A Remote Monitoring Method and System for Dense Power Transmission Channels Based on Spatiotemporal Analysis

Abstract

This invention relates to the field of power transmission line monitoring technology, and particularly to a method and system for remote monitoring of dense power transmission channels based on spatiotemporal analysis. The method includes the following steps: analyzing the spatiotemporal correlation characteristics of the operating states of construction equipment and transmission lines based on construction equipment operation data and transmission line operation data, and constructing a set of interference factors of construction equipment on the transmission lines; evaluating the anti-interference capability of the transmission lines against each interference factor in the interference factor set based on transmission line operation data; extracting the interference intensity of each interference factor in the interference factor set and determining the interference risk of each interference factor based on the anti-interference capability evaluation results; and determining the safe operating area of ​​construction equipment within the monitoring area based on the spatial distribution characteristics of the interference risk. This invention effectively improves the operational safety and intelligent management level of dense power transmission channels by combining the evaluation of the transmission line's anti-interference capability with its operating state.

Description

Technical Field

[0001] This invention relates to the field of power transmission line monitoring technology, and in particular to a method and system for remote monitoring of dense power transmission channels based on spatiotemporal analysis. Background Technology

[0002] Dense transmission channels refer to transmission line channels consisting of two or more ultra-high voltage direct current (UHVDC) lines with a minimum distance of no more than 100 meters between adjacent DC lines. Dense transmission channels have narrower line corridors and larger transmission capacity, and bear the important responsibility of cross-regional power supply. They are the lifeline for ensuring the safe operation of the power grid.

[0003] With the acceleration of urbanization and the continuous advancement of infrastructure construction, a large number of infrastructure construction, road construction, building renovation and expansion operations frequently occur in the areas surrounding power transmission lines, and the safety conflicts between construction equipment and power transmission lines are becoming increasingly prominent.

[0004] However, the resistance of transmission lines to interference from construction equipment varies significantly under different load rates and wind deflection conditions. For example, transmission lines operating under high loads are more sensitive to electromagnetic interference, while increased conductor wind deflection angle and sag significantly reduce the transmission line's tolerance to spatial intrusion. Traditional transmission channel monitoring methods typically only consider the static distance between construction equipment and transmission lines or use a single-dimensional safety threshold for risk assessment, failing to fully consider the dynamic impact of the transmission line's real-time operating status on its interference sensitivity. This results in insufficient accuracy in assessing the interference risk from construction equipment to transmission lines, making it difficult to meet the safety management needs of complex construction environments. Summary of the Invention

[0005] To overcome the defects and shortcomings of existing technologies, this invention provides a method and system for remote monitoring of dense power transmission channels based on spatiotemporal analysis. By combining the operation status of power transmission lines to evaluate their anti-interference capabilities, it effectively improves the operational safety and intelligent management level of dense power transmission channels.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides a method for remote monitoring of dense power transmission channels based on spatiotemporal analysis, comprising: S100, acquiring operation data of construction equipment and transmission line operation data within the monitoring area; S200, analyzing the spatiotemporal correlation characteristics of the operation status of construction equipment and transmission line based on the operation data of construction equipment and transmission line, and constructing a set of interference factors of construction equipment on transmission line; S300, evaluating the anti-interference capability of transmission line to each interference factor in the set of interference factors based on the operation data of transmission line; S400, extracting the interference intensity of each interference factor in the set of interference factors and determining the interference risk of each interference factor in combination with the anti-interference capability evaluation results; S500, determining the safe operating area of ​​construction equipment within the monitoring area based on the spatial distribution characteristics of interference risk.

[0008] Furthermore, the set of interference factors of the construction equipment on the transmission line described in step S200 includes:

[0009] S210. Extract the spatiotemporal matching data of construction equipment and transmission lines and construct an interference factor model of construction equipment on transmission lines. The interference factor model includes a spatial intrusion interference factor model, an electromagnetic radiation interference factor model, and a mechanical vibration interference factor model.

[0010] S220. Determine the interference intensity corresponding to each interference factor through the interference factor model and construct the interference factor set of the construction equipment on the transmission line. The interference factor set includes the interference factor type and the corresponding interference intensity.

