A method and system for monitoring a power transmission line tower based on Beidou positioning

Abstract

The application provides a power transmission line tower monitoring method and system based on Beidou positioning, and relates to the technical field of displacement measurement. The method comprises the following steps: determining a power transmission line tower to be monitored; determining a target area to which the power transmission line tower belongs; inputting reference station network data and Beidou ground enhancement station data of the target area into a correction model corresponding to the target area to obtain ionospheric correction numbers and tropospheric correction numbers of the power transmission line tower; sending the ionospheric correction numbers and the tropospheric correction numbers to a Beidou positioning module of the power transmission line tower to obtain Beidou positioning coordinates of the power transmission line tower; obtaining displacement information according to the Beidou positioning coordinates of the power transmission line tower and initial positioning coordinates; obtaining a monitoring result of the power transmission line tower according to the displacement information, an inclination angle, a wind speed, a vibration frequency spectrum and tower structure parameters of the power transmission line tower; and sending the monitoring result of the power transmission line tower to a monitoring center. Accurate monitoring results of the power transmission line tower can be obtained.

Description

Technical Field

[0001] The present application relates to the field of displacement measurement technology, and in particular to a method and system for monitoring transmission line towers based on Beidou positioning. Background Art

[0002] With the expansion of power transmission networks and the intelligent upgrade of communications infrastructure, the need for structural safety monitoring of transmission towers, such as transmission towers and communication towers, is becoming increasingly urgent. Displacement information is a core parameter for tower deformation and stability analysis, and its accuracy directly determines the reliability of structural health assessments.

[0003] However, existing tower positioning technology is affected by environmental interference, insufficient error correction and other issues, resulting in significant deviations in displacement monitoring results, making it difficult to meet the requirements of high-precision, real-time monitoring. Summary of the Invention

[0004] The technical problem to be solved by this application is to provide a method and system for monitoring transmission line towers based on Beidou positioning, which can obtain accurate monitoring results of transmission line towers. The specific solution is as follows:

[0005] A method for monitoring power transmission line towers based on Beidou positioning, the method comprising:

[0006] In response to the monitoring instruction, determining a transmission line tower to be monitored;

[0007] Determining a target area to which the transmission line tower belongs;

[0008] Acquire reference station network data and BeiDou ground-based augmentation station data for a target area where the transmission line tower belongs;

[0009] Inputting the reference station network data and the BeiDou ground-based augmentation station data into the correction model corresponding to the target area to obtain the ionospheric correction number and the tropospheric correction number of the transmission line tower;

[0010] Sending the ionospheric correction number and the tropospheric correction number to the Beidou positioning module of the transmission line tower to obtain the Beidou positioning coordinates of the transmission line tower;

[0011] Obtaining displacement information of the transmission line tower according to the Beidou positioning coordinates and the initial positioning coordinates of the transmission line tower;

[0012] Obtaining monitoring results of the transmission line tower according to displacement information, tilt angle, wind speed, vibration spectrum and tower structure parameters of the transmission line tower;

[0013] The monitoring results of the transmission line tower are sent to a monitoring center.

[0014] In the above method, optionally, the correction model is pre-constructed;

[0015] The construction process of the correction model includes:

[0016] Obtain historical reference station network data, historical BeiDou ground-based augmentation station data for the target area, and terrain relief information;

[0017] Determining, based on the terrain undulation information of the target area, a first weight parameter of the historical reference station network data and a second weight parameter of the historical Beidou ground-based augmentation station data;

[0018] The correction model is constructed based on the historical reference station network data, the first weight parameter, the historical Beidou ground-based augmentation station data and the second weight parameter.

[0019] Optionally, the above method obtains monitoring results of the transmission line tower based on displacement information, tilt angle, wind speed, vibration spectrum, and tower structure parameters of the transmission line tower, including:

[0020] Constructing time series data according to the tilt angle, wind speed, vibration spectrum and displacement information of the transmission line tower;

[0021] Inputting the time series data into a preset time convolution network (TCN) model to obtain the time series characteristics of the transmission line tower;

[0022] The time series features and the tower structure parameters of the transmission line tower are processed using a pre-built classification model to obtain monitoring results of the transmission line tower.

