A method and device for monitoring the galloping of a transmission line

Abstract

The present application relates to the technical field of monitoring the dancing of electric wires, and specifically to a method and device for monitoring the dancing of transmission lines, the method comprising: obtaining the acceleration and wind speed of each monitoring point of the electric wire; calculating the turbulence intensity of each monitoring point based on the wind speed, and performing extreme point detection, and obtaining the degree of aerodynamic influence in combination with the discrete degree of wind speed; obtaining the superposition sequence of each monitoring point; analyzing the distribution of the peak points of the superposition sequence of all monitoring points within the local range of each monitoring point, and obtaining the dancing characteristic value of each monitoring point in combination with the position characteristics of the monitoring point and the degree of aerodynamic influence; projecting in the spatial dimension in combination with the direction of the wind speed, and using simulation software in combination with the acceleration and wind speed of each monitoring point to monitor the dancing of electric wires at each monitoring point. The present application aims to solve the problem that the dancing of electric wires is difficult to monitor accurately, and to monitor the dancing of electric wires accurately.

Description

Technical Field

[0001] The present application relates to the technical field of wire dancing monitoring, and in particular to a method and device for monitoring the dancing of a transmission line. Background Art

[0002] Transmission line galloping monitoring is critical to the safety of the power system. Certain meteorological conditions, such as strong winds, low temperatures, or rain and snow, may cause line galloping, leading to tripping, wear, breakage, or tower collapse. By monitoring climate conditions and galloping information in real time, these problems can be prevented, the stability and reliability of the power grid can be improved, and the safety and continuity of power supply can be ensured.

[0003] In wire dancing monitoring, air vortex shedding and flow separation can affect accuracy. Vortex shedding is the periodic aerodynamic force formed when air flows around wires, causing wire vibration. Flow separation is the turbulence of air flow on the surface of wires, affecting aerodynamic loads and vibration characteristics. When modeling and simulating the dancing state of wires, the nonlinear and dynamically changing aerodynamic forces generated by these phenomena are difficult to accurately predict.

[0004] In the prior art, simulation models are usually based on simplified assumptions, which makes it impossible to fully capture the instantaneous changes of these complex aerodynamic forces, resulting in deviations between simulation results and actual conditions. It is difficult to judge the randomness of vibration and turbulence, which limits the accuracy of simulation predictions and results in poor monitoring accuracy of wire dancing. Summary of the invention

[0005] In view of the above, it is necessary to provide a method and device for monitoring the galloping of a transmission line to solve the above problems.

[0006] A first aspect of the present application provides a method for monitoring transmission line galloping, the method comprising:

[0007] Obtaining the power line parameters of each monitoring point of the power line, the power line parameters at least include acceleration and wind speed at all acquisition times;

[0008] The turbulence intensity at each monitoring point at each collection time is calculated based on the wind speed, and the extreme point detection is performed on all turbulence intensities at each monitoring point. According to the change characteristics between the turbulence intensities adjacent to the extreme points and the discrete degree of wind speed, the aerodynamic influence degree of each monitoring point is obtained;

[0009] According to the wind speed and acceleration of each monitoring point at all acquisition moments, the superposition sequence of each monitoring point is obtained; the distribution of the peak points of the superposition sequence of all monitoring points within the local range of each monitoring point is analyzed, and the dancing characteristic value of each monitoring point is obtained in combination with the location characteristics of the monitoring point and the degree of aerodynamic influence;

[0010] The dancing characteristic value of each monitoring point is projected in the spatial dimension in combination with the direction of wind speed. Based on the acceleration and wind speed in different spatial dimensions of each monitoring point, simulation software is used to monitor the dancing of wires at each monitoring point.

[0011] The turbulence intensity at each monitoring point at each collection moment is specifically the ratio of the standard deviation of the wind speed data at each collection moment and all previous collection moments to the average wind speed.

