dimensional coordinate position of the shooting point corresponding to the discharge channel image and the two-dimensional coordinates of the reference point; In the same three-dimensional coordinate system, any two of the shooting points are taken to observe the vertical line where the common reference point is located according to the corresponding azimuth and elevation angles to obtain two observation points of the two shooting points on the vertical line; the common reference point is a point determined by projecting the two horizontal coordinates of the reference point on the horizontal plane in the discharge channel image taken by the two shooting points; According to the distance difference between the two observation points, it is judged whether the discharge channel images taken by the two shooting points match. If so, they are divided into the image set of the corresponding discharge channel. If not, the shooting point is replaced until all shooting points are traversed.

6. The method for three-dimensional adaptive reconstruction of dynamic discharge channels based on multiple high-speed cameras according to claim 5, characterized in that: When judging whether the discharge channel images taken by the two shooting points match according to the distance difference between the two observation points, the distance difference between the two observation points is converted into an elevation error before judging, and the elevation error is calculated according to the following formula: In the formula, is the elevation angle error; is the distance difference; First shooting point Distance from the common reference point Vertical line The horizontal distance First shooting point Horizontal plane and vertical line The intersection of Second shooting point Distance from the common reference point Vertical line The horizontal distance Second shooting point Horizontal plane and vertical line The intersection of The distance difference is determined according to the following formula: In the formula, and The first shooting point According to the corresponding azimuth and elevation And the second shooting point According to the corresponding azimuth and elevation On the vertical line Two observation points observed on the and The common reference points are Distance between two observation points and distance; and are the distances between the two intersection points and the two observation points respectively; and The first shooting point And the second shooting point Height; and are respectively the distances between the points where the two shooting points are projected onto the horizontal plane where the common reference point is located and the common reference point.

7. The method for three-dimensional adaptive reconstruction of dynamic discharge channels based on multiple high-speed cameras according to claim 6, characterized in that: Constructing discharge channels in three-dimensional space at different times according to the two-dimensional coordinate sequence of each discharge channel in the matched image and the three-dimensional coordinate position of the shooting point corresponding to the matched image, comprising: For any reference point in the discharge channel , using the three-dimensional coordinate positions of at least two shooting points matched by the reference point to calculate the distances from the two shooting points to the corresponding two observation points and ; Based on distance and Calculate the reference point The distances to the two observation points are as follows: In the formula, and The reference points are The distances to the two observation points; For the reference point , its 3D reconstruction coordinates are determined according to the following formula: In the formula, , and Reconstruct coordinates for the three-dimensional reconstruction; and The reference points determined in the discharge channel images taken from the common reference point to the first shooting point and the second shooting point are respectively The horizontal coordinate of The three-dimensional reconstructed coordinates of all reference points are combined into the three-dimensional reconstructed coordinates of the discharge channel.

8. A three-dimensional adaptive reconstruction device for dynamic discharge channels based on multiple high-speed cameras, characterized in that: include: The shooting point position determination module is used to determine the shooting points of multiple high-speed cameras with the discharge gap as the center; An image acquisition module, used for capturing dynamic images of long air gap discharge at each of the shooting points through the high-speed camera; An image recognition module, used for processing the images taken at each of the shooting points, identifying the discharge channels in the images and constructing a two-dimensional coordinate sequence of the discharge channels in the corresponding images; A three-dimensional coordinate determination module, used to determine the three-dimensional coordinate position of each of the shooting points in a three-dimensional space coordinate system centered on the discharge gap; An image matching and processing module, used for matching the discharge channel images taken at different shooting points and at different times of each discharge channel, and constructing the discharge channel in three-dimensional space at different times according to the two-dimensional coordinate sequence of each discharge channel in the matched image and the three-dimensional coordinate position of the shooting point corresponding to the matched image; The three-dimensional reconstruction module is used to construct a complete dynamic three-dimensional discharge channel according to the discharge channel of each discharge channel in the three-dimensional space at different times.

9. A computer device, characterized in that: The device comprises a processor and a memory: The memory is used to store a computer program and send instructions of the computer program to the processor; The processor executes a three-dimensional adaptive reconstruction method of a dynamic discharge channel based on multiple high-speed cameras as described in any one of claims 1 to 7 according to the instructions of the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the method for three-dimensional adaptive reconstruction of a dynamic discharge channel based on multiple high-speed cameras as described in any one of claims 1 to 7 is implemented.

Images