Intelligent method and system for preventing virtual hanging of grounding wire based on pressure sensing

Abstract

The invention provides an intelligent virtual hanging prevention ground wire method and system based on pressure sensing, relates to the technical field of electric power safety, and aims to solve the problems of missing detection, misjudgment, inaccurate positioning and the like in traditional ground wire installation quality detection. The method comprises the following steps: acquiring pressure data and relative space coordinates through strain type pressure sensor groups which are uniformly distributed along the circumferential direction of a grounding wire; a three-dimensional stress distribution model of the grounding wire is constructed based on the pressure data and the space coordinates, and a stress ellipsoid analysis and segmented Hermite interpolation method is adopted to accurately reflect the stress state of the grounding wire; through singular value decomposition, spectrum characteristic analysis and curl and divergence calculation, a virtual hanging point is accurately positioned, and a space coordinate of the virtual hanging point is output. According to the method, through multi-dimensional data acquisition, a dynamic triggering mechanism and transverse strain field analysis, the accuracy and reliability of virtual hanging detection are remarkably improved, the method is suitable for ground wire monitoring under complex terrain conditions, and effective technical guarantee is provided for safe operation of a power system.

Description

Technical Field

[0001] The present invention relates to the field of electric power safety technology, and in particular to an intelligent anti-false hanging grounding wire method and system based on pressure sensing. Background Art

[0002] As a key safety device in the power system, the installation quality of the grounding wire directly affects the reliability and stability of the system. Traditional grounding wire installation quality detection mainly relies on manual inspections and simple mechanical sensors. This method has inherent defects such as strong subjectivity and low detection accuracy. With the development of intelligent sensing technology, grounding wire monitoring methods based on pressure sensing have gradually been applied, and the stress state of the grounding wire is detected by arranging pressure sensors on the grounding wire. However, most of the current pressure sensing solutions use single-point measurement or linear arrangement. This arrangement is often difficult to accurately reflect the actual stress state of the grounding wire under complex terrain conditions, especially in the presence of multi-point stress and torsional deformation, which is prone to missed detection and misjudgment.

[0003] The existing ground wire virtual hanging detection technology has three main deficiencies: first, the traditional pressure sensing scheme lacks a systematic analysis of the overall stress state of the ground wire, making it difficult to effectively identify local stress anomalies; second, the existing data processing methods are mostly based on simple threshold judgments, which cannot accurately distinguish between normal force changes and stress anomalies caused by virtual hanging; finally, in terms of virtual hanging point positioning, due to the lack of a unified spatial reference system and a complete mechanical model, it is difficult to accurately locate the virtual hanging point, affecting the maintenance efficiency. These problems are particularly prominent under complex terrain conditions, which seriously restricts the level of assurance of the installation quality of the ground wire. Summary of the invention

[0004] In order to solve the above problems, the present invention provides an intelligent anti-false hanging grounding wire method and system based on pressure sensing.

[0005] The technical solution adopted by the present invention is:

[0006] An intelligent method for preventing false hanging of ground wire based on pressure sensing comprises the following steps:

[0007] Step S1: Obtaining pressure data and relative spatial coordinates of multiple preset positioning points on the grounding line;

[0008] Step S2: constructing a three-dimensional force distribution model of the grounding wire according to the pressure data and the relative spatial coordinates; the three-dimensional force distribution model includes a mapping relationship between the spatial position and pressure value of each positioning point of the grounding wire;

[0009] Step S3: Analyze the uneven stress area of ​​the grounding wire based on the three-dimensional stress distribution model, determine the specific spatial position of the virtual hanging point and output positioning information; the positioning information includes the spatial coordinates of the virtual hanging point on the grounding wire.

[0010] Further, in step S1, obtaining pressure data and relative spatial coordinates of a plurality of preset positioning points on the grounding line includes the following steps:

[0011] Step S1.1: obtaining pressure data of a plurality of pressure sensors on the grounding wire, wherein the pressure sensors are evenly distributed along the circumference of the grounding wire;

[0012] Step S1.2: Determine the relative spatial coordinates of the pressure sensor based on its installation position, establish a corresponding relationship between the pressure data and the spatial coordinates, and establish a three-dimensional coordinate system with the starting end of the grounding wire as the origin.

[0013] Further, the sensor is a strain type pressure sensor group, each group of strain type pressure sensor group includes a plurality of first strain gauges uniformly distributed along the circumference of the grounding wire and a plurality of second strain gauges arranged along the axial direction of the grounding wire;

[0014] If the difference ratio between the strain value of the first strain gauge and the strain values ​​of its two adjacent first strain gauges is the largest, and the strain value of the first strain gauge is greater than the sum of the strain values ​​of its two adjacent first strain gauges, all the second strain gauges in the same cross section as the first strain gauge are activated to construct a transverse strain field;

[0015] The lateral strain field is divided into two left and right areas relative to the first strain gauge, the sum of the strain values ​​of the second strain gauge in the two areas is calculated, and the midpoint of the line connecting the endpoint of the area with the largest sum of strain values ​​and the position of the first strain gauge is determined as the torsion center position.

[0016] Further, in step S2, a three-dimensional force distribution model of the grounding wire is constructed according to the pressure data and the relative space coordinates, including the following steps:

[0017] Step S2.1: constructing a three-dimensional force distribution point cloud of the grounding wire based on the pressure data and the relative spatial coordinates, and performing stress state analysis on the three-dimensional force distribution point cloud;

[0018] Step S2.2: Based on the catenary characteristics of the grounding wire, the piecewise Hermite interpolation method is used to perform surface fitting on the data points of the three-dimensional force distribution point cloud to construct a three-dimensional force distribution model.

