An intelligent galloping detection system with long-term maintenance-free continuous operation

Abstract

The present invention provides an intelligent galloping detection system that can operate continuously without maintenance for a long time. Galloping detection module: It is used to obtain real-time scene images of the transmission line in real time through a monitoring terminal sleeved on the transmission line, judge whether the transmission line is galloping, and output a galloping result; Result verification module: It is used to obtain real-time attitude data of the transmission line through a sensing device arranged on the monitoring terminal, and determine the galloping result according to the attitude data, and output a determination result; Equipment self-check module: It is used to monitor the operation data of the monitoring terminal in real time, and judge whether there is a fault in the monitoring terminal according to the inspection result and the determination result.

Description

Technical Field

[0001] The present invention relates to the technical field of circuit transmission, and particularly to an intelligent dancing detection system that operates continuously with long-term maintenance-free operation. Background Art

[0002] At present, with the increasing scale of the power grid, as the main means of power transmission, the safe and stable operation of transmission lines is the primary issue that must be considered in our country. Transmission line galloping is a serious disaster that endangers the safe and stable operation of the line. It is a low-frequency, large-amplitude self-excited vibration generated by eccentrically iced conductors under the excitation of wind, often causing flashover tripping, damage to fittings and insulators, broken strands and broken wires of conductors, loosening and falling off of tower bolts, damage to tower materials, damage to the foundation, and even serious accidents such as tower collapse.

[0003] Due to the change of the global climate, natural disaster events caused by extreme weather are increasing year by year. The problem of transmission safety under the influence of complex meteorological and geological environments is becoming more and more prominent, which is likely to cause large-amplitude line galloping of transmission lines, and is extremely likely to lead to large-area failures and paralysis of the power grid. Mastering the accurate position of transmission line galloping, timely discovering and investigating and maintaining dangerous areas, reducing the threat of line galloping to the power grid, and thus ensuring the safe and reliable operation of the power grid is one of the key problems that the power system urgently needs to solve.

[0004] The commonly used method for monitoring existing conductor galloping is the acceleration method. Multiple monitoring nodes based on acceleration sensors are installed on the conductor. By collecting the acceleration data of each sensor and through filtering and upper computer data processing, the galloping amplitude and frequency of the conductor are obtained. This method has the problems that the acceleration sensor is greatly affected by the external environment and has low accuracy; multiple sensors are often installed between two towers, and the installation requirements are high, the system and algorithm are relatively complex, and the cost is high. Installing more devices means more maintenance is required. Summary of the Invention

[0005] The present invention provides an intelligent dancing detection system that operates continuously with long-term maintenance-free operation to solve the situation where the commonly used method for monitoring existing conductor galloping is the acceleration method. Multiple monitoring nodes based on acceleration sensors are installed on the conductor. By collecting the acceleration data of each sensor and through filtering and upper computer data processing, the galloping amplitude and frequency of the conductor are obtained. This method has the problems that the acceleration sensor is greatly affected by the external environment and has low accuracy; multiple sensors are often installed between two towers, and the installation requirements are high, the system and algorithm are relatively complex, and the cost is high. Installing more devices means more maintenance is required.

[0006] An intelligent dancing detection system that operates continuously with long-term maintenance-free operation includes:

[0007] Dancing detection module: It is used to obtain the real-time scene image of the transmission line in real time through the monitoring terminal sleeved on the transmission line, judge whether the transmission line is dancing, and output the dancing result;

[0008] Result verification module: It is used to obtain the attitude data of the transmission line in real time through the sensing device set on the monitoring terminal, and judge the dancing result according to the attitude data, and output the judgment result;

[0009] Device self-check module: It is used to monitor the operation data of the monitoring terminal in real time, and judge whether there is a fault in the monitoring terminal according to the inspection result and the judgment result.

