Power transmission line galloping early warning method, system, equipment and medium

Abstract

The invention provides a power transmission line galloping early warning method, system and device and a medium, and can be applied to the technical field of line galloping prediction. The power transmission line galloping early warning method comprises the steps of generating galloping risk information of a target overhead power transmission line according to M pieces of weight information and M galloping risk values of the target overhead power transmission line; in response to detecting that the galloping risk information represents that the target overhead transmission line has a galloping risk, predicting weather prediction information of the target area in the target time period according to the information of the target time period and historical weather information of the target area; and in response to the fact that the weather prediction information is detected to meet a predetermined condition, generating a line galloping early warning result of the target overhead transmission line according to the weather 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 in particular to a transmission line galloping early warning method, system, equipment and medium. Background Art

[0002] The stable operation of overhead transmission lines is crucial for electricity users. However, the sudden dancing of overhead transmission lines may affect the stability of power transmission of overhead transmission lines. There are many factors that affect the occurrence of line dancing. In order to ensure the stable operation of the line, it is necessary to timely and accurately warn of the possible dancing 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 dancing phenomenon, the accuracy of the early warning of the dancing 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] A first aspect of the present invention provides a power transmission line galloping warning method, comprising: in response to receiving a galloping warning instruction for a target overhead power transmission line located in a target area during a target period, generating galloping risk information of the target overhead power transmission line according to M weight information and M galloping risk values ​​of the target overhead power transmission line; the mth weight information represents the importance of the mth galloping prediction indicator relative to other M-1 galloping prediction indicators when the galloping risk of the target overhead power transmission line is predicted according to the mth galloping prediction indicator among the M galloping prediction indicators; the mth galloping prediction indicator ... The risk value represents the risk degree of the target overhead transmission line galloping when the mth galloping prediction index is used as the evaluation standard, where M is an integer greater than 1 and m is a positive integer less than or equal to M; in response to detecting the galloping risk information representing the existence of the galloping risk of the target overhead transmission line, the meteorological forecast information of the target area within the target period is predicted according to the information of the target period and the historical meteorological information of the target area; in response to detecting that the meteorological forecast information meets the predetermined conditions, the line galloping warning result of the target overhead transmission line is generated according to the meteorological forecast 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; based on the information of the target time period and the historical meteorological information of the target area, the meteorological forecast 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 forecast information, I is an integer greater than 1, and i is a positive integer less than or equal to I; the above method also includes: 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 characterizes 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.

[0006] According to an embodiment of the present invention, the i-th meteorological forecast information is processed using a second predetermined model to determine the i-th meteorological risk information, including: obtaining phase information of the target overhead transmission line; and processing the i-th meteorological forecast information and phase information using the 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 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, the overhead three-phase conductor is imaged to obtain N continuous frames of conductor images, where N is an integer greater than 1; the N frames of conductor images are segmented according to the image of each phase conductor in the three-phase conductor in the N frames of conductor images to obtain N frames of conductor images for each phase conductor; the N frames of conductor images for each phase conductor are binarized to obtain N frames of binarized images for each phase conductor; according to the closed image with the largest area in the N frames of binarized images for each phase conductor, feature extraction is performed from each of the N frames of binarized images for each phase conductor to obtain N frames of conductor features for each phase conductor; for each phase conductor, according to the displacement change of the nth conductor feature relative to the first conductor feature, the n-1th displacement change information is obtained, where n is a positive integer less than or equal to N; and label information corresponding to the sample meteorological information is generated according to the N-1 displacement change information for each phase conductor.

[0008] According to an embodiment of the present invention, the meteorological forecast 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 conductor axial information of the target overhead transmission line; based on the meteorological forecast information and the parameters of the target overhead transmission line, a line dancing warning result of the target overhead transmission line is generated, including: determining the 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 angle information, and outputting the line dancing level information of the target overhead transmission line; based on the line dancing level information, a line dancing warning result is generated.

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

[0010] According to an embodiment of the present invention, the dancing risk value includes wind speed information at the location of the target overhead transmission line; the above method also includes: using a sensor to collect initial wind speed information of the target area; determining the height difference between the target overhead transmission line and the sensor based on the height information of the target overhead transmission line and the height information of the sensor; determining a target wind speed conversion function from wind speed conversion functions corresponding to Q height difference ranges based on the height difference, 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 wind speed information.

[0011] A second aspect of the present invention provides a transmission line galloping warning system, comprising: a server, configured to: in response to receiving a galloping warning instruction for a target overhead transmission line located 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 mth weight information represents the importance of the mth galloping prediction indicator relative to other M-1 galloping prediction indicators when the galloping risk of the target overhead transmission line is predicted according to the mth galloping prediction indicator among the M galloping prediction indicators; the mth galloping risk value represents the importance of the mth galloping prediction indicator when the galloping risk of the target overhead transmission line is predicted according to the mth galloping prediction indicator among the M galloping prediction indicators; the risk degree of galloping of the target overhead transmission line under certain conditions, 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 forecast information of the target area within 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 forecast information meets a predetermined condition, generating a line galloping warning result of the target overhead transmission line according to the meteorological 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.

[0012] A third aspect of the present invention provides an electronic device, comprising: one or more processors; a memory for storing one or more computer programs, wherein the one or more processors execute the 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 the steps of the above method are implemented when the above computer program or instruction is executed by a processor.

