Transmission Line Galloping Early Warning Method, System, Device and Medium

Abstract

The present invention provides a method, system, device and medium for early warning of transmission line galloping, which can be applied to the technical field of line galloping prediction. The method for early warning of transmission line galloping includes: generating galloping risk information of the target overhead transmission line according to M weight information and M galloping risk values of the target overhead transmission line; in response to detecting that the galloping risk information indicates that there is a galloping risk in the target overhead transmission line, predicting meteorological prediction information of the target area within the target time period according to the information of the target time period and the historical meteorological information of the target area; in response to detecting that the meteorological prediction information meets a predetermined condition, generating a line galloping early warning result of the target overhead transmission line according to the meteorological prediction information and the parameters of the target overhead transmission line.

Description

Technical Field

[0001] The present invention relates to the technical field of line galloping prediction, and particularly to a transmission line galloping early warning method, system, device and medium. Background Art

[0002] The stable operation of overhead transmission lines is crucial for power consumers. However, the sudden galloping of overhead transmission lines may affect the stability of power transmission of overhead transmission lines. There are many influencing factors for the occurrence of line galloping. To ensure the stable operation of the line, it is necessary to timely and accurately give an early warning of the possible galloping of the line, so as to take preventive measures to ensure the stable operation of the line. However, due to the suddenness and uncertainty of the galloping phenomenon, the accuracy of galloping early warning is low and the timeliness is poor. Summary of the Invention

[0003] In view of the above problems, the present invention provides a transmission line galloping early warning method, system, device and medium.

[0004] The first aspect of the present invention provides a transmission line galloping early warning method, including: in response to receiving a galloping early warning instruction for a target overhead transmission line located in a target area during a target period, generating galloping risk information of the target overhead transmission line according to M weight information and M galloping risk values of the target overhead transmission line; the m-th weight information represents the importance degree of the m-th galloping prediction index relative to the other M-1 galloping prediction indexes when predicting the galloping risk of the target overhead transmission line according to the m-th galloping prediction index among the M galloping prediction indexes; the m-th galloping risk value represents the risk degree of the galloping of the target overhead transmission line when taking the m-th galloping prediction index as the evaluation criterion, M is an integer greater than 1, and m is a positive integer less than or equal to M; in response to detecting that the galloping risk information indicates that the target overhead transmission line has a galloping risk, predicting the meteorological prediction information of the target area during the target period according to the information of the target period and the historical meteorological information of the target area; in response to detecting that the meteorological prediction information meets a predetermined condition, generating a line galloping early warning result of the target overhead transmission line according to the meteorological prediction information and the parameters of the target overhead transmission line.

[0005] According to an embodiment of the present invention, the target area includes I sub-areas; according to the information of the target time period and the historical meteorological information of the target area, the meteorological prediction information of the target area within the target time period is predicted, including: processing the information of the target time period and the i-th historical meteorological information of the i-th sub-area by using a first predetermined model to obtain the i-th meteorological prediction information, where I is an integer greater than 1, and i is a positive integer less than or equal to I; the above method further includes: processing the i-th meteorological prediction information by using a second predetermined model to determine the i-th meteorological risk information, where the i-th meteorological risk information represents the risk probability of galloping of the target overhead transmission line under the meteorological conditions of the i-th meteorological prediction information; determining the target meteorological risk information from the I meteorological risk information, where the target meteorological risk information represents that there is a galloping risk of the target overhead transmission line under the meteorological conditions of the meteorological prediction information corresponding to the target meteorological risk information; in response to detecting that the number of the target meteorological risk information in the I meteorological risk information is greater than or equal to a predetermined number, determining that the meteorological prediction information of the target area meets the predetermined condition.

[0006] According to an embodiment of the present invention, processing the i-th meteorological prediction information by using a second predetermined model to determine the i-th meteorological risk information includes: obtaining the phase information of the target overhead transmission line; and processing the i-th meteorological prediction information and the phase information by using a second predetermined model to determine the i-th meteorological risk information.

[0007] According to an embodiment of the present invention, the second predetermined model is trained by using sample meteorological information and label information corresponding to the sample meteorological information; the label information is obtained by the following method: under the meteorological conditions of the sample meteorological information, image acquisition is performed on the overhead three-phase conductors to obtain N consecutive frame images of the conductors, where N is an integer greater than 1; segmenting the N frame images of the conductors according to the images of each phase of the three-phase conductors in the N frame images of the conductors to obtain N frame images of each phase of the conductors; performing binarization processing on the N frame images of each phase of the conductors to obtain N binarized images of each phase of the conductors; according to the largest closed image in area among the N binarized images of each phase of the conductors, performing feature extraction on each of the N binarized images of each phase of the conductors to obtain N frame conductor features of each phase of the conductors; for each phase of the conductors, according to the displacement change of the n-th conductor feature relative to the 1st conductor feature, obtaining the (n - 1)-th displacement change information, where n is a positive integer less than or equal to N; generating label information corresponding to the sample meteorological information according to the N - 1 displacement change information of each phase of the conductors.

[0008] According to an embodiment of the present invention, the meteorological prediction information includes the minimum temperature information, relative humidity information, maximum wind speed information, and wind direction information within a target time period; the parameters of the target overhead transmission line include the axial information of the conductors of the target overhead transmission line; according to the meteorological prediction information and the parameters of the target overhead transmission line, a line galloping warning result of the target overhead transmission line is generated, including: determining the included angle information between the wind direction information and the axial information of the conductors; using a third predetermined model to process the minimum temperature information, relative humidity information, maximum wind speed information, and included angle information, and outputting the line galloping level information of the target overhead transmission line; and generating a line galloping warning result according to the line galloping level information.

[0009] According to an embodiment of the present invention, according to M weight information and M galloping risk values of a target overhead transmission line, galloping risk information of the target overhead transmission line is generated, including: determining the m-th target weight information according to the m-th weight information, the m-th galloping risk value, M weight information, and M galloping risk values; determining J first galloping prediction indicators and K second galloping prediction indicators from M galloping prediction indicators according to an index evaluation criterion, where the evaluation criteria between the first galloping prediction indicators and the second galloping prediction indicators are different, and J and K are positive integers; using a first normalization function to process the galloping risk value of the j-th first galloping prediction indicator among the J first galloping prediction indicators to obtain the j-th first index value, where j is a positive integer less than or equal to J; using a second normalization function to process the galloping risk value of the k-th second galloping prediction indicator among the K second galloping prediction indicators to obtain the k-th second index value, where k is a positive integer less than or equal to K; and generating the galloping risk information of the target overhead transmission line according to the J first index values, the K second index values, and the M target weight information.

[0010] According to an embodiment of the present invention, the galloping risk value includes the wind speed information at the location where the target overhead transmission line is located; the above method further includes: using a sensor to collect the initial wind speed information of the target area; determining the height difference between the target overhead transmission line and the sensor according to the height information of the target overhead transmission line and the height information of the sensor; determining a target wind speed conversion function from Q wind speed conversion functions corresponding to Q height difference ranges, where Q is an integer greater than 1; and using the target wind speed conversion function to process the initial wind speed information to obtain the wind speed information.

[0011] The second aspect of the present invention provides a dancing warning system for a transmission line, including: a server, configured to: in response to receiving a dancing warning instruction for a target overhead transmission line located in a target area during a target period, generate dancing risk information of the target overhead transmission line according to M weight information and M dancing risk values of the target overhead transmission line; the m-th weight information represents the importance degree of the m-th dancing prediction index relative to the other M-1 dancing prediction indexes when predicting the dancing risk of the target overhead transmission line according to the m-th dancing prediction index among the M dancing prediction indexes; the m-th dancing risk value represents the risk degree of the target overhead transmission line dancing when taking the m-th dancing prediction index as the evaluation criterion, M is an integer greater than 1, and m is a positive integer less than or equal to M; in response to detecting that the dancing risk information indicates that the target overhead transmission line has a dancing risk, predict the meteorological prediction information of the target area during the target period according to the information of the target period and the historical meteorological information of the target area; in response to detecting that the meteorological prediction information meets a predetermined condition, generate a line dancing warning result of the target overhead transmission line according to the meteorological prediction information and the parameters of the target overhead transmission line; a visual terminal device, connected to the server, configured to: receive the line dancing warning result and display the line dancing warning result through the visualization interface of the visual terminal device.

[0012] The third aspect of the present invention provides an electronic device, including: one or more processors; a memory for storing one or more computer programs, wherein, the above one or more processors execute the above one or more computer programs to implement the steps of the above method.

[0013] The fourth aspect of the present invention further provides a computer-readable storage medium, on which a computer program or instruction is stored, and when the computer program or instruction is executed by a processor, the steps of the above method are implemented.