[0019] Further, in step S2.1, a stress state analysis is performed on the three-dimensional force distribution point cloud, including calculating the principal stress direction and the characteristic value of the stress ellipsoid of each data point of the three-dimensional force distribution point cloud, and determining the stress state of the data point based on the shape factor of the stress ellipsoid; wherein the shape factor is the ratio of the lengths of the three principal axes of the stress ellipsoid;

[0020] Calculate the shear stress ratio and principal stress ratio of adjacent data points respectively; the shear stress ratio is the ratio of tangential stress to normal stress; the principal stress ratio is the ratio of maximum principal stress to minimum principal stress;

[0021] If the extreme point of the shear stress ratio coincides with the extreme point of the principal stress ratio in space, and the strain energy density at the spatial position is greater than the average strain energy density of the surrounding data points, or the ratio of the maximum principal axis to the second largest principal axis of the shape factor is less than the ratio of the minimum principal axis to the second largest principal axis, and the angle between the direction of the maximum principal axis and the tangent direction of the grounding line at the corresponding position of the data point is greater than the angle between the direction of the minimum principal axis and the normal direction of the grounding line, then the spatial position is regarded as a stress singular point, and the area containing the stress singular point is marked as a stress mutation area.

[0022] Furthermore, in step S2.2, the constructed three-dimensional force distribution model must simultaneously satisfy:

[0023] Under the action of gravity, the tangential stress at any point of the grounding line is proportional to the horizontal distance from any point to the lowest point, and the normal stress is proportional to the vertical distance from any point to the lowest point;

[0024] In the stress mutation area, the boundary conditions of the piecewise Hermite interpolation function are adjusted to achieve stress continuity and local strain coordination;

[0025] Among them, local strain compatibility means that the main direction of the strain tensor at the boundary of the stress mutation zone maintains a continuous gradient with the main direction of the strain tensor in the non-stress mutation zone.

[0026] Further, in step S3, the ground wire force imbalance area is analyzed based on the three-dimensional force distribution model, the specific spatial position of the virtual hanging point is determined and the positioning information is output, including the following steps:

[0027] Step S3.1: Calculate the stress distribution curvature of the grounding wire, perform singular value decomposition, determine the direction of the main curvature, and identify the area of ​​uneven stress;

[0028] Step S3.2: In the force-unbalanced area, the spectrum characteristics of the three-dimensional force distribution model are analyzed based on discrete Fourier transform, the spectrum characteristics are arranged in descending order according to the energy size, the first N-order characteristic components are extracted, and their projections in the main curvature direction are calculated, the peak position of the projection is determined, and the peak position is marked as the candidate position of the virtual hanging point;

[0029] Step S3.3: Calculate the curl and divergence of the stress field around the candidate position of the virtual hanging point. If the curl value at the candidate position of the virtual hanging point is greater than the curl value of any point around the candidate position of the virtual hanging point, and the divergence value at the candidate position of the virtual hanging point is less than the divergence value of any point around the candidate position of the virtual hanging point, then the candidate position of the virtual hanging point is determined as the specific spatial position of the virtual hanging point, and the three-dimensional coordinates of the specific spatial position are output as the positioning information.

[0030] Further, in step S3.1, the singular value decomposition includes calculating the eigenvalue and eigenvector of the curvature; determining the direction corresponding to the eigenvector with the largest eigenvalue as the principal curvature direction, and if multiple intersections of the principal curvature directions are detected in the stress mutation zone, determining the area surrounded by the lines between the intersections as the stress imbalance area;

[0031] When processing the stress distribution curvature of the grounding wire, a stress distribution curvature matrix K is first constructed. Each element in this matrix represents the principal curvature value at the corresponding position, that is, it describes the degree of bending of the force at this point. Based on these data, the singular value decomposition SVD algorithm is used to analyze the stress distribution curvature matrix K.

[0032] Through singular value decomposition (SVD), the original curvature matrix is ​​decomposed into three components: U, Σ, and V T ; Among them, U is the left singular vector matrix, which describes the main change direction in the original data space; Σ is a diagonal matrix, and the elements on its diagonal represent the eigenvalues; V is a matrix composed of eigenvectors, and each column corresponds to an eigenvector; the eigenvalue indicates the importance of each eigenvector, and the eigenvector corresponding to the maximum eigenvalue indicates the direction of the principal curvature, that is, the direction in which the force changes most significantly.

[0033] A pressure-sensing-based intelligent anti-virtual-hanging grounding wire system, which is used to implement the above-mentioned pressure-sensing-based intelligent anti-virtual-hanging grounding wire method, comprises: an acquisition module, which acquires pressure data and relative spatial coordinates of multiple preset positioning points on the grounding wire; a model building module, which builds a three-dimensional force distribution model of the grounding wire according to the pressure data and the relative spatial coordinates; and a positioning module, which analyzes the uneven force area of ​​the grounding wire based on the three-dimensional force distribution model, determines the specific spatial position of the virtual hanging point and outputs positioning information.