[0012] The aerodynamic influence degree of each monitoring point is obtained as follows:

[0013] According to the difference between the turbulence intensity at adjacent moments corresponding to each extreme point, the separation weight at the moment corresponding to each extreme point is obtained;

[0014] According to the distribution characteristics of wind speed in the adjacent time periods corresponding to each extreme point, the confidence level at the time period corresponding to each extreme point is obtained;

[0015] The average level of the separation weights and confidence levels of all extreme points at each monitoring point at the corresponding moment is fused as the aerodynamic influence degree of each monitoring point.

[0016] The separation weight at the time corresponding to each extreme point is specifically the absolute value of the difference between the turbulence intensity at the adjacent time to the time corresponding to each extreme point.

[0017] The confidence level at each extreme point corresponding to the moment is obtained as follows:

[0018] A window corresponding to each extreme point is constructed with the time corresponding to each extreme point as the center, and the confidence level of each extreme point corresponding to the time is obtained according to the discrete degree of wind speed at all acquisition times in the window corresponding to the time of each extreme point.

[0019] The step of obtaining the superposition sequence of each monitoring point is as follows:

[0020] For each monitoring point, the wind speed and acceleration at each collection time are added, and the addition results corresponding to all collection times constitute the superposition sequence of each monitoring point.

[0021] The step of obtaining the dancing characteristic value of each monitoring point is as follows:

[0022] Preset the adjacent monitoring points for each monitoring point;

[0023] According to the difference characteristics of the discrete degree of all peak points corresponding to the collection time in the superposition sequence of each monitoring point and the adjacent monitoring points, combined with the location characteristics of the monitoring points, the dynamic impact factor between each monitoring point and the adjacent monitoring points is obtained;

[0024] According to the dynamic influence factor between each monitoring point and all adjacent monitoring points, combined with the aerodynamic influence degree, the dancing characteristic value of each monitoring point is obtained: the dancing characteristic value of the i-th monitoring point is recorded as , its formula form is: ;in, represents the number of neighboring monitoring points of the i-th monitoring point; It represents the aerodynamic influence degree of the jth neighboring monitoring point of the i-th monitoring point; Represents the dynamic impact factor between the i-th monitoring point and its j-th adjacent monitoring point.

[0025] The dynamic influence factor between each monitoring point and the adjacent monitoring points is obtained as follows:

[0026] Obtain the discrete degree of all peak points corresponding to the time in the superposition sequence of each monitoring point;

[0027] Obtain the distance between each monitoring point and each adjacent monitoring point, recorded as the first distance; obtain the maximum distance between all adjacent monitoring points of each monitoring point, recorded as the second distance; calculate the ratio of the first distance to the second distance;

[0028] The difference in discreteness at corresponding moments of all peak points in the superimposed sequence of each monitoring point and its adjacent monitoring points is fused with the ratio to obtain a dynamic influencing factor between each monitoring point and its adjacent monitoring points.

[0029] The process of monitoring the dancing of electric wires at each monitoring point includes:

[0030] The dancing characteristic value of each monitoring point is taken as the length of the dancing vector, and the direction of the wind speed is taken as the direction of the dancing vector; the projection of each spatial dimension of the dancing vector is multiplied by the acceleration component of all acquisition moments of the corresponding dimension, and the multiplication result and other current parameters are used as the input of ABAQUS simulation software to monitor the dancing of the wires at each monitoring point; the other current parameters include at least: the length of the wire, and the distance between the monitoring point and the two ends of the wire.

[0031] In a second aspect, an embodiment of the present application further provides a transmission line dancing monitoring device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of any one of the above-mentioned methods when executing the computer program.

[0032] In the above scheme, the wire parameters of each monitoring point of the wire are first obtained. The wire will be affected by dynamic factors such as wind force and load in actual operation, which can help predict the specific behavior of the wire under these factors; because the change of turbulence intensity will cause eddy shedding and flow separation to affect the dancing of the wire, the turbulence intensity is analyzed and the aerodynamic influence degree is constructed. Its beneficial effect is that it can accurately evaluate the influence of eddy shedding and flow separation on the dancing of the wire, thereby improving the accuracy of subsequent simulation of the dancing of the wire; in view of the potential amplification effect of the dancing of the wire, the superposition sequence is analyzed and the dancing characteristic value is constructed, which helps to use the wire dancing characteristics of the monitoring points in the local range to reflect the potential amplification degree of the wire dancing at each monitoring point, and eliminate the limitation of the data of a single monitoring point; the acceleration and wind speed are processed in combination with the dancing characteristic value as the input of the simulation software to reflect the dancing state of the wire under different wind speed conditions, which helps to solve the problem that the dancing of the wire is difficult to monitor accurately, and realize more refined simulation analysis and more accurate monitoring of the distance of the wire dancing. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A flowchart of a method for monitoring the galloping of a transmission line provided in accordance with an embodiment of the present application;

