Low-voltage distribution box data real-time acquisition method and system

Abstract

The application discloses a low-voltage distribution box data real-time acquisition method and system, relates to the technical field of data acquisition, and comprises the following steps: obtaining a boundary layer conductance matrix based on a thin cavity region between a door plate lining and a device mounting plate of a low-voltage distribution box; obtaining a suture texture matrix based on a capillary channel region and the boundary layer conductance matrix, and constructing an adjacency matrix based on the suture texture matrix; determining pheromone of each adjacent node pair in the adjacency matrix based on the suture texture matrix; obtaining a target path based on the adjacency matrix, and constructing a pheromone matrix according to the target path and the pheromone of the adjacent node pair; obtaining a loop allowance degree vector based on the pheromone matrix, and generating a real-time acquisition state vector of the low-voltage distribution box based on the loop allowance degree vector; and the application improves the identification precision of the interference source.

Description

Technical Field

[0001] This invention relates to the field of data acquisition technology, and in particular to a method and system for real-time data acquisition from low-voltage distribution boxes. Background Technology

[0002] Low-voltage distribution boxes at the end of commercial complexes are typically located in air conditioning return air areas, equipment mezzanines, or areas with frequent personnel activity. They operate under conditions of intermittent air supply, diurnal temperature variations, and uneven heat exchange between the door panel and the box body. This creates a thin cavity space with restricted airflow between the door panel lining and the device mounting plate. Within this space, temperature and humidity fluctuations, dust accumulation, and uneven surface morphology can lead to localized condensation and contaminant adhesion. This results in the formation of boundary conductive pathways on narrow slits, recessed structures, and rough insulating surfaces, where moisture is trapped and continuously distributed along the solid interface. These boundary conductive pathways are spatially networked and can conduct charge between different locations, altering the potential distribution within the thin cavity and affecting the current path. In this environment, low-voltage distribution boxes not only need to collect real-time parameters such as voltage, current, and power for each branch circuit, but also need to address the changes in the electrical environment of the acquisition link caused by the boundary conductive pathways to ensure that the collected results accurately reflect the power supply operation status.

[0003] Under the aforementioned environmental conditions, the presence of boundary conductivity paths alters the potential assignment of the sampling reference surface, causing the electrical signals acquired in the acquisition link to be mixed with the boundary conductivity effects introduced by non-power supply paths. This results in the real-time acquisition quantities of each branch circuit deviating from the actual operating state. Existing technologies typically monitor and control based on the original acquisition quantities, lacking processing methods to address the influence of boundary conductivity paths. This can easily lead to inconsistencies between the acquisition results and the actual power supply state, thereby affecting the accuracy of power distribution operation decisions and remote control. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies that lack processing methods for the influence of boundary conductive paths, and to propose a real-time data acquisition method and system for low-voltage distribution boxes.

[0005] To address the problems existing in the prior art, the present invention adopts the following technical solution: A method for real-time data acquisition from a low-voltage distribution box includes: S1. The boundary conductance matrix is ​​obtained based on the thin cavity region between the door panel lining of the low-voltage distribution box and the device mounting plate. S2. Obtain the stitching texture matrix based on the capillary channel region and boundary conductivity matrix, and construct the adjacency matrix based on the stitching texture matrix; S3. Based on the stitching texture matrix, determine the pheromone of each pair of adjacent nodes in the adjacency matrix; S4. Obtain the target path based on the adjacency matrix, and construct the pheromone matrix based on the pheromone of the target path and the adjacent node pairs; S5. Obtain the loop allowance vector based on the pheromone matrix, and generate the real-time acquisition status vector of the low-voltage distribution box based on the loop allowance vector.

[0006] Preferably, the boundary conductance matrix is ​​obtained based on the thin cavity region between the door panel liner of the low-voltage distribution box and the device mounting plate, including: Position the thin cavity area between the door panel lining of the low-voltage distribution box and the component mounting plate; A microelectrode array is disposed in the thin cavity region; wherein, the microelectrode array is composed of multiple sets of grid electrode pairs; Synchronous sampling is performed on each grid electrode pair to obtain the boundary potential difference signal and the boundary current signal; The boundary potential difference signals are arranged into a matrix to obtain the boundary potential difference matrix; The boundary current signals are arranged into a matrix to obtain the boundary current matrix; The boundary potential difference matrix and the boundary current matrix are calculated element by element to obtain the boundary conductance matrix.

