Distribution line construction safety management method based on Beidou

Abstract

The invention relates to the technical field of line construction safety management, and discloses a Beidou-based distribution line construction safety management method, which comprises the steps of constructing a distribution line construction area terrain index system, carrying out terrain index data acquisition on the distribution line area according to the constructed index system by utilizing a Beidou positioning technology to obtain a terrain index value; performing feature extraction on different areas of the distribution line by combining the distribution line azimuth information and the acquired topographic index values to obtain feature vectors of the different areas of the distribution line; and a distribution line icing area risk early warning model is constructed to carry out icing risk early warning on different areas of the distribution line, corresponding protection measures are taken according to the risk early warning levels of the different areas of the distribution line to carry out safety construction, and the construction safety and effect are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of line construction safety management, and in particular to a Beidou-based distribution line construction safety management method. Background Art

[0002] With the rapid economic development and the advancement of urbanization, the demand for electricity continues to grow. As an important part of the power system, the safe and reliable operation of distribution lines is of great significance to the national economy and social development. As an important part of the modern power system, transmission lines carry the important task of transmitting electricity from power plants to users. However, in cold areas, especially in winter, transmission lines are often affected by icing, which poses a challenge to the safe operation of the power system. Icing refers to the accumulation of ice on the surface of the conductor under extreme low temperature conditions. These ice layers increase the weight of the conductor and increase the sag of the conductor, which may cause the wire to break or cause the tower to overturn. In addition, the ice layer may also affect the spacing between the conductor and the insulator, increasing the risk of breakdown between the conductor and the ground or other conductors. In order to effectively remove the line icing, it is necessary to formulate corresponding terrain identification and safe construction methods for different terrain and climatic conditions to ensure the safe operation of the transmission line. Summary of the invention

[0003] In view of this, the present invention proposes a Beidou-based distribution line construction safety management method, which uses the high-precision positioning technology of the Beidou system to monitor the environmental conditions of transmission lines in different areas in real time, helping power system operators to better manage icing problems, and ensure the safety of people’s lives and property and the stable operation of the power system.

[0004] To achieve the above object, the present invention provides a Beidou-based distribution line construction safety management method, comprising the following steps:

[0005] S1: Construct a terrain index system for the distribution line construction area, and use Beidou positioning technology to collect terrain index data for the distribution line area according to the constructed index system to obtain terrain index values;

[0006] S2: extracting features of different areas of the distribution line by combining the distribution line location information and the collected terrain index values ​​to obtain feature vectors of different areas of the distribution line;

[0007] S3: Constructing a distribution line icing area risk warning model to provide icing risk warning for different areas of the distribution line, wherein weighted nearest neighbor analysis is an implementation method of the icing area risk warning model;

[0008] S4: Take corresponding protective measures for safe construction according to the risk warning levels of different areas of the distribution lines.

[0009] Optionally, in step S1, a terrain index system for the distribution line construction area is constructed, and terrain index data of the distribution line area is collected according to the constructed index system using Beidou positioning technology to obtain terrain index values, including:

[0010] S11: The terrain index system of the distribution line construction area includes terrain parameter index and terrain morphology index. The terrain parameter index includes slope, slope direction, ground curvature, terrain undulation and surface roughness. The terrain morphology index includes mountain top point, valley point and saddle point.

[0011] S12: Use Beidou positioning to accurately obtain the track position coordinates of the UAV. During the UAV cruising process, laser ranging is performed on the target area to obtain the relative position coordinates of the target point relative to the UAV. The precise position coordinates of the target area are obtained based on the track position coordinates of the UAV and the relative position coordinates of the target area.

[0012] S13: Calculate the terrain index of the distribution line construction area according to the calculated precise position coordinates of the target area to obtain a terrain index value.