[0034] A computer device or a computer-readable storage medium. The computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the steps of the intelligent anti-false hanging grounding wire method based on pressure sensing are implemented;

[0035] A computer program is stored on the computer-readable storage medium, and when the computer program is executed by the processor, the steps of the above-mentioned intelligent anti-false hanging grounding wire method based on pressure sensing are implemented.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] This intelligent anti-virtual hanging grounding wire method based on pressure sensing introduces a multi-dimensional measurement scheme of a strain type pressure sensor group in the data acquisition link, and combines the dynamic trigger mechanism and lateral strain field analysis to achieve accurate detection of torsional deformation; in the model construction process, a three-dimensional model that accurately reflects the stress state of the grounding wire is established through stress ellipsoid analysis and a segmented interpolation method based on the catenary characteristics; in the virtual hanging point positioning stage, a method combining singular value decomposition and spectrum feature analysis is adopted to achieve accurate positioning of the virtual hanging point.

[0038] This intelligent anti-false hanging grounding wire method based on pressure sensing not only significantly improves the accuracy of false hanging detection, but also can adapt to various application scenarios under complex terrain conditions, effectively solves the problems of missed detection and misjudgment in traditional technologies, and provides reliable technical guarantee for the safe operation of grounding wires. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0040] Figure 1 It is a schematic diagram of the overall process of the intelligent anti-false hanging grounding wire method based on pressure sensing of the present invention;

[0041] Figure 2 This is a diagram of the computer equipment in the intelligent anti-false hanging grounding wire method based on pressure sensing of the present invention. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings of the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without creative work are within the scope of protection of the present invention.

[0043] Example 1

[0044] In order to solve the problems of missed detection, misjudgment and inaccurate positioning in the traditional ground wire installation quality inspection, this embodiment provides an intelligent anti-false hanging ground wire method based on pressure sensing.

[0045] Figure 1 The overall process diagram of the intelligent anti-false hanging grounding wire method based on pressure sensing is shown, including the following steps:

[0046] S1: Obtain the pressure data and relative spatial coordinates of multiple preset positioning points on the grounding line.

[0047] The preset positioning points include pressure sensors uniformly distributed along the circumference of the grounding line.

[0048] S1.1: Obtain pressure data of multiple pressure sensors on the grounding wire, where the pressure sensors are evenly distributed along the circumference of the grounding wire; wherein the installation spacing between the pressure sensors is a preset value.

[0049] The pressure sensor is a strain type pressure sensor group, each group of strain type pressure sensor groups includes a plurality of first strain gauges uniformly distributed along the circumference of the grounding wire and a plurality of second strain gauges arranged along the axial direction of the grounding wire; if the difference ratio between the strain value of the first strain gauge and the strain values ​​of its two adjacent first strain gauges is the largest, and the strain value of the first strain gauge is greater than the sum of the strain values ​​of its two adjacent first strain gauges, then all the second strain gauges in the same cross section as the first strain gauge are activated to construct a transverse strain field.

[0050] Specifically, the lateral strain field is divided into two left and right areas relative to the first strain gauge, the sum of the strain values ​​of the second strain gauge in the two areas is calculated, and the midpoint of the line connecting the endpoint of the area with the largest sum of strain values ​​and the position of the first strain gauge is determined as the torsion center position.

[0051] S1.2: Determine the relative spatial coordinates of each pressure sensor based on its installation position, and establish a corresponding relationship between the pressure data and the relative spatial coordinates; wherein the relative spatial coordinates establish a three-dimensional coordinate system with the starting end of the grounding wire as the origin.

[0052] In this embodiment, in order to realize the accurate detection and positioning of the virtual hanging point of the grounding wire, the intelligent anti-virtual hanging grounding wire method based on pressure sensing is proposed. Specifically, multiple groups of strain type pressure sensors are evenly installed along the circumference of the grounding wire, and each group of sensors includes a first strain gauge distributed in the circumference and a second strain gauge arranged in the axial direction. Compared with the prior art that only uses a single pressure sensor, the sensor group arrangement scheme can simultaneously obtain pressure and torsional deformation data. When the grounding wire is virtual hanging, abnormal strain distribution often occurs in the local area. By comparing the strain value difference ratio between the first strain gauge and its adjacent sensor, once the abnormal strain is detected, the second strain gauge array in the area is immediately activated to construct a lateral strain field. This trigger mechanism not only reduces the data processing burden of the system, but also improves the sensitivity of abnormality detection. By dividing the lateral strain field into relative areas and analyzing the strain value distribution, the torsion center position can be accurately located. This positioning method based on strain field analysis breaks through the limitations of traditional single-point measurement.

[0053] While acquiring pressure data, the intelligent anti-virtual hanging grounding wire method based on pressure sensing establishes a complete set of spatial coordinate mapping systems. By establishing a three-dimensional coordinate system with the starting end of the grounding wire as the origin, accurate spatial position information is calibrated for each pressure sensor. This solution solves the problem of spatial positioning ambiguity that is prevalent in the prior art. In traditional methods, due to the lack of a unified spatial reference system, it is often difficult to accurately describe the specific location of the virtual hanging point, resulting in low maintenance efficiency. The intelligent anti-virtual hanging grounding wire method based on pressure sensing not only provides reliable data support for the subsequent construction of a three-dimensional force distribution model by establishing an accurate correspondence between pressure data and spatial coordinates, but also realizes the precise positioning of the virtual hanging point position. This scheme combining data acquisition with spatial positioning significantly improves the detection accuracy and practicality of the system. Especially in the case of complex terrain or limited installation space, the intelligent anti-virtual hanging grounding wire method based on pressure sensing can provide more comprehensive and accurate monitoring data, effectively improving the reliability of grounding wire virtual hanging detection. In addition, this standardized spatial coordinate system also facilitates the integration and comparison of grounding wire monitoring data in different sections, providing a technical basis for the intelligent management of large-scale grounding wire systems.