[0023] Optionally, the method described above processes the time series features and the tower structure parameters of the transmission line tower using a pre-built classification model to obtain monitoring results of the transmission line tower, including:

[0024] Inputting the time series characteristics and the tower structure parameters of the transmission line tower into a pre-built classification model to obtain a classification result output by the classification model; the classification result represents the risk level of the transmission line tower;

[0025] Calculating a risk score of the transmission line tower according to the displacement information, the tilt angle, the wind speed, the vibration spectrum, and the risk level;

[0026] The risk score of the transmission line tower is used as the monitoring result of the transmission line tower.

[0027] Optionally, the above method, after obtaining the monitoring result of the transmission line tower, further comprises:

[0028] Input the displacement information, Beidou positioning coordinates, tilt angle, wind speed, vibration spectrum and the monitoring results of the transmission line tower into a three-dimensional GIS platform to obtain a status view of the transmission line tower;

[0029] Output a status view of the transmission line tower.

[0030] A transmission line tower monitoring system based on Beidou positioning, comprising:

[0031] A first determining unit, configured to determine a transmission line tower to be monitored in response to a monitoring instruction;

[0032] A second determining unit is used to determine the target area to which the transmission line tower belongs;

[0033] an acquisition unit, configured to acquire reference station network data and BeiDou ground-based augmentation station data of a target area to which the transmission line tower belongs;

[0034] A first execution unit is configured to input the reference station network data and the BeiDou Ground-Based Augmentation Station data into a correction model corresponding to the target area to obtain ionospheric corrections and tropospheric corrections for the transmission line tower;

[0035] a first transmission unit, configured to transmit the ionospheric correction number and the tropospheric correction number to a Beidou positioning module of the transmission line tower to obtain Beidou positioning coordinates of the transmission line tower;

[0036] A second execution unit is configured to obtain displacement information of the transmission line tower according to the Beidou positioning coordinates and the initial positioning coordinates of the transmission line tower;

[0037] a third execution unit, configured to obtain a monitoring result of the transmission line tower according to the displacement information, tilt angle, wind speed, vibration spectrum and tower structure parameters of the transmission line tower;

[0038] The second transmission unit is used to send the monitoring result of the transmission line tower to the monitoring center.

[0039] In the above system, optionally, the first execution unit is further configured to:

[0040] Obtain historical reference station network data, historical BeiDou ground-based augmentation station data for the target area, and terrain relief information;

[0041] Determining, based on the terrain undulation information of the target area, a first weight parameter of the historical reference station network data and a second weight parameter of the historical Beidou ground-based augmentation station data;

[0042] Modeling is performed based on the historical reference station network data, the first weight parameter, the historical Beidou ground-based augmentation station data, and the second weight parameter to obtain a correction model.

[0043] In the above system, optionally, the third execution unit includes:

[0044] A construction subunit, configured to construct time series data according to the tilt angle, wind speed, vibration spectrum and displacement information of the transmission line tower;

[0045] A first execution subunit is configured to input the time series data into a preset TCN model to obtain time series characteristics of the transmission line tower;

[0046] The second execution subunit is used to process the time series features and the tower structure parameters of the transmission line tower by using a pre-built classification model to obtain a monitoring result of the transmission line tower.

[0047] In the above system, optionally, the second execution subunit includes:

[0048] A first execution module is configured to input the time series characteristics and the tower structure parameters of the transmission line tower into a pre-built classification model to obtain a classification result output by the classification model; the classification result represents the risk level of the transmission line tower;

[0049] a calculation module, configured to calculate a risk score of the transmission line tower based on the displacement information, the tilt angle, the wind speed, the vibration spectrum, and the risk level;

[0050] The second execution module is configured to use the risk score of the transmission line tower as the monitoring result of the transmission line tower.

[0051] The above system may optionally further include:

[0052] a fourth execution unit, configured to input the displacement information, Beidou positioning coordinates, tilt angle, wind speed, vibration spectrum, and monitoring results of the transmission line tower into a three-dimensional GIS platform to obtain a status view of the transmission line tower;

[0053] The output unit is used to output a status view of the transmission line tower.