[0034] Figure 2 A schematic diagram of a partial maximum value detection result of turbulence intensity provided in one embodiment of the present application;

[0035] Figure 3 A schematic diagram of a detection result of a partial minimum value of turbulence intensity provided in one embodiment of the present application;

[0036] Figure 4 A flow chart for obtaining the degree of aerodynamic influence provided in one embodiment of the present application. DETAILED DESCRIPTION

[0037] In the description of the embodiments of the present application, words such as "exemplary", "or", "for example" and the like are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "or", "for example" and the like is intended to present related concepts in a concrete manner.

[0038] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art in the present application. The terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application.

[0039] It should also be noted that the terms "first" and "second" in this application and the accompanying drawings are used to distinguish similar objects, rather than to describe a specific order or sequence. The method disclosed in the embodiments of the present application or the method shown in the flow chart includes one or more steps for implementing the method. Without departing from the scope of protection of the present application, the execution order of multiple steps can be interchanged with each other, and some steps can also be deleted.

[0040] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0041] The following is a detailed description of a method and device for monitoring transmission line galloping provided by the present application in conjunction with the accompanying drawings.

[0042] See also Figure 1 , which shows a flow chart of a method for monitoring the galloping of a transmission line provided by an embodiment of the present application, the method comprising the following steps:

[0043] The first step is to obtain the wire parameters of each monitoring point of the wire. The wire parameters at least include acceleration and wind speed at all acquisition times.

[0044] Wire dancing monitoring devices are evenly installed on the overhead part of the wires, wherein the wire dancing monitoring devices include wind speed and direction sensors and acceleration sensors, and the location of the monitoring devices is taken as a monitoring point; it should be noted that acceleration and wind speed are a vector, which has both magnitude and direction; wind speed and direction sensors and acceleration sensors are used to measure the acceleration component and wind speed component of the wire in the three directions of x, y and z respectively, and the acceleration vectors and wind speed vectors in these three directions are synthesized using the principle of vector addition to obtain the acceleration and wind speed of the wire at each monitoring point; it should be noted that with the wire dancing monitoring device as the origin, the straight line where the wire is located is defined as the x-axis, the straight line perpendicular to the wire and perpendicular to the ground is defined as the y-axis, and the straight line perpendicular to the xy plane is defined as the z-axis.

[0045] In this embodiment, the collection interval of all sensors in the wire dancing monitoring device is set to 0.5s, and all collected data are normalized to eliminate the influence of dimension, so as to facilitate subsequent analysis.

[0046] The second step is to calculate the turbulence intensity at each monitoring point at each collection time based on the wind speed, perform extreme point detection on all turbulence intensities at each monitoring point, and obtain the aerodynamic impact degree of each monitoring point based on the change characteristics between the turbulence intensities adjacent to the extreme points and the discrete degree of wind speed.

[0047] When the electric wires dance, the aerodynamic phenomena such as vortex shedding and flow separation generated are usually closely related to the turbulence intensity of the wind. Turbulence intensity is an important parameter that describes wind speed fluctuations or wind direction changes. It reflects the relative intensity of wind speed and is the ratio of the wind speed standard deviation (root mean square of wind speed) to the average wind speed. The calculation of turbulence intensity is a well-known technology and will not be elaborated here. The turbulence intensity of each monitoring point at each collection moment is obtained by using the wind speed data at each collection moment and all previous collection moments.