[0054] S2: Construct a three-dimensional force distribution model of the grounding wire based on the pressure data and relative spatial coordinates.

[0055] The three-dimensional force distribution model includes the mapping relationship between the spatial position and pressure value of each positioning point of the grounding wire.

[0056] S2.1: Construct a three-dimensional force distribution point cloud of the grounding wire based on the pressure data and relative spatial coordinates, and perform stress state analysis on the three-dimensional force distribution point cloud.

[0057] Specifically, each data point of the three-dimensional force distribution point cloud includes a mapping relationship between the spatial position of the grounding wire positioning point and the pressure value.

[0058] Furthermore, the stress state analysis mainly includes the following contents:

[0059] Calculate the principal stress direction and stress ellipsoid eigenvalue of each data point of the three-dimensional force distribution point cloud, and determine the stress state of the data point based on the shape factor of the stress ellipsoid; the shape factor is the ratio of the lengths of the three principal axes of the stress ellipsoid;

[0060] Calculate the shear stress ratio and principal stress ratio of adjacent data points respectively; the shear stress ratio is the ratio of tangential stress to normal stress, and the principal stress ratio is the ratio of maximum principal stress to minimum principal stress;

[0061] If the extreme point of the shear stress ratio coincides with the extreme point of the principal stress ratio in space, and the strain energy density at the spatial position is greater than the average strain energy density of the surrounding data points, or the ratio of the maximum principal axis to the second largest principal axis of the shape factor is less than the ratio of the minimum principal axis to the second largest principal axis, and the angle between the direction of the maximum principal axis and the tangent direction of the grounding line at the corresponding position of the data point is greater than the angle between the direction of the minimum principal axis and the normal direction of the grounding line, then the spatial position is regarded as a stress singular point, and the area containing the stress singular point is marked as a stress mutation area.

[0062] It should be noted that the calculation of the principal stress direction and the eigenvalue of the stress ellipsoid includes: first, constructing a stress tensor matrix based on the pressure data collected by the pressure sensor. The matrix contains the normal stress and shear stress components at the data points. Then, by solving the characteristic equation of the stress tensor matrix, the three principal stress values ​​and the corresponding eigenvectors are obtained. These eigenvectors represent the direction of action of the principal stress, and the eigenvalues ​​represent the stress magnitude in the corresponding direction, and also serve as the three principal axis lengths of the stress ellipsoid, constituting the eigenvalues ​​of the stress ellipsoid.

[0063] S2.2: Based on the catenary characteristics of the grounding wire, the piecewise Hermite interpolation method is used to perform surface fitting on the data points of the three-dimensional force distribution point cloud to construct a three-dimensional force distribution model.

[0064] Among them, the three-dimensional force distribution model must simultaneously meet the following requirements: under the action of gravity, the tangential stress at any point on the grounding line is proportional to the horizontal distance from any point to the lowest point, and the normal stress is proportional to the vertical distance from any point to the lowest point; in the stress mutation zone, the boundary conditions of the piecewise Hermite interpolation function are adjusted to satisfy stress continuity and local strain coordination. Local strain coordination means that the main direction of the strain tensor at the boundary of the stress mutation zone and the main direction of the strain tensor in the non-stress mutation zone maintain continuous gradual changes.

[0065] The expression of the Hermite interpolation function is:

[0066]

[0067]

[0068] h 00 (t) = 2t 3 -3t 2 +1;

[0069] h 10 (t) = t 3 -2t 2 +t;

[0070] h 01 (t)=-2t 3 +3t 2 ;

[0071] h 11 (t) = t 3 -t 2 ;

[0072] In this three-dimensional interpolation function, H(x, y, z) is the interpolation function used to describe the stress distribution of the grounding wire in three-dimensional space; t is the normalization parameter used to interpolate between adjacent data points; σ i represents the stress value at point i; m i Indicates the rate of change of stress; h 00 (t), h 10 (t), h 01 (t), h 11 (t) is the basis function of Hermite interpolation, which ensures the continuity and smoothness of the interpolation function; R n Represents the non-stress mutation area; R s Indicates the stress mutation area; the adjustment coefficients α and β are introduced in the stress mutation area to adjust the boundary characteristics of the interpolation function: α controls the continuity of the stress value, and β controls the gradual change of the main direction of the strain tensor; the basis function h 00 ~h 11 The continuity of stress distribution is maintained, and at the same time, the proportional relationship between tangential stress and horizontal distance and the proportional relationship between normal stress and vertical distance are ensured by introducing the arc length parameter s, which satisfies the catenary characteristics of the grounding wire; s represents the arc length parameter along the grounding wire.

[0073] The design of this piecewise function not only ensures the continuity of the overall stress distribution, but also realizes the special treatment of the stress mutation zone through local parameter adjustment.