[0014] According to the embodiments of the present invention, by generating dancing risk information according to the weight information and dancing risk values of the target overhead transmission line, it is possible to determine, based on the dancing risk information, that the target overhead transmission line is a line with a dancing risk. Then, according to the historical meteorological information of the target area and the information of the target period, the meteorological prediction information of the target area during the target period is predicted, so as to determine whether the meteorology in the target area during the target period is a meteorological condition that is likely to cause the target overhead line to dance. When the meteorological prediction information meets the predetermined condition, it can be determined that the meteorological prediction information of the target area during the target period is likely to cause the target overhead line to dance, and thus, further according to the meteorological prediction information and the parameters of the target overhead transmission line, a relatively accurate warning of the dancing condition of the target overhead transmission line during the target period can be made, so as to timely prevent the potential dancing risk of the target overhead transmission line before the target period arrives and ensure the stable power transmission of the target overhead line. Description of the Drawings

[0015] Through the following description of the embodiments of the present invention with reference to the accompanying drawings, the above content and other objects, features, and advantages of the present invention will become clearer. In the drawings:

[0016] Figure 1 Shows an application scenario diagram of the transmission line galloping early warning method according to an embodiment of the present invention;

[0017] Figure 2 Shows a flowchart of the transmission line galloping early warning method according to an embodiment of the present invention;

[0018] Figure 3 Shows a schematic diagram of the galloping prediction index layer according to an embodiment of the present invention;

[0019] Figures 4A to 4D Respectively show schematic diagrams of the galloping areas according to embodiments of the present invention;

[0020] Figure 5 Shows a flowchart of the transmission line galloping early warning method according to another embodiment of the present invention;

[0021] Figure 6 Shows a structural block diagram of the transmission line galloping early warning system according to an embodiment of the present invention; and

[0022] Figure 7 Shows a block diagram of an electronic device suitable for implementing the transmission line galloping early warning method according to an embodiment of the present invention. Detailed Embodiments

[0023] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present invention. In the following detailed description, for the sake of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present invention. However, obviously, one or more embodiments can also be implemented without these specific details. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessarily confusing the concepts of the present invention.

[0024] The terms used herein are merely for describing specific embodiments and are not intended to limit the present invention. The terms "including", "comprising", etc. used herein indicate the presence of the described features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0025] All terms used herein, including technical and scientific terms, have the meanings commonly understood by those of ordinary skill in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0026] In the case of using expressions such as "at least one of A, B, and C, etc.", generally, it should be interpreted according to the meaning commonly understood by those of ordinary skill in the art (for example, "a system having at least one of A, B, and C" should include, but not be limited to, a system having only A, only B, only C, having A and B, having A and C, having B and C, and / or having A, B, and C, etc.).

[0027] Figure 1 The application scenario diagram of the transmission line galloping early warning method according to an embodiment of the present invention is shown.

[0028] As Figure 1 shown, the application scenario 100 according to this embodiment may include a terminal device 110, a server 120, a network 130, a sensor 140, and an image collector 150. The network 130 is used to provide a medium for communication links among the terminal device 110, the server 120, the sensor 140, and the image collector 150. The network 130 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0029] The user can use the terminal device 110 to interact with the server 120 through the network 130 to receive or send messages, etc. Various communication client applications may be installed on the terminal device 110, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only as examples).

[0030] The terminal device 110 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, and desktop computers, etc.

[0031] The server 120 can be a server that provides various services, such as a background management server (for example only) that supports the websites browsed by users using the terminal device 110. The background management server can analyze and process data such as user requests received, and feedback the processing results (such as web pages, information, or data obtained or generated according to user requests, etc.) to the terminal device. For example, the server 120 can be used to obtain and store meteorological information and image information of the overhead transmission line through the network 130, and can complete operations such as data storage, retrieval, backup, and invocation of historical information. And, real-time operations on the image collector 150 can be achieved through the network 130, including taking pictures and video live broadcasts, etc.

[0032] The sensor 140 can include and is not limited to a wind speed and direction sensor, etc. The wind speed and direction sensor can be used to collect wind speed information and wind direction information of the location area, etc. A power supply device can also be deployed in the area where the sensor 140 and the image collector 150 are located to supply power to the sensor 140 and the image collector 150.

[0033] It should be noted that the transmission line galloping warning method provided by the embodiments of the present invention can generally be executed by the server 120. The transmission line galloping warning method provided by the embodiments of the present invention can also be executed by a server or a server cluster different from the server 120 and capable of communicating with the terminal device 110.

[0034] It should be understood that Figure 1 the numbers of the terminal device, server, sensor, and image collector in

[0035] are merely illustrative. According to the implementation requirements, there can be any number of terminal devices, servers, sensors, and image collectors. Figure 1 Based on the scenario described below, the transmission line galloping warning method of the embodiments of the invention will be described in detail below.

[0036] Figure 2 The flowchart of the transmission line galloping warning method according to the embodiments of the present invention is shown.

[0037] As Figure 2 shown, the transmission line galloping warning method of this embodiment includes operations S210 to S230.

[0038] In operation S210, in response to receiving a galloping warning instruction for a target overhead transmission line in a target area during a target period, according to the M weight information and M galloping risk values of the target overhead transmission line, generate the galloping risk information of the target overhead transmission line.

[0039] According to an embodiment of the present invention, the m-th weight information may represent the importance degree of the m-th dancing prediction index relative to the other M-1 dancing prediction indexes when predicting the dancing risk of the target overhead transmission line according to the m-th dancing prediction index. The m-th dancing risk value may represent the risk degree of the dancing of the target overhead transmission line when the m-th dancing prediction index is used as the evaluation criterion, where M is an integer greater than 1, and m is a positive integer less than or equal to M.

[0040] In operation S220, in response to detecting that the dancing risk information indicates that there is a dancing risk for the target overhead transmission line, the meteorological prediction information of the target area within the target time period is predicted according to the information of the target time period and the historical meteorological information of the target area.

[0041] In operation S230, in response to detecting that the meteorological prediction information meets a predetermined condition, a line dancing early warning result of the target overhead transmission line is generated according to the meteorological prediction information and the parameters of the target overhead transmission line. Among them, the predetermined condition may be a condition for determining whether the meteorological prediction information has a risk of causing the overhead transmission line to dance. For example, the predetermined condition may be a condition determined based on a predetermined threshold of each meteorological factor (such as humidity, wind speed, etc.) in the meteorological prediction information.

[0042] According to an embodiment of the present invention, the target area may be the area where the target overhead transmission line is located. The target time period may be a future time period after the current time period. The galloping early warning instruction is an early warning instruction for determining whether the target overhead transmission line will gallop during the target time period. When receiving the galloping early warning instruction, galloping prediction indicators can be selected, and weight information and galloping risk values under these indicators can be obtained according to the galloping prediction indicators. The galloping prediction indicators can be indicators that can reflect the development of the galloping state of the overhead transmission line. The weight information and galloping risk values can be predetermined. For example, when a user needs to obtain the galloping early warning result of an overhead transmission line within a certain area from 3:00 pm to 4:00 pm on the third day in the future, the "from 3:00 pm to 4:00 pm on the third day in the future" can be used as the target time period, and this area can be used as the target area, and the galloping early warning instruction carrying the information of the target time period, the information of the target area, and the information of this overhead transmission line is sent to the server through the terminal device. The server can first query the weight information and galloping risk values under M galloping prediction indicators pre-stored in the server according to the information of the target overhead transmission line (such as identification information such as the number), and calculate the galloping risk information according to the weight information and galloping risk values. The weight information can be fixed, while the galloping risk values of the galloping prediction indicators may be updated due to the data obtained regularly, so the calculation results calculated according to the M weight information and M galloping risk values will also change accordingly. For example, the weight information and galloping risk value of the m-th galloping prediction indicator can be multiplied to obtain the m-th intermediate calculation result, and then the calculation result can be obtained according to the sum of the M intermediate settlement results. The calculation result can be compared with a predetermined threshold value, so as to generate galloping risk information according to the comparison result. The galloping risk information can be used to characterize whether the target overhead transmission line has potential galloping risks.

[0043] Specifically, Figure 3 FIG. shows a schematic diagram of the galloping prediction indicator layer according to an embodiment of the present invention.

[0044] As Figure 3 shown, the galloping prediction indicators may include prediction indicators related to line characteristics and prediction indicators related to the environment where the line is located. The prediction indicators related to characteristic factors may include galloping amplitude 311, galloping frequency 312, galloping area type 313, conductor type 314, and so on. The prediction indicators related to environmental factors may include wind speed 321, temperature 322, ice coating thickness 323, and humidity 324, and so on. Moreover, the historical data of the target overhead transmission line itself or the historical data of lines of the same type as the target overhead transmission line also reflects the development and change of the galloping state to a certain extent. Thus, the galloping prediction indicators may also include prediction indicators related to historical data. The prediction indicators related to historical data may include galloping frequency change amount 331 and galloping amplitude change amount 332, and so on.

[0045] For example, an overhead transmission line can be one or more phases of a three-phase line. Since the harm of galloping is generally mainly due to the phase-to-phase flashover caused by the insufficient air gap length between each phase line, the galloping amplitude used to reflect the size of the galloping range becomes the most important galloping prediction index. The galloping frequency is the vibration characteristic parameter of the line galloping itself. Moreover, line galloping mostly occurs on ice-covered lines, and the ice thickness of the line is comprehensively determined by temperature, rainfall, and geographical environment.