[0013] Optionally, in the step S12, the drone cruise process performs laser ranging on the target area to obtain the relative position coordinates of the target point relative to the drone, including:

[0014] S12.1: The UAV is equipped with a laser sensor to perform laser ranging on the target area during flight to obtain the distance information between the target point and the UAV;

[0015] S12.2: using an inertial measurement unit on the drone to obtain attitude information of the drone, where the attitude information includes a pitch angle and a roll angle;

[0016] S12.3: Based on the distance information obtained by laser ranging and the drone attitude information, calculate the relative position coordinates of the target point relative to the drone. The calculation formula is:

[0017] x rel =d·cos(θ)·sin(φ)

[0018] y rel =d·sin(θ)

[0019] z rel =d·cos(θ)·cos(φ)

[0020] in:

[0021] d represents the distance between the target point and the UAV;

[0022] θ represents the pitch angle, which is the up and down rotation angle of the drone;

[0023] φ represents the roll angle, which is the left and right rotation angle of the drone;

[0024] (x rel ,y rel ,z rel ) represents the position coordinates of the target point relative to the UAV.

[0025] Optionally, in step S13, the terrain index of the distribution line construction area is calculated according to the calculated precise position coordinates of the target area to obtain a terrain index value, including:

[0026] The slope represents the inclination of the terrain surface, and the calculation formula is:

[0027]

[0028] in:

[0029] and They represent the rate of change of the terrain height z at the coordinate (x, y, z) relative to the horizontal directions x and y respectively;

[0030] The slope aspect represents the azimuth of the slope surface relative to the true north direction, and the calculation formula is:

[0031]

[0032] The ground curvature indicates the degree of concavity and convexity of the ground surface, including profile curvature and plane curvature, wherein the profile curvature calculation formula is:

[0033]

[0034] The plane curvature calculation formula is:

[0035]

[0036] The terrain relief represents the difference between the elevation of the regional location and the average elevation of the region, and the calculation formula is:

[0037]

[0038] in:

[0039] z i represents the elevation of point i;

[0040] Indicates the average elevation of all points in the area;

[0041] The surface roughness indicates the undulation of the local terrain surface, and the calculation formula is:

[0042]

[0043] in:

[0044] n represents the number of points in the area.

[0045] Optionally, in step S2, feature extraction is performed on different areas of the distribution line in combination with the distribution line location information and the collected terrain index values ​​to obtain feature vectors of different areas of the distribution line, including:

[0046] S21: according to the distribution line location information, a circular area with a preset radius is used and the center of the circle is placed on the distribution line to move according to the distribution line location information to obtain terrain index information in the circular area during the movement process, and feature extraction is performed to obtain terrain feature vectors of different areas;

[0047] S22: Extracting circular area features including statistical features and terrain features, and combining the extracted features into a vector, wherein the statistical features include:

[0048] Mean: the average value of the elevation of all points in the circular area;

[0049] Standard deviation: the standard deviation of the elevation of all points in the circular area;

[0050] Maximum value: the maximum value of all point elevations in the circular area;

[0051] Minimum value: the minimum value of all point elevations in the circular area;

[0052] Median: The median of all point elevations within the circular area;

[0053] The terrain features include the regional slope mean, regional aspect mean, regional surface roughness, and whether the region contains mountain tops, valley points, and saddle points;

[0054] S23: Performing terrain semantic coding on the combined vector to obtain a terrain feature vector, wherein a sparse autoencoder is an implementation method of the semantic coding.

[0055] Optionally, in step S23, performing terrain semantic coding on the combined vector to obtain a terrain feature vector includes:

[0056] The terrain semantic coding includes an encoder, a sparse constraint and a decoder, wherein the encoder encodes the combined vector through a hidden layer and maps the data to a low-dimensional vector representation; the sparse constraint captures the key terrain features in the low-dimensional vector through KL divergence to obtain a sparse low-dimensional vector; the decoder receives the sparse low-dimensional vector, and restores the combined vector through reverse mapping and reconstruction. The encoding process calculation formula of the encoder is:

[0057] h=f(Wx+b)

[0058] in:

[0059] f(·) represents the activation function;

[0060] W represents the weight of the encoder;

[0061] b represents the encoder bias term;

[0062] The sparsification constraint calculation formula is:

[0063]

[0064] in:

[0065] Ω(h) represents the sparsity constraint term;

[0066] h represents the encoder output vector;

[0067] represents the vector after sparse processing;

[0068] The decoder calculation formula is:

[0069]

[0070] in:

[0071] g(·) represents the activation function of the decoder;

[0072] W ′ represents the weight of the decoder;

[0073] b ′ Represents the decoder bias term.