[0014] According to an embodiment of the present invention, by generating the galloping risk information according to the weight information and the galloping risk value of the target overhead transmission line, the target overhead transmission line can be determined as a line with a galloping risk according to the galloping risk information. Then, according to the historical meteorological information of the target area and the information of the target period, the meteorological forecast information of the target area in the target period is predicted, so as to judge whether the meteorological conditions in the target area in the target period are meteorological conditions that are likely to cause the target overhead line to gallop. When the meteorological forecast information meets the predetermined conditions, it can be determined that the meteorological forecast information of the target area in the target period is likely to cause the target overhead line to gallop, so that the galloping condition of the target overhead transmission line in the target period can be further accurately warned according to the meteorological forecast information and the parameters of the target overhead transmission line, so as to timely prevent the potential galloping risk of the target overhead transmission line before the target period arrives, and ensure the stable power transmission of the target overhead line. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The above contents and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:

[0016] Figure 1 A diagram showing an application scenario of a power transmission line galloping warning method according to an embodiment of the present invention;

[0017] Figure 2 A flow chart of a method for early warning of power transmission line galloping according to an embodiment of the present invention is shown;

[0018] Figure 3 A schematic diagram of a dancing prediction index layer according to an embodiment of the present invention is shown;

[0019] Figures 4A to 4D Schematic diagrams of dance areas according to embodiments of the present invention are respectively shown;

[0020] Figure 5 A flow chart showing a method for early warning of power transmission line galloping according to another embodiment of the present invention is shown;

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

[0022] Figure 7 A block diagram of an electronic device suitable for implementing a power transmission line galloping early warning method according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0023] Below, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present invention. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of embodiments of the present invention. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of concepts of the present invention.

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

[0025] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled 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] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

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

[0028] like Figure 1 As 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 a communication link between 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 optical fiber 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 can 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 any electronic device having a display screen and supporting web browsing, including but not limited to a smart phone, a tablet computer, a laptop computer, a desktop computer, and the like.

[0031] The server 120 may be a server that provides various services, such as a background management server that provides support for websites browsed by users using the terminal device 110 (for example only). The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device. For example, the server 120 may be used to obtain and store meteorological information and image information of overhead power transmission lines through the network 130, and may complete operations such as storage, retrieval, backup of data, and calling of historical information. In addition, real-time operation of the image collector 150 may be implemented through the network 130, including taking pictures and live video.

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

[0033] It should be noted that the power transmission line galloping warning method provided in the embodiment of the present invention can generally be executed by the server 120. The power transmission line galloping warning method provided in the embodiment of the present invention can also be executed by a server or 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 number of terminal devices, servers, sensors and image collectors in the embodiment is only for illustration. According to the implementation requirements, there may be any number of terminal devices, servers, sensors and image collectors.

[0035] The following will be based on Figure 1 The scenario described above is described below in detail about the power transmission line galloping warning method according to an embodiment of the present invention.

[0036] Figure 2 A flow chart of a transmission line galloping warning method according to an embodiment of the present invention is shown.

[0037] like Figure 2 As shown, the power 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 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.

[0039] According to an embodiment of the present invention, the mth weight information may represent the importance of the mth galloping prediction index relative to the 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. The mth galloping risk value may represent the risk level of the galloping of the target overhead transmission line when the mth galloping 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 galloping risk information indicates that the target overhead transmission line has a galloping risk, weather forecast information of the target area in the target period is predicted based on information of the target period and historical weather information of the target area.

[0041] In operation S230, in response to detecting that the weather forecast information satisfies a 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. The predetermined condition may be a condition for determining whether the weather forecast information has a risk of causing the overhead transmission line to gallop. For example, the predetermined condition may be a condition determined based on a predetermined threshold value of each meteorological factor (such as humidity, wind speed, etc.) in the weather forecast information.

[0042] According to an embodiment of the present invention, the target area may be an area where the target overhead transmission line is located. The target period may be a future period located after the current period. The dancing warning instruction is an early warning instruction for determining whether the target overhead transmission line will dance within the target period. In the case of receiving the dancing warning instruction, a dancing prediction index may be selected, and the weight information and the dancing risk value under the index may be obtained according to the dancing prediction index. The dancing prediction index may be an index that can reflect the development of the dancing state of the overhead transmission line. The weight information and the dancing risk value may be predetermined. For example, when a user needs to obtain the line dancing early warning result of an overhead transmission line located in a certain area between 3:00 and 4:00 p.m. on the third day in the future, the "3:00 to 4:00 p.m. on the third day in the future" may be used as the target period, and the area may be used as the target area, and the dancing warning instruction carrying the information of the target period, the information of the target area, and the information of the overhead transmission line may be sent to the server through the terminal device. The server may first query the weight information and dancing risk value under the M dancing 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 dancing risk information according to the weight information and the dancing risk value. The weight information may be fixed, and the dancing risk value of the dancing prediction indicator may be updated due to the data obtained at regular intervals, so that the calculation result calculated according to the M weight information and the M dancing risk values ​​will also change accordingly. For example, the weight information and the dancing risk value of the mth dancing prediction indicator may be multiplied to obtain the mth intermediate calculation result, and then the above calculation result is obtained according to the sum of the M intermediate settlement results. The calculation result can be compared with a predetermined threshold, so as to generate the dancing risk information according to the comparison result. The dancing risk information can be used to characterize whether the target overhead transmission line has a potential dancing risk.

[0043] Specifically, Figure 3 A schematic diagram of a dancing prediction indicator layer according to an embodiment of the present invention is shown.

[0044] like Figure 3 As shown, the dancing prediction index may include prediction indexes related to line characteristics and prediction indexes related to the environment in which the line is located. Prediction indexes related to characteristic factors may include dancing amplitude 311, dancing frequency 312, dancing area type 313, conductor type 314, etc. Prediction indexes related to environmental factors may include wind speed 321, temperature 322, ice thickness 323, humidity 324, etc. Moreover, the historical data of the target overhead transmission line itself or the historical data of the line of the same type as the target overhead transmission line also reflects the development and change of the dancing state to a certain extent. In this way, the dancing prediction index may also include prediction indexes related to historical data. Prediction indexes related to historical data may include dancing frequency change 331 and dancing amplitude change 332, etc.

[0045] For example, an overhead transmission line can be a single-phase line or a multi-phase line in a three-phase line. Since the harm of galloping is generally caused by phase-to-phase flashover due to insufficient air gap length between phases, the galloping amplitude used to reflect the size of the galloping range has become the most important galloping prediction indicator. The galloping frequency is the vibration characteristic parameter of the line galloping itself. In addition, line galloping often occurs on ice-covered lines, and the thickness of ice on the line is determined by the temperature, rainfall and geographical environment.