[0011] Furthermore, the evaluation of the transmission line's anti-interference capability against various interference factors in the interference factor set in step S300 includes:

[0012] S310. Obtain historical transmission line operation data and historical interference factor data;

[0013] S320. By combining historical transmission line operation data with clustering algorithms, transmission lines are divided into different operation status categories and a transmission line operation status set is constructed.

[0014] S330. Determine the anti-interference capability coefficient of the transmission line to each interference factor under different operating conditions of the transmission line based on historical interference factor data.

[0015] S340. Determine the operating status of the transmission line based on the transmission line operation data and extract the anti-interference capability coefficients of each interference factor to evaluate the anti-interference capability of the transmission line against each interference factor under the influence of the transmission line operating status.

[0016] Further, determining the anti-interference capability coefficient in step S330 includes:

[0017] S331. Extract the historical interference intensity of each interference factor and the fluctuation amplitude of the corresponding transmission line operation data by using historical interference factor data and historical transmission line operation data. The fluctuation amplitude includes voltage deviation rate, frequency deviation rate and harmonic distortion rate.

[0018] S332. Determine the Pearson correlation coefficient between the historical interference intensity of each interference factor and the fluctuation range of the transmission line operation data at the corresponding time, and use the difference between 1 and the mean absolute value of the Pearson correlation coefficient as the anti-interference capability coefficient of the transmission line against each interference factor.

[0019] Further, the determination of the interference risk of each interference factor in step S400 includes:

[0020] S410. Obtain the interference intensity of each interference factor in the interference factor set and the anti-interference capability coefficient of each interference factor.

[0021] S420. Determine the interference risk coefficient of each interference factor by combining the interference intensity and anti-interference capability coefficient of each interference factor using the logarithmic proportion method:

[0022] ;

[0023] in, Interference factor Interference risk coefficient Interference factor The intensity of interference, For transmission lines to interference factors The anti-interference capability coefficient.

[0024] Further, the step S500 of determining the safe operating area for construction equipment within the monitored area includes:

[0025] S510. Divide the monitoring area into grid units and determine the interference risk coefficient of each interference factor corresponding to the grid unit.

[0026] S520. The interference risk coefficients of each interference factor in the grid cell are weighted and summed to obtain the comprehensive interference risk coefficient of the construction equipment to the transmission line at the grid cell.

[0027] S530. Grid cells with a comprehensive interference risk coefficient greater than the preset comprehensive interference risk threshold are identified as the safe operating area for construction equipment within the monitoring area.

[0028] Secondly, the present invention provides a remote monitoring system for dense power transmission channels based on spatiotemporal analysis, comprising:

[0029] The data acquisition module is used to acquire operational data of construction equipment and power transmission lines within the monitored area;

[0030] The spatial correlation feature analysis module, connected to the data acquisition module, is used to analyze the spatiotemporal correlation features of the operating status of construction equipment and transmission lines based on the operating data of construction equipment and the operating data of transmission lines, and to construct a set of interference factors of construction equipment on transmission lines.

[0031] An anti-interference capability assessment module, connected to the spatial correlation feature analysis module, is used to assess the anti-interference capability of a transmission line against various interference factors in the interference factor set based on transmission line operation data.

[0032] The interference risk assessment module, connected to the anti-interference capability assessment module, is used to extract the interference intensity of each interference factor in the interference factor set and determine the interference risk of each interference factor in combination with the anti-interference capability assessment results.

[0033] The safe operation area assessment module, connected to the interference risk assessment module, is used to determine the safe operation area of ​​construction equipment within the monitoring area based on the spatial distribution characteristics of interference risks.

[0034] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0035] This invention constructs a multi-dimensional interference factor model that includes spatial intrusion, electromagnetic radiation, and mechanical vibration, and combines this model with the dynamic assessment of the transmission line's anti-interference capability against different interference factors based on the transmission line's operating status. This enables accurate identification and quantitative assessment of construction interference risks, thereby dynamically reflecting the potential impact of construction equipment on the safe operation of transmission lines and effectively delineating the safe operating area for construction equipment. As a result, it significantly improves the operational safety and intelligent management level of dense transmission channels. Attached Figure Description

[0036] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0037] Figure 1 This is a flowchart illustrating the remote monitoring method for dense power transmission channels based on spatiotemporal analysis provided in an embodiment of the present invention.