[0054] Based on the above-mentioned implementation of the present application, a transmission line tower monitoring method and system based on Beidou positioning is provided. In response to a monitoring instruction, a transmission line tower to be monitored is determined; a target area to which the transmission line tower belongs is determined; reference station network data and Beidou ground-based augmentation station data of the target area to which the transmission line tower belongs are obtained; the reference station network data and the Beidou ground-based augmentation station data are input into a correction model corresponding to the target area to obtain ionospheric corrections and tropospheric corrections of the transmission line tower; the ionospheric corrections and the tropospheric corrections are sent to the Beidou positioning module of the transmission line tower to obtain the Beidou positioning coordinates of the transmission line tower; the displacement information of the transmission line tower is obtained based on the Beidou positioning coordinates and initial positioning coordinates of the transmission line tower; the monitoring results of the transmission line tower are obtained based on the displacement information, tilt angle, wind speed, vibration spectrum and tower structure parameters of the transmission line tower; and the monitoring results of the transmission line tower are sent to a monitoring center. Accurate transmission line tower monitoring results can be obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without any creative work.

[0056] Figure 1 A method flow chart of a transmission line tower monitoring method based on Beidou positioning provided in this application;

[0057] Figure 2 A flowchart of the construction process of a correction model provided in this application;

[0058] Figure 3 A flowchart of a process for obtaining monitoring results of a transmission line tower provided in this application;

[0059] Figure 4 This is a schematic diagram of the structure of a transmission line tower monitoring system based on Beidou positioning provided in this application. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0061] In this application, the terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0062] The embodiment of the present invention provides a method for monitoring power transmission line towers based on Beidou positioning, which is applied to the edge service end. The method flow chart of the method is as follows: Figure 1 As shown, specifically including:

[0063] S101: In response to a monitoring instruction, determine a transmission line tower to be monitored.

[0064] In this embodiment, the edge service terminal receives a monitoring instruction from the monitoring center or a preset trigger condition, and the monitoring instruction includes identification information or screening conditions of the tower to be monitored. The identification information may include a number or geographic location code, etc. The screening conditions may include a preset monitoring period, a list of towers associated with abnormal events, etc.

[0065] Optionally, by parsing the monitoring instructions, the edge server matches and extracts the characteristic data of the target tower from the stored transmission line tower database, including but not limited to the tower identification, initial positioning coordinates and associated information of the area to which it belongs, thereby determining the transmission line tower to be monitored. The initial positioning coordinates can be the initial longitude and latitude recorded by the Beidou positioning module.

[0066] In an embodiment, the triggering mechanism of the monitoring instruction may include a timing trigger, an external event trigger, or a manual remote instruction issuance, and the external event may be a meteorological disaster warning event.

[0067] S102: Determine the target area to which the transmission line tower belongs.

[0068] In this embodiment, the tower may be mapped to a corresponding target area based on the initial positioning coordinates of the tower determined in S101 in combination with a preset area division rule.

[0069] In this embodiment, the target area is pre-divided according to the service coverage of the BeiDou Ground-Based Augmentation Station, terrain characteristics (such as undulation information) and power grid management zones, and stored in the regional database of the edge service end.

[0070] Specifically, a spatial matching algorithm is used to compare the tower's coordinates with the target region's spatial boundary data to determine the target region to which it belongs. This target region is used to invoke the corresponding correction model and associated augmentation station data to adapt to the impact of regional differences on ionospheric / tropospheric corrections. The spatial matching algorithm can be geo-fence matching or coordinate range filtering.

[0071] S103: Acquire reference station network data and BeiDou ground-based augmentation station data of the target area to which the transmission line tower belongs.

[0072] In this embodiment, the edge server calls or actively collects two data sources through a preset interface:

[0073] Reference station network data: Real-time or historical observation data (such as pseudoranges, carrier phases, and satellite ephemeris) from a widely distributed network of reference stations are obtained from multiple sites. The reference station network data has a wide coverage area and is used to provide a baseline correction reference for ionospheric and tropospheric delays.

[0074] Beidou Ground-Based Augmentation Station Data: Extracts high-temporal-spatial density augmentation data from Beidou Ground-Based Augmentation Stations deployed in the target area. The data is spatially encrypted and locally optimized for the target area. The augmentation data can be at least one of the following: differential correction signals and regional atmospheric parameters.

[0075] In this embodiment, when acquiring data, the corresponding enhanced station data is screened and associated according to the geographic code or service identifier of the target area to ensure spatial matching between the data and the target area.

[0076] S104: Inputting the reference station network data and the BeiDou ground-based augmentation station data into a correction model corresponding to the target area to obtain ionospheric corrections and tropospheric corrections for the transmission line tower.