[0046] To form galloping, in addition to icing, wind excitation is also required to provide energy for line galloping. In addition, an unreasonable combination of line structure parameters is also likely to cause galloping. For example, bundled conductors are more likely to gallop than single conductors, and large-section conductors are more likely to gallop than small-section conductors. The frequency of conductor galloping is closely related to meteorological conditions and microtopography. Areas with flat terrain, many lake wind mouths, harsh meteorological conditions, and many glaze days are all areas where galloping is more likely to be induced. Therefore, the galloping area types can be divided according to the frequency of line galloping. Thus, the galloping area types can include, for example, Figure 4A the canyon wind tunnel type galloping area as shown in Figure 4B the pass fluctuation type galloping area as shown in Figure 4C the alpine watershed type galloping area as shown in Figure 4D and the terrain uplift type galloping area as shown in Figure 4A It can be seen from the reference Figure 4B that when the line crosses a steep canyon, the "narrowing effect" occurs when the air flow enters the canyon from the open area, and the air flow will accelerate through the canyon, making the line prone to icing and affecting the probability of line galloping; it can be seen from the reference Figure 4C that when the line crosses the pass along the ridge of the mountain, when the air flow passes through the concave part under the ridge from the open area, the air will gather towards the center and accelerate through, making the line prone to icing and affecting the probability of line galloping; it can be seen from the reference Figure 4D that when the line crosses the watershed, the air flow rises from the windward slope and accelerates through the top of the mountain due to the open and unobstructed area, resulting in strong wind, making the line prone to icing and affecting the probability of line galloping; it can be seen from the reference Figure 4D that when the line climbs from a lower altitude area such as a plain, hill, or basin to a higher peak or cliff, the air flow temperature decreases due to the lifting effect, and local strong convection is likely to occur, making the line prone to icing and affecting the probability of line galloping. However, this is only an example, and the present invention can also include a water vapor amplification type galloping area, etc. In the water vapor amplification type galloping area, the transmission line crosses surface waters such as rivers and adjacent lakes. Due to the different thermal properties of land and water, temperature differences and pressure differences will be generated, which is conducive to the formation of a local circulation of land and water winds. Moreover, the small surface friction of the water body is conducive to the formation of strong winds, making the line prone to icing and affecting the probability of line galloping. This classification method is simple and feasible, has a certain rationality, and can objectively and comprehensively reflect the galloping situation of the conductors in this area.

[0047] The specific dancing risk values of the target overhead line under various dancing prediction indicators can be obtained through the monitoring data of the line dancing site, historical data records, and querying the line operation materials. For example, an image collector can be used to collect images of the overhead transmission line to obtain continuous line images; according to the position changes of the line in adjacent line images, the line dancing displacement can be determined; and then based on the line dancing displacement, the amplitude of the dancing amplitude can be determined. Here, the amplitude of the dancing amplitude is the dancing risk value under the "dancing amplitude" indicator. The same applies to others and will not be elaborated here. Moreover, based on the line dancing displacement and the image acquisition frequency, integral calculation can be performed to obtain the dancing acceleration, and then frequency spectrum analysis of the dancing acceleration can be carried out to obtain the dancing risk value of another dancing prediction indicator of the line dancing - the dancing frequency. The temperature and humidity can be collected by using temperature and humidity sensors in the target area where the overhead transmission line is located, and the wind speed and wind direction are also collected by using wind speed and wind direction sensors deployed in the area where the overhead transmission line is located.

[0048] The dancing risk values of the dancing area type and the conductor type, combined with the actual operation materials of the line, are given by expert scoring. For example, experts can score each dancing area according to the probability of the same type of conductor dancing in various types of dancing areas. Or they can score each conductor according to the dancing probability of various types of conductors in the same dancing area. By subtracting the dancing amplitude and dancing frequency obtained from the current sampling from those obtained from the previous sampling, and then dividing them by the dancing amplitude and dancing frequency collected previously, the change rates of the dancing amplitude and the dancing frequency can be obtained respectively.

[0049] The ice coating thickness can be observed by fixing a section of wire with the same specifications parallel to the target overhead transmission line on the tower in the area where the overhead transmission line is located. Or it can also be deduced by collecting the de-icing volume of the target overhead transmission line on-site and the ice coating thickness attached to other objects. Thus, the index values of various dancing prediction indicators can be obtained as the dancing risk values.

[0050] Based on the above various levels, a fuzzy hierarchical evaluation index system for line dancing state based on fuzzy theory can be established by combining the principle of establishing a hierarchical model. The weight information can be determined based on this system. For example, in this evaluation index system, as Figure 3 shown, the top layer from top to bottom is the target layer, which is used to predict the line dancing state; the second layer is the index layer, and its evaluation content is 3 first-level indicators; the third layer is the sub-index layer, and its evaluation content is 10 second-level indicators. Among them, the dancing area type and the conductor type are qualitative indicators, and the rest are quantitative indicators.

[0051] The assessment of the galloping state of overhead transmission lines is a comprehensive judgment with multiple levels and indicators. The weights of each indicator are extremely important parameters, and whether they are determined scientifically and reasonably directly affects the accuracy of the assessment. From the established hierarchical indicator system, it can be seen that to determine the weights of each factor in the indicator layer and sub-indicator layer, 4 priority relationship matrices need to be established, and then the 4 priority relationship matrices are transformed into fuzzy consistent judgment matrices by using the fuzzy analytic hierarchy process. Through the relationship ranking method, the weights of each factor are calculated and determined.

[0052] For example, an evaluation factor set can be established. The evaluation factor set is a set composed of various factors that affect the evaluation object (i.e., line galloping). For example, in the evaluation factor set , the element represents each evaluation factor (i.e., each galloping prediction index), and m represents the number of galloping prediction indexes.

[0053] Then, according to the evaluation factor set, a priority relationship matrix F=(f ij ) m×m can be established. The priority relationship matrix F=(f ij ) m×m represents the relative importance of each factor in each layer of factors. f represents a functional relationship, that is, an element in the priority relationship matrix F. i and j represent a certain element in the m×m matrix, that is, the element in the i-th row and j-th column. When constructing the priority relationship matrix, in order to accurately describe the relative importance degree of any two factors with respect to a certain criterion, this study adopted the nine scales from 0.1 to 0.9 shown in Table 1 below to construct F=(f ij ) m×m . Thus, the priority relationship matrix F=(f ij ) m×m can be transformed into a fuzzy consistent matrix A=(a ij ) m×m . a represents a functional relationship and is also an element in the fuzzy consistent matrix A. In Table 1, r ij represents the membership degree obtained by evaluating the above element u i according to the j-th element in the judgment set. r jiThe meaning is similar to this and will not be elaborated here. The evaluation set V = {Normal, Swing, Low - amplitude galloping, High - amplitude galloping}. "Normal" means that the conductor has no galloping, the operating state is normal, the working performance is stable, and the possibility of line failure is extremely low, and it can operate safely for a long time; "Swing" means that the reliability of some individual state variables of the conductor decreases slightly, there is a slight swinging situation of the line, but the operating state of the conductor is basically stable, it can continue to operate, and the possibility of line failure is low; "Low - amplitude galloping" means that some state variables of the conductor galloping reflect that the line has galloping, the operating state of the conductor is poor, and faults such as phase - to - phase flashover and tripping may occur, and it is necessary to arrange staff for inspection; "High - amplitude galloping" indicates that the overall operating state of the line is poor, the amplitude of the conductor galloping is large, and accidents such as phase - to - phase flashover and tripping are likely to occur. It is necessary to closely monitor the development of its state and carry out relevant processing immediately.

[0054] Table 1

[0055]

[0056] Next, according to the fuzzy consistent matrix, the weight set of evaluation indexes can be established. For the evaluation target, the importance of each factor is different, and the weight can be used to reflect the importance of each evaluation factor. For the fuzzy consistent matrix A=(a ij ) m×m established in the previous step, the corresponding weight information of each factor can be obtained by using the relationship sorting method.

[0057] Specifically in the present invention, the characteristic factors in the index layer reflect the development trend of the line galloping state and have the strongest importance. The environmental factors will change the cross - section force of the line, thus affecting the state of the line galloping, and their importance is slightly less than that of the characteristic factors. Since generally, the time interval between two consecutive samplings is short and the historical data changes generally little, their importance is weak. Based on this, the preference relation matrices F 目标层 、F 特征因素 、F 环境因素 and F 历史数据 can be constructed as follows. Among them, the preference relation matrix F 目标层 characterizes the importance of the index layer relative to the target layer (that is, the risk degree of generating galloping risk). The preference relation matrix F 特征因素 characterizes the importance of each galloping prediction index under the characteristic factors relative to the characteristic factors. The preference relation matrix F 环境因素 characterizes the importance of each galloping prediction index under the environmental factors relative to the environmental factors. The preference relation matrix F 历史数据 characterizes the importance of each galloping prediction index under the historical data relative to the historical data.

[0058] (1).

[0059] (2).

[0060] (3).

[0061] (4).

[0062] The precedence relation matrix F 目标层 , F 特征因素 , F 环境因素 and F 历史数据 can be transformed into the fuzzy consistent matrix A 目标层 , A 特征因素 , A 环境因素 and A 历史数据 :

[0063] (5).

[0064] (6).

[0065] (7).

[0066] (8).

[0067] Thus, the weight information of each factor in the sub-index layer can be calculated, as shown in Table 2 below.

[0068] Table 2 Weight Information of Each Factor

[0069]

[0070] It should be supplemented and explained that the meanings of the above symbols are only used in the above embodiments.

[0071] According to the embodiments of the present invention, after obtaining the galloping risk values and weight information of each galloping prediction index of the target overhead transmission line, the galloping risk values and weight information can be calculated to obtain a calculation result, and the calculation result is compared with a predetermined threshold. In the case where the calculation result is greater than the threshold, galloping risk information indicating that the target overhead transmission line has a galloping risk is generated. Otherwise, galloping risk information indicating that the target overhead transmission line does not have a galloping risk can be generated.