[0010] Preferably, the dancing detection module:

[0011] Camera unit: It is used to take pictures of the transmission line in real time and obtain the real-time scene image of the transmission line;

[0012] Point cloud processing unit: It is used to determine the original point cloud data of the transmission line according to the real-time scene image, where

[0013] The original point cloud data includes three-dimensional coordinates and timestamps;

[0014] Tensor acquisition unit: It is used to determine the three-dimensional bounding box of the transmission line and the transmission line feature tensor according to the original point cloud data; where

[0015] The transmission line feature tensor is obtained by the following method:

[0016] Voxelize the original point cloud data, determine the point cloud feature tensor through feature extraction, and obtain the three-dimensional bounding box of the transmission line based on the 3D detection head; select the point cloud feature tensor according to the three-dimensional bounding box to obtain the point cloud target feature tensor of the transmission line;

[0017] Image processing unit: The user obtains the image data collected at different times and from different perspectives, the acquisition timestamp of each image data, the three-dimensional bounding box of the candidate target output by the point cloud acquisition device and the point cloud processing module; output the image target feature tensor of the candidate target; where

[0018] The image processing module performs feature extraction based on the image data and its timestamp, and combines the three-dimensional bounding box to obtain the image target feature tensor of the transmission line;

[0019] Dancing judgment unit: It is used to determine the tensor change diagram of the transmission line at different times according to the point cloud target feature tensor and the image target feature tensor, and judge whether the transmission line is dancing according to the tensor change diagram; where

[0020] When the tensor in the tensor variation diagram is a straight line, and the line fitting of the point cloud target feature tensor and the image target feature tensor at different times indicates that the transmission line is not dancing;

[0021] When the tensor in the tensor variation diagram is a curve, and the line fitting of the point cloud target feature tensor and the image target feature tensor at different times does not match, it indicates that the transmission line is dancing.

[0022] Preferably, the camera unit includes:

[0023] Front camera group: The front camera group includes a first camera and a second camera; among them,

[0024] The first camera and the second camera respectively acquire the front images of the transmission line from different perspectives;

[0025] Rear camera group: The rear camera group includes a third camera and a fourth camera; among them,

[0026] The third camera and the fourth camera respectively acquire the rear images of the transmission line from different perspectives.

[0027] Preferably, the point cloud processing unit includes:

[0028] Monitoring unit: used to perform key point detection on the initial point cloud data of the real-time scene image; among them,

[0029] The key point detection is the area detection of the transmission line in the real-time scene image;

[0030] Coordinate construction unit: For each detected key point, construct a local coordinate system with the key point as the center and the feature vector as the coordinate axis;

[0031] Projection unit: Convert the key point and its neighborhood point set to the local coordinate, obtain the converted local point cloud, project the converted local point cloud onto three coordinate planes, and then divide the projected point cloud into several grids;

[0032] Point cloud analysis unit: used to perform coordinate transformation according to the several grids to determine the original point cloud data

[0033] Preferably, the result verification module includes:

[0034] Simulation unit: used to obtain the sensing data of the sensing device, and obtain the simulated horizontal displacement and vertical displacement at each moment based on the acceleration sensing technology; among them,

[0035] The sensing data includes the acceleration data and angular velocity data of the transmission line;

[0036] Conversion unit: used to convert the simulated horizontal displacement and vertical displacement at each moment into discrete horizontal displacement and vertical displacement at each moment;

[0037] Fitting unit: used to register the discrete horizontal displacement and vertical displacement at each moment to obtain the attitude equation of the transmission line, and determine the attitude data of the transmission line according to the attitude equation;

[0038] Result determination unit: used to calculate the horizontal tensor and vertical tensor of the transmission line according to the attitude data, import the tensor change diagram according to the horizontal tensor and vertical tensor, and perform result determination on the galloping result according to the tensor change diagram, and output the determination result.

[0039] Preferably, the result verification module further includes:

[0040] Detection device position real-time acquisition unit: used to acquire the position information and viewing angle information of the detection terminal;

[0041] Point cloud determination unit: used to acquire the required point cloud data according to the position information and viewing angle information;

[0042] Sensing position unit: used to determine the target position information and target orientation information of the required sensing device according to the point cloud data;

[0043] Setting unit: used to set the sensing device according to the target position information and target orientation information.

[0044] Preferably, the result verification module further includes:

[0045] Real-time attitude data acquisition unit: used to acquire the real-time attitude data of the transmission line according to the sensing device;

[0046] Initial attitude data acquisition unit: used to acquire the initial attitude data of the transmission line when the sensing device is started;

[0047] Matching unit: used to compare the real-time attitude data with the initial attitude data, and when the actual attitude data does not match the initial attitude data, determine the angle offset and speed offset of the transmission line switching from the initial attitude to the current attitude according to the actual attitude data and the initial attitude data; wherein,

[0048] The initial attitude data is the data detected by the attitude detection sensor when the transmission line is in the initial attitude;

[0049] The angle offset is the angle by which the transmission line deflects relative to the initial attitude with the first coordinate axis as the rotation axis, and the first coordinate axis is the initial direction of the transmission line in the horizontal plane when it is in the initial attitude.