[0077] In this embodiment, the acquired reference station network data and Beidou ground-based augmentation station data can be input into the correction model corresponding to the target area. The correction model is a regional customized model, which has integrated terrain undulation information during its construction and assigned dynamic weights to the two types of data.

[0078] The model generates corrections in the following way:

[0079] Ionospheric corrections: Based on the large-scale ionospheric delay distribution provided by the reference station network data and combined with the data from the augmentation stations, the system compensates for disturbances such as scintillation and gradient changes in the local ionosphere, generating high-precision ionospheric delay corrections for the target area.

[0080] Tropospheric correction number: Using the local meteorological parameters such as temperature, humidity and air pressure of the enhancement station data and the tropospheric zenith delay data of the reference station network, the tropospheric path delay correction value at the location of the target tower is calculated through a weighted fusion algorithm.

[0081] S105: Send the ionospheric correction number and the tropospheric correction number to the Beidou positioning module of the transmission line tower to obtain the Beidou positioning coordinates of the transmission line tower.

[0082] In this embodiment, the edge server transmits ionospheric and tropospheric corrections to the BeiDou positioning module on the target tower via wireless communication protocols, triggering the BeiDou positioning module to execute either the real-time kinematic (RTK) or precise point positioning (PPP) algorithms. Based on the raw observation data and the received corrections, the BeiDou positioning module calculates BeiDou positioning coordinates with millimeter- to centimeter-level accuracy. The positioning results are then transmitted back to the edge server via encrypted data packets, completing a closed-loop correction process.

[0083] S106: Obtaining displacement information of the transmission line tower according to the Beidou positioning coordinates and the initial positioning coordinates of the transmission line tower.

[0084] In this embodiment, the initial positioning coordinates of the tower can be retrieved from the storage unit of the edge server. The spatial difference between the real-time Beidou positioning coordinates and the initial coordinates is calculated to generate a three-dimensional displacement vector and a total displacement. The three-dimensional displacement vector can be the displacement in the east, north, and elevation directions.

[0085] Optionally, the displacement data is smoothed by using a Kalman filter or a sliding average algorithm to eliminate short-term noise interference and extract a stable displacement trend.

[0086] S107: Obtain monitoring results of the transmission line tower according to the displacement information, tilt angle, wind speed, vibration spectrum and tower structure parameters of the transmission line tower.

[0087] In this embodiment, the tilt angle can be obtained by the tilt sensor built into the tower; the wind speed can be collected by a meteorological sensor; the vibration spectrum can be the result of the accelerometer frequency domain analysis; and the structural parameters may include information such as material, height, and design load.

[0088] In this embodiment, the tower's tilt angle, wind speed, vibration spectrum, and displacement information can be aligned by timestamp to form a multidimensional time series dataset. A temporal convolutional network model is used to extract features from this time series data, capturing the long-term dependencies and abnormal fluctuation patterns of the tower's dynamic behavior. This yields time series features. This abnormal fluctuation pattern can be the coupled effect of wind speed, vibration, and displacement.

[0089] Optionally, the temporal features output by the Temporal Convolutional Network (TCN) model and the tower structural parameters are fed into a pre-trained classification model (e.g., random forest, neural network) to output a risk classification result (e.g., normal, warning, dangerous). This is further combined with parameters such as displacement, tilt angle exceeding threshold, and wind speed extremes to generate a quantitative risk score using a weighted scoring algorithm as the final monitoring result.

[0090] S108: Sending the monitoring result of the transmission line tower to a monitoring center.

[0091] In this embodiment, the monitoring results may include risk levels or risk scores, etc. The edge server encapsulates the monitoring results, raw sensor data (such as displacement, tilt angle), and Beidou positioning coordinates into a standard data message and transmits it to the remote monitoring center via an encrypted communication link.

[0092] In this embodiment, after receiving the data, the monitoring center can trigger an alarm push, generate a maintenance work order, or start a visualization display on a three-dimensional GIS platform, such as a status view overlaid with a risk heat map.

[0093] In an embodiment provided in the present application, based on the above solution, optionally, the correction model is pre-constructed;

[0094] The construction process of the correction model is as follows: Figure 2 Shown, including:

[0095] S201: Acquire historical reference station network data, historical Beidou ground-based augmentation station data of the target area, and terrain undulation information.