[0072] When generating the galloping risk information indicating the galloping risk of the target overhead transmission line, the meteorological conditions in the target area during the target period can be further predicted to obtain the meteorological prediction information of the target area during the target period, so that the galloping risk of the target overhead transmission line can be further judged based on this meteorological prediction information. The similarities between multiple meteorological factors of the historical meteorological information that has caused the galloping of overhead transmission lines with similar or the same specifications as the target overhead transmission line and multiple meteorological factors of the above meteorological prediction information can be determined. The multiple meteorological factors can include humidity, temperature, wind speed, wind direction, and so on. When at least one of the multiple similarities between the multiple meteorological factors of the historical meteorological information and the multiple meteorological factors of the meteorological prediction information is greater than or equal to the predetermined similarity threshold, it can be determined that the meteorological prediction information meets the predetermined conditions; otherwise, it is determined that the meteorological prediction information does not meet the predetermined conditions. For example, when the similarity between a certain meteorological factor in the historical meteorological information and the corresponding meteorological factor in the meteorological prediction information is greater than or equal to the predetermined similarity threshold, it is determined that the meteorological prediction information meets the predetermined conditions. For example, when the similarity between the humidity information in the historical meteorological information and the humidity information in the meteorological prediction information is greater than or equal to the predetermined similarity threshold, it can be determined that the meteorological prediction information meets the predetermined conditions.

[0073] When the meteorological prediction information meets the predetermined conditions, the environmental factors and the specific structural characteristics of the line can be further combined according to the meteorological prediction information and the parameters of the target overhead transmission line, so as to generate an accurate line galloping warning result. The line galloping warning result can be divided into a warning result indicating that the target overhead transmission line gallops during the target period and a warning result indicating that the target overhead transmission line does not gallop during the target period. The line galloping warning result can be sent to the visual terminal device for display, so that relevant personnel can take relevant measures for the target overhead transmission line according to the line galloping warning result to avoid the galloping of the target overhead transmission line during the target period and ensure the stability of power transmission.

[0074] According to an embodiment of the present invention, by generating galloping risk information based on the weight information and galloping risk value of the target overhead transmission line, it is possible to determine, based on the galloping risk information, that the target overhead transmission line is a line with galloping risk. Then, based on the historical meteorological information of the target area and the information of the target time period, the meteorological prediction information of the target area within the target time period is predicted, so as to determine whether the meteorology in the target area within the target time period is a meteorological condition that is likely to cause galloping of the target overhead line. When the meteorological prediction information meets the predetermined conditions, it can be determined that the meteorological prediction information of the target area within the target time period is likely to cause galloping of the target overhead line. Thus, based on the meteorological prediction information and the parameters of the target overhead transmission line, a relatively accurate early warning of the galloping condition of the target overhead transmission line within the target time period can be further carried out, so as to timely prevent the potential galloping risk of the target overhead transmission line before the target time period arrives and ensure the stable power transmission of the target overhead line.

[0075] According to an embodiment of the present invention, the galloping risk value includes the wind speed information at the location where the target overhead transmission line is located. The above method further includes: using a sensor to collect the initial wind speed information of the target area. According to the height information of the target overhead transmission line and the height information of the sensor, the height difference between the target overhead transmission line and the sensor is determined. According to the height difference, the target wind speed conversion function is determined from the wind speed conversion functions corresponding to Q height difference ranges, where Q is an integer greater than 1. The initial wind speed information is processed using the target wind speed conversion function to obtain the wind speed information.

[0076] According to an embodiment of the present invention, the height information of the target overhead transmission line represents the height of the geometric center of the target overhead transmission line relative to the ground, or may also be the height of the suspension point of the target overhead transmission line relative to the ground. The above sensor may refer to a wind speed and direction sensor, and the height information of the sensor represents the height of the installation position of the sensor relative to the ground. In one embodiment, the sensor may be installed on the ground.

[0077] According to an embodiment of the present invention, an initial wind speed information of a target area can be collected by using a wind speed and direction sensor. Then, according to the height information of the target overhead transmission line and the height information of the sensor, a height difference between the target overhead transmission line and the sensor can be determined. Thereafter, according to the height difference, a target wind speed conversion function can be determined from wind speed conversion functions corresponding to Q height difference ranges. The wind speed conversion function can include a first wind speed conversion function and a second wind speed conversion function. When the height difference range is less than a predetermined value (such as 90 m, 100 m, 110 m, etc.), the first wind speed conversion function can be used to convert the initial wind speed information into wind speed information. When the height difference range is greater than or equal to the predetermined value, the second wind speed conversion function can be used to convert the initial wind speed information into wind speed information. The wind speed information herein is the wind speed dancing risk value in the above dancing prediction index.

[0078] For example, the first wind speed conversion function is shown in the following formula (9):

[0079] (9).

[0080] The second wind speed conversion function is shown in the following formula (10):

[0081] (10).

[0082] In formulas (9) and (10), v is the wind speed information; v0 is the initial wind speed information; H is the height information of the target overhead transmission line; H0 is the height information of the sensor; Z0 is a predetermined constant corresponding to the ground condition, generally taking a value of 0.01 - 0.2, taking a value of 0.03 when the target overhead transmission line is in an open area, and taking a value of 0.003 when the target overhead transmission line is on the sea surface; the predetermined exponent a takes a value of 1 / 6.9 when the target overhead transmission line is in an open area, and takes a value of 1 / 9.3 when the target overhead transmission line is on the sea surface. It should be noted that the symbol meanings here are only used to explain the content of formulas (9) and (10). Similarly, the symbol meanings in other formulas below are only used to explain the content of the corresponding formulas, and will not be elaborated one by one below.

[0083] According to an embodiment of the present invention, due to differences in the position of the transmission line, the height of the air flow, and the wind speed distribution, and as the height changes, the change of the wind speed usually shows a non - linear distribution. Especially in areas with complex terrain, the wind speed performance at different heights may be different. Therefore, by determining a target wind speed conversion function suitable for the height difference from multiple wind speed conversion functions according to the height difference between the sensor and the target overhead transmission line to process the initial wind speed information, accurate wind speed information can be obtained, thereby improving the accuracy of the dancing risk information.

[0084] According to an embodiment of the present invention, based on M weight information and M galloping risk values of a target overhead transmission line, galloping risk information of the target overhead transmission line is generated, including: determining the m-th target weight information according to the m-th weight information, the m-th galloping risk value, M weight information and M galloping risk values. According to the index evaluation standard, J first galloping prediction indexes and K second galloping prediction indexes are determined from M galloping prediction indexes. The evaluation criteria between the first galloping prediction indexes and the second galloping prediction indexes are different, and J and K are positive integers. The galloping risk value of the j-th first galloping prediction index among the J first galloping prediction indexes is processed by using a first normalization function to obtain the j-th first index value, where j is a positive integer less than or equal to J. The galloping risk value of the k-th second galloping prediction index among the K second galloping prediction indexes is processed by using a second normalization function to obtain the k-th second index value, where k is a positive integer less than or equal to K. And according to the J first index values and the K second index values, galloping risk information of the target overhead transmission line is generated.

[0085] According to an embodiment of the present invention, the weight information in Table 2 above is fixed and will not change due to different states (such as environmental state and conductor state, etc.) and evaluation factors. However, in the conductor galloping evaluation index system, when some factors (such as the change amount of galloping amplitude) deviate seriously from the normal value, it indicates that the conductor galloping develops rapidly and needs to be processed immediately. However, in the evaluation model of the above weight information, due to the small weight information of this factor, the generated galloping risk information indicating that there is no galloping risk on the line may be obtained, making it difficult for the galloping risk information to truly reflect the real change state of the conductor galloping. Therefore, it is necessary to further process the weight information.

[0086] For example, the weight information can be processed by the following formula (11) to obtain the target weight information:

[0087] (11).

[0088] In formula (11), x i is the galloping risk value of the i-th galloping prediction index, m is the number of galloping prediction indexes, w i is the target weight information of the i-th galloping prediction index, w 0 i is the weight information of the i-th galloping prediction index, a is a predetermined exponent, represents the value obtained by accumulating the results of multiplying each value calculated by multiplying the first galloping risk value and the first weight information. The value of a reflects the requirement for balance and will largely affect the final evaluation result. a = 0.2 can be applicable to general engineering situations.

[0089] Through the above formula (11), the role of extreme values can be highlighted. When extreme values appear in the galloping risk value, the final result calculated based on the galloping risk value and the target weight information will quickly approach zero to reflect this situation, so that the generated galloping risk information can be more accurate. Considering that when comprehensively evaluating and calculating the weight information of the percentage assessment standard, it will result in large-denominator data, bringing a large rounding error. Considering the convenience of calculation and the accuracy requirement, the percentage assessment value is converted into a percentage here.

[0090] According to an embodiment of the present invention, in the above multi-index fuzzy comprehensive evaluation, since the dimensions of each sub-index are different and the orders of magnitude of the sub-index values are also different, it is necessary to normalize the galloping risk value. The galloping risk value of the galloping prediction index can be normalized according to the optimal index value and the limit index value of the galloping prediction index. Among them, the optimal index value and the limit index value can be determined in advance.

[0091] The first galloping prediction index can be an index of the type that the smaller the value, the better (that is, the smaller the value, the lower the galloping risk). The first normalization function is shown in formula (12):

[0092] (12).

[0093] The second galloping prediction index can be an index of the type that the larger the value, the better (that is, the larger the value, the lower the galloping risk). The second normalization function is shown in formula (12):

[0094] (13).

[0095] In formulas (12) and (13), x i is the i-th index value, C0 is the optimal index value of the i-th galloping prediction index, C 01 is the limit index value of the i-th galloping prediction index, Ci is the i-th galloping risk value, and k is the influence degree of parameter change on the galloping state, which can be taken as 1. For example, the above formula is only used to process quantitative galloping prediction indexes. The first galloping prediction risk index and the second galloping risk prediction index are quantitative galloping prediction indexes. Among the above-mentioned quantitative galloping prediction indexes, except that temperature and galloping frequency are indexes of the type that the larger the value, the better, the rest are indexes of the type that the smaller the value, the better.