[0050] Preferably, the device self-checking module includes:

[0051] A parameter acquisition unit: used to acquire the determination result and the reference operation parameters of the detection terminal;

[0052] A test unit: used to determine test data corresponding to the test scenario of the selected detection terminal, the test data includes descriptions of one or more test cases, where each test case includes one or more operation parameters of the detection terminal in the selected test scenario, and the common parameters among the one or more operation parameters are encapsulated as common key parameters that can be shared by multiple test cases, and at least one of the test cases includes a reference to the common key parameters;

[0053] An analysis unit: used to analyze the determined test data to generate the one or more test cases, execute the one or more test cases; and

[0054] Generate a test report based on the response of the monitoring terminal to the one or more operation parameters, and based on the test report, determine whether there is a fault in the monitoring terminal.

[0055] Preferably, the device self-checking module further includes:

[0056] A reporting unit: used to determine whether the parameters of the monitoring terminal exceed the threshold range of the reference parameter threshold according to the test report; where

[0057] When exceeding the threshold range of the reference parameter threshold, generate the location identifier of the monitoring middle end, and send the location identifier to a preset remote control center;

[0058] Wherein, the remote control center at least includes: one or more local servers, one or more cloud servers;

[0059] Preferably, generating the test report includes the following steps:

[0060] Acquire the reference operation parameters input by the user, and determine keywords in the reference operation parameter information;

[0061] Determine whether there is a test record matching the reference operation parameters in a preset record library according to the keywords; the preset record library includes test records generated according to historical application test information;

[0062] If there is a test record matching the reference operation parameters, generate a test report according to the test record.

[0063] Other features and advantages of the present invention will be set forth in the following description, and in part will be obvious from the description, or may be learned by practice of the present invention. The objectives and other advantages of the present invention may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

[0064] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Description of the Drawings

[0065] The accompanying drawings are used to provide a further understanding of the present invention, and constitute a part of the description. They are used together with the embodiments of the present invention to explain the present invention, and do not constitute a limitation to the present invention. In the drawings:

[0066] Figure 1 It is a system composition diagram of an intelligent galloping detection system with long-term maintenance-free continuous operation in an embodiment of the present invention;

[0067] Figure 2 It is a composition diagram of the galloping detection module in an embodiment of the present invention;

[0068] Figure 3 It is a composition diagram of the result verification module in an embodiment of the present invention;

[0069] Figure 4 It is a composition diagram of the device self-check module in an embodiment of the present invention. Detailed Embodiments

[0070] The following describes the preferred embodiments of the present invention with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only for explaining and illustrating the present invention, and are not used to limit the present invention.

[0071] As shown in the Figure 1 drawings, the present invention is an intelligent galloping detection system with long-term maintenance-free continuous operation, including:

[0072] Galloping detection module: used to obtain the real-time scene image of the transmission line in real time through the monitoring terminal sleeved on the transmission line, judge whether the transmission line is galloping, and output the galloping result;

[0073] Result verification module: used to obtain the attitude data of the transmission line in real time through the sensing device set on the monitoring terminal, and judge the galloping result according to the attitude data, and output the judgment result;

[0074] Device self-check module: used to monitor the operation data of the monitoring terminal in real time, and judge whether there is a fault in the monitoring terminal according to the inspection result and the judgment result.

[0075] In the above technical solution, as shown in the Figure 1As shown in the figure, the three modules of the present invention mainly aim to achieve two purposes. One is to realize the galloping monitoring of transmission lines, and the other is to output the monitoring results of equipment. In this process, the galloping detection module of the present invention judges whether there is galloping of the transmission line through the point cloud processing of the scene image, and generally this result is correct. To prevent incorrect results, the present invention uses the result verification module to re-judge the galloping monitoring result based on the attitude data of the transmission line to make the result more accurate. Then, when the equipment performs self-check, the present invention will output the data of the equipment itself, and judge whether the monitoring terminal is faulty based on the data of the equipment itself and the judgment result. First, because it is an operation fault, this can be judged according to the real-time monitoring of the operation data. However, when there is a fault in the galloping detection, it may not be judged from the operation data. At this time, based on this result, if the judgment result is incorrect, there may be a fault in the galloping detection. The galloping detection is mainly based on the image of the monitoring terminal. If the camera for taking pictures is dirty, it also belongs to a fault. This kind of fault can only be judged whether there is a problem through the verification result of the result verification module.