[0096] In this embodiment, a historical observation data set can be obtained from a widely distributed reference station network, including but not limited to ionospheric delay observations, tropospheric zenith delay, satellite ephemeris and multi-band pseudorange / carrier phase data, with a time span covering the typical meteorological and space environment period of the target area.

[0097] Optionally, historical augmentation data can be retrieved from Beidou ground-based augmentation stations deployed in the target area, including differential correction signals, regional atmospheric parameters and high-precision positioning results. The data spatial density must meet the minimum resolution requirements of the terrain characteristics of the target area.

[0098] In this embodiment, the terrain undulation information of the target area can be extracted through a digital elevation model, an airborne lidar point cloud or a geographic information system platform. The terrain undulation information can be a terrain undulation quantitative parameter, such as elevation standard deviation, slope, and surface roughness index, to form a terrain feature vector.

[0099] S202: Determine a first weight parameter of the historical reference station network data and a second weight parameter of the historical Beidou ground-based augmentation station data according to the terrain undulation information of the target area.

[0100] In this embodiment, the first weight parameter and the second weight parameter are dynamically adjusted according to the terrain undulation information. For example, the higher the terrain complexity, the larger the second weight parameter of the enhanced station data is, so as to improve the local correction accuracy.

[0101] Optionally, a mapping relationship between terrain relief parameters and weights of reference station network data and enhanced station data is established. For example, the following rules are used to dynamically assign weights:

[0102] When the slope is less than the preset slope threshold, the first weight parameter of the reference station network data can be set higher (such as 0.7) and the second weight parameter of the enhanced station data can be set lower (such as 0.3), relying on the wide-area datum correction.

[0103] When the slope is not less than the preset slope threshold, the second weight parameter of the enhanced station data can be set to above 0.8 to enhance the correction capability of local atmospheric disturbances and terrain shielding effects.

[0104] In this embodiment, the terrain relief parameters can be converted into weight coefficients through normalization and linear weighting function. For example, the weight formula is defined as:

[0105] , W2=1−W1

[0106] Among them, S is the slope value; k is the terrain sensitivity coefficient, which is calibrated through historical data regression; W1 is the first weight parameter, and W2 is the second weight parameter.

[0107] S203: Constructing the correction model according to the historical reference station network data, the first weight parameter, the historical Beidou ground-based augmentation station data and the second weight parameter.

[0108] In this embodiment, the historical reference station network data and the enhanced station data can be aligned in time and space to eliminate the data acquisition delay and coordinate system differences; the ionospheric delay residual and the tropospheric delay residual are extracted as model training labels.

[0109] A multi-source data fusion model can be constructed using least squares estimation or machine learning algorithms (such as random forests and gradient boosting trees). Input features include the wide-area correction value of the reference station network, the local correction value of the augmentation station, and the terrain feature vector. W1 and W2 are introduced as feature weights. The model output is a combined correction for the ionospheric and tropospheric delays in the target area.

[0110] The model accuracy is evaluated through cross-validation and residual analysis, and the hyperparameters in the weight mapping rule are adjusted using the particle swarm optimization (PSO) algorithm until the root mean square error (RMSE) of the model on the test set meets the preset threshold (e.g., ≤2 cm).

[0111] In one embodiment provided in the present application, based on the above-mentioned solution, optionally, a process of obtaining monitoring results of the transmission line tower according to the displacement information, tilt angle, wind speed, vibration spectrum and tower structure parameters of the transmission line tower is as follows: Figure 3 Shown, including:

[0112] S301: Constructing time series data according to the tilt angle, wind speed, vibration spectrum and displacement information of the transmission line tower.

[0113] In this embodiment, the sensors that can collect the tilt angle, wind speed, vibration spectrum and displacement information are time-stamp aligned through a unified clock source, and then the tilt angle, wind speed, vibration spectrum and displacement information are arranged in chronological order using a preset time window to generate time series data, that is, a multi-dimensional feature matrix.

[0114] S302: Input the time series data into a preset time convolution network (TCN) model to obtain the time series characteristics of the transmission line tower.

[0115] In this embodiment, time series data is input into the TCN model, processed by multi-layer convolution and nonlinear activation function, and a high-dimensional time series feature vector is output.