[0038] Figure 2 This is a flowchart illustrating step S200 provided in an embodiment of the present invention;

[0039] Figure 3 This is a flowchart illustrating step S300 provided in an embodiment of the present invention;

[0040] Figure 4 This is a flowchart illustrating step S330 provided in an embodiment of the present invention;

[0041] Figure 5This is a flowchart illustrating step S400 provided in an embodiment of the present invention;

[0042] Figure 6 This is a flowchart illustrating step S500 provided in an embodiment of the present invention;

[0043] Figure 7 This is a schematic diagram of the structure of the remote monitoring system for dense power transmission channels based on spatiotemporal analysis provided in an embodiment of the present invention;

[0044] Figure 8 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0045] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations thereof. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0046] Please see Figure 1 , Figure 1 This is a schematic diagram of the overall process of the remote monitoring method for dense power transmission channels based on spatiotemporal analysis provided in this embodiment of the invention, which specifically includes the following steps:

[0047] S100. Obtain the operation data of construction equipment and transmission lines within the monitoring area. The operation data of construction equipment includes the operation trajectory, working range and working time of the construction equipment. The operation data of transmission lines includes the temperature of transmission conductors, current load rate, wind deflection angle of conductors, conductor sag, electric field strength and spatial position of transmission conductors and transmission towers.

[0048] S200. Based on the operation data of construction equipment and the operation data of transmission lines, analyze the spatiotemporal correlation characteristics of the operation status of construction equipment and transmission lines, and construct a set of interference factors of construction equipment on transmission lines.

[0049] The spatial intrusion interference factor reflects whether the operating space of construction equipment overlaps with the protection zone of transmission lines, i.e., it determines whether there are physical risks such as mechanical collisions, conductor contact, or insufficient safety distances. The electromagnetic radiation interference factor indicates the risk of interference or even malfunction caused by electromagnetic waves generated during the operation of construction equipment to the operation of transmission lines. The mechanical vibration interference factor describes the impact of ground vibrations caused by construction equipment on the stability of transmission tower foundations or conductor vibrations. The interference of construction equipment on transmission lines will reduce the operational safety and stability of the transmission lines. Please refer to [link to relevant documentation]. Figure 2 , Figure 2 This is a flowchart illustrating step S200 provided in an embodiment of the present invention, including:

[0050] S210. Extract the spatiotemporal matching data between construction equipment and transmission lines and construct an interference factor model of the construction equipment on the transmission lines. The interference factor model includes a spatial intrusion interference factor model, an electromagnetic radiation interference factor model, and a mechanical vibration interference factor model. Among them, the spatial intrusion interference factor model can be... , The interference intensity of the spatial intrusion interference factor. The overlapping volume of the operating space envelope of construction equipment and the protection zone of power transmission lines. For the spatial volume of the transmission line protection zone, through It reflects the proportion of intrusion of construction equipment into the protection zone of transmission lines. The larger the ratio, the higher the intrusion proportion and the more serious the space intrusion interference.

[0051] The electromagnetic radiation interference factor model can be used to... , The interference intensity is the electromagnetic radiation interference factor. This refers to the electromagnetic radiation power density of the construction equipment, i.e., the source intensity of the electromagnetic radiation. The radiation gain coefficient of construction equipment describes its ability to concentrate electromagnetic radiation in a certain direction. It can be obtained by measurement and calculation using a high-frequency current sensor or interference detection antenna. This refers to the minimum spatial distance between construction equipment and power transmission lines. This is used to describe the electromagnetic wave propagation law where the electromagnetic wave power density decreases with the square of the distance.

[0052] The mechanical vibration disturbance factor model can be used to , The interference intensity of the mechanical vibration interference factor. The amplitude of vibration generated by the construction equipment. This indicates the design vibration amplitude of the transmission line tower. This represents the ratio of the current vibration amplitude generated by the construction equipment to the tower's design safety reference value, and is used to normalize the vibration amplitude. The vibration attenuation coefficient of the foundation medium can be obtained through vibration propagation tests. The horizontal distance between the construction equipment and the transmission tower, where, This represents the exponential decay model, used to describe the exponential energy loss of vibration in a medium, which conforms to the geomechanical decay law.