[0048] Aerodynamic phenomena such as vortex shedding and flow separation can significantly affect the dancing of wires. When wind speed changes cause wire vibrations, these aerodynamic phenomena may lead to the generation and shedding of local vortices, increasing the lateral force of the wires and thus the dancing amplitude. At the same time, flow separation may change the flow field around the wires, affecting the stability of the wires and increasing the dancing distance. These factors work together to cause the wires to dance over a longer distance under the action of wind.

[0049] The extreme point detection is performed on the turbulence intensity at all acquisition moments of each monitoring point. According to the difference in turbulence intensity between adjacent moments corresponding to each extreme point, the separation weight at each extreme point is obtained:

[0050] In the process of obtaining the separation weights of this embodiment, the differences between variables are measured by calculating the absolute values ​​of the differences, and the standard deviation is used to measure the discreteness of multiple variables, that is, the separation weight at each extreme point corresponding to the moment is specifically: the absolute value of the difference between the turbulence intensity at the moment before and the moment after each extreme point corresponding to the moment.

[0051] Among them, the schematic diagram of the maximum detection results of the turbulence intensity part is as follows Figure 2 As shown in the figure, the schematic diagram of the detection results of the minimum value of the turbulence intensity is as follows Figure 3 shown.

[0052] It should be understood that the extreme point of turbulence intensity indicates that the stronger the change in turbulence intensity before and after that moment, the more likely it is to cause eddy separation or flow separation at that moment, which will cause an increase in the dancing distance of the wire.

[0053] A window corresponding to each extreme point is constructed with the time corresponding to each extreme point as the center, and the confidence level of each extreme point corresponding to the time is obtained according to the discrete degree of wind speed at all acquisition times in the window corresponding to the time of each extreme point.

[0054] In the process of obtaining the confidence of this embodiment, the standard deviation is used to measure the discreteness of multiple variables, that is, the standard deviation of wind speed at all acquisition moments in the window corresponding to each extreme point is calculated as the confidence at the moment corresponding to each extreme point.

[0055] It should be understood that near the time corresponding to the extreme point, the greater the volatility of the wind speed, the greater the instability of the wind flow, which will increase the possibility of vortex shedding and flow separation phenomena, and thus the greater the confidence level at the corresponding time.

[0056] The average level after fusing the separation weights and confidence levels of all extreme points at each monitoring point at the corresponding moment is taken as the aerodynamic influence degree of each monitoring point:

[0057] In this embodiment, the average of the product of the separation weight and the confidence level of all extreme value points of each monitoring point at the corresponding time is taken as the aerodynamic influence degree of each monitoring point.

[0058] Among them, the flow chart for obtaining the degree of aerodynamic influence is as follows: Figure 4 shown.

[0059] It should be understood that the degree of aerodynamic influence combines the influence of the stability of wind speed and wind force and the dynamic changes of turbulence intensity on the dancing of wires. Its magnitude reflects the intensity of the aerodynamic influence of the aerodynamic phenomena of vortex shedding and flow separation caused by changes in turbulence intensity on the dancing of wires at a specific moment. The larger the value, the greater the influence of aerodynamic factors on the wires. The aerodynamic influence causes the wires to be subjected to greater forces, causing the wires to deviate from their normal position, resulting in an increase in the dancing distance of the wires.

[0060] The third step: obtain the superposition sequence of each monitoring point according to the wind speed and acceleration at all collection moments of each monitoring point; analyze the distribution of the peak points of the superposition sequence of all monitoring points within the local range of each monitoring point, and obtain the dancing characteristic value of each monitoring point in combination with the location characteristics of the monitoring point and the degree of aerodynamic influence.

[0061] The dancing of wires has certain propagation characteristics, that is, the dancing at one location may be transmitted to adjacent locations through the tension and elasticity of the wires, forming a chain reaction. The propagation of the dancing may complicate the vibration mode of the wires, affect the dancing of adjacent wires, and may induce resonance, further amplifying the dancing amplitude of the wires.

[0062] For each monitoring point, the wind speed and acceleration at each acquisition time are added together, and the addition results corresponding to all acquisition times form a superposition sequence of each monitoring point. It should be noted that since the wind speed and acceleration at each acquisition time have been normalized before, the influence of dimension has been eliminated, so the calculation can be performed; acceleration is the response of the wire structure to wind force, and wind force is an external force. Superimposing the two actually considers the dynamic behavior of the wire under the action of wind while considering the external force and the response of the structure, thereby evaluating the dancing intensity of the wire and further reflecting the dancing distance of the wire.