[0074] It should be noted that, in this embodiment, the core of step S2 is to combine the traditional pressure data processing method with the stress ellipsoid analysis in material mechanics. By constructing a three-dimensional force distribution point cloud and introducing the shape factor, shear stress ratio and principal stress ratio of the stress ellipsoid, a more comprehensive theoretical basis is provided for the identification of stress mutation zones. In the shape factor judgment, a judgment mechanism for abnormal stress state is established by analyzing the relationship between the main axis of the stress ellipsoid and the geometric characteristics of the grounding wire. This method breaks through the limitations of traditional judgment based on a single stress value, and can accurately identify potential virtual hanging risk points in the grounding wire based on the essence of material mechanics. At the same time, in the process of model construction, a segmented Hermite interpolation method is designed based on the catenary characteristics of the grounding wire. The continuity constraint of the main direction of the strain tensor ensures the model accuracy in the stress mutation zone. This processing method not only conforms to the actual force characteristics of the grounding wire, but also ensures the accuracy of the model in the characteristic area.

[0075] In practical applications, the S2 step of the present invention solves two key technical problems: First, under complex terrain conditions, the grounding wire often has multi-point force and torsional deformation coupling, and the traditional single pressure threshold judgment method is difficult to accurately identify the real virtual hanging point. By introducing stress ellipsoid analysis and combining the spatial overlap characteristics of shear stress ratio and principal stress ratio, it is possible to effectively distinguish between normal force changes and stress anomalies caused by virtual hanging. Secondly, at the boundary of the stress mutation zone, the traditional interpolation method often has the problem of discontinuous stress distribution, which affects the accuracy of virtual hanging point positioning. By establishing a continuity constraint based on the main direction of the strain tensor, accurate modeling of the stress mutation zone is achieved, laying a reliable data foundation for the subsequent virtual hanging point positioning. This multi-dimensional stress analysis method not only improves the accuracy of virtual hanging detection, but also reduces the misjudgment rate, which is of great significance for improving the reliability of safe operation of the grounding wire.

[0076] S3: Analyze the uneven stress area of ​​the ground wire based on the three-dimensional force distribution model, determine the specific spatial position of the virtual hanging point and output the positioning information.

[0077] The positioning information includes the spatial coordinates of the virtual hanging point on the ground line.

[0078] S3.1: Calculate the stress distribution curvature of the grounding wire based on the three-dimensional force distribution model and perform singular value decomposition on the curvature.

[0079] Specifically, the singular value decomposition includes calculating the eigenvalue and eigenvector of the curvature; the direction corresponding to the eigenvector with the largest eigenvalue is determined as the principal curvature direction; if multiple intersections of the principal curvature directions are detected in the stress mutation zone, the area surrounded by the lines between the intersections is determined as the unbalanced force area.

[0080] When dealing with the stress distribution curvature of the grounding wire, a stress distribution curvature matrix K is first constructed. Each element in this matrix represents the principal curvature value at the corresponding position, that is, it describes the degree of curvature of the force at that point. Based on these data, the singular value decomposition SVD algorithm is used to analyze the stress distribution curvature matrix K. Through SVD decomposition, the original curvature matrix is ​​decomposed into three components: U, Σ, and V T Among them, U is the left singular vector matrix, which describes the main change direction in the original data space; Σ is a diagonal matrix, and the elements on its diagonal represent the eigenvalues; and V is a matrix composed of eigenvectors, and each column corresponds to an eigenvector; V T is the transposed matrix of matrix V, that is, the row vector of V becomes V T The column vector of V becomes V T The eigenvalue indicates the importance of each eigenvector, and the eigenvector corresponding to the maximum eigenvalue indicates the direction of the principal curvature, that is, the direction in which the force changes most significantly.

[0081] It should be noted that the singular value decomposition of the curvature of the stress distribution of the grounding wire is essentially to transform the complex three-dimensional stress distribution into an orthogonal eigenspace. When the grounding wire is suspended, the stress distribution will change significantly in a specific direction, and this change will be reflected in the eigenvalues ​​of the singular value decomposition. The eigenvector with the largest eigenvalue represents the direction in which the stress changes most significantly, that is, the direction of the principal curvature. The intersection of multiple principal curvature directions often means that the stress field has undergone significant distortion or mutation in this area, which is highly consistent with the mechanical properties of the grounding wire when it is suspended.

[0082] S3.2: In the area of ​​uneven force, the spectrum characteristics of the three-dimensional force distribution model are analyzed based on discrete Fourier transform, the spectrum characteristics are arranged in descending order according to the energy size, and the first N order characteristic components are extracted; the projection of the characteristic components in the direction of the main curvature is calculated, the peak position of the projection is determined, and the peak position is marked as the candidate position of the virtual hanging point.

[0083] Among them, the analysis process of the spectral characteristics is to determine the direction of the main curvature, and then extract a series of discrete data points from the three-dimensional stress distribution model along the main curvature direction in the area of ​​uneven force to form a discrete sequence. Subsequently, the fast Fourier transform FFT is applied to convert the discrete sequence into the frequency domain. Frequency domain analysis helps to identify periodic components and regularities in the signal. The frequency components are sorted according to the energy size, and the first N components with the highest energy are selected as characteristic components. This method aims to highlight the abnormal stress characteristics caused by virtual hanging, because high-frequency components often carry information about local stress mutations, while low-frequency components reflect more of the overall trend.