[0053] S220. The interference intensity corresponding to each interference factor is determined by the interference factor model, and a set of interference factors of construction equipment on the transmission line is constructed. The interference factor set includes the interference factor type and the corresponding interference intensity. The interference effect of construction equipment disturbing the transmission line is quantitatively expressed through the interference factor set, providing data support for subsequent interference risk assessment, so that the entire monitoring system has the ability to quantitatively perceive and dynamically respond to external interference.

[0054] S300. Evaluate the anti-interference capability of transmission lines against various interference factors in the interference factor concentration based on transmission line operation data.

[0055] The immunity of transmission lines to different interference factors is not fixed but dynamically adjusts with changes in their operating state. When transmission lines are under high load, high temperature, or abnormal electrical parameters, their resistance to external interference decreases. For example, under conditions of increased conductor sag or significant fluctuations in electric field strength, transmission lines are more susceptible to spatial intrusion or electromagnetic interference. Therefore, accurately determining the current operating state of transmission lines and assessing their immunity under that state is crucial for improving the accuracy of interference risk assessment. Please refer to [link to relevant documentation]. Figure 3 , Figure 3 This is a flowchart illustrating step S300 provided in an embodiment of the present invention, including:

[0056] S310. Obtain historical transmission line operation data and historical interference factor data;

[0057] S320. By combining historical transmission line operation data with clustering algorithms, transmission lines are divided into different operation status categories and a transmission line operation status set is constructed. The operation status categories in the transmission line operation status set are determined with reference to DL / T1249-2013 "Technical Guidelines for Operation Status Assessment of Overhead Transmission Lines", specifically including normal status, attention status, abnormal status, and severe status. The clustering algorithm can be any one of K-Means algorithm, DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm, and GMM (Gaussian Mixture Models) algorithm. By constructing the transmission line operation status set, a unified analysis framework is established for the response characteristics of each interference factor under different states, laying the foundation for realizing dynamic anti-interference capability assessment under state awareness.

[0058] S330. Based on historical interference factor data, determine the anti-interference capability coefficient of the transmission line to various interference factors under different transmission line operating conditions. Please refer to [link to relevant documentation]. Figure 4 , Figure 4This is a flowchart illustrating step S330 provided in an embodiment of the present invention, including:

[0059] S331. By extracting the historical interference intensity of each interference factor and the fluctuation amplitude of the corresponding transmission line operation data at the historical time through historical interference factor data and historical transmission line operation data, the fluctuation amplitude includes voltage deviation rate, frequency deviation rate and harmonic distortion rate. By extracting the historical interference intensity and the corresponding fluctuation amplitude, the degree of influence of interference behavior on the operation stability of transmission lines can be effectively characterized, and a quantitative correlation between interference behavior and line state response can be established.

[0060] S332. Determine the Pearson correlation coefficient between the historical interference intensity of each interference factor and the fluctuation amplitude of the transmission line operating data at the corresponding time, and use the difference between 1 and the mean absolute value of the Pearson correlation coefficient as the anti-interference capability coefficient of the transmission line against each interference factor: ,in, For transmission lines to interference factors The anti-interference capability coefficient, Interference factor The Pearson correlation coefficient between historical interference intensity and voltage deviation rate of transmission lines. Interference factor The Pearson correlation coefficient between historical interference intensity and frequency deviation rate of transmission lines. Interference factor The Pearson correlation coefficient between historical interference intensity and harmonic distortion rate of transmission lines, with For example:

[0061] ;

[0062] in, Interference factor exist Historical interference intensity at any given moment Interference factor Historical average interference intensity For transmission lines in Voltage deviation rate at time t, This represents the average voltage deviation rate of the transmission line. The monitoring duration for historical interference factor data and historical transmission line operation data, Interference factor The Pearson correlation coefficient between historical interference intensity and voltage deviation rate of transmission lines;

[0063] By using the Pearson correlation coefficient between historical interference intensity and fluctuation amplitude to reflect the fluctuation sensitivity of transmission lines under different operating conditions, the anti-interference capability coefficient is determined to achieve a standardized quantitative expression of anti-interference capability. The anti-interference capability coefficient can be used to keenly capture the tolerance of the line to different interferences, avoid subjective weighting, and achieve data-driven objective anti-interference capability modeling.