[0076] Preferably, as shown in the appendix Figure 2 As shown, the galloping detection module:

[0077] The camera unit: is used to take real-time pictures of the transmission line to obtain the real-time scene image of the transmission line; the real-time scene image includes the real-time scene images on both sides of the transmission line, and the scene image encompasses the 360-degree scene around the transmission line.

[0078] The point cloud processing unit: is used to determine the original point cloud data of the transmission line according to the real-time scene image, wherein,

[0079] The original point cloud data includes three-dimensional coordinates and time stamps;

[0080] Since the present invention performs galloping detection, when the three-dimensional coordinates are determined, it is easier to judge whether the transmission line is stable through the change of coordinates. The time stamp is used to mark the data of the transmission line at each moment.

[0081] The tensor acquisition unit: is used to determine the three-dimensional bounding box of the transmission line and the transmission line feature tensor according to the original point cloud data; wherein,

[0082] The transmission line feature tensor is obtained through the following method:

[0083] The three-dimensional bounding box is the maximum range of the galloping of the transmission line, and this range is reflected in the form of a box body, which is convenient for calculating the transmission line feature tensor. The feature tensor is the intensity of the galloping in the galloping characteristics of the transmission line.

[0084] Voxelize the original point cloud data, determine the point cloud feature tensor through feature extraction, and based on the 3D detection head, obtain the three-dimensional bounding box of the transmission line;

[0085] Select the point cloud feature tensor of the transmission line according to the three-dimensional bounding box; the three-dimensional bounding box is box-shaped, which is convenient for collecting the feature tensor when the transmission line is dancing.

[0086] Image processing unit: The user obtains the image data collected at different times and from different perspectives, the acquisition timestamp of each image data, the three-dimensional bounding box of the candidate target output by the point cloud acquisition device and the point cloud processing module; the output is the image target feature tensor of the candidate target; among them,

[0087] The image processing module extracts features based on the image data and its timestamp, and combines the three-dimensional bounding box to obtain the image target feature tensor of the transmission line;

[0088] The image processing unit is to determine a feature tensor through image data under the point cloud data. When constructing the tensor change diagram with the feature tensor of the point cloud data, it can be judged whether the transmission line is dancing by whether the two feature tensors are linear and in a fitting state. Because there are deviations in both the feature tensor of the point cloud data and the feature tensor of the image data alone, but by comparing the two with each other, this deviation can be minimized.

[0089] Dancing judgment unit: used to determine the tensor change diagram of the transmission line at different times according to the point cloud target feature tensor and the image target feature tensor, and judge whether the transmission line is dancing according to the tensor change diagram; among them,

[0090] When the tensor in the tensor change diagram is a straight line, and the lines of the point cloud target feature tensor and the image target feature tensor at different times fit, it means that the transmission line is not dancing;

[0091] When the tensor in the tensor change diagram is a curve, and the lines of the point cloud target feature tensor and the image target feature tensor at different times do not fit, it means that the transmission line is dancing.

[0092] In the above technical solution, the present invention processes the point cloud of the scene image, calculates the cloud target tensor of the point cloud and the image target feature tensor of the image processing module, and judges whether there is dancing through the fluctuation of the tensor at different times. Moreover, it can also judge whether there is dancing based on whether the two fit.

[0093] Preferably, as shown in the appendix Figure 2 As shown, the camera unit includes:

[0094] Front camera group: The front camera group includes a first camera and a second camera; among them,

[0095] The first camera and the second camera respectively acquire front images of the transmission line from different perspectives;

[0096] Rear camera group: The rear camera group includes a third camera and a fourth camera; among them,

[0097] The third camera and the fourth camera respectively acquire rear images of the transmission line from different perspectives.

[0098] In the above technical solution, the imaging unit of the present invention is two groups of binocular vision cameras. Through front and rear imaging, image acquisition is realized. The present invention monitors both the front and rear of the transmission line through two groups of binocular vision images, which is convenient for more accurately judging the dancing state of the transmission line by comparing both sides.