[0084] Calculating the projection of the characteristic components in the direction of the principal curvature is a further processing of the results of the first two steps. In order to further refine the positioning, the selected N characteristic components are reconstructed back to the spatial domain through inverse transformation to restore their representation in the actual physical space. Then, the projection of these reconstructed characteristic components in the direction of the principal curvature is calculated. This step uses the standard vector projection method to determine the peak position by analyzing the local extreme points of the projection curve. The peak position usually appears where the stress changes sharply, which is a sign of the occurrence of virtual hanging. Therefore, the peak position can be used as an important reference for the candidate position of the virtual hanging point.

[0085] It should be noted that the stress distribution in the unbalanced stress area is converted to the frequency domain space by discrete Fourier transform. In the frequency domain, the stress anomaly caused by virtual hanging will appear as specific frequency components, which are often more significant in energy. By extracting the first N-order characteristic components and projecting them in the direction of the main curvature, the stress fluctuations caused by the normal stress of the grounding wire and the environmental noise can be effectively filtered out, highlighting the stress anomaly characteristics caused by virtual hanging. This method is particularly suitable for virtual hanging detection under complex terrain conditions, because in this case, the stress distribution in the time domain is often more complex, while the virtual hanging characteristics can be clearly separated in the frequency domain.

[0086] S3.3: Calculate the curl and divergence of the stress field around each candidate virtual hanging point position. If the curl value at the candidate virtual hanging point position is greater than the curl value of any point around the candidate virtual hanging point position, and the divergence value at the candidate virtual hanging point position is less than the divergence value of any point around the candidate virtual hanging point position, then the candidate virtual hanging point position is determined as the specific spatial position of the virtual hanging point, and the three-dimensional coordinates of the specific spatial position are output as positioning information.

[0087] Among them, the curl characterizes the local rotation characteristics of the stress field, and the divergence characterizes the divergence characteristics of the stress distribution. After determining the candidate positions of the virtual hanging points, in order to further confirm the specific spatial coordinates of these positions, it is necessary to calculate the curl Curl and divergence of the stress field in the candidate positions and their neighborhoods. First, for each candidate position of the virtual hanging point, a local analysis area centered on the position is defined. The area should contain enough surrounding data points to ensure that sufficient information on the changes in the local stress field can be captured. Based on the three-dimensional force distribution model, a stress tensor field is constructed in this local analysis area. The stress tensor field describes the stress state in all directions inside the material, including normal stress and shear stress components. By integrating the pressure sensor readings and other relevant information, the stress tensor corresponding to each data point is estimated, thus laying the foundation for the subsequent calculation of the curl and divergence.

[0088] For the calculation of curl, curl is an important physical quantity that measures the degree of rotation in a vector field and is used to characterize the local rotation characteristics in a stress field. Specifically, for each candidate virtual hanging point and its neighboring data points, the tangential stress component in their respective stress tensors is extracted, and the curl is approximately solved using the finite difference method or other numerical methods. This process involves calculating the tangential stress difference between adjacent points. Especially in the three-dimensional case, the stress changes in three mutually perpendicular directions must be considered simultaneously to accurately reflect the rotation characteristics of the stress field. For the calculation of divergence, divergence is used to measure the existence of a source or sink in a vector field, that is, whether the stress diffuses outward or converges inward from a certain point. Therefore, for each candidate virtual hanging point and the surrounding data points, the normal stress component in its stress tensor is extracted, and a similar numerical method, such as the finite difference method, is applied to estimate the divergence, and then the divergence value at each point is obtained to quantify the concentration or dispersion of stress at that location.

[0089] After completing the calculation of the above curl and divergence, the comparison and decision stage is entered. By comparing the curl and divergence values ​​at the candidate position of the virtual hanging point with the corresponding values ​​of the surrounding points, significant features can be identified. If the curl value at a candidate position of a virtual hanging point is significantly higher than any point around it, it indicates that there is an obvious stress rotation phenomenon at this position, suggesting that there may be a virtual hanging situation; if the divergence value at this position is lower than all the surrounding points, it means that the stress here tends to converge inward rather than diffuse outward, which is another important manifestation of the virtual hanging feature. When both conditions are met, the candidate position of the virtual hanging point can be confirmed as an actual virtual hanging point, and its three-dimensional coordinates can be output as the final positioning information. This method not only improves the reliability of the detection results, but also enhances the ability to deal with virtual hanging problems under complex terrain conditions. By combining the calculation of curl and divergence, the spatial distribution characteristics of the stress field can be deeply analyzed from a mechanical perspective, so as to more accurately identify and locate the virtual hanging points on the grounding wire, providing a solid technical guarantee for the safe operation of the power system.

[0090] It should be noted that near the virtual hanging point of the grounding wire, the stress field will show unique geometric characteristics. The curl of the stress field reflects the rotation trend of the local stress. At the virtual hanging point, due to the abnormal stress state of the grounding wire, the stress field will show obvious rotation characteristics, which is manifested as the local maximum value of the curl. At the same time, the stress field at the virtual hanging point will show the characteristic of inward convergence, that is, the stress converges from the surrounding to the virtual hanging point. This characteristic is manifested as a local minimum in divergence. The combined characteristics of maximum curl and minimum divergence accurately describe the distribution pattern of the stress field at the virtual hanging point, providing a reliable theoretical basis for the precise positioning of the virtual hanging point.