[0063] The superposition sequence is used as input, and the peak search algorithm is used to output all the peaks of the superposition sequence and the acquisition time of all the peaks. The peak of the superposition sequence represents the maximum comprehensive dancing intensity that the wire may reach under the action of wind at the monitoring point. It should be noted that the peak search algorithm is an existing well-known technology, and this application will not elaborate on it.

[0064] Preset the neighboring monitoring points of each monitoring point; according to the difference characteristics of the discrete degree of all peak points corresponding to the collection time in the superposition sequence of each monitoring point and the neighboring monitoring points, combined with the location characteristics of the monitoring point, obtain the dynamic impact factor between each monitoring point and its neighboring monitoring points:

[0065] Obtain the discreteness of all peak points at corresponding moments in the superimposed sequence of each monitoring point; obtain the distance between each monitoring point and each adjacent monitoring point, recorded as the first distance; obtain the maximum distance between all adjacent monitoring points of each monitoring point, recorded as the second distance; calculate the ratio of the first distance to the second distance; and fuse the difference in the discreteness of each monitoring point and its adjacent monitoring points with the ratio as the dynamic influencing factor between each monitoring point and its adjacent monitoring points.

[0066] In this embodiment, during the calculation of the dynamic impact factor, each monitoring point is taken as the center, and the three monitoring points on the left and right are taken as the neighboring monitoring points of each monitoring point. The implementer can adjust it according to the actual situation. It should be noted that if there are less than three neighboring pixel points on one side, only the existing monitoring points are selected to form the neighboring monitoring points of each monitoring point; the difference in the degree of discreteness of each monitoring point and its neighboring monitoring points is specifically: the standard deviation of the peak point of the superposition sequence of each monitoring point is calculated at the corresponding time, and the absolute value of the difference between the standard deviation of each monitoring point and each neighboring monitoring point is calculated to obtain the difference in the degree of discreteness; the dynamic impact factor is specifically the product of the absolute value of the difference and the ratio.

[0067] It should be understood that the dynamic impact factor between two monitoring points evaluates the dynamic impact between the two monitoring points by quantifying the difference between the dancing amplitudes of each monitoring point and its adjacent monitoring points. The dynamic impact factor reflects the degree of influence of the dancing of the adjacent monitoring points of each monitoring point on each monitoring point.

[0068] Furthermore, according to the dynamic influence factor between each monitoring point and all adjacent monitoring points, combined with the aerodynamic influence degree, the dancing characteristic value of each monitoring point is obtained:

[0069] In this embodiment, the dancing characteristic value of the i-th monitoring point is recorded as , its formula form is: ;in, represents the number of neighboring monitoring points of the i-th monitoring point; It represents the aerodynamic influence degree of the jth neighboring monitoring point of the i-th monitoring point; Represents the dynamic impact factor between the i-th monitoring point and its j-th adjacent monitoring point.

[0070] It should be understood that the larger the dynamic impact factor, the easier it is for the adjacent monitoring point to cause the corresponding monitoring point to amplify the galloping, so the corresponding monitoring point's galloping characteristic value is larger. The galloping characteristic value reflects the potential amplification degree of the wire galloping at each monitoring point. The larger its value, the more the galloping of the wire will be significantly enhanced due to the aerodynamic influence and the dynamic influence of the adjacent monitoring point.

[0071] The fourth step: Project the dancing characteristic value of each monitoring point in the spatial dimension in combination with the direction of wind speed. Based on the acceleration and wind speed in different spatial dimensions of each monitoring point, use simulation software to monitor the dancing of wires at each monitoring point.

[0072] Since wind speed and direction sensors and accelerometers can measure the acceleration changes and wind speed changes of wires in three spatial dimensions, namely the x, y, and z directions, in monitoring the dancing of wires, wind speed and direction sensors and accelerometers can capture the dynamic changes of these vibrations and thus obtain the dancing behavior of wires.