[0074] Optionally, in step S3, constructing a distribution line icing area risk warning model to provide icing risk warning for different areas of the distribution line includes:

[0075] S31: for the terrain feature vector v1 obtained by encoding, calculating the Euclidean distance between v1 and other terrain feature vectors;

[0076] S32: according to a preset K value, determine a set of K terrain feature vectors closest to v1 as a neighbor set of v1;

[0077] S33: Calculate the weight of each terrain feature vector according to the distance from v1 to each terrain feature vector in the neighboring set. The calculation formula is:

[0078]

[0079] in;

[0080] d irepresents the distance from v1 to the i-th nearest neighbor terrain feature vector;

[0081] S34: Based on the calculated weight, a voting decision is made to determine the icing risk level of v1. The calculation formula is:

[0082]

[0083] in:

[0084] represents the predicted icing risk level of the terrain feature vector;

[0085] w i represents the weight of the i-th nearest neighbor terrain feature vector;

[0086] y i represents the icing risk level of the i-th nearest neighbor terrain feature vector;

[0087] j represents the icing risk level;

[0088] i represents the nearest neighbor terrain feature vector index;

[0089] Represents an indicator function, which returns 1 if the condition in the brackets is true, otherwise it returns 0.

[0090] Optionally, step S4 takes corresponding protective measures to carry out safe construction according to the risk warning levels of different areas of the distribution line.

[0091] In order to solve the above problem, the present invention provides an electronic device, the electronic device comprising:

[0092] A memory storing at least one instruction;

[0093] Communication interface, enabling electronic equipment to communicate; and

[0094] The processor executes the instructions stored in the memory to implement the above-mentioned Beidou-based distribution line construction safety management method.

[0095] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored. The at least one instruction is executed by a processor in an electronic device to implement the above-mentioned Beidou-based distribution line construction safety management method.

[0096] Compared with the prior art, the present invention proposes a Beidou-based distribution line construction safety management method, which has the following advantages:

[0097] First, this scheme proposes a terrain indicator system for the distribution line construction area. By systematically classifying and summarizing the terrain features, a complete indicator system is constructed, which can more accurately describe the terrain conditions of the construction area and provide basic data for subsequent feature extraction and risk warning.

[0098] At the same time, this scheme extracts features from different areas by combining the location information of the distribution line and the collected terrain index values, and obtains the feature vectors of different areas of the distribution line, which can more comprehensively reflect the terrain characteristics of each area and provide a basis for subsequent risk warnings.

[0099] In addition, this scheme proposes an icing area risk warning model based on weighted nearest neighbor analysis. By performing weighted K nearest neighbor algorithm analysis on the feature vectors of different areas, the icing risk of distribution lines can be accurately predicted, helping construction personnel to identify potential icing risk areas in a timely manner and improve the safety and effectiveness of construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0100] Figure 1 A schematic diagram of a flow chart of a Beidou-based power distribution line construction safety management method provided by an embodiment of the present invention;

[0101] Figure 2 A schematic diagram of the structure of an electronic device for implementing a Beidou-based distribution line construction safety management method provided by one embodiment of the present invention.

[0102] In the figure: 1 electronic device, 10 processor, 11 memory, 12 program, 13 communication interface.

[0103] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0104] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0105] The embodiment of the present application provides a Beidou-based distribution line construction safety management method. The execution subject of the Beidou-based distribution line construction safety management method includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided in the embodiment of the present application. In other words, the Beidou-based distribution line construction safety management method can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0106] Embodiment 1:

[0107] S1: Construct a terrain index system for the distribution line construction area, and use Beidou positioning technology to collect terrain index data for the distribution line area according to the constructed index system to obtain terrain index values.