[0046] In order to form dancing, in addition to ice, wind excitation is also required to provide energy for the line dancing. In addition, unreasonable line structure parameter combinations are also prone to cause dancing. For example, split conductors are more likely to dance than single conductors, and large-section conductors are more likely to dance than small-section conductors. The frequency of conductor dancing is closely related to meteorological conditions and micro-topography. Places with flat terrain, many lake vents, severe meteorological conditions, and many rainy and frost days are all areas that are more likely to induce dancing. Therefore, the dancing area type can be divided according to the frequency of line dancing. In this way, the dancing area type can include, for example, Figure 4A The canyon wind tunnel dance area shown in the figure Figure 4B The wave dance area at the pass shown, Figure 4C The alpine watershed dance area shown and Figure 4D The terrain-lifted dance area shown. Figure 4A It can be seen that the line crosses a steep canyon. When the airflow enters the canyon from the open area, a "narrow channel effect" is generated. The airflow will accelerate through the canyon, making the line prone to ice, affecting the probability of line dancing; reference Figure 4B It can be seen that the line runs along the ridge of the mountain and crosses the pass. When the airflow passes through the concave part of the ridge from the open space, the air will gather towards the center and pass faster, making the line easy to be covered with ice, affecting the probability of line dancing; reference Figure 4C It can be seen that when the line crosses the watershed, the airflow rises from the windward slope and passes over the top of the mountain, which is open and unobstructed, and accelerates to pass through, resulting in strong winds, making the line prone to ice, affecting the probability of line dancing; reference Figure 4D It can be seen that the line climbs from the lower terrain of plains, hills or basins to higher peaks or steep cliffs. The temperature of the airflow decreases due to the lifting effect, which easily produces local strong convection, making the line easy to be covered with ice, affecting the probability of line dancing. However, this is only an example, and the present invention can also include water vapor enhancement dancing areas, etc. In the water vapor enhancement dancing area, the transmission line crosses surface water bodies such as rivers and adjacent lakes. Due to the different thermal properties of land and water, there will be temperature differences and air pressure differences, which is easy to form a local circulation of water and land winds, and the small friction on the surface of the water body is conducive to the formation of strong winds, making the line easy to be covered with ice, affecting the probability of line dancing. This division method is simple and easy to implement, has a certain degree of rationality, and can more objectively and comprehensively reflect the dancing of the conductors in the area.

[0047] The specific galloping risk value of the target overhead line under each galloping prediction index can be obtained by monitoring data of the line galloping site, historical data records, and querying line operation data. For example, the image acquisition device can be used to collect images of overhead transmission lines to obtain continuous line images; the line galloping displacement is determined according to the position change of the line in the adjacent line image; and then the amplitude of the galloping amplitude is determined according to the line galloping displacement. Here, the amplitude of the galloping amplitude is the galloping risk value under the "galloping amplitude" index. The same is true for other reasons, which will not be repeated here. In addition, based on the line galloping displacement and the image acquisition frequency, the galloping acceleration can be obtained by integral calculation, and then the galloping acceleration can be analyzed by spectrum analysis to obtain the galloping risk value of another galloping prediction index of the line galloping - the galloping frequency. The temperature and humidity can be collected in the target area where the overhead transmission line is located using a temperature and humidity sensor, and the wind speed and wind direction are also collected using a wind speed and wind direction sensor deployed in the area where the overhead transmission line is located.

[0048] The dancing risk values ​​of the dance area type and the dancing risk values ​​of the conductor type are given through expert scoring in combination with the actual operation data of the line. For example, experts can score each dance area based on the probability that the same type of conductor will dance due to various types of dance areas. Each conductor can also be scored based on the dancing probability of various types of conductors in the same dance area. The dancing amplitude and dancing frequency obtained by this sampling are subtracted from the dancing amplitude and dancing frequency obtained by the previous sampling, and then divided by the dancing amplitude and dancing frequency collected previously, respectively, to obtain the dancing amplitude change rate and dancing frequency change rate, respectively.

[0049] The ice thickness can be observed by fixing a wire of the same specification on the tower in the area where the overhead transmission line is located in parallel with the target overhead transmission line. Alternatively, it can be calculated by collecting the volume of ice shed from the target overhead transmission line and the thickness of ice attached to other objects on site. Thus, the index value of each galloping prediction index can be obtained as the galloping risk value.

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

[0051] The evaluation of the galloping state of overhead transmission lines is a comprehensive evaluation of multiple hierarchical indicators. The weight of each indicator is an extremely important parameter. Whether it is determined scientifically and reasonably directly affects the accuracy of the evaluation. 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, four priority relationship matrices need to be established, and then the fuzzy hierarchical analysis method is used to transform the four priority relationship matrices into fuzzy consistent judgment matrices. The weight of each factor is calculated and determined by the relationship sorting method.

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

[0053] Then, we can establish the priority relationship matrix F=(f ij ) m×m . The priority relation matrix F=(f ij ) m×m It indicates the relative importance of each factor in each level of factors. f represents a functional relationship, that is, an element in the priority relationship matrix F. i and j represent an element of 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 of any two factors with respect to a certain criterion, this study uses nine scales of 0.1~0.9 as shown in Table 1 below to construct F=(f ij ) m×m . So the priority relationship matrix F=(f ij ) m×m Transformed into a fuzzy consistent matrix A=(a ij ) m×m a represents a functional relationship and is also an element in the fuzzy consistency matrix A. In Table 1, r ij Indicates that the above element u is evaluated according to the jth element in the judgment set. i The degree of membership obtained by evaluating. jiThe meaning of is similar to this, so I will not elaborate on it here. Judgment set V = {normal, swing, low-amplitude dancing, high-amplitude dancing}. "Normal" means that the conductor does not dance, the operating state is normal, the working performance is stable, the possibility of line failure is extremely low, and it can operate safely for a long time; "swing" means that the reliability of individual state quantities of the conductor has slightly decreased, and the line has a slight swing, but the operating state of the conductor is basically stable and can continue to operate, and the possibility of line failure is low; "low-amplitude dancing" means that some state quantities of the conductor dancing reflect that the line has danced, the conductor operating state is poor, and phase-to-phase flashover, tripping and other faults may occur, and staff need to be arranged for inspection; "high-amplitude dancing" indicates that the overall operating state of the line is poor, the conductor dancing amplitude is large, and phase-to-phase flashover, tripping and other accidents are prone to occur. It is necessary to pay close attention to its state development and take relevant measures immediately.