[0073] The dancing characteristic value of each monitoring point is taken as the length of the dancing vector, and the direction of the wind speed is taken as the direction of the dancing vector; the projection of each spatial dimension of the dancing vector is multiplied by the acceleration component of all acquisition moments of the corresponding dimension, and the multiplication result, wind speed, length of the wire, and the distance between the monitoring point and the two ends of the wire are taken as input. The dancing of the wire is modeled and simulated by ABAQUS simulation software, and the visualization tool of ABAQUS is used to view the dancing of the wire at each monitoring point of the wire.

[0074] In this embodiment, the wire dancing amplitude of all monitoring points at each acquisition time is obtained by using a visualization tool, and the maximum-minimum function is used for normalization processing, and the monitoring points where the wire dancing amplitude is greater than a preset threshold are regarded as abnormal points, and an early warning is issued to the staff. The preset threshold is 0.8.

[0075] The processing of acceleration helps to more accurately simulate the vibration characteristics of power lines, including vibration frequency, amplitude and vibration mode. By processing acceleration, the dynamic response of power lines under specific wind conditions can be more clearly identified and simulated. This enhancement helps the simulation software capture more subtle dynamic changes, thereby improving the accuracy of the simulation and obtaining more accurate monitoring results of power line dancing.

[0076] Based on the same inventive concept as the above method, an embodiment of the present application also provides a transmission line dancing monitoring device, including a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, it implements the steps of any one of the above-mentioned transmission line dancing monitoring methods.

[0077] In summary, the embodiment of the present application first obtains the wire parameters of each monitoring point of the wire. In actual operation, the wire will be affected by dynamic factors such as wind force and load, which can help predict the specific behavior of the wire under these factors; because the change of turbulence intensity will cause eddy shedding and flow separation to affect the dancing of the wire, the turbulence intensity is analyzed and the aerodynamic influence degree is constructed. The beneficial effect is that it can accurately evaluate the influence of eddy shedding and flow separation on the dancing of the wire, thereby improving the accuracy of subsequent simulation of the dancing of the wire; in view of the potential amplification effect of the dancing of the wire, the superposition sequence is analyzed and the dancing characteristic value is constructed, which helps to use the wire dancing characteristics of the monitoring points in the local range to reflect the potential amplification degree of the wire dancing at each monitoring point, and eliminate the limitation of the data of a single monitoring point; the acceleration and wind speed are processed in combination with the dancing characteristic value as the input of the simulation software to reflect the dancing state of the wire under different wind speed conditions, which helps to solve the problem that the dancing of the wire is difficult to accurately monitor, and realize more refined simulation analysis and more accurate monitoring of the distance of the wire dancing.

[0078] The flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to the embodiment of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the function marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two continuous boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and the block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two continuous operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

[0079] For those skilled in the art, it is obvious that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the basic features of the present application. Therefore, no matter from which point of view, the above embodiments of the present application should be regarded as exemplary and non-restrictive; the technical solutions recorded in the above embodiments are modified, or some of the technical features are replaced by equivalents, which does not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method for monitoring transmission line galloping, characterized in that: The method comprises the following steps: Obtaining the power line parameters of each monitoring point of the power line, the power line parameters at least include acceleration and wind speed at all acquisition times; The turbulence intensity at each monitoring point at each collection time is calculated based on the wind speed, and the extreme point detection is performed on all turbulence intensities at each monitoring point. According to the change characteristics between the turbulence intensities adjacent to the extreme points and the discrete degree of wind speed, the aerodynamic influence degree of each monitoring point is obtained; According to the wind speed and acceleration of each monitoring point at all acquisition moments, the superposition sequence of each monitoring point is obtained; the distribution of the peak points of the superposition sequence of all monitoring points within the local range of each monitoring point is analyzed, and the dancing characteristic value of each monitoring point is obtained in combination with the location characteristics of the monitoring point and the degree of aerodynamic influence; The dancing characteristic values ​​of each monitoring point are projected in the spatial dimension in combination with the direction of wind speed. Based on the acceleration and wind speed of different spatial dimensions of each monitoring point, simulation software is used to monitor the dancing of wires at each monitoring point. The steps of obtaining the dancing characteristic value of each monitoring point are: Preset the adjacent monitoring points for each monitoring point; According to the difference characteristics of the discrete degree of all peak points corresponding to the collection time in the superposition sequence of each monitoring point and the adjacent monitoring points, combined with the location characteristics of the monitoring points, the dynamic impact factor between each monitoring point and the adjacent monitoring points is obtained; According to the dynamic influence factor between each monitoring point and all adjacent monitoring points, combined with the aerodynamic influence degree, the dancing characteristic value of each monitoring point is obtained: the dancing characteristic value of the i-th monitoring point is recorded as , its formula form is: ;in, represents the number of neighboring monitoring points of the i-th monitoring point; It represents the aerodynamic influence degree of the jth neighboring monitoring point of the i-th monitoring point; Represents the dynamic impact factor between the i-th monitoring point and its j-th adjacent monitoring point.