[0099] Preferably, as shown in the appendix Figure 2 The point cloud processing unit includes:

[0100] Monitoring unit: used to perform key point detection on the initial point cloud data of the real-time scene image; among them,

[0101] The key point detection is the area detection of the transmission line in the real-time scene image;

[0102] The area of the transmission line is the key to dancing judgment. Because in the present invention, the larger the dancing trajectory of the transmission line, the smaller the area of the transmission line in the photos taken by binocular vision. Because as the angle changes, when the transmission line dances to the highest point, the visible distance of the transmission line is only its root, and the area is the smallest. In the stable state, the panoramic view of the transmission line can be photographed to determine the transmission line with the largest area.

[0103] Coordinate construction unit: For each detected key point, a local coordinate system is constructed with the key point as the center and the eigenvector as the coordinate axis; the meaning of the local coordinate system is a coordinate system that can only display part of the transmission line.

[0104] In the present invention, the coordinate system is established with key points, not taking the key area in each image as the center, but using the calculated area value as the center to construct a local coordinate system. This coordinate system is a characteristic coordinate system used to display the dancing intensity of the transmission line under different areas.

[0105] Projection unit: Convert the key points and their neighborhood point sets to the local coordinates to obtain the converted local point cloud, project the converted local point cloud onto three coordinate planes, and then divide the projected point cloud into several grids;

[0106] For real-time dancing data, it is transformed into the local coordinate system. In the scenario of the local coordinate system, through the above method for point cloud data, a large number of images will be obtained during the dancing of the transmission line. These numerous images are all transformed into the local coordinate system, and a large amount of local point cloud data can be generated. These local point cloud data are projected onto three coordinate planes, which are respectively the first vertical coordinate plane under the shooting angle of the front camera group; the second vertical coordinate plane under the shooting angle of the rear camera group, and the horizontal coordinate plane. When the transmission line is dancing, the first vertical coordinate plane and the second vertical coordinate plane are in a symmetric state.

[0107] Point cloud analysis unit: used to perform coordinate transformation according to the several grids to determine the original point cloud data.

[0108] Grid division is to fuse the three planes into a three-dimensional coordinate system, and then divide it into grids. For each grid passed through in the trajectory during the dancing process, its coordinates are determined and used as the original point cloud data. The purpose of grid processing is to more precisely and accurately track the dancing trajectory of the transmission line.

[0109] In the above technical solution, after converting the image into point cloud data, the present invention constructs a coordinate system to convert different avatar features in the real-time scene image into several grids, realizing grid-based point cloud processing.

[0110] Preferably, as shown in the appendix Figure 3 The result verification module includes:

[0111] Simulation unit: used to obtain the sensing data of the sensing device and obtain the simulated horizontal displacement and vertical displacement at each moment based on the acceleration sensing technology; where

[0112] The sensing data includes the acceleration data and angular velocity data of the transmission line;

[0113] The simulation unit is to perform trajectory simulation through the sensing data, and this trajectory simulation can determine the displacement data in the horizontal and vertical directions during the dancing process.

[0114] Conversion unit: used to convert the simulated horizontal displacement and vertical displacement at each moment into discrete horizontal displacement and vertical displacement at each moment;

[0115] Because there will be a large number of trajectories during the dancing of the transmission line, these trajectories will generate a large number of discrete coordinates. Through these discrete coordinates, the unique data in the discrete case can be determined during the simulation process, realizing the discrete analysis of the data.

[0116] Fitting unit: used to register the discrete horizontal displacement and vertical displacement at each moment, obtain the attitude equation of the transmission line, and determine the attitude data of the transmission line according to the attitude equation; the fitting unit is to register the horizontal displacement and vertical displacement, and this registration requires that the data of the horizontal displacement should be adapted to the data of the vertical displacement and conform to the law of galloping, so as to construct an analog attitude equation of the transmission line.

[0117] Result determination unit: used to calculate the horizontal tensor and vertical tensor of the transmission line according to the attitude data, import the tensor change diagram according to the horizontal tensor and vertical tensor, and determine the result of the galloping according to the tensor change diagram, and output the determination result. This attitude equation can obtain an analog horizontal tensor and vertical tensor. By verifying the change data result in the tensor change diagram of the present invention with this horizontal tensor and vertical tensor, when the verification is successful, an accurate galloping detection result can be output. When the verification result is incorrect, it means that the device is damaged.