[0054] Table 1

[0055]

[0056] Next, we can establish the evaluation index weight set based on the fuzzy consistency matrix. 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. ij ) m×m , we can use the relational sorting method to find out the corresponding weight information of each factor.

[0057] Specifically in the present invention, the characteristic factors in the index layer reflect the development trend of the line galloping state and are of the greatest importance. Environmental factors will change the cross-sectional stress of the line, thereby affecting the state of line galloping, and are slightly less important than characteristic factors. In general, the time interval between two consecutive samplings is short, and the historical data changes are generally small, so the importance is weak. Based on this, the priority relationship matrix F can be constructed 目标层 、F 特征因素 、F 环境因素 and F 历史数据 , as shown below. Among them, the priority relationship matrix F 目标层 It represents the importance of the indicator layer relative to the target layer (that is, the risk level of dancing risk). 特征因素 It represents the importance of each dancing prediction index under the characteristic factors relative to the characteristic factors. 环境因素 It represents the importance of each dancing prediction index under environmental factors relative to the environmental factors. 历史数据 It represents the importance of each dancing prediction index under historical data relative to the historical data.

[0058] (1).

[0059] (2).

[0060] (3).

[0061] (4).

[0062] The priority relationship matrix F 目标层 、F 特征因素 、F 环境因素 and F 历史数据 , 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] Therefore, the weight information of each factor at the sub-indicator layer can be calculated, as shown in Table 2 below.

[0068] Table 2 Weight information of each factor

[0069]

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

[0071] According to an embodiment of the present invention, after obtaining the dancing risk value and weight information under each dancing prediction index of the target overhead transmission line, the dancing risk value and the weight information can be calculated to obtain a calculation result, and the calculation result can be compared with a predetermined threshold value. When the calculation result is greater than the threshold value, dancing risk information characterizing that the target overhead transmission line has a dancing risk is generated. Otherwise, dancing risk information characterizing that the target overhead transmission line does not have a dancing risk can be generated.

[0072] In the case of generating galloping risk information characterizing the existence of galloping risk of the target overhead transmission line, the meteorological conditions of the target area within the target period can be further predicted to obtain the meteorological forecast information of the target area within the target period, so that the galloping risk of the target overhead transmission line can be further judged according to the meteorological forecast information. The similarity between multiple meteorological factors of the historical meteorological information that have caused the overhead transmission line with similar or identical specifications to the target overhead transmission line to gallop and the multiple meteorological factors of the above-mentioned meteorological forecast information can be determined, and the multiple meteorological factors can include humidity, temperature, wind speed and wind direction, etc. In the case that 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 forecast information is greater than or equal to a predetermined similarity threshold, it can be determined that the meteorological forecast information meets the predetermined condition, otherwise, it is determined that the meteorological forecast information does not meet the predetermined condition. For example, in the case that the similarity between a certain meteorological factor in the historical meteorological information and the corresponding meteorological factor in the meteorological forecast information is greater than or equal to a predetermined similarity threshold, it is determined that the meteorological forecast information meets the predetermined condition. For example, when the similarity between the humidity information in the historical meteorological information and the humidity information in the meteorological forecast information is greater than or equal to a predetermined similarity threshold, it can be determined that the meteorological forecast information meets the predetermined condition.

[0073] When the meteorological forecast information meets the predetermined conditions, the environmental factors and the specific structural characteristics of the line can be further combined according to the meteorological forecast information and the parameters of the target overhead transmission line, so as to generate accurate line galloping warning results. The line galloping warning results can be divided into warning results that characterize the galloping of the target overhead transmission line within the target period and warning results that characterize the non-galloping of the target overhead transmission line within the target period. The line galloping warning results can be sent to the visual terminal device and displayed so that relevant personnel can take relevant measures on the target overhead transmission line according to the line galloping warning results to avoid the galloping of the target overhead transmission line within the target period, thereby ensuring the stability of power transmission.

[0074] According to an embodiment of the present invention, by generating the galloping risk information according to the weight information and the galloping risk value of the target overhead transmission line, the target overhead transmission line can be determined as a line with a galloping risk according to the galloping risk information. Then, according to the historical meteorological information of the target area and the information of the target period, the meteorological forecast information of the target area in the target period is predicted, so as to judge whether the meteorological conditions in the target area in the target period are meteorological conditions that are likely to cause the target overhead line to gallop. When the meteorological forecast information meets the predetermined conditions, it can be determined that the meteorological forecast information of the target area in the target period is likely to cause the target overhead line to gallop, so that the galloping condition of the target overhead transmission line in the target period can be further accurately warned according to the meteorological forecast information and the parameters of the target overhead transmission line, so as to timely prevent the potential galloping risk of the target overhead transmission line before the target 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 wind speed information at the location of the target overhead transmission line. The above method also includes: using a sensor to collect 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, a target wind speed conversion function is determined 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 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, and may also be the height of the suspension point of the target overhead transmission line relative to the ground. The above-mentioned sensor may be a wind speed and direction sensor, and the height information of the sensor represents the height of the setting position of the sensor relative to the ground. In one embodiment, the sensor may be set on the ground.

[0077] According to an embodiment of the present invention, a wind speed and wind direction sensor can be used to collect initial wind speed information of the target area. Then, 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, and then according to the height difference, the target wind speed conversion function can be determined from the wind speed conversion functions corresponding to the Q height difference ranges. The wind speed conversion function may 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 initial wind speed information can be converted into wind speed information using the first wind speed conversion function. When the height difference range is greater than or equal to the predetermined value, the initial wind speed information can be converted into wind speed information using the second wind speed conversion function. The wind speed information here is the dancing risk value of the wind speed in the above-mentioned 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 wind speed information; v0 is initial wind speed information; H is height information of target overhead transmission line; H0 is sensor height information; Z0 is a predetermined constant corresponding to ground conditions, 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 index 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 meaning of the symbols here is only used to explain the contents of formulas (9) and (10). Similarly, the meaning of the symbols in other formulas below is also only used to explain the contents of the corresponding formulas, and will not be repeated one by one below.