[0116] For example, the TCN model can automatically identify the following patterns:

[0117] Vibration-wind speed coupling effect: the vibration energy mutation corresponding to the tower resonant frequency at a specific wind speed;

[0118] Displacement hysteresis response: the delayed correlation between tilt angle and displacement after the continuous action of strong wind.

[0119] S303: Processing the time series features and the tower structure parameters of the transmission line tower using a pre-built classification model to obtain monitoring results of the transmission line tower.

[0120] In this embodiment, the time series feature vectors and tower structure parameters output by TCN can be input into the classification model. The time series feature vectors can be dynamic behavior representations, and the tower structure parameters can include material strength, design height, load, tower base type, etc.

[0121] In this embodiment, a random forest or deep neural network (DNN) can be used to train a classifier through supervised learning. The label data is the risk level divided by historical fault cases. The risk level can be divided into normal, warning, dangerous, etc.

[0122] In this embodiment, the probability distribution of each risk level may be determined, and the risk level corresponding to the maximum probability may be selected as the classification result.

[0123] In one embodiment provided in the present application, based on the above solution, optionally, the using of a pre-built classification model to process the time series features and the tower structure parameters of the transmission line tower to obtain the monitoring results of the transmission line tower includes:

[0124] Inputting the time series characteristics and the tower structure parameters of the transmission line tower into a pre-built classification model to obtain a classification result output by the classification model; the classification result represents the risk level of the transmission line tower;

[0125] Calculating a risk score of the transmission line tower according to the displacement information, the tilt angle, the wind speed, the vibration spectrum, and the risk level;

[0126] The risk score of the transmission line tower is used as the monitoring result of the transmission line tower.

[0127] In this embodiment, the risk score of the transmission line tower is calculated as follows:

[0128]

[0129] Where R is the risk score, is the displacement, is the displacement weight; is the tilt angle deviation value, determined based on the tilt angle, is the weight of the tilt angle deviation value; V is the vibration energy anomaly index, which is determined based on the vibration spectrum. is the weight of the vibration energy anomaly index; C is the risk level coefficient, which is determined based on the risk level in the classification result. is the weight of the risk level coefficient.

[0130] In an embodiment provided in the present application, based on the above solution, optionally, after obtaining the monitoring result of the transmission line tower, the method further includes:

[0131] Input the displacement information, Beidou positioning coordinates, tilt angle, wind speed, vibration spectrum and the monitoring results of the transmission line tower into a three-dimensional GIS platform to obtain a status view of the transmission line tower;

[0132] outputting a state view of the power transmission line tower.

[0133] In this embodiment, the Beidou positioning coordinates, displacement vector, tilt angle and other data of the tower are input into a three-dimensional GIS platform, and are spatially matched with the pre-stored three-dimensional model of the tower.

[0134] Based on the monitoring results, the model state is dynamically rendered, for example, the displacement direction and magnitude are represented by the length / color of the arrow; and the tower model is color-coded according to the risk score.

[0135] In this embodiment, data synchronization is maintained with the edge server through the WebSocket communication protocol, realizing second-level refreshing of the monitoring results. And it supports clicking the tower model to view detailed parameters such as vibration spectrum graph and risk score history curve.

[0136] Referring to Figure 4 A structure schematic diagram of a power transmission line tower monitoring system based on Beidou positioning is provided for the embodiments of the present application, and the system comprises:

[0137] The first determination unit 401 is configured to determine a power transmission line tower to be monitored in response to a monitoring instruction.

[0138] The second determination unit 402 is configured to determine a target area to which the power transmission line tower belongs.

[0139] The acquisition unit 403 is configured to acquire reference station network data and Beidou ground-based augmentation station data of a target area to which the power transmission line tower belongs.

[0140] The first execution unit 404 is configured to input the reference station network data and the Beidou ground-based augmentation station data into a correction model corresponding to the target area, to obtain ionospheric correction numbers and tropospheric correction numbers of the power transmission line tower.

[0141] The first transmission unit 405 is configured to send the ionospheric correction numbers and the tropospheric correction numbers to a Beidou positioning module of the power transmission line tower, to obtain Beidou positioning coordinates of the power transmission line tower.

[0142] The second execution unit 406 is configured to obtain displacement information of the power transmission line tower according to the Beidou positioning coordinates of the power transmission line tower and initial positioning coordinates.