2. A method for monitoring transmission line galloping as claimed in claim 1, characterized in that: The turbulence intensity at each monitoring point at each collection moment is specifically the ratio of the standard deviation of the wind speed data at each collection moment and all previous collection moments to the average wind speed.

3. A method for monitoring transmission line galloping as claimed in claim 1, characterized in that: The aerodynamic influence degree of each monitoring point is obtained as follows: According to the difference between the turbulence intensity at adjacent moments corresponding to each extreme point, the separation weight at the moment corresponding to each extreme point is obtained; According to the distribution characteristics of wind speed in the adjacent time periods corresponding to each extreme point, the confidence level at the time period corresponding to each extreme point is obtained; The average level of the separation weights and confidence levels of all extreme points at each monitoring point at the corresponding moment is fused as the aerodynamic influence degree of each monitoring point.

4. A method for monitoring transmission line galloping as claimed in claim 3, characterized in that: The separation weight at the time corresponding to each extreme point is specifically the absolute value of the difference between the turbulence intensity at the adjacent time to the time corresponding to each extreme point.

5. A method for monitoring transmission line galloping as claimed in claim 3, characterized in that: The confidence level at each extreme point corresponding to the moment is obtained as follows: A window corresponding to each extreme point is constructed with the time corresponding to each extreme point as the center, and the confidence level of each extreme point corresponding to the time is obtained according to the discrete degree of wind speed at all acquisition times in the window corresponding to the time of each extreme point.

6. A method for monitoring transmission line galloping as claimed in claim 1, characterized in that: The method of obtaining the superposition sequence of each monitoring point is specifically as follows: For each monitoring point, the wind speed and acceleration at each collection time are added, and the addition results corresponding to all collection times constitute the superposition sequence of each monitoring point.

7. A method for monitoring transmission line galloping as claimed in claim 1, characterized in that: The dynamic influence factor between each monitoring point and the adjacent monitoring points is obtained as follows: Obtain the discrete degree of all peak points corresponding to the time in the superposition sequence of each monitoring point; Obtain the distance between each monitoring point and each adjacent monitoring point, recorded as the first distance; obtain the maximum distance between all adjacent monitoring points of each monitoring point, recorded as the second distance; calculate the ratio of the first distance to the second distance; The difference in discreteness at corresponding moments of all peak points in the superimposed sequence of each monitoring point and its adjacent monitoring points is fused with the ratio to obtain a dynamic influencing factor between each monitoring point and its adjacent monitoring points.

8. A method for monitoring transmission line galloping as claimed in claim 1, characterized in that: The process of monitoring the dancing of wires at each monitoring point includes: The dancing characteristic value of each monitoring point is taken as the length of the dancing vector, and the direction of the wind speed is taken as the direction of the dancing vector; the projection of each spatial dimension of the dancing vector is multiplied by the acceleration component of all acquisition moments of the corresponding dimension, and the multiplication result and other current parameters are used as the input of ABAQUS simulation software to monitor the dancing of the wires at each monitoring point; the other current parameters include at least: the length of the wire, and the distance between the monitoring point and the two ends of the wire.

9. A transmission line galloping monitoring device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

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