[0108] In the step S1, a terrain index system for the distribution line construction area is constructed, and the terrain index data of the distribution line area is collected according to the constructed index system using Beidou positioning technology to obtain terrain index values, including:

[0109] S11: The terrain index system of the distribution line construction area includes terrain parameter index and terrain morphology index. The terrain parameter index includes slope, slope direction, ground curvature, terrain undulation and surface roughness. The terrain morphology index includes mountain top point, valley point and saddle point.

[0110] S12: Use Beidou positioning to accurately obtain the track position coordinates of the UAV. During the UAV cruising process, laser ranging is performed on the target area to obtain the relative position coordinates of the target point relative to the UAV. The precise position coordinates of the target area are obtained based on the track position coordinates of the UAV and the relative position coordinates of the target area.

[0111] S13: Calculate the terrain index of the distribution line construction area according to the calculated precise position coordinates of the target area to obtain a terrain index value.

[0112] In the step S12, the drone cruise process performs laser ranging on the target area to obtain the relative position coordinates of the target point relative to the drone, including:

[0113] S12.1: The UAV is equipped with a laser sensor to perform laser ranging on the target area during flight to obtain the distance information between the target point and the UAV;

[0114] S12.2: using an inertial measurement unit on the drone to obtain attitude information of the drone, where the attitude information includes a pitch angle and a roll angle;

[0115] S12.3: Based on the distance information obtained by laser ranging and the drone attitude information, calculate the relative position coordinates of the target point relative to the drone. The calculation formula is:

[0116] x rel =d·cos(θ)·sin(φ)

[0117] y rel =d·sin(θ)

[0118] z rel =d·cos(θ)·cos(φ)

[0119] in:

[0120] d represents the distance between the target point and the UAV;

[0121] θ represents the pitch angle, which is the up and down rotation angle of the drone;

[0122] φ represents the roll angle, which is the left and right rotation angle of the drone;

[0123] (x rel ,y rel ,z rel ) represents the position coordinates of the target point relative to the UAV.

[0124] In the step S13, the terrain index of the distribution line construction area is calculated according to the calculated precise position coordinates of the target area to obtain the terrain index value, including:

[0125] The slope represents the inclination of the terrain surface, and the calculation formula is:

[0126]

[0127] in:

[0128] and They represent the rate of change of the terrain height z at the coordinate (x, y, z) relative to the horizontal directions x and y respectively;

[0129] The slope aspect represents the azimuth of the slope surface relative to the true north direction, and the calculation formula is:

[0130]

[0131] The ground curvature indicates the degree of concavity and convexity of the ground surface, including profile curvature and plane curvature, wherein the profile curvature calculation formula is:

[0132]

[0133] The plane curvature calculation formula is:

[0134]

[0135] The terrain relief represents the difference between the elevation of the regional location and the average elevation of the region, and the calculation formula is:

[0136]

[0137] in:

[0138] z i represents the elevation of point i;

[0139] Indicates the average elevation of all points in the area;

[0140] The surface roughness indicates the degree of undulation of the local terrain surface, and the calculation formula is:

[0141]

[0142] in:

[0143] n represents the number of points in the area.

[0144] S2: Combine the distribution line location information and the collected terrain index values ​​to extract features of different areas of the distribution line to obtain feature vectors of different areas of the distribution line.

[0145] In the step S2, feature extraction is performed on different areas of the distribution line in combination with the distribution line location information and the collected terrain index values ​​to obtain feature vectors of different areas of the distribution line, including:

[0146] S21: according to the distribution line location information, a circular area with a preset radius is used and the center of the circle is placed on the distribution line to move according to the distribution line location information to obtain terrain index information in the circular area during the movement process, and feature extraction is performed to obtain terrain feature vectors of different areas;

[0147] S22: Extracting circular area features including statistical features and terrain features, and combining the extracted features into a vector, wherein the statistical features include:

[0148] Mean: the average value of the elevation of all points in the circular area;

[0149] Standard deviation: the standard deviation of the elevation of all points in the circular area;

[0150] Maximum value: the maximum value of all point elevations in the circular area;

[0151] Minimum value: the minimum value of all point elevations in the circular area;

[0152] Median: The median of all point elevations within the circular area;

[0153] The terrain features include the regional slope mean, regional aspect mean, regional surface roughness, and whether the region contains mountain tops, valley points, and saddle points;

[0154] S23: Performing terrain semantic coding on the combined vector to obtain a terrain feature vector, wherein a sparse autoencoder is an implementation method of the semantic coding.