[0091] In summary, the intelligent anti-virtual hanging grounding wire method based on pressure sensing introduces a multi-dimensional measurement scheme of a strain gauge pressure sensor group in the data acquisition link, and combines the dynamic trigger mechanism and lateral strain field analysis to achieve accurate detection of torsional deformation; in the model construction process, a three-dimensional model that accurately reflects the stress state of the grounding wire is established through stress ellipsoid analysis and a segmented interpolation method based on the characteristics of the catenary; in the virtual hanging point positioning stage, a method combining singular value decomposition and spectral feature analysis is used to achieve accurate positioning of the virtual hanging point. This multi-dimensional intelligent detection scheme not only significantly improves the accuracy of virtual hanging detection, but also can adapt to various application scenarios under complex terrain conditions, effectively solves the problems of missed detection and misjudgment in traditional technologies, and provides reliable technical guarantees for the safe operation of grounding wires.

[0092] Example 2

[0093] Based on the intelligent anti-virtual hanging grounding wire method based on pressure sensing proposed in Example 1, this embodiment provides an intelligent anti-virtual hanging grounding wire system based on pressure sensing, including:

[0094] The acquisition module is used to obtain the pressure data and relative spatial coordinates of multiple preset positioning points on the grounding wire; the model building module is used to build a three-dimensional force distribution model of the grounding wire based on the pressure data and the relative spatial coordinates; the positioning module is used to analyze the unbalanced force area of ​​the grounding wire based on the three-dimensional force distribution model, determine the specific spatial position of the virtual hanging point and output the positioning information. The intelligent anti-virtual hanging grounding wire system based on pressure sensing is used to implement an intelligent anti-virtual hanging grounding wire method based on pressure sensing.

[0095] Example 3

[0096] Reference Figure 2 , this embodiment is different from the previous embodiment in that: if the function is implemented in the form of a software function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device, which can be a personal computer, a server, or a network device, etc., to execute all or part of the steps of the method described in each embodiment. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0097] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus, such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions, or used in conjunction with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with these instruction execution systems, devices or apparatuses.

[0098] More specific examples of computer-readable media, which are not an exhaustive list, include the following: an electrical connection with one or more wirings, i.e. an electronic device, a portable computer disk case, i.e. a magnetic device, a random access memory RAM, a read-only memory ROM, an erasable and programmable read-only memory EPROM or flash memory, an optical fiber device, and a portable compact disk read-only memory CDROM. In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0099] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array PGA, a field programmable gate array FPGA, etc.

[0100] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. An intelligent method for preventing false hanging of ground wire based on pressure sensing, characterized in that: The following steps are involved: Step S1: Obtaining pressure data and relative spatial coordinates of multiple preset positioning points on the grounding line; Step S2: constructing a three-dimensional force distribution model of the grounding wire according to the pressure data and the relative spatial coordinates; the three-dimensional force distribution model includes a mapping relationship between the spatial position and pressure value of each positioning point of the grounding wire; Step S3: Analyze the uneven stress area of ​​the grounding wire based on the three-dimensional stress distribution model, determine the specific spatial position of the virtual hanging point and output positioning information; the positioning information includes the spatial coordinates of the virtual hanging point on the grounding wire.

2. The intelligent method for preventing false hanging of ground wire based on pressure sensing according to claim 1 is characterized in that: In step S1, the pressure data and relative spatial coordinates of a plurality of preset positioning points on the grounding line are obtained, including the following steps: Step S1.1: obtaining pressure data of a plurality of pressure sensors on the grounding wire, wherein the pressure sensors are evenly distributed along the circumference of the grounding wire; Step S1.2: Determine the relative spatial coordinates of the pressure sensor based on its installation position, establish a corresponding relationship between the pressure data and the spatial coordinates, and establish a three-dimensional coordinate system with the starting end of the grounding wire as the origin.

3. The intelligent method for preventing false hanging of ground wire based on pressure sensing according to claim 2 is characterized in that: The sensor is a strain type pressure sensor group, each group of strain type pressure sensor group includes a plurality of first strain gauges uniformly distributed along the circumference of the grounding wire and a plurality of second strain gauges arranged along the axial direction of the grounding wire; If the difference ratio between the strain value of the first strain gauge and the strain values ​​of its two adjacent first strain gauges is the largest, and the strain value of the first strain gauge is greater than the sum of the strain values ​​of its two adjacent first strain gauges, all the second strain gauges in the same cross section as the first strain gauge are activated to construct a transverse strain field; The lateral strain field is divided into two left and right areas relative to the first strain gauge, the sum of the strain values ​​of the second strain gauge in the two areas is calculated, and the midpoint of the line connecting the endpoint of the area with the largest sum of strain values ​​and the position of the first strain gauge is determined as the torsion center position.

4. The intelligent method for preventing false hanging of ground wire based on pressure sensing according to claim 1 is characterized in that: In step S2, a three-dimensional force distribution model of the grounding wire is constructed according to the pressure data and the relative spatial coordinates, including the following steps: Step S2.1: constructing a three-dimensional force distribution point cloud of the grounding wire based on the pressure data and the relative spatial coordinates, and performing stress state analysis on the three-dimensional force distribution point cloud; Step S2.2: Based on the catenary characteristics of the grounding wire, the piecewise Hermite interpolation method is used to perform surface fitting on the data points of the three-dimensional force distribution point cloud to construct a three-dimensional force distribution model.