[0096] Taking the galloping amplitude as an example, the limit index value of the galloping amplitude can generally be about 5 m, and the most ideal situation of the line operation state is that there is no galloping, that is, the optimal index value of the galloping amplitude is 0 m. Thus, the following normalization formula (14) can be obtained:

[0097] (14).

[0098] Similarly, the normalization formulas for the other seven quantitative indicators can be derived, as shown in Table 3. Thus, the dancing risk values of each dancing prediction indicator can be normalized using the respective normalization formulas shown in Table 3, thereby obtaining the indicator values of each dancing prediction indicator.

[0099] Table 3

[0100]

[0101] For qualitative indicators, this study established an expert scoring table for the dancing area type and conductor type, and quantified the dancing risk values of the dancing area type and conductor type into numbers between 0 and 1 through the scoring table. The smaller the score in the scoring table, the better the indicator performance. The expert scores for the dancing area type and conductor type are shown in Tables 4 and 5:

[0102] Table 4

[0103]

[0104] Table 5

[0105]

[0106] According to the embodiments of the present invention, by determining the target weight information based on the weight information, dancing risk value, total weight information, and total dancing risk value, the dancing risk information can more accurately reflect the potential dancing risk of the target overhead transmission line. On this basis, different normalization functions are used to normalize the dancing risk values for different evaluation criteria, so that the dancing risk values for different evaluation criteria can be accurately unified to the same dimension. Then, based on the first indicator value and the second indicator value obtained after normalization and the target weight information, accurate dancing risk information is obtained, improving the accuracy of determining the dancing risk of the target overhead transmission line.

[0107] According to the embodiments of the present invention, the dancing of overhead conductors is closely related to different external meteorological conditions and the structural parameters of the line itself. However, the existing physical models for overhead conductor dancing are not accurate enough, and some of the parameters in these models are difficult to obtain in real time through measurement on actual lines. Merely using physical models for early warning of overhead conductor dancing has low accuracy and practicality.

[0108] On this basis, the inventor found that the early warning of galloping of overhead conductors can be attributed to a classification prediction problem under supervised learning. For a classification prediction problem, the basic goal of statistical learning is to build a learner with strong generalization ability based on the observed data. However, in most cases, since the accuracy of the learner is greatly affected by domain knowledge, training data and their distributions, especially for those prediction problems whose physical nature has not been fully understood, such as conductor galloping due to icing, it is difficult to directly construct a learner with high accuracy to achieve the prediction and early warning of a specific line or a specific line section at one time. However, the internal cause of conductor galloping is the line structure parameters. When the internal cause remains relatively unchanged, the change of things is determined by the external cause. Therefore, a model can be constructed first to predict the change of external meteorological conditions, and then to predict whether a specific line (such as a certain conductor section) will gallop after determining that the meteorological conditions reach the galloping condition.

[0109] It is possible to predict the meteorological prediction information of the target area within the target time period, and then use a classifier to process the meteorological prediction information to obtain meteorological risk information, so that the galloping risk status of the target overhead transmission line can be determined according to the meteorological risk information. For example, the target area includes I sub-areas. According to the information of the target time period and the historical meteorological information of the target area, the meteorological prediction information of the target area within the target time period is predicted, including: using a first predetermined model to process the information of the target time period and the i-th historical meteorological information of the i-th sub-area to obtain the i-th meteorological prediction information, where I is an integer greater than 1 and i is a positive integer less than or equal to I. The above method further includes: using a second predetermined model to process the i-th meteorological prediction information to determine the i-th meteorological risk information, where the i-th meteorological risk information characterizes the risk probability of galloping of the target overhead transmission line under the meteorological conditions of the i-th meteorological prediction information. The target meteorological risk information is determined from the I meteorological risk information, and the target meteorological risk information characterizes that there is a galloping risk of the target overhead transmission line under the meteorological conditions corresponding to the target meteorological risk information. In response to detecting that the number of target meteorological risk information in the I meteorological risk information is greater than or equal to a predetermined number, it is determined that the meteorological prediction information of the target area meets a predetermined condition (i.e., the above-mentioned meteorological easy-galloping condition).

[0110] For example, the first predetermined model can be constructed based on SVM (Support Vector Machine) or GRNN (Generalized Regression Neural Network). The Generalized Regression Neural Network is composed of a radial basis neural network with an additional linear layer. It is based on mathematical statistics and has strong capabilities in solving nonlinear problems. Compared with the Back Propagation Neural Network (BPNN), GRNN can also fit any nonlinear continuous function, and its prediction performance may be better than that of BPNN; GRNN has a fast training speed and can be used for real-time data processing; GRNN requires fewer training samples, overcoming the problem of insufficient data volume; GRNN has a simpler structure; and there is only one parameter to be optimized in GRNN, namely the smoothing parameter. Therefore, GRNN is selected to construct the first predetermined model.

[0111] The fast training speed of the GRNN network can be fully utilized, and a method of dynamically dividing the training set can be adopted. That is, when predicting the meteorological elements in the target time period, the meteorological element data in a predetermined time length (such as 10 days) before the target time period are used as the training set of the network. Predict the meteorological elements and analyze the prediction effect of the GRNN network.

[0112] For example, the first predetermined model can be obtained by training the first initial model based on the meteorological information and information in different historical time periods.

[0113] Specifically, taking the target time period as a certain moment t (which can be the starting moment of the target time period) as an example, considering the mutual influence among air pressure, wind direction, wind speed, temperature, and humidity, the input of the network will include all five factors, and then the air pressure, wind direction, wind speed, temperature, and humidity are predicted separately. Since the prediction time span is small, valuable information is also contained in the meteorological data at adjacent moments on adjacent dates. Therefore, the input of the network is constructed according to the following rules: Assuming that the air pressure, wind direction, wind speed, temperature, or humidity at moment t of a certain day is predicted, then the air pressure, wind direction, wind speed, temperature, and humidity at moment t-1 of the same day are required, as well as the air pressure, wind direction, wind speed, temperature, and humidity at moments t-2, t-1, t, t+1, and t+2 of the previous day, and the air pressure, wind direction, wind speed, temperature, and humidity at moments t-2, t-1, t, t+1, and t+2 of the day before the previous day. Therefore, during the training process, the output of the first predetermined model can be input as:

[0114] (15).

[0115] Among them, P t-1 、Dt-1 , S t-1 , T t-1 and H t-1 respectively represent the air pressure, wind direction, wind speed, temperature and humidity at the t-1 moment of the same day. P 1 t-2 , D 1 t-2 , S 1 t-2 , T 1 t-2 and H 1 t-2 respectively represent the air pressure, wind direction, wind speed, temperature and humidity at the t-2 moment of the previous day. P 1 t-1 , D 1 t-1 , S 1 t-1 , T 1 t-1 and H 1 t-1 respectively represent the air pressure, wind direction, wind speed, temperature and humidity at the t-1 moment of the previous day. P 1 t , D 1 t , S 1 t , T 1 t and H 1 t respectively represent the air pressure, wind direction, wind speed, temperature and humidity at the t moment of the previous day. P 1 t+1 , D 1 t+1 , S 1 t+1 , T 1 t+1 and H 1 t+1 respectively represent the air pressure, wind direction, wind speed, temperature and humidity at the t+1 moment of the previous day. P 1 t+2 , D 1 t+2 , S 1 t+2 , T 1 t+2 and H 1 t+2 respectively represent the air pressure, wind direction, wind speed, temperature and humidity at the t+2 moment of the previous day. P 2 t-2 , D 2 t-2 , S 2 t-2 , T2 t-2 and H 2 t-2 respectively represent the air pressure, wind direction, wind speed, temperature and humidity at the t-2 moment two days ago, P 2 t -1 , D 2 t-1 , S 2 t-1 , T 2 t-1 and H 2 t-1 respectively represent the air pressure, wind direction, wind speed, temperature and humidity at the t-1 moment two days ago, P 2 t , D 2 t , S 2 t , T 2 t and H 2 t respectively represent the air pressure, wind direction, wind speed, temperature and humidity at the t moment two days ago, P 2 t+1 , D 2 t+1 , S 2 t+1 , T 2 t+1 and H 2 t+1 respectively represent the air pressure, wind direction, wind speed, temperature and humidity at the t+1 moment two days ago, P 2 t+2 , D 2 t+2 , S 2 t+2 , T 2 t+2 and H 2 t+2 respectively represent the air pressure, wind direction, wind speed, temperature and humidity at the t+2 moment two days ago.

[0116] The output of the first predetermined model can be:

[0117] (16).

[0118] Among them, P, D, S, T and H respectively represent the air pressure, wind direction, wind speed, temperature and humidity predicted at the t moment.

[0119] Based on this, for variable meteorological conditions, a dynamic prediction model can be established, that is, every time a meteorological prediction is made, the network is trained once. Thus, at each prediction, the optimal parameters of the first predetermined model are only related to the current prediction and are not fixed, which can ensure better prediction accuracy. In this way, it is possible to avoid the situation where, at different times, due to large changes in meteorological conditions, the degree of influence of meteorology on the galloping of overhead transmission lines varies greatly. By timely training the first initial model with new meteorological information, the accuracy of galloping early warning can be improved, thereby ensuring the safety of overhead transmission lines.