[0143] The third execution unit 407 is configured to obtain monitoring results of the power transmission line tower according to the displacement information of the power transmission line tower, a tilt angle, a wind speed, a vibration spectrum and tower structure parameters.

[0144] The second transmission unit 408 is configured to send the monitoring results of the power transmission line tower to a monitoring center.

[0145] In the above system, optionally, the first execution unit 404 is further configured to:

[0146] Obtain historical reference station network data, historical BeiDou ground-based augmentation station data for the target area, and terrain relief information;

[0147] Determining, based on the terrain undulation information of the target area, a first weight parameter of the historical reference station network data and a second weight parameter of the historical Beidou ground-based augmentation station data;

[0148] Modeling is performed based on the historical reference station network data, the first weight parameter, the historical Beidou ground-based augmentation station data, and the second weight parameter to obtain a correction model.

[0149] In the above system, optionally, the third execution unit 406 includes:

[0150] A construction subunit, configured to construct time series data according to the tilt angle, wind speed, vibration spectrum and displacement information of the transmission line tower;

[0151] A first execution subunit is configured to input the time series data into a preset TCN model to obtain time series characteristics of the transmission line tower;

[0152] The second execution subunit is used to process the time series features and the tower structure parameters of the transmission line tower by using a pre-built classification model to obtain a monitoring result of the transmission line tower.

[0153] In the above system, optionally, the second execution subunit includes:

[0154] A first execution module is configured to input the time series characteristics and the tower structure parameters of the transmission line tower into a pre-built classification model to obtain a classification result output by the classification model; the classification result represents the risk level of the transmission line tower;

[0155] a calculation module, configured to calculate a risk score of the transmission line tower based on the displacement information, the tilt angle, the wind speed, the vibration spectrum, and the risk level;

[0156] The second execution module is configured to use the risk score of the transmission line tower as the monitoring result of the transmission line tower.

[0157] The above system may optionally further include:

[0158] a fourth execution unit, configured to input the displacement information, Beidou positioning coordinates, tilt angle, wind speed, vibration spectrum, and monitoring results of the transmission line tower into a three-dimensional GIS platform to obtain a status view of the transmission line tower;

[0159] The output unit is used to output a status view of the transmission line tower.

[0160] It should be noted that the various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the various embodiments can be referenced to each other.

[0161] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0162] For the convenience of description, the above devices are described as being divided into various units according to their functions. Of course, when implementing this application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0163] Through the description of the above embodiments, it can be seen that those skilled in the art can clearly understand that the present application can be implemented by means of software plus the necessary general hardware platform. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present application or certain parts of the embodiments.

[0164] The above is a detailed introduction to a transmission line tower monitoring method based on Beidou positioning provided by this application. This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method of this application and its core idea; at the same time, for general technical personnel in this field, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on this application.

Claims

1. A transmission line tower monitoring method based on Beidou positioning, characterized in that: include: In response to the monitoring instruction, determining a transmission line tower to be monitored; Determine a target area to which the transmission line tower belongs, where the target area is pre-divided based on the service coverage of the BeiDou Ground-Based Augmentation Station, terrain characteristics, and power grid management zones; Acquire reference station network data and BeiDou ground-based augmentation station data for a target area where the transmission line tower belongs; Inputting the reference station network data and the BeiDou Ground-Based Augmentation Station data into a correction model corresponding to the target area to obtain ionospheric corrections and tropospheric corrections for the transmission line tower, wherein the correction model is pre-built; Sending the ionospheric correction number and the tropospheric correction number to the Beidou positioning module of the transmission line tower to obtain the Beidou positioning coordinates of the transmission line tower; Obtaining displacement information of the transmission line tower according to the Beidou positioning coordinates and the initial positioning coordinates of the transmission line tower; Constructing time series data according to the tilt angle, wind speed, vibration spectrum and displacement information of the transmission line tower; Inputting the time series data into a preset time convolutional network (TCN) model, so that the TCN model captures the long-term dependency and abnormal fluctuation pattern of the dynamic behavior of the transmission line tower to obtain time series features, wherein the abnormal fluctuation pattern includes the coupling effect of wind speed, vibration, and displacement; Inputting the time series characteristics and the tower structure parameters of the transmission line tower into a pre-built classification model to obtain the risk level of the transmission line tower; Calculating a risk score of the transmission line tower according to the displacement information, the tilt angle, the wind speed, the vibration spectrum, and the risk level; Using the risk score of the transmission line tower as the monitoring result of the transmission line tower; Sending the monitoring results of the transmission line tower to a monitoring center; The process of constructing the correction model includes: Obtain historical reference station network data, historical BeiDou ground-based augmentation station data for the target area, and terrain relief information; A first weight parameter is calculated based on normalization processing and a linear weighting function, a slope value in the terrain relief information, and a terrain sensitivity coefficient, and a second weight parameter is determined based on the first weight parameter; The correction model is constructed based on the historical reference station network data, the first weight parameter, the historical Beidou ground-based augmentation station data and the second weight parameter.