[0155] In the step S23, terrain semantic encoding is performed on the combined vector to obtain a terrain feature vector, including:

[0156] The terrain semantic coding includes an encoder, a sparse constraint and a decoder, wherein the encoder encodes the combined vector through a hidden layer and maps the data to a low-dimensional vector representation; the sparse constraint captures the key terrain features in the low-dimensional vector through KL divergence to obtain a sparse low-dimensional vector; the decoder receives the sparse low-dimensional vector, and restores the combined vector through reverse mapping and reconstruction. The encoding process calculation formula of the encoder is:

[0157] h=f(Wx+b)

[0158] in:

[0159] f(·) represents the activation function;

[0160] W represents the weight of the encoder;

[0161] b represents the encoder bias term;

[0162] The sparsification constraint calculation formula is:

[0163]

[0164] in:

[0165] Ω(h) represents the sparsity constraint term;

[0166] h represents the encoder output vector;

[0167] represents the vector after sparse processing;

[0168] The decoder calculation formula is:

[0169]

[0170] in:

[0171] g(·) represents the activation function of the decoder;

[0172] W ′ represents the weight of the decoder;

[0173] b ′ Represents the decoder bias term.

[0174] S3: Construct a distribution line icing area risk warning model to provide icing risk warning for different areas of the distribution line, wherein weighted nearest neighbor analysis is an implementation method of the icing area risk warning model.

[0175] In the step S3, a distribution line icing area risk warning model is constructed to provide icing risk warning for different areas of the distribution line, including:

[0176] S31: for the terrain feature vector v1 obtained by encoding, calculating the Euclidean distance between v1 and other terrain feature vectors;

[0177] S32: according to a preset K value, determine a set of K terrain feature vectors closest to v1 as a neighbor set of v1;

[0178] S33: Calculate the weight of each terrain feature vector according to the distance from v1 to each terrain feature vector in the neighboring set. The calculation formula is:

[0179]

[0180] in;

[0181] d i represents the distance from v1 to the i-th nearest neighbor terrain feature vector;

[0182] S34: Based on the calculated weight, a voting decision is made to determine the icing risk level of v1. The calculation formula is:

[0183]

[0184] in:

[0185] represents the predicted icing risk level of the terrain feature vector;

[0186] w i represents the weight of the i-th nearest neighbor terrain feature vector;

[0187] y i represents the icing risk level of the i-th nearest neighbor terrain feature vector;

[0188] j represents the icing risk level;

[0189] i represents the nearest neighbor terrain feature vector index;

[0190] Represents an indicator function, which returns 1 if the condition in the brackets is true, otherwise it returns 0.

[0191] S4: Take corresponding protective measures for safe construction according to the risk warning levels of different areas of the distribution lines.

[0192] Embodiment 2:

[0193] like Figure 2 , is a schematic diagram of the structure of an electronic device for implementing a Beidou-based distribution line construction safety management method provided by an embodiment of the present invention.

[0194] The electronic device 1 may include a processor 10 , a memory 11 , a communication interface 13 and a bus, and may also include a computer program stored in the memory 11 and executable on the processor 10 , such as a program 12 .

[0195] The memory 11 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. The memory 11 may be an internal storage unit of the electronic device 1 in some embodiments, such as a mobile hard disk of the electronic device 1. The memory 11 may also be an external storage device of the electronic device 1 in other embodiments, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 1. Further, the memory 11 may also include both an internal storage unit of the electronic device 1 and an external storage device. The memory 11 may be used not only to store application software and various types of data installed in the electronic device 1, such as the code of the program 12, etc., but also to temporarily store data that has been output or is to be output.

[0196] The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect the various components of the entire electronic device, and executes or executes the programs or modules stored in the memory 11 (such as the program 12 for realizing the safety management of power distribution line construction based on Beidou), and calls the data stored in the memory 11 to execute various functions of the electronic device 1 and process data.