[0064] S340. Determine the operating status of the transmission line based on the transmission line operation data and extract the anti-interference capability coefficients of each interference factor to evaluate the anti-interference capability of the transmission line to each interference factor under the influence of the transmission line operation status. By identifying the actual operating status of the current transmission line and automatically matching the anti-interference capability coefficients of various interference factors under the corresponding status, the anti-interference capability assessment is closer to the actual operating conditions of the line, thereby enhancing the accuracy of subsequent interference risk assessment. The specific steps for determining the operating status of the transmission line based on the transmission line operation data include: (1) extracting the key feature parameters of the transmission line operation data and constructing the state feature vector; (2) standardizing the state feature vector with Z-score; (3) inputting the standardized state feature vector into the clustering algorithm in step S320 to determine the clustering category, that is, the transmission line operation status corresponding to the transmission line operation data.

[0065] S400. Extract the interference intensity of each interference factor from the interference factor set and determine the interference risk of each interference factor in combination with the anti-interference capability assessment results.

[0066] Interference intensity reflects the degree of external disturbance exerted on transmission lines by construction equipment; it is a quantitative indicator of the interference source. The anti-interference capability coefficient, on the other hand, represents the transmission line's ability to withstand various disturbances under its current operating conditions; it is an indicator of the response capability of the affected object. The essence of interference risk depends on the correlation between interference intensity and the anti-interference capability coefficient. Only by combining both can a comprehensive assessment be made of the actual threat that construction equipment may pose to the safe operation of the line. Please refer to [link / reference]. Figure 5 , Figure 5 This is a flowchart illustrating step S400 provided in an embodiment of the present invention, including:

[0067] S410. Obtain the interference intensity of each interference factor in the interference factor set and the anti-interference capability coefficient of each interference factor.

[0068] S420. Determine the interference risk coefficient of each interference factor by combining the interference intensity and anti-interference capability coefficient of each interference factor using the logarithmic proportion method:

[0069] ;

[0070] in, Interference factor Interference risk coefficient Interference factor The intensity of interference, The larger the value, the more severe the external disturbance, and the higher the corresponding risk potential. For transmission lines to interference factors The interference immunity coefficient describes the transmission line's tolerance to this type of interference. This ratio represents the proportional relationship between the intensity of external interference and the line's tolerance capacity, i.e., the antagonistic relationship between interference and anti-interference. The larger the ratio, the more likely the interference is to exceed the line's tolerance range, and thus the greater the interference risk. The number 1 is used to ensure that even in the absence of interference, i.e. Interference risk coefficient This means that the risk of interference is zero at this point, thus ensuring that the logarithmic result is non-negative. The role of the logarithmic form is to represent the original proportional relationship. Nonlinear compression is performed to avoid the maxima dominating the output;

[0071] S500: Determine the safe operating area for construction equipment within the monitoring area based on the spatial distribution characteristics of interference risks;

[0072] In densely populated power transmission corridors, construction activities cause complex types of interference to transmission lines. Once construction equipment enters high-risk areas, it can easily lead to transmission line faults or equipment damage. By comprehensively assessing the risk distribution of various interference factors and scientifically delineating safe operating zones for construction equipment, uncontrollable interference with line operation can be effectively avoided, improving operational safety and grid stability. Please refer to [link to relevant documentation]. Figure 6 , Figure 6 This is a flowchart illustrating step S500 provided in an embodiment of the present invention, including:

[0073] S510. Divide the monitoring area into grid units and determine the interference risk coefficient of each interference factor corresponding to the grid unit. By dividing the monitoring area into regular grid units and combining the spatiotemporal relationship between construction equipment and transmission lines in each unit, the risk coefficient of each interference factor can be determined. Grid processing helps to achieve a fine characterization of the risk distribution in the area.

[0074] S520. The comprehensive interference risk coefficient of the construction equipment at the grid unit to the transmission line is obtained by weighted summation of the interference risk coefficients of each interference factor in the grid unit. The comprehensive interference risk coefficient of each unit location is obtained by weighted summation of the risk coefficients of each interference factor in the grid unit, which can comprehensively reflect the superimposed impact of multiple interference types on the transmission line.