[0120] According to an embodiment of the present invention, the second predetermined model can be constructed based on the SVM algorithm. The second predetermined model can be obtained by pre-training a second initial model with sample meteorological information and risk label information corresponding to the sample meteorological information. The risk label information can be obtained by manually marking the sample meteorological information according to the risk probability of the overhead transmission line galloping under the meteorological conditions of the sample meteorological information, and the present invention does not limit this here.

[0121] According to an embodiment of the present invention, by using the first predetermined model to perform meteorological predictions for each sub-region within the target region, and then using the second predetermined model to respectively perform risk assessments on the meteorological prediction information of each sub-region, the meteorological risk information of each sub-region within the target region can be obtained. Since the meteorology of each sub-region will affect each other to a certain extent, the influence of the meteorology of the target region on the galloping of the target overhead transmission line during the target time period can be comprehensively evaluated based on the meteorological risk information of each sub-region, so as to accurately determine whether the meteorological prediction information of the target region meets the predetermined conditions.

[0122] According to an embodiment of the present invention, using the second predetermined model to process the i-th meteorological prediction information to determine the i-th meteorological risk information includes: obtaining the phase information of the target overhead transmission line. And using the second predetermined model to process the i-th meteorological prediction information and the phase information to determine the i-th meteorological risk information.

[0123] According to an embodiment of the present invention, since the target overhead transmission line is one or more of the three-phase conductors, when the target overhead transmission line gallops, it may entangle with other conductors, resulting in an interphase short circuit, that is, an electrical fault, affecting the stability of the target overhead transmission line. There are differences in the arrangement positions on the tower and the line directions among the conductors of different phases. Thus, based on the sample phase information, sample meteorological information, and risk label information of the overhead transmission conductors, the second initial model can be trained to obtain the second predetermined model, so that the second predetermined model can be used to process the meteorological prediction information and the phase information to determine accurate meteorological risk information.

[0124] According to an embodiment of the present invention, the second predetermined model is trained using sample meteorological information and label information corresponding to the sample meteorological information. The label information is obtained by the following method: Under the meteorological conditions of the sample meteorological information, image acquisition is performed on the overhead three-phase conductors to obtain N consecutive conductor images, where N is an integer greater than 1. According to the images of each phase of the three-phase conductors in the N conductor images, the N conductor images are segmented to obtain N conductor images of each phase of the conductors. Binary processing is performed on the N conductor images of each phase of the conductors to obtain N binary images of each phase of the conductors. According to the largest closed image in area among the N binary images of each phase of the conductors, feature extraction is performed on each of the N binary images of each phase of the conductors to obtain N conductor features of each phase of the conductors. For each phase of the conductors, according to the displacement change of the nth conductor feature relative to the 1st conductor feature, the (n - 1)th displacement change information is obtained, where n is a positive integer less than or equal to N. According to the N - 1 displacement change information of each phase of the conductors, label information corresponding to the sample meteorological information (i.e., the above-mentioned risk label information) is generated.

[0125] According to an embodiment of the present invention, an image collector can be used to perform image acquisition on the overhead three-phase conductors to obtain N consecutive conductor images. Then, the foreground (i.e., the conductors) and the background (other parts except the conductors) in the images of each phase of the conductors can be respectively labeled. Then, using the trained image semantic segmentation algorithm, the three-phase conductors are respectively segmented to obtain the images of each phase of the conductors.

[0126] Subsequently, binary processing is performed on each frame of the image, and the largest closed region in the binary image is retained, so as to obtain complete and continuous conductor features. For each phase of the conductors, according to the displacement change of the geometric center of the nth conductor feature relative to the geometric center of the 1st conductor feature, the (n - 1)th displacement change information can be obtained. Thus, according to the phase of the conductor and the displacement change information corresponding to the conductor, label information corresponding to the sample meteorological information can be constructed. In this case, using the sample meteorological information and the risk label information to train the initial model to obtain the trained second predetermined model, the second predetermined model can be used to process the meteorological prediction information and the phase information to obtain accurate meteorological risk information.

[0127] According to an embodiment of the present invention, the meteorological prediction information includes the minimum temperature information, relative humidity information, maximum wind speed information, and wind direction information within a target time period. The parameters of the target overhead transmission line include the axial information of the conductors of the target overhead transmission line. According to the meteorological prediction information and the parameters of the target overhead transmission line, a line galloping warning result of the target overhead transmission line is generated, including: determining the included angle information between the wind direction information and the conductor axial information. Using a third predetermined model to process the minimum temperature information, relative humidity information, maximum wind speed information, and included angle information, and outputting the line galloping level information of the target overhead transmission line. According to the line galloping level information, a line galloping warning result is generated.

[0128] According to an embodiment of the present invention, since whether the line gallops after reaching the easy-galloping meteorological conditions is also closely related to the structure of the conductor, the meteorological prediction information and the target overhead transmission line information can be combined to generate a line galloping warning result. For example, the minimum temperature information, relative humidity information, maximum wind speed information, and wind direction information in the meteorological prediction information can be obtained, and then the included angle information can be calculated based on the wind direction information and the conductor axial information, so that the minimum temperature information, relative humidity information, maximum wind speed information, and included angle information can be processed using a third predetermined model to obtain the line galloping level information. The third predetermined model can be constructed based on the AdaBoost (Adaptive Boosting) algorithm. For example, the minimum temperature information, relative humidity information, maximum wind speed information, sample included angle information, and grade label information in the historical meteorological information can be used to train the third initial model to obtain the trained third predetermined model. The grade label information can be obtained by manually marking the historical meteorological information according to the influence of the minimum temperature information, relative humidity information, maximum wind speed information, and sample included angle information on the galloping of the overhead transmission line, which is not limited in the present invention.

[0129] For example, the meteorological prediction information input to the third predetermined model can be expressed as . Wherein, is the minimum temperature information in the meteorological forecast information, is the relative humidity information in the meteorological forecast information, is the maximum wind speed information in the meteorological forecast information, is the included angle information corresponding to the meteorological forecast information.

[0130] The confidence level can be calculated through the following formula (17): Obtained from the meteorological forecast input feature vector , the confidence level can be calculated using formula (17) :

[0131] (17).

[0132] In formula (17), f is the galloping prediction result, C t (e) is the classification error rate, t is the number of the t-th training, and a t is the coefficient.

[0133] , a larger positive (negative) boundary indicates a higher confidence in predicting galloping on this line (not occurring), and a smaller boundary indicates a lower confidence in the prediction result.

[0134] Finally, according to the value of the galloping prediction result, the risk level of the transmission line galloping warning can be set as shown in Table 6.

[0135] For the I and II level galloping warnings with a confidence level greater than 40% in the output result of the transmission line galloping warning, key prevention and control should be carried out, inspection and monitoring should be strengthened, and dispatching emergency plans should be made; at the same time, for the III level galloping warning with a relatively small confidence level, one should not be negligent, and full preparations should be made to minimize the damage caused by the transmission line galloping as much as possible.

[0136] Table 6

[0137]

[0138] In addition, the present invention can also combine parameters such as the conductor structure, cross-section, and span to predict the galloping level information of the line. The method is similar to the above and will not be elaborated here.

[0139] According to the embodiment of the present invention, by using the lowest temperature information, relative humidity information, wind speed information, and the included angle information between the wind direction and the conductor axis direction, the galloping condition of the target overhead transmission line in the target time period can be accurately warned by combining the meteorological information and the conductor structure information.

[0140] Figure 5 The flowchart of the transmission line galloping warning method according to another embodiment of the present invention is shown.

[0141] In operation S510, in response to receiving a galloping warning instruction for a target overhead transmission line in a target time period located in a target area, galloping risk information of the target overhead transmission line is generated according to M weight information and M galloping risk values of the target overhead transmission line.

[0142] In operation S520, in response to detecting that the galloping risk information indicates that the target overhead transmission line has a galloping risk, the information of the target time period and the i-th historical meteorological information of the i-th sub-region are processed by using a first predetermined model to obtain the i-th meteorological prediction information.

[0143] In operation S530, the i-th meteorological prediction information is processed by using a second predetermined model to determine the i-th meteorological risk information.

[0144] In operation S540, target meteorological risk information is determined from I pieces of meteorological risk information.

[0145] In operation S550, in response to detecting that the number of target meteorological risk information among the I pieces of meteorological risk information is greater than or equal to a predetermined number, the included angle information between the wind direction information and the conductor axial information is determined.

[0146] In operation S560, the included angle information between the wind direction information and the conductor axial information is determined.

[0147] In operation S570, the minimum temperature information, relative humidity information, maximum wind speed information, and included angle information are processed using a third predetermined model to output the line galloping level information of the target overhead transmission line.

[0148] In operation S580, a line galloping warning result is generated according to the line galloping level information.

[0149] Based on the above transmission line galloping warning method, the present invention also provides a transmission line galloping warning system. The following will be combined with Figure 6 to describe this system in detail.

[0150] Figure 6 The structural block diagram of the transmission line galloping warning system according to an embodiment of the present invention is shown.

[0151] As Figure 6 shown, the transmission line galloping warning system 600 of this embodiment includes a server 610 and a visual terminal device 620. The server 610 includes a first generation module 611, a prediction module 612, and a second generation module 613. The visual terminal device 620 includes a display module 621.