[0083] According to an embodiment of the present invention, due to differences in the location of the transmission line, the height of the airflow and the wind speed distribution, and the change in wind speed with the change in height usually presents a nonlinear distribution, especially in areas with complex terrain, the wind speed may behave differently at different heights. Therefore, by selecting a target wind speed conversion function suitable for the height difference between the sensor and the target overhead transmission line from a plurality of wind speed conversion functions 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, according to M weight information and M galloping risk values ​​of the target overhead transmission line, the galloping risk information of the target overhead transmission line is generated, including: determining the mth target weight information according to the mth weight information, the mth galloping risk value, the M weight information and the M galloping risk value. According to the index evaluation standard, J first galloping prediction indicators and K second galloping prediction indicators are determined from the M galloping prediction indicators, the evaluation standards between the first galloping prediction indicators and the second galloping prediction indicators are different, and J and K are positive integers. The galloping risk value of the jth first galloping prediction indicator among the J first galloping prediction indicators is processed by a first normalization function to obtain the jth first indicator value, where j is a positive integer less than or equal to J. The galloping risk value of the kth second galloping prediction indicator among the K second galloping prediction indicators is processed by a second normalization function to obtain the kth second indicator 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 ​​and the K second index values.

[0085] According to an embodiment of the present invention, the weight information in the above Table 2 is fixed and will not change due to different states (such as environmental states and wire states, etc.) and evaluation factors. However, in the wire galloping evaluation index system, when certain factors (such as the change in the galloping amplitude) seriously deviate from the normal value, it means that the wire galloping develops very quickly and needs to be processed immediately. However, in the evaluation model of the above weight information, the weight information of this factor may be small, resulting in the generation of galloping risk information that indicates that there is no galloping risk in the line, making it difficult for the galloping risk information to truly reflect the actual change state of the wire galloping. Therefore, the weight information needs to be further processed.

[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 dancing risk value of the i-th dancing prediction index, m is the number of dancing prediction indicators, w i is the target weight information of the i-th dancing prediction index, w 0 i is the weight information of the i-th dancing prediction index, a is the predetermined index, It represents the value obtained by accumulating the results obtained by multiplying the first galloping risk value and the first weight information. The value of a reflects the requirement for balance and will greatly affect the final evaluation result. a=0.2 can be applied to general engineering situations.

[0089] The above formula (11) can highlight the role of extreme values. When extreme values ​​appear in the dancing risk value, the final result calculated based on the dancing risk value and the target weight information will quickly approach zero to reflect this situation, so that the generated dancing risk information can be more accurate. Considering that the comprehensive evaluation and calculation of the weight information of the percentage evaluation standard will result in large denominator data, resulting in large rounding errors. Considering the convenience of calculation and accuracy requirements, the percentage evaluation value is converted into a percentage here.

[0090] According to an embodiment of the present invention, in the above-mentioned multi-index fuzzy comprehensive evaluation, since the dimensions of each sub-index are different, the order of magnitude of the sub-index values ​​are also different, and thus the dancing risk value needs to be normalized. The dancing risk value of the dancing prediction index can be normalized according to the optimal index value and the limit index value of the dancing prediction index. The optimal index value and the limit index value can be predetermined.

[0091] The first galloping prediction index can be an index of a better type as it is smaller (i.e., 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 that is larger and better (i.e., 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 dancing prediction index, C 01 The limit index value of the i-th dancing prediction index, Ci is the i-th dancing risk value, and k is the degree of influence of parameter change on the dancing state, which can be taken as 1. For example, the above formula is only used to process quantitative dancing prediction indicators. The first dancing prediction risk index and the second dancing risk prediction index are quantitative dancing prediction indicators. Among the quantitative dancing prediction indicators mentioned above, except for temperature and dancing frequency, which are indicators of the type of the larger the better, the rest are indicators of the type of the smaller 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 line operation state is no galloping, that is, the optimal index value of the galloping amplitude is 0 m. Therefore, the following normalized formula (14) can be obtained:

[0097] (14).

[0098] Similarly, the normalization formulas of the other seven quantitative indicators can be derived, as shown in Table 3. In this way, the normalization formulas shown in Table 3 can be used to normalize the dancing risk values ​​of the dancing prediction indicators, thereby obtaining the indicator values ​​of the dancing prediction indicators.

[0099] Table 3

[0100]

[0101] For qualitative indicators, this study established an expert scoring table for dance area type and lead type, which quantified the dancing risk value of both dance area type and lead type into a number between 0 and 1. The smaller the score in the scoring table, the better the indicator performance. The expert scores of dance area type and lead type are shown in Table 4 and Table 5:

[0102] Table 4

[0103]

[0104] Table 5

[0105]

[0106] According to an embodiment of the present invention, by determining the target weight information according to the weight information, the galloping risk value, the total weight information and the total galloping risk value, the galloping risk information can more accurately reflect the potential galloping risk of the target overhead transmission line. On this basis, the galloping risk values ​​of different evaluation standards are normalized using different normalization functions, so that the galloping risk values ​​of different evaluation standards can be accurately unified to the same dimension, and then according to the first index value and the second index value obtained after normalization and the target weight information, accurate galloping risk information is obtained, thereby improving the accuracy of determining the galloping risk of the target overhead transmission line.

[0107] According to the embodiments of the present invention, the galloping of overhead wires is closely related to different external meteorological conditions and the structural parameters of the line itself. However, the existing physical models for the galloping of overhead wires are not accurate enough, and some parameters in these models are difficult to obtain in real time through measurement on actual lines. The overhead wire galloping warning is only purely based on the physical model, which has low accuracy and practicality.