[0075] S530. Grid cells with a comprehensive interference risk coefficient greater than the preset comprehensive interference risk threshold are used to identify safe operating areas for construction equipment within the monitoring area. By performing spatial connectivity analysis on high-risk grid cells, continuous safe operating areas can be identified and delineated, improving the efficiency of construction operation decisions and reducing the probability of construction equipment accidentally entering high-risk areas.

[0076] In this embodiment of the invention, the determination of parameters such as weighting and preset comprehensive interference risk threshold can be as follows: a dataset is constructed by acquiring operation data of construction equipment and operation data of transmission lines, and the comprehensive interference risk coefficient of construction equipment on transmission lines is calculated. At the same time, the judgment results of experts on the degree of interference of construction equipment on transmission lines are obtained. The calculated comprehensive interference risk coefficient and judgment results are imported into fitting software, and the weighting and preset comprehensive interference risk threshold that meet the maximum judgment accuracy are output.

[0077] Please see Figure 7 , Figure 7 This is a schematic diagram of the structure of a remote monitoring system for dense power transmission channels based on spatiotemporal analysis provided in an embodiment of the present invention, including:

[0078] The data acquisition module 210 is used to acquire the operation data of construction equipment and the operation data of power transmission lines within the monitoring area;

[0079] The spatial correlation feature analysis module 220 is connected to the data acquisition module 210 and is used to analyze the spatiotemporal correlation features of the operating status of construction equipment and transmission line based on the operating data of construction equipment and the operating data of transmission line, and to construct a set of interference factors of construction equipment on transmission line.

[0080] The anti-interference capability assessment module 230 is connected to the spatial correlation feature analysis module 220 and is used to assess the anti-interference capability of the transmission line against each interference factor in the interference factor set based on the transmission line operation data.

[0081] Interference risk assessment module 240, connected to anti-interference capability assessment module 230, is used to extract the interference intensity of each interference factor in the interference factor set and determine the interference risk of each interference factor in combination with the anti-interference capability assessment results.

[0082] The safe operation area assessment module 250 is connected to the interference risk assessment module 240 and is used to determine the safe operation area of ​​construction equipment within the monitoring area based on the spatial distribution characteristics of interference risk.

[0083] In this embodiment of the invention, the spatiotemporal correlation feature analysis module 220 is used to analyze the spatiotemporal correlation features of the operating status of construction equipment and transmission lines based on construction equipment operation data and transmission line operation data, and to construct a set of interference factors of construction equipment on transmission lines, including:

[0084] Spatiotemporal matching data of construction equipment and transmission lines are extracted and interference factor models of construction equipment on transmission lines are constructed. The interference factor models include spatial intrusion interference factor models, electromagnetic radiation interference factor models and mechanical vibration interference factor models.

[0085] The interference intensity corresponding to each interference factor is determined by the interference factor model, and a set of interference factors of construction equipment on the transmission line is constructed. The set of interference factors includes the type of interference factor and the corresponding interference intensity.

[0086] In this embodiment of the invention, the anti-interference capability assessment module 230 is used to assess the anti-interference capability of a transmission line against various interference factors in a set of interference factors based on transmission line operation data, including:

[0087] Obtain historical transmission line operation data and historical interference factor data;

[0088] By combining historical transmission line operation data with clustering algorithms, transmission lines are divided into different operation status categories and a transmission line operation status set is constructed.

[0089] Based on historical interference factor data, the anti-interference capability coefficients of transmission lines under different operating conditions are determined, including:

[0090] The historical interference intensity of each interference factor and the fluctuation amplitude of the corresponding transmission line operation data are extracted by historical interference factor data and historical transmission line operation data. The fluctuation amplitude includes voltage deviation rate, frequency deviation rate and harmonic distortion rate.

[0091] The Pearson correlation coefficient between the historical interference intensity of each interference factor and the fluctuation range of the transmission line operation data at the corresponding time is determined, and the difference between 1 and the mean absolute value of the Pearson correlation coefficient is used as the anti-interference capability coefficient of the transmission line against each interference factor.

[0092] The operating status of the transmission line is determined based on the transmission line operation data, and the anti-interference capability coefficients of each interference factor are extracted to evaluate the anti-interference capability of the transmission line against each interference factor under the influence of the transmission line operating status.