[0118] In the above technical solution, in the stage of result verification, the present invention first obtains the analog horizontal displacement and vertical displacement at each moment based on the acceleration sensing technology. After knowing the horizontal displacement and vertical displacement of the transmission line, an attitude equation based on the galloping of the transmission line can be constructed through the discrete state of the coordinates at different moments. Through this attitude equation, the change determination of the horizontal tensor and vertical tensor can be realized, and whether there is displacement can be judged through the change of the tensor.

[0119] Preferably, the result verification module further includes:

[0120] Detection device position real-time acquisition unit: used to acquire the position information and viewing angle information of the detection terminal; the position information represents the longitude and latitude coordinates of the detection terminal, and the viewing angle information is the viewing angles of the camera groups on both sides of the detection terminal.

[0121] Point cloud determination unit: used to acquire the required point cloud data according to the position information and viewing angle information; the position information and viewing angle information can simulate the point cloud data, and the sensing device and camera direction of the device can be judged through the simulation of the point cloud data. This is because if there are dirt or dirty interfering objects on the camera group blocking the camera, the viewing angle may not be clear or the viewing angle may be abnormal when partially seen. And the sensing data will also be relatively abnormal. The following determination of the target position information and target orientation information is also for timely modification and adjustment in case of abnormalities.

[0122] Sensing position unit: used to determine the target position information and target orientation information of the required sensing device according to the point cloud data;

[0123] Setting unit: configured to set the sensing device according to the target position information and the target orientation information.

[0124] Preferably, the result verification module further includes:

[0125] Real-time attitude data acquisition unit: configured to acquire the real-time attitude data of the transmission line according to the sensing device; the real-time attitude data is the real-time transmission trajectory of the transmission line.

[0126] Initial attitude data acquisition unit: configured to acquire the initial attitude data of the transmission line when the sensing device is started; the initial attitude data is the attitude trajectory when the transmission line is stationary or slightly moving at startup. The slight movement is because the present invention is installed at a high altitude and is prone to galloping.

[0127] Matching unit: configured to compare the real-time attitude data with the initial attitude data, and when the actual attitude data does not match the initial attitude data, determine the angular offset and speed offset of the transmission line switching from the initial attitude to the current attitude according to the actual attitude data and the initial attitude data; wherein,

[0128] The initial attitude data is the data detected by the attitude detection sensor when the transmission line is in the initial attitude;

[0129] This part takes the initial attitude data as the reference data and the real-time attitude data as the result data, compares the two data, and judges the offset of galloping through the comparison result.

[0130] The angular offset is the angle by which the transmission line deflects relative to the initial attitude with the first coordinate axis as the rotation axis, and the first coordinate axis is the initial direction of the transmission line in the horizontal plane when it is in the initial attitude.

[0131] Preferably, the device self-check module includes:

[0132] Parameter acquisition unit: configured to acquire the determination result and the reference operating parameters of the detection terminal; the reference operating parameters are the parameters set by different detection sensors and camera groups during the detection process of the detection terminal.

[0133] Testing unit: configured to determine the test data corresponding to the test scenario of the selected detection terminal, the test data includes the description of one or more test cases, wherein each test case includes one or more operating parameters of the detection terminal in the selected test scenario, and the common parameters among the one or more operating parameters are encapsulated as common key parameters that can be shared by multiple test cases, and at least one of the test cases includes a reference to the common key parameters;

[0134] In the above technical solution, in order to set corresponding test parameters in each test scenario, the present invention encapsulates the common key parameters of multiple tests based on the operation results of the test data under different test scenarios, so as to judge the operation status of the detection terminal and determine whether the detection terminal is faulty. The common key parameters in the present invention are the parameters generated during the test. After these parameters are determined, fast fault identification can be achieved in case of different fault situations. The test case is the test method. By performing tests through the corresponding test methods, a fault response can be obtained quickly.

[0135] Parsing unit: configured to parse the determined test data to generate the one or more test cases, execute the one or more test cases; and

[0136] generate a test report based on the response of the monitoring terminal to the one or more operating parameters, and based on the test report, determine whether the monitoring terminal has a fault.

[0137] Preferably, as shown in the appendix Figure 4 The device self-checking module further includes:

[0138] Report unit: configured to judge whether the parameters of the monitoring terminal exceed the threshold range of the reference parameter threshold according to the test report; wherein,

[0139] when exceeding the threshold range of the reference parameter threshold, generate the location identifier of the monitoring middle end and send the location identifier to a preset remote control center;

[0140] wherein, the remote control center at least includes: one or more local servers, one or more cloud servers;

[0141] In the above technical solution, since the final detection of the present invention needs to be sent to the operation and maintenance personnel, and the present invention is also provided with communication capabilities, multiple local servers and cloud servers can be set up, combined with edge computing technology, to achieve edge detection, judge whether there is a device fault, and can also determine the device fault faster.