[0108] On this basis, the inventors found that the overhead wire dancing warning can be attributed to a classification prediction problem under supervised learning. For a classification prediction problem, the basic goal of statistical learning is to establish a learner with strong generalization ability based on observed data. However, in most cases, since the accuracy of the learner is greatly affected by domain knowledge and training data and its distribution, especially for those prediction problems whose physical nature has not been fully understood, such as the dancing of wires covered with ice, it is difficult to directly construct a learner with high precision to achieve prediction and warning of a certain line or a specific line section at one time. However, the internal cause of the wire dancing is the line structure parameters, and when the internal cause is relatively unchanged, the change of things is determined by external factors. Therefore, a model can be constructed first to predict the changes in external meteorological conditions, and then predict whether a specific line (such as a certain wire segment) will dance after determining that the weather has reached the dancing conditions.

[0109] The meteorological forecast information of the target area within the target time period can be predicted, and then the meteorological forecast information is processed by a classifier to obtain meteorological risk information, so that the risk condition 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 forecast information of the target area within the target time period is predicted, including: using the 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 forecast information, I is an integer greater than 1, and i is a positive integer less than or equal to I. The above method also includes: using the 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. The target meteorological risk information is determined from the I meteorological risk information, and the target meteorological risk information characterizes 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 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 a predetermined condition (ie, the above-mentioned meteorological susceptibility 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 a strong ability to solve 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 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; GRNN has a simpler structure; GRNN needs to optimize only one parameter, namely the smoothing parameter. Therefore, GRNN is selected to construct the first predetermined model.

[0111] We can make full use of the rapidity of GRNN training network and adopt the method of dynamic division of training set, that is, when predicting the meteorological elements in the target period, the meteorological element data of the predetermined time (such as 10 days) before the target period is used as the training set of the network. We can predict the meteorological elements and analyze the prediction effect of GRNN network.

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

[0113] Specifically, taking the target period as a certain time t (which can be the starting time of the target period) as an example, considering the mutual influence between 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 will be predicted separately. Since the time span of the prediction is small, the meteorological data at adjacent times of adjacent dates also contain valuable information. 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 time t of a certain day is predicted, the air pressure, wind direction, wind speed, temperature and humidity at time t-1 of the same day are required, and the air pressure, wind direction, wind speed, temperature and humidity at time t-2, t-1, t, t+1 and t+2 of the previous day are also required. The air pressure, wind direction, wind speed, temperature and humidity at time t-2, t-1, t, t+1 and t+2 of the previous two days are also required. 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 They represent the air pressure, wind direction, wind speed, temperature and humidity at time t-1 of the day, respectively. 1 t-2 , D 1 t-2 , S 1 t-2 、T 1 t-2 and H 1 t-2 They represent the air pressure, wind direction, wind speed, temperature and humidity at time t-2 of the previous day, respectively. 1 t-1 , D 1 t-1 , S 1 t-1 、T 1 t-1 and H 1 t-1 They represent the air pressure, wind direction, wind speed, temperature and humidity at time t-1 of the previous day, respectively. 1 t , D 1 t , S 1 t 、T 1 t and H 1 t They represent the air pressure, wind direction, wind speed, temperature and humidity at time t of the previous day, respectively. 1 t+1 , D 1 t+1 , S 1 t+1 、T 1 t+1 and H 1 t+1 They represent the air pressure, wind direction, wind speed, temperature and humidity at time t+1 of the previous day, respectively. 1 t+2 , D 1 t+2 , S 1 t+2 、T 1 t+2 and H 1 t+2 They represent the air pressure, wind direction, wind speed, temperature and humidity at time t+2 of the previous day, respectively. 2 t-2 , D 2 t-2 , S 2 t-2 、T2 t-2 and H 2 t-2 They represent the air pressure, wind direction, wind speed, temperature and humidity at time t-2 two days before, respectively. 2 t -1 , D 2 t-1 , S 2 t-1 、T 2 t-1 and H 2 t-1 They represent the air pressure, wind direction, wind speed, temperature and humidity at time t-1 two days before, respectively. 2 t , D 2 t , S 2 t 、T 2 t and H 2 t They represent the air pressure, wind direction, wind speed, temperature and humidity at time t two days ago, respectively. 2 t+1 , D 2 t+1 , S 2 t+1 、T 2 t+1 and H 2 t+1 They represent the air pressure, wind direction, wind speed, temperature and humidity at time t+1 two days ago, respectively. 2 t+2 , D 2 t+2 , S 2 t+2 、T 2 t+2 and H 2 t+2 They respectively represent the air pressure, wind direction, wind speed, temperature and humidity at time t+2 two days ago.

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

[0117] (16).

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

[0119] Based on this, for changeable meteorological conditions, a dynamic prediction model can be established, that is, each time a meteorological forecast is made, the network is trained once. Therefore, in each prediction, the optimal parameters of the first predetermined model are only related to the prediction made this time, and are not fixed and unchanged, so that better prediction accuracy can be guaranteed. In this way, the situation where the degree of meteorological influence on the galloping of overhead transmission lines changes greatly due to large changes in meteorological conditions at different time periods is avoided. By timely using new meteorological information to train the first initial model, the accuracy of the galloping warning can be improved, thereby ensuring the safety of the overhead transmission lines.

[0120] According to an embodiment of the present invention, the second predetermined model may be constructed based on an SVM algorithm. The second predetermined model may be obtained by pre-training a second initial model using sample meteorological information and risk label information corresponding to the sample meteorological information. The risk label information may be obtained by manually marking the sample meteorological information according to the risk probability of the overhead transmission line dancing caused by the meteorological conditions of the sample meteorological information, and the present invention is not limited thereto.