[0093] In this embodiment of the invention, the interference risk assessment module 240 is used to extract the interference intensity of each interference factor in the interference factor set and determine the interference risk of each interference factor in combination with the anti-interference capability assessment results, including:

[0094] Obtain the interference intensity of each interference factor in the interference factor set and the anti-interference capability coefficient of each interference factor;

[0095] The interference risk coefficient of each interference factor is determined by combining the interference intensity and anti-interference capability coefficient of each interference factor using the logarithmic ratio method.

[0096] In this embodiment of the invention, the safe operation area assessment module 250 is used to determine the safe operation area of ​​construction equipment within the monitoring area based on the spatial distribution characteristics of interference risk, including:

[0097] The monitoring area is divided into grid cells, and the interference risk coefficient of each interference factor corresponding to the grid cell is determined.

[0098] The comprehensive interference risk coefficient of the construction equipment to the transmission line at the grid cell is obtained by weighted summation of the interference risk coefficients of each interference factor in the grid cell.

[0099] Grid cells with a comprehensive interference risk coefficient greater than the preset comprehensive interference risk threshold are identified as safe operating areas for construction equipment within the monitored area.

[0100] The parameters and steps for implementing the corresponding functions of each unit module in the spatiotemporal analysis-based remote monitoring system for dense power transmission channels of the present invention described above can be referred to the parameters and steps in the embodiments of the spatiotemporal analysis-based remote monitoring method for dense power transmission channels described above, and will not be repeated here.

[0101] Please refer to Figure 8 The present invention also provides an electronic device 300, including a memory 310, a processor 320, and a communication bus 330; the memory 310 and the processor 320 are connected via the communication bus 330. The memory 310 stores a method for remote monitoring of dense power transmission channels based on spatiotemporal analysis, as provided in the above embodiments, which can be loaded and executed by the processor 320.

[0102] The memory 310 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 310 may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for at least one function, and instructions for implementing the spatiotemporal analysis-based remote monitoring method for dense power transmission channels provided in the above embodiments. The data storage area may store data involved in the spatiotemporal analysis-based remote monitoring method for dense power transmission channels provided in the above embodiments.

[0103] Processor 320 may include one or more processing cores. Processor 320 executes instructions, programs, code sets, or instruction sets stored in memory 310, and calls data stored in memory 310 to perform various functions and process data according to the present invention. Processor 320 may be at least one of the following: Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), Central Processing Unit (CPU), Controller, Microcontroller, and Microprocessor. It is understood that, for different devices, the electronic devices used to implement the functions of processor 320 may also be other types, and the embodiments of the present invention do not specifically limit this.

[0104] The communication bus 330 may include a path for transmitting information between the aforementioned components. The communication bus 330 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus 330 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 The symbol is represented by a single double arrow, but this does not mean that there is only one bus or one type of bus.

[0105] This invention provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed as described in the above embodiments for remote monitoring of dense power transmission channels based on spatiotemporal analysis.

[0106] In this embodiment of the invention, the computer-readable storage medium can be a tangible device that holds and stores instructions used by an instruction execution device. The computer-readable storage medium can be, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof. Specifically, the computer-readable storage medium can be a portable computer disk, a hard disk, a USB flash drive, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), lectern random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory stick, floppy disk, optical disk, magnetic disk, mechanical encoding device, or any combination thereof.

[0107] The terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0108] The above description is merely a preferred embodiment of the present invention and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this application is not limited to the technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the foregoing concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions claimed in this invention.