[0197] The communication interface 13 may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device 1 and other electronic devices, and to achieve connection and communication between internal components of the electronic device.

[0198] The bus may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0199] Figure 2 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 2 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0200] For example, although not shown, the electronic device 1 may also include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include any components such as one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, etc. The electronic device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0201] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device 1 and to display a visual user interface.

[0202] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0203] The program 12 stored in the memory 11 in the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve:

[0204] Construct a terrain index system for the distribution line construction area, and use Beidou positioning technology to collect terrain index data for the distribution line area according to the constructed index system to obtain terrain index values;

[0205] Combining the distribution line location information and the collected terrain index values, feature extraction is performed on different areas of the distribution line to obtain feature vectors of different areas of the distribution line;

[0206] Construct a distribution line icing area risk warning model to provide icing risk warning for different areas of the distribution line;

[0207] Take corresponding protective measures to ensure safe construction according to the risk warning levels in different areas of the distribution lines.

[0208] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figure 1 to Figure 2 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0209] It should be noted that the serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments. And the terms "including", "comprising" or any other variants thereof in this article are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "including a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0210] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0211] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A Beidou-based distribution line construction safety management method, characterized in that: The method comprises: S1: Construct a terrain index system for the distribution line construction area, and use Beidou positioning technology to collect terrain index data for the distribution line area according to the constructed index system to obtain terrain index values; S2: extracting features of different areas of the distribution line by combining the distribution line location information and the collected terrain index values ​​to obtain feature vectors of different areas of the distribution line; S3: Constructing a risk warning model for icing areas of distribution lines to carry out icing risk warning for different areas of distribution lines, and obtaining risk warning levels for different areas of distribution lines; wherein weighted nearest neighbor analysis is used as an implementation method of the risk warning model for icing areas; S4: Take corresponding protective measures for safe construction according to the risk warning levels of different areas of the distribution lines.

2. A Beidou-based distribution line construction safety management method as claimed in claim 1, characterized in that: In the step S1, a terrain index system for the distribution line construction area is constructed, and the terrain index data of the distribution line area is collected according to the constructed index system using Beidou positioning technology to obtain terrain index values, including: S11: The terrain index system of the distribution line construction area includes terrain parameter index and terrain morphology index. The terrain parameter index includes slope, slope direction, ground curvature, terrain undulation and surface roughness. The terrain morphology index includes mountain top point, valley point and saddle point. S12: Use Beidou positioning to accurately obtain the track position coordinates of the UAV. During the UAV cruising process, laser ranging is performed on the target area to obtain the relative position coordinates of the target point relative to the UAV. The precise position coordinates of the target area are obtained based on the track position coordinates of the UAV and the relative position coordinates of the target area. S13: Calculate the terrain index of the distribution line construction area according to the calculated precise position coordinates of the target area to obtain a terrain index value.

3. A Beidou-based distribution line construction safety management method as claimed in claim 2, characterized in that: In the step S12, the drone cruise process performs laser ranging on the target area to obtain the relative position coordinates of the target point relative to the drone, including: S12.1: The UAV is equipped with a laser sensor to perform laser ranging on the target area during flight to obtain the distance information between the target point and the UAV; S12.2: using an inertial measurement unit on the drone to obtain attitude information of the drone, where the attitude information includes a pitch angle and a roll angle; S12.3: Based on the distance information obtained by laser ranging and the drone attitude information, calculate the relative position coordinates of the target point relative to the drone. The calculation formula is: x rel =d·cos(θ)·sin(φ) y rel =d sin(θ) z rel =d·cos(θ)·cos(φ) in: d represents the distance between the target point and the UAV; θ represents the pitch angle, which is the up and down rotation angle of the drone; φ represents the roll angle, which is the left and right rotation angle of the drone; (x rel ,y rel ,z rel ) represents the position coordinates of the target point relative to the UAV.