[0121] According to an embodiment of the present invention, by using a first predetermined model to perform weather forecasts for each sub-region within the target region, and then using a second predetermined model to perform risk assessment on the weather forecast information of each sub-region, the weather risk information of each sub-region within the target region can be obtained. Since the weather of each sub-region will affect each other to a certain extent, the weather risk information of each sub-region can be used to comprehensively judge the impact of the weather in the target region during the target period on the galloping of the target overhead transmission line, so that it can be accurately determined that the weather forecast 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 forecast information and determine the i-th meteorological risk information includes: obtaining phase information of the target overhead transmission line. And using the second predetermined model to process the i-th meteorological forecast 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 dances, it may be entangled with other conductors, thereby causing a phase-to-phase short circuit, that is, an electrical fault, which affects the stability of the target overhead transmission line. There are differences between the arrangement positions and line directions of conductors of different phases on the pole tower. Therefore, based on the sample phase information, sample meteorological information and risk label information of the overhead transmission line, 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 forecast information and 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, an overhead three-phase conductor is imaged to obtain N frames of continuous 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. The N frames of conductor images of each phase conductor are binarized to obtain N frames of binarized images of each phase conductor. According to the closed image with the largest area in the N frames of binarized images of each phase conductor, feature extraction is performed from each of the N frames of binarized 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, the n-1th 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 conductor, 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 collect images of overhead three-phase conductors to obtain N consecutive frames of conductor images. Then, the foreground (i.e., conductor) and background (other parts except the conductor) in the image of each phase conductor can be labeled respectively. Then, the trained image semantic segmentation algorithm is used to segment the three-phase conductors respectively to obtain images of each phase conductor.

[0126] Then, each frame of the image is binarized, and the largest closed area in the binarized image is retained to obtain a complete and continuous conductor feature. For each phase of the conductor, the n-1th displacement change information can be obtained based on the displacement change of the geometric center of the nth conductor feature relative to the geometric center of the first conductor feature. Therefore, label information corresponding to the sample meteorological information can be constructed based on the phase of the conductor and the displacement change information corresponding to the conductor. In this case, the sample meteorological information and risk label information are used to train the initial model to obtain a trained second predetermined model, and the second predetermined model can be used to process the meteorological forecast information and phase information to obtain accurate meteorological risk information.

[0127] According to an embodiment of the present invention, 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. According to the weather forecast 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 angle information between the wind direction information and the conductor axial information. The minimum temperature information, relative humidity information, maximum wind speed information and angle information are processed by a third predetermined model, and the line galloping level information of the target overhead transmission line is output. 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 or not is closely related to the structure of the conductor after reaching the meteorological conditions prone to galloping, the meteorological forecast 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 forecast information can be obtained, and then the angle information can be calculated according to the wind direction information and the conductor axial information, so that the minimum temperature information, relative humidity information, maximum wind speed information and angle information can be processed by the third predetermined model to obtain the line galloping level information. The third predetermined model can be constructed based on the AdaBoost (adaptive boost) algorithm. For example, the minimum temperature information, relative humidity information, maximum wind speed information and sample angle information and grade label information in the historical meteorological information can be used to train the third initial model to obtain a 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 angle information on the galloping of the overhead transmission line, and the present invention is not limited here.

[0129] For example, the weather forecast information input by the third predetermined model can be expressed as .in, is the lowest temperature information in the weather forecast information. is the relative humidity information in the weather forecast information, is the maximum wind speed information in the weather forecast information, is the angle information corresponding to the weather forecast information.

[0130] The confidence can be calculated by the following formula (17): The confidence can be calculated using formula (17) :

[0131] (17).

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

[0133] , a larger positive (negative) margin indicates a higher confidence in predicting the occurrence (non-occurrence) of dancing on the line, and a smaller margin indicates a lower confidence in the prediction result.

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

[0135] For the level I and II power line galloping warnings with a confidence level greater than 40% in the output results, we should focus on prevention and control, strengthen patrol monitoring, and make dispatch emergency plans; at the same time, we should not take the level III power line galloping warnings with a lower confidence level lightly, and we should be fully prepared to minimize the damage caused by the transmission line galloping.

[0136] Table 6

[0137]

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

[0139] According to an embodiment of the present invention, by combining meteorological information and conductor structure information with the minimum temperature information, relative humidity information, wind speed information and the angle information between the wind direction and the conductor axis, an accurate warning can be given to the dancing condition of the target overhead transmission line within the target time period.

[0140] Figure 5 A flow chart of a power 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 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.

[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 period and the i-th historical meteorological information of the i-th sub-area are processed using a first predetermined model to obtain i-th meteorological forecast information.

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

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

[0145] In operation S550, 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, angle information between the wind direction information and the conductor axial information is determined.

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

[0147] In operation S570, the minimum temperature information, the relative humidity information, the maximum wind speed information, and the angle information are processed using a third predetermined model to output 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-mentioned transmission line galloping warning method, the present invention also provides a transmission line galloping warning system. Figure 6 The system is described in detail.

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

[0151] like Figure 6 As 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 generating module 611 is used to generate the 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 receiving the galloping warning instruction for the target overhead transmission line located in the target area during the target period; the mth weight information represents the importance of the mth galloping prediction index relative to the 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 the evaluation standard, M is an integer greater than 1, and m is a positive integer less than or equal to M. In one embodiment, the first generating module 611 can be used to perform the operation S210 described above, which will not be repeated here.

[0153] The prediction module 612 is used to predict the weather forecast information of the target area in the target period according to the information of the target period and the historical weather information of the target area in response to detecting that the galloping risk information indicates that the target overhead transmission line has a galloping risk. In one embodiment, the prediction module 612 can be used to perform the operation S220 described above, which will not be repeated here.

[0154] The second generation module 613 is used to generate 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 in response to detecting that the weather forecast information meets the predetermined condition. In one embodiment, the second generation module 613 can be used to perform the operation S230 described above, which will not be repeated here.

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

[0156] According to an embodiment of the present invention, the prediction module 612 includes a first processing submodule. The server 610 also includes a second processing submodule, a first determining submodule and a first generating submodule. Among them, the first processing submodule is used to process the information of the target time period and the i-th historical meteorological information of the i-th sub-area using the first predetermined model 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; the second processing submodule is used to process the i-th meteorological forecast information using the second predetermined model to determine the i-th meteorological risk information, the i-th meteorological risk information characterizes the risk probability of the target overhead transmission line dancing under the meteorological conditions of the i-th meteorological forecast information; the first determining submodule is used to determine the target meteorological risk information from I meteorological risk information, the target meteorological risk information characterizes the existence of the target overhead transmission line dancing risk under the meteorological conditions of the meteorological forecast information corresponding to the target meteorological risk information; the first generating submodule is used to generate the dancing risk information characterizing the existence of the dancing risk of the target overhead transmission line 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 the predetermined number.