5. The intelligent method for preventing false hanging of ground wire based on pressure sensing according to claim 4 is characterized in that: In step S2.1, a stress state analysis is performed on the three-dimensional force distribution point cloud, including calculating the principal stress direction and the characteristic value of the stress ellipsoid of each data point of the three-dimensional force distribution point cloud, and determining the stress state of the data point based on the shape factor of the stress ellipsoid; wherein the shape factor is the ratio of the lengths of the three principal axes of the stress ellipsoid; Calculate the shear stress ratio and principal stress ratio of adjacent data points respectively; the shear stress ratio is the ratio of tangential stress to normal stress; the principal stress ratio is the ratio of maximum principal stress to minimum principal stress; If the extreme point of the shear stress ratio coincides with the extreme point of the principal stress ratio in space, and the strain energy density at the spatial position is greater than the average strain energy density of the surrounding data points, or the ratio of the maximum principal axis to the second largest principal axis of the shape factor is less than the ratio of the minimum principal axis to the second largest principal axis, and the angle between the direction of the maximum principal axis and the tangent direction of the grounding line at the corresponding position of the data point is greater than the angle between the direction of the minimum principal axis and the normal direction of the grounding line, then the spatial position is regarded as a stress singular point, and the area containing the stress singular point is marked as a stress mutation area.

6. The intelligent method for preventing false hanging of ground wire based on pressure sensing according to claim 4 is characterized in that: In step S2.2, the constructed three-dimensional force distribution model must simultaneously satisfy: Under the action of gravity, the tangential stress at any point of the grounding line is proportional to the horizontal distance from any point to the lowest point, and the normal stress is proportional to the vertical distance from any point to the lowest point; In the stress mutation area, the boundary conditions of the piecewise Hermite interpolation function are adjusted to achieve stress continuity and local strain coordination; Among them, local strain compatibility means that the main direction of the strain tensor at the boundary of the stress mutation zone maintains a continuous gradient with the main direction of the strain tensor in the non-stress mutation zone.

7. The intelligent method for preventing false hanging of ground wire based on pressure sensing according to claim 1 is characterized in that: In step S3, the ground wire stress imbalance area is analyzed based on the three-dimensional stress distribution model, the specific spatial position of the virtual hanging point is determined and the positioning information is output, including the following steps: Step S3.1: Calculate the stress distribution curvature of the grounding wire, perform singular value decomposition, determine the direction of the main curvature, and identify the area of ​​uneven stress; Step S3.2: In the force-unbalanced area, the spectrum characteristics of the three-dimensional force distribution model are analyzed based on discrete Fourier transform, the spectrum characteristics are arranged in descending order according to the energy size, the first N-order characteristic components are extracted, and their projections in the main curvature direction are calculated, the peak position of the projection is determined, and the peak position is marked as the candidate position of the virtual hanging point; Step S3.3: Calculate the curl and divergence of the stress field around the candidate position of the virtual hanging point. If the curl value at the candidate position of the virtual hanging point is greater than the curl value of any point around the candidate position of the virtual hanging point, and the divergence value at the candidate position of the virtual hanging point is less than the divergence value of any point around the candidate position of the virtual hanging point, then the candidate position of the virtual hanging point is determined as the specific spatial position of the virtual hanging point, and the three-dimensional coordinates of the specific spatial position are output as the positioning information.

8. The intelligent method for preventing false hanging of ground wire based on pressure sensing according to claim 1 is characterized in that: In step S3.1, the singular value decomposition includes calculating the eigenvalue and eigenvector of the curvature; determining the direction corresponding to the eigenvector with the largest eigenvalue as the principal curvature direction; if multiple intersections of the principal curvature directions are detected in the stress mutation zone, the area surrounded by the lines between the intersections is determined as the stress imbalance zone; When processing the stress distribution curvature of the grounding wire, a stress distribution curvature matrix K is first constructed. Each element in this matrix represents the principal curvature value at the corresponding position, that is, it describes the degree of curvature of the force at that point. Based on these data, the singular value decomposition SVD algorithm is used to analyze the stress distribution curvature matrix K; Through singular value decomposition (SVD), the original curvature matrix is ​​decomposed into three components: U, Σ, and V T ; Among them, U is the left singular vector matrix, which describes the main change direction in the original data space; Σ is a diagonal matrix, and the elements on its diagonal represent the eigenvalues; V is a matrix composed of eigenvectors, and each column corresponds to an eigenvector; the eigenvalue indicates the importance of each eigenvector, and the eigenvector corresponding to the maximum eigenvalue indicates the direction of the principal curvature, that is, the direction in which the force changes most significantly.

9. An intelligent anti-virtual hanging grounding wire system based on pressure sensing, the intelligent anti-virtual hanging grounding wire system is used to implement the intelligent anti-virtual hanging grounding wire method based on pressure sensing according to any one of claims 1 to 8, characterized in that: The intelligent anti-false hanging grounding wire system includes: An acquisition module, which acquires pressure data and relative spatial coordinates of multiple preset positioning points on the grounding line; A model building module, which builds a three-dimensional force distribution model of the grounding wire according to the pressure data and the relative spatial coordinates; A positioning module analyzes the uneven stress area of ​​the grounding wire based on the three-dimensional stress distribution model, determines the specific spatial position of the virtual hanging point and outputs positioning information.

10. A computer device or a computer readable storage medium, characterized in that: The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the intelligent anti-false hanging grounding wire method based on pressure sensing according to any one of claims 1 to 8 when executing the computer program; A computer program is stored on a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the intelligent anti-false hanging grounding wire method based on pressure sensing described in any one of claims 1 to 8 are implemented.

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