[0152] The first generation module 611 is configured to, in response to receiving a galloping warning instruction for a target overhead transmission line in a target area during a target period, generate galloping risk information of the target overhead transmission line according to M weight information and M galloping risk values of the target overhead transmission line; the m-th weight information characterizes the importance degree of the m-th galloping prediction index relative to the other M - 1 galloping prediction indexes when predicting the galloping risk of the target overhead transmission line according to the m-th galloping prediction index among the M galloping prediction indexes; the m-th galloping risk value characterizes the risk degree of the galloping of the target overhead transmission line when the m-th galloping prediction index is used as an evaluation criterion, M is an integer greater than 1, and m is a positive integer less than or equal to M. In one embodiment, the first generation module 611 can be used to execute the operation S210 described above, which will not be elaborated here.

[0153] The prediction module 612 is configured to, in response to detecting that the dancing risk information indicates that there is a dancing risk for the target overhead transmission line, predict the meteorological prediction information of the target area within the target time period according to the information of the target time period and the historical meteorological information of the target area. In one embodiment, the prediction module 612 may be configured to perform the operation S220 described above, which will not be elaborated herein.

[0154] The second generation module 613 is configured to, in response to detecting that the meteorological prediction information meets a predetermined condition, generate a line dancing warning result of the target overhead transmission line according to the meteorological prediction information and the parameters of the target overhead transmission line. In one embodiment, the second generation module 613 may be configured to perform the operation S230 described above, which will not be elaborated herein.

[0155] The display module 621 is configured to receive the line dancing warning result and display the line dancing warning result through the visualization interface of the visual terminal device 620.

[0156] According to an embodiment of the present invention, the prediction module 612 includes a first processing sub-module. The server 610 further includes a second processing sub-module, a first determination sub-module, and a first generation sub-module. Among them, the first processing sub-module is configured to process the information of the target time period and the i-th historical meteorological information of the i-th sub-region by using a first predetermined model to obtain the i-th meteorological prediction information, where I is an integer greater than 1, and i is a positive integer less than or equal to I; the second processing sub-module is configured to process the i-th meteorological prediction information by using a second predetermined model to determine the i-th meteorological risk information, and the i-th meteorological risk information represents the risk probability of the target overhead transmission line dancing under the meteorological conditions of the i-th meteorological prediction information; the first determination sub-module is configured to determine the target meteorological risk information from the I meteorological risk information, and the target meteorological risk information represents that there is a dancing risk for the target overhead transmission line under the meteorological conditions of the meteorological prediction information corresponding to the target meteorological risk information; the first generation sub-module is configured to, in response to detecting that the number of the target meteorological risk information in the I meteorological risk information is greater than or equal to a predetermined number, generate dancing risk information indicating that there is a dancing risk for the target overhead transmission line.

[0157] According to an embodiment of the present invention, the determination sub-module further includes an acquisition unit and a determination unit. Among them, the acquisition unit is configured to acquire the phase information of the target overhead transmission line; the determination unit is configured to process the i-th meteorological prediction information and the phase information by using a second predetermined model to determine the i-th meteorological risk information.

[0158] According to an embodiment of the present invention, the server 610 further includes a collection module, a segmentation module, a binarization module, an extraction module, an obtaining module, and a third generation module. Among them, the collection module is used to collect images of the overhead three-phase conductors under the meteorological conditions of the sample meteorological information, obtaining N consecutive frame images of the conductors, where N is an integer greater than 1; the segmentation module is used to segment the N frame images of the conductors according to the images of each phase of the three-phase conductors in the N frame images of the conductors, obtaining N frame images of each phase of the conductors; the binarization module is used to perform binarization processing on the N frame images of each phase of the conductors, obtaining N binarized images of each phase of the conductors; the extraction module is used to perform feature extraction on each of the N binarized images of each phase of the conductors according to the largest closed image in area among the N binarized images of each phase of the conductors, obtaining N frame conductor features of each phase of the conductors; the obtaining module is used to, for each phase of the conductors, obtain the (n - 1)-th displacement change information according to the displacement change of the n-th conductor feature relative to the 1st conductor feature, where n is a positive integer less than or equal to N; the third generation module is used to generate label information corresponding to the sample meteorological information according to the N - 1 displacement change information of each phase of the conductors.

[0159] According to an embodiment of the present invention, the second generation module 613 further includes a second determination sub-module, a third processing sub-module, and a second generation sub-module. Among them, the second determination sub-module is used to determine the included angle information between the wind direction information and the conductor axial information; the third processing sub-module is used to process the lowest temperature information, relative humidity information, maximum wind speed information, and included angle information by using a third predetermined model, and output the line galloping level information of the target overhead transmission line; the second generation sub-module is used to generate a line galloping warning result according to the line galloping level information.

[0160] According to an embodiment of the present invention, the first generation module 611 includes a third determination sub-module, a division sub-module, a fourth processing sub-module, a fifth processing sub-module, and a third generation sub-module. Among them, the third determination sub-module is configured to determine the m-th target weight information according to the m-th weight information, the m-th galloping risk value, the M weight information, and the M galloping risk values; the division sub-module is configured to divide the M galloping prediction indicators into J first galloping prediction indicators and K second galloping prediction indicators according to the index evaluation criteria, and the evaluation criteria between the first galloping prediction indicators and the second galloping prediction indicators are different, where J and K are positive integers, and J + K = M; the fourth processing sub-module is configured to process the j-th target weight information and the j-th galloping risk value of the j-th first galloping prediction indicator among the J first galloping prediction indicators by using a first normalization function to obtain the j-th first index value, where j is a positive integer less than or equal to J; the fifth processing sub-module is configured to process the k-th target weight information and the k-th galloping risk value of the k-th second galloping prediction indicator among the K second galloping prediction indicators by using a second normalization function to obtain the k-th second index value, where k is a positive integer less than or equal to K; the third generation sub-module is configured to generate the galloping risk information of the target overhead transmission line according to the J first index values and the K second index values.

[0161] According to an embodiment of the present invention, the server 610 further includes a collection module, a first determination module, a second determination module, and a processing module. Among them, the collection module is configured to collect the initial wind speed information of the target area by using a sensor; the first determination module is configured to determine the height difference between the target overhead transmission line and the sensor according to the height information of the target overhead transmission line and the height information of the sensor; the second determination module is configured to determine the target wind speed conversion function from the wind speed conversion functions corresponding to Q height difference ranges according to the height difference, where Q is an integer greater than 1; the processing module is configured to process the initial wind speed information by using the target wind speed conversion function to obtain the wind speed information.

[0162] According to an embodiment of the present invention, any plurality of modules among the first generation module 611, the prediction module 612, and the second generation module 613 may be combined and implemented in one module, or any one of them may be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules may be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present invention, at least one of the first generation module 611, the prediction module 612, and the second generation module 613 may be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on chip, a system on substrate, a system on package, an application specific integrated circuit (ASIC), or may be implemented by any other reasonable means such as hardware or firmware through circuit integration or packaging, or may be implemented in any one of the three implementation manners of software, hardware, and firmware, or in any suitable combination of several of them. Alternatively, at least one of the first generation module 611, the prediction module 612, and the second generation module 613 may be at least partially implemented as a computer program module, and when the computer program module is run, it may execute corresponding functions.

[0163] Figure 7 The block diagram of an electronic device suitable for implementing the transmission line galloping warning method according to an embodiment of the present invention is shown.

[0164] As Figure 7 shown, the electronic device 700 according to an embodiment of the present invention includes a processor 701, which can perform various appropriate actions and processes according to a program stored in a read only memory (ROM) 702 or a program loaded from a storage section 708 into a random access memory (RAM) 703. The processor 701 may include, for example, a general microprocessor (such as a CPU), an instruction set processor, and / or a related chipset, and / or a dedicated microprocessor (such as an application specific integrated circuit (ASIC)), etc. The processor 701 may also include on-board memory for caching purposes. The processor 701 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0165] In the RAM 703, various programs and data required for the operation of the electronic device 700 are stored. The processor 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. The processor 701 performs various operations of the method flow according to the embodiments of the present invention by executing the programs in the ROM 702 and / or the RAM 703. It should be noted that the programs may also be stored in one or more memories other than the ROM 702 and the RAM 703. The processor 701 may also perform various operations of the method flow according to the embodiments of the present invention by executing the programs stored in the one or more memories.

[0166] According to an embodiment of the present invention, the electronic device 700 may further include an input / output (I / O) interface 705, and the input / output (I / O) interface 705 is also connected to the bus 704. The electronic device 700 may further include one or more of the following components connected to the input / output (I / O) interface 705: an input portion 706 including a keyboard, a mouse, etc.; an output portion 707 including, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage portion 708 including a hard disk, etc.; and a communication portion 709 including a network interface card such as a LAN card, a modem, etc. The communication portion 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the input / output (I / O) interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 710 as needed so that a computer program read from it can be installed into the storage portion 708 as needed.

[0167] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist separately without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the one or more programs are executed, the method according to the embodiments of the present invention is implemented.

[0168] According to an embodiment of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, it may include but is not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In the present invention, the computer-readable storage medium may be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present invention, the computer-readable storage medium may include the above-described ROM 702 and / or RAM 703 and / or one or more memories other than ROM 702 and RAM 703.

[0169] An embodiment of the present invention further includes a computer program product, which includes a computer program that contains program code for executing the method shown in the flowchart. When the computer program product runs in a computer system, the program code is used to enable the computer system to implement the transmission line galloping warning method provided by the embodiment of the present invention.

[0170] When the computer program is executed by the processor 701, it executes the above functions defined in the system / apparatus of the embodiment of the present invention. According to an embodiment of the present invention, the above-described systems, apparatuses, modules, units, etc. can be implemented by computer program modules.