[0142] Preferably, the device self-checking module further includes:

[0143] Obtain the reference operating parameters input by the user and determine keywords in the reference operating parameter information;

[0144] Determine whether there is a test record matching the reference operating parameters in a preset record library; the preset record library includes test records generated according to historical application test information;

[0145] If there is a test record matching the reference operating parameters, generate a test report according to the test record.

[0146] In the above technical solution, when performing equipment self-check, for the reference operating parameters, generally, they are actively input by the operation and maintenance personnel. And for generating test reports, because if a new test report is generated every time of detection, a large amount of calculation is required and the process is complicated. Therefore, the present invention is based on the historical data at this time, performs parameter matching through the historical test data, and can realize the rapid generation of the report by extracting the corresponding data from the report corresponding to the matching result in the historical operating parameters. In the prior art, because the data is constantly changing, the report can only be a new report each time, while the present invention only needs to modify the corresponding parameters on the old report through parameter matching, or directly call the content of the corresponding part in the old report when there is parameter matching.

[0147] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these changes and modifications therein.

Claims

1. An intelligent galloping detection system for long-term maintenance-free continuous operation, characterized in that, it includes: Galloping detection module: used to obtain real-time scene images of the transmission line in real time through a monitoring terminal sleeved on the transmission line, judge whether the transmission line is galloping, and output a galloping result; Result verification module: used to obtain the attitude data of the transmission line in real time through the sensing device set on the monitoring terminal, and judge the galloping result according to the attitude data, and output a judgment result; Device self-check module: used to monitor the operation data of the monitoring terminal in real time, and judge whether the monitoring terminal has a fault according to the galloping result and the judgment result; The galloping detection module includes: Camera unit: used to take real-time pictures of the transmission line and obtain real-time scene images of the transmission line; Point cloud processing unit: used to determine the original point cloud data of the transmission line according to the real-time scene image, where, the original point cloud data includes three-dimensional coordinates and timestamps; Tensor acquisition unit: used to determine the three-dimensional bounding box of the transmission line and the transmission line feature tensor according to the original point cloud data; where, The transmission line feature tensor is obtained in the following way: Voxelize the original point cloud data, determine the point cloud feature tensor through feature extraction, and obtain the three-dimensional bounding box of the transmission line based on the 3D detection head; select the point cloud feature tensor according to the three-dimensional bounding box to obtain the point cloud target feature tensor of the transmission line; Image processing unit: obtain image data collected at different times and from different perspectives, the acquisition timestamp of each image data, and the three-dimensional bounding box of the candidate target; output the image target feature tensor for the candidate target; where, The image processing unit performs feature extraction based on the image data and its timestamp, and combines the three-dimensional bounding box to obtain the image target feature tensor of the transmission line; Galloping judgment unit: used to determine the tensor change diagram of the transmission line at different times according to the point cloud target feature tensor and the image target feature tensor, and judge whether the transmission line is galloping according to the tensor change diagram; where, When the tensor in the tensor change diagram is a straight line, and the line fitting of the point cloud target feature tensor and the image target feature tensor at different times indicates that the transmission line is not galloping; When the tensor in the tensor change diagram is a curve, and the line fitting of the point cloud target feature tensor and the image target feature tensor at different times is not consistent, it indicates that the transmission line is galloping.

2. The intelligent galloping detection system for long-term maintenance-free continuous operation according to claim 1, characterized in that, The camera unit includes: Front camera group: The front camera group includes a first camera and a second camera; where, The first camera and the second camera respectively obtain front images of the transmission line from different perspectives; Rear camera group: The rear camera group includes a third camera and a fourth camera; where, The third camera and the fourth camera respectively obtain rear images of the transmission line from different perspectives.

3. The intelligent galloping detection system for long-term maintenance-free continuous operation according to claim 2, characterized in that, The point cloud processing unit includes: Monitoring unit: used to perform key point detection on the initial point cloud data of the real-time scene image; among them, the key point detection is the area detection of the transmission line in the real-time scene image; Coordinate construction unit: for each detected key point, construct a local coordinate system with the key point as the center and the feature vector as the coordinate axis; Projection unit: convert the key point and its neighborhood point set to the local coordinate system to obtain the converted local point cloud, project the converted local point cloud onto three coordinate planes, and then divide the projected point cloud into several grids; Point cloud analysis unit: used to perform coordinate transformation according to the several grids to determine the original point cloud data.