2. The method according to claim 1, characterized in that After obtaining the monitoring result of the transmission line tower, the method further includes: Input the displacement information, Beidou positioning coordinates, tilt angle, wind speed, vibration spectrum and the monitoring results of the transmission line tower into a three-dimensional GIS platform to obtain a status view of the transmission line tower; Output a status view of the transmission line tower.

3. A transmission line tower monitoring system based on Beidou positioning, characterized in that: include: A first determining unit, configured to determine a transmission line tower to be monitored in response to a monitoring instruction; A second determining unit is used to determine the target area to which the transmission line tower belongs; The target area is pre-divided based on the service coverage of the BeiDou Ground-Based Augmentation Station, terrain characteristics, and power grid management zones; an acquisition unit, configured to acquire reference station network data and BeiDou ground-based augmentation station data of a target area to which the transmission line tower belongs; a first execution unit, configured to input the reference station network data and the BeiDou Ground-Based Augmentation Station data into a correction model corresponding to the target area to obtain ionospheric corrections and tropospheric corrections for the transmission line tower, wherein the correction model is pre-built; a first transmission unit, configured to transmit the ionospheric correction number and the tropospheric correction number to a Beidou positioning module of the transmission line tower to obtain Beidou positioning coordinates of the transmission line tower; A second execution unit is configured to obtain displacement information of the transmission line tower according to the Beidou positioning coordinates and the initial positioning coordinates of the transmission line tower; a third execution unit, configured to obtain a monitoring result of the transmission line tower according to the displacement information, tilt angle, wind speed, vibration spectrum and tower structure parameters of the transmission line tower; A second transmission unit, configured to transmit the monitoring result of the transmission line tower to a monitoring center; The third execution unit includes: A construction subunit, configured to construct time series data according to the tilt angle, wind speed, vibration spectrum and displacement information of the transmission line tower; a first execution subunit, configured to input the time series data into a preset time convolutional network (TCN) model, so that the TCN model captures the long-term dependencies and abnormal fluctuation patterns of the dynamic behavior of the transmission line tower to obtain time series features, wherein the abnormal fluctuation pattern includes a coupling effect of wind speed, vibration, and displacement; A second execution subunit is configured to process the time series features and the tower structure parameters of the transmission line tower using a pre-built classification model to obtain a monitoring result of the transmission line tower; The second execution subunit includes: A first execution module is configured to input the time series characteristics and the tower structure parameters of the transmission line tower into a pre-built classification model to obtain a classification result output by the classification model; the classification result represents the risk level of the transmission line tower; a calculation module, configured to calculate a risk score of the transmission line tower based on the displacement information, the tilt angle, the wind speed, the vibration spectrum, and the risk level; A second execution module is configured to use the risk score of the transmission line tower as the monitoring result of the transmission line tower; The first execution unit is further configured to: Obtain historical reference station network data, historical BeiDou ground-based augmentation station data for the target area, and terrain relief information; A first weight parameter is calculated based on normalization processing and a linear weighting function, a slope value in the terrain relief information, and a terrain sensitivity coefficient, and a second weight parameter is determined based on the first weight parameter; The correction model is constructed based on the historical reference station network data, the first weight parameter, the historical Beidou ground-based augmentation station data and the second weight parameter.

4. The system according to claim 3, characterized in that Also includes: a fourth execution unit, configured to input the displacement information, Beidou positioning coordinates, tilt angle, wind speed, vibration spectrum, and monitoring results of the transmission line tower into a three-dimensional GIS platform to obtain a status view of the transmission line tower; The output unit is used to output a status view of the transmission line tower.

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