[0171] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices and magnetic storage devices. In another embodiment, the computer program may also be transmitted and distributed in the form of a signal on a network medium, and is downloaded and installed through the communication part 709, and / or installed from the removable medium 711. The program code contained in the computer program can be transmitted by any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0172] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 709, and / or installed from the removable medium 711. When the computer program is executed by the processor 701, it executes the above functions defined in the system of the embodiment of the present invention. According to an embodiment of the present invention, the above-described systems, devices, apparatuses, modules, units, etc. can be implemented by computer program modules.

[0173] In accordance with embodiments of the present invention, program code for executing the computer programs provided by the embodiments of the present invention may be written in any combination of one or more programming languages. Specifically, these computing programs may be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages include, but are not limited to, such as Java, C++, Python, the "C" language, or similar programming languages. The program code may be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or it may be connected to an external computing device (e.g., by connecting through the Internet using an Internet service provider).

[0174] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, as well as combinations of blocks in the block diagram or flowchart, may be implemented by a dedicated hardware-based system for performing the specified functions or operations, or by a combination of dedicated hardware and computer instructions.

[0175] Those skilled in the art can understand that the features described in the various embodiments of the present invention can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in the present invention. In particular, without departing from the spirit and teachings of the present invention, the features described in the various embodiments of the present invention can be combined and / or combined in various ways. All such combinations and / or combinations fall within the scope of the present invention.

[0176] The above describes the embodiments of the present invention. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present invention. Although the embodiments are described separately above, this does not mean that the measures in each embodiment cannot be used advantageously in combination. Without departing from the scope of the present invention, those skilled in the art can make various substitutions and modifications, and all such substitutions and modifications should fall within the scope of the present invention.

Claims

1. A transmission line galloping early warning method, characterized in that: include: In response to receiving a galloping warning instruction for a target overhead transmission line located in a target area during a target period, galloping risk information of the target overhead transmission line is generated according to M weight information and M galloping risk values ​​of the target overhead transmission line; the mth weight information represents the importance of the mth galloping prediction index relative to other M-1 galloping prediction indexes when the galloping risk of the target overhead transmission line is predicted according to the mth galloping prediction index among the M galloping prediction indexes; the mth galloping risk value represents the risk degree of the galloping of the target overhead transmission line when the mth galloping prediction index is used as an evaluation standard, M is an integer greater than 1, and m is a positive integer less than or equal to M; In response to detecting that the galloping risk information indicates that the target overhead transmission line has a galloping risk, forecasting weather forecast information of the target area within the target period based on information of the target period and historical weather information of the target area; In response to detecting that the weather forecast information satisfies a predetermined condition, generating a line galloping warning result of the target overhead transmission line according to the weather forecast information and the parameters of the target overhead transmission line; The target area includes I sub-areas; The step of predicting the weather forecast information of the target area within the target period according to the information of the target period and the historical weather information of the target area comprises: using a first predetermined model to process the information of the target period and the i-th historical weather information of the i-th sub-area to obtain the i-th weather forecast information, where I is an integer greater than 1 and i is a positive integer less than or equal to 1; The method further includes: using a second predetermined model to process the i-th meteorological forecast information to determine i-th meteorological risk information, wherein the i-th meteorological risk information represents a risk probability of the target overhead transmission line galloping under the meteorological conditions of the i-th meteorological forecast information; Determine target meteorological risk information from I meteorological risk information, wherein the target meteorological risk information indicates that the target overhead transmission line has a risk of galloping under the meteorological conditions of the meteorological forecast information corresponding to the target meteorological risk information; In response to detecting that the number of target meteorological risk information in the I meteorological risk information is greater than or equal to a predetermined number, it is determined that the meteorological forecast information of the target area meets the predetermined condition.

2. The method according to claim 1, characterized in that The step of processing the i-th meteorological forecast information by using the second predetermined model to determine the i-th meteorological risk information includes: Acquiring phase information of the target overhead transmission line; and The i-th meteorological forecast information and the phase information are processed using the second predetermined model to determine the i-th meteorological risk information.

3. The method according to claim 2, characterized in that The second predetermined model is trained using sample meteorological information and label information corresponding to the sample meteorological information; The label information is obtained by the following method: Under the meteorological conditions of the sample meteorological information, an image of the overhead three-phase conductor is collected to obtain N consecutive frames of conductor images, where N is an integer greater than 1; According to the image of each phase conductor in the three-phase conductor in the N frames of conductor images, the N frames of conductor images are segmented to obtain N frames of conductor images of each phase conductor; Binarizing the N frames of wire images of each phase wire to obtain the N frames of binary images of each phase wire; According to the largest closed image in the N frames of binary images of each phase conductor, feature extraction is performed from each of the N frames of binary images of each phase conductor to obtain N frames of conductor features of each phase conductor; For each phase conductor, according to the displacement change of the nth conductor feature relative to the first conductor feature, obtain n-1th displacement change information, where n is a positive integer less than or equal to N; According to the N-1 displacement change information of each phase conductor, label information corresponding to the sample meteorological information is generated.

4. The method according to any one of claims 1 to 3, characterized in that: The weather forecast information includes the minimum temperature information, relative humidity information, maximum wind speed information and wind direction information within the target time period; the parameters of the target overhead transmission line include the conductor axial information of the target overhead transmission line; The generating, according to the meteorological forecast information and the parameters of the target overhead power transmission line, a line galloping warning result of the target overhead power transmission line comprises: Determine the angle information between the wind direction information and the conductor axial information; Processing the minimum temperature information, the relative humidity information, the maximum wind speed information and the angle information using a third predetermined model, and outputting line galloping level information of the target overhead transmission line; The line dancing warning result is generated according to the line dancing level information.

5. The method according to any one of claims 1 to 3, characterized in that: The step of generating the galloping risk information of the target overhead transmission line according to the M weight information and the M galloping risk values ​​of the target overhead transmission line comprises: Determining mth target weight information according to the mth weight information, the mth dancing risk value, the M weight information and the M dancing risk values; According to the index evaluation standard, J first dancing prediction indicators and K second dancing prediction indicators are determined from the M dancing prediction indicators, the evaluation standards of the first dancing prediction indicators and the second dancing prediction indicators are different, and J and K are positive integers; Processing the dancing risk value of the j-th first dancing prediction index among the J first dancing prediction indexes by using a first normalization function to obtain a j-th first index value, where j is a positive integer less than or equal to J; Processing the dancing risk value of the kth second dancing prediction index among the K second dancing prediction indexes using a second normalization function to obtain a kth second index value, where k is a positive integer less than or equal to K; and The galloping risk information of the target overhead transmission line is generated according to the J first index values, the K second index values ​​and the M target weight information.

6. The method according to any one of claims 1 to 3, characterized in that: The galloping risk value includes wind speed information at the location of the target overhead transmission line; The method further comprises: Using sensors to collect initial wind speed information of the target area; Determining a height difference between the target overhead power transmission line and the sensor according to the height information of the target overhead power transmission line and the height information of the sensor; According to the height difference, determining a target wind speed conversion function from wind speed conversion functions corresponding to Q height difference ranges, where Q is an integer greater than 1; The initial wind speed information is processed using the target wind speed conversion function to obtain the wind speed information.

7. A transmission line galloping warning system, characterized in that: include: Servers for: In response to receiving a galloping warning instruction for a target overhead transmission line located in a target area during a target period, galloping risk information of the target overhead transmission line is generated according to M weight information and M galloping risk values ​​of the target overhead transmission line; the mth weight information represents the importance of the mth galloping prediction index relative to other M-1 galloping prediction indexes when the galloping risk of the target overhead transmission line is predicted according to the mth galloping prediction index among the M galloping prediction indexes; the mth galloping risk value represents the risk degree of the galloping of the target overhead transmission line when the mth galloping prediction index is used as an evaluation standard, M is an integer greater than 1, and m is a positive integer less than or equal to M; In response to detecting that the galloping risk information indicates that the target overhead transmission line has a galloping risk, forecasting weather forecast information of the target area within the target period based on information of the target period and historical weather information of the target area; The target area includes I sub-areas; the forecasting of the meteorological forecast information of the target area within the target period based on the information of the target period and the historical meteorological information of the target area includes: using a first predetermined model to process the information of the target period and the i-th historical meteorological information of the i-th sub-area to obtain the i-th meteorological forecast information, where I is an integer greater than 1 and i is a positive integer less than or equal to I; using a second predetermined model to process the i-th meteorological forecast information to determine the i-th meteorological risk information, the i-th meteorological risk information characterizing the risk probability of the target overhead transmission line dancing under the meteorological conditions of the i-th meteorological forecast information; determining the target meteorological risk information from the I meteorological risk information, the target meteorological risk information characterizing the existence of the risk of the target overhead transmission line dancing under the meteorological conditions of the meteorological forecast information corresponding to the target meteorological risk information; in response to detecting that the number of target meteorological risk information in the I meteorological risk information is greater than or equal to the predetermined number, determining that the meteorological forecast information of the target area meets the predetermined condition; In response to detecting that the weather forecast information satisfies the predetermined condition, a line galloping warning result of the target overhead transmission line is generated according to the weather forecast information and the parameters of the target overhead transmission line; a visual terminal device is connected to the server and is used to: receive the line galloping warning result and display the line galloping warning result through a visual interface of the visual terminal device.

8. An electronic device, comprising: one or more processors; a memory for storing one or more computer programs, It is characterized in that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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