[0157] According to an embodiment of the present invention, the determination submodule further includes an acquisition unit and a determination unit. The acquisition unit is used to acquire the phase information of the target overhead transmission line; the determination unit is used to process the i-th meteorological forecast information and phase information 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 acquisition module and a third generation module. Among them, the acquisition module is used to acquire images of the overhead three-phase conductors under the meteorological conditions of the sample meteorological information to obtain continuous N frames of conductor images, where N is an integer greater than 1; the segmentation module is used to segment the N frames of conductor images according to the image of each phase conductor in the three-phase conductors in the N frames of conductor images to obtain N frames of conductor images of each phase conductor; the binarization module is used to binarize the N frames of conductor images of each phase conductor to obtain N frames of binarized images of each phase conductor; the extraction module is used to extract features from the N frames of binarized images of each phase conductor according to the closed image with the largest area in the N frames of binarized images of each phase conductor to obtain N frames of conductor features of each phase conductor; the acquisition module is used to obtain the n-1th displacement change information for each phase conductor according to the displacement change of the nth conductor feature relative to the first 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 conductor.

[0159] According to an embodiment of the present invention, the second generation module 613 further includes a second determination submodule, a third processing submodule and a second generation submodule. The second determination submodule is used to determine the angle information between the wind direction information and the conductor axial information; the third processing submodule is used to process the minimum temperature information, relative humidity information, maximum wind speed information and angle information using a third predetermined model, and output the line galloping level information of the target overhead transmission line; the second generation submodule 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 submodule, a division submodule, a fourth processing submodule, a fifth processing submodule and a third generation submodule. The third determination submodule is used to determine the mth target weight information according to the mth weight information, the mth dancing risk value, the M weight information and the M dancing risk value; the division submodule is used to divide the M dancing prediction indicators into J first dancing prediction indicators and K second dancing prediction indicators according to the indicator evaluation standard, the first dancing prediction indicators and the second dancing prediction indicators have different evaluation standards, J and K are positive integers, J+K=M; the fourth processing submodule is used to use the first normalization function to calculate the jth first dancing prediction indicator among the J first dancing prediction indicators The j-th target weight information and the j-th dancing risk value of the prediction indicator are processed to obtain the j-th first indicator value, where j is a positive integer less than or equal to J; the fifth processing submodule is used to use the second normalization function to process the k-th target weight information and the k-th dancing risk value of the k-th second dancing prediction indicator among the K second dancing prediction indicators to obtain the k-th second indicator value, where k is a positive integer less than or equal to K; the third generating submodule is used to generate the dancing risk information of the target overhead transmission line according to the J first indicator values ​​and the K second indicator 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. The collection module is used to collect the initial wind speed information of the target area using a sensor; the first determination module is used 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 used 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 used to process the initial wind speed information using the target wind speed conversion function to obtain the wind speed information.

[0162] According to an embodiment of the present invention, any multiple modules of the first generation module 611, the prediction module 612, and the second generation module 613 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can 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 can 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 a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, at least one of the first generation module 611, the prediction module 612, and the second generation module 613 can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function can be executed.

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

[0164] like Figure 7 As 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 part 708 to a random access memory (RAM) 703. The processor 701 may include, for example, a general-purpose microprocessor (such as a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (for example, an application-specific integrated circuit (ASIC)), etc. The processor 701 may also include an onboard 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 RAM 703, various programs and data required for the operation of electronic device 700 are stored. Processor 701, ROM 702 and RAM 703 are connected to each other via bus 704. Processor 701 performs various operations of the method flow according to the embodiment of the present invention by executing the programs in ROM 702 and / or RAM 703. It should be noted that the program can also be stored in one or more memories other than ROM 702 and RAM 703. Processor 701 can also perform various operations of the method flow according to the embodiment 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, which 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 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 therefrom is 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 embodiment; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment 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: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present invention, the computer-readable storage medium may include the ROM 702 and / or RAM 703 described above and / or one or more memories other than ROM 702 and RAM 703.

[0169] The embodiment of the present invention also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the power transmission line galloping warning method provided in the embodiment of the present invention.

[0170] The computer program executes the above functions defined in the system / device of the embodiment of the present invention when it is executed by the processor 701. According to the embodiment of the present invention, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0171] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 709, and / or installed from the removable medium 711. The program code contained in the computer program may be transmitted using any appropriate 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, the above functions defined in the system of the embodiment of the present invention are performed. According to the embodiment of the present invention, the system, device, means, module, unit, etc. described above can be implemented by a computer program module.

[0173] According to an embodiment of the present invention, the program code for executing the computer program provided by the embodiment of the present invention can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0174] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0175] It will be appreciated by those skilled in the art that the features described in the various embodiments of the present invention may 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 may be combined and / or combined in various ways. All of these combinations and / or combinations fall within the scope of the present invention.

[0176] The embodiments of the present invention are described above. However, these embodiments are only for the purpose of illustration, and are not intended to limit the scope of the present invention. Although each embodiment is described above, it does not mean that the measures in each embodiment cannot be used in combination advantageously. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which should all 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, a line galloping warning result of the target overhead power transmission line is generated according to the weather forecast information and the parameters of the target overhead power transmission line.

2. The method according to claim 1, characterized in that 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.

3. The method according to claim 2, 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.

4. The method according to claim 3, 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.

5. The method according to any one of claims 1 to 4, 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.

6. The method according to any one of claims 1 to 4, 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.

7. The method according to any one of claims 1 to 4, 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.

8. 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; 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 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 the visual interface of the visual terminal device.

9. 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 7.

10. 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 7 are implemented.

Images