4. An intelligent galloping detection system that is continuously operated with long-term maintenance-free as described in claim 3, characterized in that, the result verification module includes: Simulation unit: used to obtain the sensing data of the sensing device and obtain the simulated horizontal displacement and vertical displacement at each moment based on the acceleration sensing technology; among them, the sensing data includes the acceleration data and angular velocity data of the transmission line; Conversion unit: used to convert the simulated horizontal displacement and vertical displacement at each moment into discrete horizontal displacement and vertical displacement at each moment; Fitting unit: used to register the discrete horizontal displacement and vertical displacement at each moment to obtain the attitude equation of the transmission line, and determine the attitude data of the transmission line according to the attitude equation; Result determination unit: used to calculate the horizontal tensor and vertical tensor of the transmission line according to the attitude data, import the tensor change diagram according to the horizontal tensor and vertical tensor, and perform result determination on the galloping result according to the tensor change diagram, and output the determination result.

5. An intelligent galloping detection system that is continuously operated with long-term maintenance-free as described in claim 4, characterized in that, the result verification module further includes: Detection device position real-time acquisition unit: used to acquire the position information and viewing angle information of the monitoring terminal; Point cloud determination unit: used to acquire the required point cloud data according to the position information and viewing angle information; Sensing position unit: used to determine the target position information and target orientation information of the required sensing device according to the point cloud data; Setting unit: used to set the sensing device according to the target position information and target orientation information.

6. An intelligent galloping detection system that is continuously operated with long-term maintenance-free as described in claim 5, characterized in that, the result verification module further includes: Real-time attitude data acquisition unit: used to acquire the real-time attitude data of the transmission line according to the sensing device; Initial attitude data acquisition unit: used to acquire the initial attitude data of the transmission line when the sensing device is started; Matching unit: used to compare the real-time attitude data with the initial attitude data, and in the case where the real-time attitude data does not match the initial attitude data, determine the angle offset and speed offset of the transmission line switching from the initial attitude to the current attitude according to the real-time attitude data and the initial attitude data; among them, the initial attitude data is the data detected by the real-time attitude data acquisition unit when the transmission line is in the initial attitude. The angle offset is the angle by which the transmission line deflects relative to the initial attitude with the first coordinate axis as the rotation axis, and the first coordinate axis is the initial direction of the transmission line in the horizontal plane in the initial attitude.

7. An intelligent galloping detection system for long-term maintenance-free continuous operation according to claim 1, characterized in that the device self-checking module includes: a parameter acquisition unit: configured to acquire the determination result and the reference operation parameters of the monitoring terminal; a test unit: configured to determine test data corresponding to the test scenario of the selected monitoring terminal, the test data including descriptions of one or more test cases, where each test case includes one or more operation parameters of the monitoring terminal in the selected test scenario, and the common parameters among the one or more operation parameters are encapsulated as common key parameters that can be shared by multiple test cases, and at least one of the test cases includes a reference to the common key parameter; an analysis unit: configured to analyze the determined test data to generate the one or more test cases, execute the one or more test cases; and, generate a test report based on the response of the monitoring terminal to the one or more operation parameters, and determine whether there is a fault in the monitoring terminal based on the test report.

8. An intelligent galloping detection system for long-term maintenance-free continuous operation according to claim 7, characterized in that the device self-checking module further includes: a reporting unit: configured to determine whether the parameters of the monitoring terminal exceed the threshold range of the reference parameter threshold according to the test report; where when exceeding the threshold range of the reference parameter threshold, generate the location identifier of the monitoring terminal and send the location identifier to a preset remote control center; wherein, the remote control center includes at least: one or more local servers, one or more cloud servers.

9. An intelligent galloping detection system for long-term maintenance-free continuous operation according to claim 7, characterized in that generating the test report includes: acquiring the reference operation parameters input by the user and determining keywords in the reference operation parameters; determining whether there is a test record matching the reference operation parameters in a preset record library according to the keywords; the preset record library includes test records generated according to historical application test information; if there is a test record matching the reference operation parameters, generate a test report according to the test record.

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