Claims

1. A remote monitoring method for dense power transmission channels based on spatiotemporal analysis, characterized in that, include: S100: Obtain operational data of construction equipment and power transmission lines within the monitored area; S200. Based on the operation data of construction equipment and the operation data of transmission lines, analyze the spatiotemporal correlation characteristics of the operation status of construction equipment and transmission lines, and construct a set of interference factors of construction equipment on transmission lines. S300. Evaluate the anti-interference capability of transmission lines against various interference factors in the interference factor concentration based on transmission line operation data. S400. Extract the interference intensity of each interference factor from the interference factor set and determine the interference risk of each interference factor in combination with the anti-interference capability assessment results. S500: Determine the safe operating area for construction equipment within the monitoring area based on the spatial distribution characteristics of interference risks; Step S300, which describes evaluating the transmission line's immunity to various interference factors in the interference factor set, includes: S310. Obtain historical transmission line operation data and historical interference factor data; S320. By combining historical transmission line operation data with clustering algorithms, transmission lines are divided into different operation status categories and a transmission line operation status set is constructed. S330. Determine the anti-interference capability coefficient of the transmission line to each interference factor under different operating conditions of the transmission line based on historical interference factor data. S340. Determine the operating status of the transmission line based on the transmission line operation data and extract the anti-interference capability coefficients of each interference factor to evaluate the anti-interference capability of the transmission line against each interference factor under the influence of the transmission line operating status. Determining the anti-interference capability coefficient in step S330 includes: S331. Extract the historical interference intensity of each interference factor and the fluctuation amplitude of the corresponding transmission line operation data by using historical interference factor data and historical transmission line operation data. The fluctuation amplitude includes voltage deviation rate, frequency deviation rate and harmonic distortion rate. S332. Determine the Pearson correlation coefficient between the historical interference intensity of each interference factor and the fluctuation range of the transmission line operation data at the corresponding time, and use the difference between 1 and the mean absolute value of the Pearson correlation coefficient as the anti-interference capability coefficient of the transmission line against each interference factor.

2. The method for remote monitoring of dense power transmission channels based on spatiotemporal analysis according to claim 1, characterized in that, The set of interference factors of the construction equipment on the transmission line described in step S200 includes: S210. Extract the spatiotemporal matching data of construction equipment and transmission lines and construct an interference factor model of construction equipment on transmission lines. The interference factor model includes a spatial intrusion interference factor model, an electromagnetic radiation interference factor model, and a mechanical vibration interference factor model. S220. Determine the interference intensity corresponding to each interference factor through the interference factor model and construct the interference factor set of the construction equipment on the transmission line. The interference factor set includes the interference factor type and the corresponding interference intensity.

3. The method for remote monitoring of dense power transmission channels based on spatiotemporal analysis according to claim 1, characterized in that, Determining the interference risk of each interference factor in step S400 includes: S410. Obtain the interference intensity of each interference factor in the interference factor set and the anti-interference capability coefficient of each interference factor. S420. Determine the interference risk coefficient of each interference factor by combining the interference intensity and anti-interference capability coefficient of each interference factor using the logarithmic proportion method: ； in, Interference factor Interference risk coefficient Interference factor The intensity of interference, For transmission lines to interference factors The anti-interference capability coefficient.

4. The method for remote monitoring of dense power transmission channels based on spatiotemporal analysis according to claim 1, characterized in that, Determining the safe operating area for construction equipment within the monitored area in step S500 includes: S510. Divide the monitoring area into grid units and determine the interference risk coefficient of each interference factor corresponding to the grid unit. S520. The interference risk coefficients of each interference factor in the grid cell are weighted and summed to obtain the comprehensive interference risk coefficient of the construction equipment to the transmission line at the grid cell. S530. Grid cells with a comprehensive interference risk coefficient greater than the preset comprehensive interference risk threshold are identified as the safe operating area for construction equipment within the monitoring area.

5. A remote monitoring system for dense power transmission channels based on spatiotemporal analysis, used to implement the remote monitoring method for dense power transmission channels based on spatiotemporal analysis as described in any one of claims 1-4, characterized in that, The system includes: The data acquisition module is used to acquire operational data of construction equipment and power transmission lines within the monitored area; The spatial correlation feature analysis module, connected to the data acquisition module, is used to analyze the spatiotemporal correlation features of the operating status of construction equipment and transmission lines based on the operating data of construction equipment and the operating data of transmission lines, and to construct a set of interference factors of construction equipment on transmission lines. An anti-interference capability assessment module, connected to the spatial correlation feature analysis module, is used to assess the anti-interference capability of a transmission line against various interference factors in the interference factor set based on transmission line operation data. The interference risk assessment module, connected to the anti-interference capability assessment module, is used to extract the interference intensity of each interference factor in the interference factor set and determine the interference risk of each interference factor in combination with the anti-interference capability assessment results. The safe operation area assessment module, connected to the interference risk assessment module, is used to determine the safe operation area of ​​construction equipment within the monitoring area based on the spatial distribution characteristics of interference risks.

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