4. A Beidou-based distribution line construction safety management method as claimed in claim 2, characterized in that: In the step S13, the terrain index of the distribution line construction area is calculated according to the calculated precise position coordinates of the target area to obtain the terrain index value, including: The slope represents the inclination of the terrain surface, and the calculation formula is: in: and They represent the rate of change of the terrain height z at the coordinate (x, y, z) relative to the horizontal directions x and y respectively; The slope aspect represents the azimuth of the slope surface relative to the true north direction, and the calculation formula is: The ground curvature indicates the degree of concavity and convexity of the ground surface, including profile curvature and plane curvature, wherein the profile curvature calculation formula is: The plane curvature calculation formula is: The terrain relief represents the difference between the elevation of the regional location and the average elevation of the region, and the calculation formula is: in: z i represents the elevation of point i; Indicates the average elevation of all points in the area; The surface roughness indicates the undulation of the local terrain surface, and the calculation formula is: in: n represents the number of points in the area.

5. A Beidou-based distribution line construction safety management method as claimed in claim 1, characterized in that: In the step S2, feature extraction is performed on different areas of the distribution line in combination with the distribution line location information and the collected terrain index values ​​to obtain feature vectors of different areas of the distribution line, including: S21: according to the distribution line location information, a circular area with a preset radius is used and the center of the circle is placed on the distribution line to move according to the distribution line location information to obtain terrain index information in the circular area during the movement process, and feature extraction is performed to obtain terrain feature vectors of different areas; S22: Extracting circular area features including statistical features and terrain features, and combining the extracted features into a vector, wherein the statistical features include: Mean: the average value of the elevation of all points in the circular area; Standard deviation: the standard deviation of the elevation of all points in the circular area; Maximum value: the maximum value of all point elevations in the circular area; Minimum value: the minimum value of all point elevations in the circular area; Median: The median of all point elevations within the circular area; The terrain features include the regional slope mean, regional aspect mean, regional surface roughness, and whether the region contains mountain tops, valley points, and saddle points; S23: Performing terrain semantic coding on the combined vector to obtain a terrain feature vector, wherein a sparse autoencoder is an implementation method of the semantic coding.

6. A Beidou-based distribution line construction safety management method as claimed in claim 5, characterized in that: In the step S23, terrain semantic encoding is performed on the combined vector to obtain a terrain feature vector, including: The terrain semantic coding includes an encoder, a sparse constraint and a decoder, wherein the encoder encodes the combined vector through a hidden layer and maps the data to a low-dimensional vector representation; the sparse constraint captures the key terrain features in the low-dimensional vector through KL divergence to obtain a sparse low-dimensional vector; the decoder receives the sparse low-dimensional vector, and restores the combined vector through reverse mapping and reconstruction. The encoding process calculation formula of the encoder is: h=f(Wx+b) in: f(·) represents the activation function; W represents the weight of the encoder; b represents the encoder bias term; The sparsification constraint calculation formula is: in: Ω(h) represents the sparsity constraint term; h represents the encoder output vector; represents the vector after sparse processing; The decoder calculation formula is: in: g(·) represents the activation function of the decoder; W ′ represents the weight of the decoder; b ′ Represents the decoder bias term.

7. A Beidou-based distribution line construction safety management method as claimed in claim 1, characterized in that: In the step S3, a distribution line icing area risk warning model is constructed to provide icing risk warning for different areas of the distribution line, including: S31: for the terrain feature vector v1 obtained by encoding, calculating the Euclidean distance between v1 and other terrain feature vectors; S32: according to a preset K value, determine a set of K terrain feature vectors closest to v1 as a neighbor set of v1; S33: Calculate the weight of each terrain feature vector according to the distance from v1 to each terrain feature vector in the neighboring set. The calculation formula is: in; d i represents the distance from v1 to the i-th nearest neighbor terrain feature vector; S34: Based on the calculated weight, a voting decision is made to determine the icing risk level of v1. The calculation formula is: in: represents the predicted icing risk level of the terrain feature vector; w i represents the weight of the i-th nearest neighbor terrain feature vector; y i represents the icing risk level of the i-th nearest neighbor terrain feature vector; j represents the icing risk level; i represents the nearest neighbor terrain feature vector index; Represents an indicator function, which returns 1 if the condition in the brackets is true, otherwise it returns 0.

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