[0007] Preferably, the stitching texture matrix is ​​obtained based on the capillary channel region and the boundary conductivity matrix, including: The narrow slit region, the recessed region, and the region covered by the rough insulating coating within the thin cavity region are defined as the capillary channel region; Based on the capillary channel region, the grid positions corresponding to each grid electrode pair in the thin cavity region are marked and assigned values ​​to obtain the structural mask matrix. The capillary conduction matrix is ​​obtained by multiplying the boundary conduction matrix and the structure mask matrix element by element. The stitching texture matrix is ​​obtained by performing row and column differences on the capillary conduction matrix.

[0008] Preferably, constructing an adjacency matrix based on the stitched texture matrix includes: Based on the index relationship of each grid point position in the thin cavity region, the boundary potential difference matrix, capillary conduction matrix and stitch texture matrix are flattened and arranged sequentially to obtain the node sequence; Based on the node sequence, establish adjacent node pairs; Calculate the edge weights of adjacent node pairs; Construct an adjacency matrix based on adjacent node pairs and edge weights.

[0009] Preferably, based on the stitching texture matrix, the pheromone of each pair of adjacent nodes in the adjacency matrix is ​​determined, including: The initial pheromone intensity of each adjacent node pair in the adjacency matrix is ​​determined based on the capillary conduction matrix and the stitching texture matrix. Based on the initial pheromone intensity, the pheromone of each pair of adjacent nodes in the adjacency matrix is ​​determined.

[0010] Preferably, obtaining the target path based on the adjacency matrix includes: Based on the correspondence between the grid points within the thin cavity region and the reference regions on the door panel side and the mounting plate side, determine the starting node set and the ending node set; In each iteration of the ant colony algorithm, a target starting node is selected from the set of starting nodes; Based on the adjacency matrix, a path is constructed from the set of starting nodes to ending nodes of the target to obtain the target path.

[0011] Preferably, a pheromone matrix is ​​constructed based on the pheromones of the target path and adjacent node pairs, including: After each iteration, the pheromones of adjacent node pairs are incrementally updated according to the target path to obtain the updated pheromones. After each iteration, the updated pheromone is evaporated to obtain the evaporated pheromone. A pheromone matrix is ​​constructed based on the pheromone after evaporation and the adjacency matrix.

[0012] Preferably, the loop permissibility vector is obtained based on the pheromone matrix, including: Calculate the node participation vector based on the pheromone matrix; Based on the branch circuits and thin cavity regions of the low-voltage distribution box, a circuit-node proximity matrix is ​​constructed; Perform matrix multiplication on the loop-node proximity matrix and the node participation vector to obtain the loop pollution weight vector; The loop contamination weight vector is transformed element by element to obtain the loop permissibility vector.

[0013] Preferably, the real-time acquisition status vector of the low-voltage distribution box is generated based on the loop tolerance vector, including: Based on the real-time data collected from each branch circuit in the low-voltage distribution box, a circuit state vector is generated. The reliable loop state vector is obtained by multiplying the loop permissibility vector and the loop state vector element by element. The reliable loop state vector is used as the real-time acquisition state vector of the low-voltage distribution box.

[0014] To address the above problems, the present invention also provides a real-time data acquisition system for low-voltage distribution boxes, the system comprising: The boundary conductivity generation module obtains the boundary conductivity matrix based on the thin cavity region between the door panel lining of the low-voltage distribution box and the device mounting plate. The stitch texture mapping module obtains the stitch texture matrix based on the capillary channel region and the boundary conductivity matrix, and constructs an adjacency matrix based on the stitch texture matrix; The initial information setting module determines the pheromone of each pair of adjacent nodes in the adjacency matrix based on the stitching texture matrix. The path information generation module obtains the target path based on the adjacency matrix and constructs a pheromone matrix based on the pheromone of the target path and adjacent node pairs. The status output module obtains the loop allowance vector based on the pheromone matrix and generates the real-time status vector of the low-voltage distribution box based on the loop allowance vector.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention deploys a microelectrode array in the thin cavity region between the door panel liner and the device mounting plate to obtain the boundary potential difference matrix, boundary current matrix, and boundary conductivity matrix. Combined with the capillary channel region, a capillary conduction matrix and a stitching texture matrix are formed. The boundary conductivity state is characterized from the spatial distribution level, which can locate the formation range and change relationship of the boundary conductivity path, and provide a basis for subsequent identification of the degree of disturbance of the acquisition link.

[0016] 2. The present invention further flattens the boundary potential difference data, capillary conduction data and suture texture data into a node sequence, establishes adjacent node pairs and constructs an adjacency matrix, and then determines the initial pheromone intensity based on the capillary conduction matrix and the suture texture matrix. By searching the target path, updating the pheromone incrementally and evaporating to update, a pheromone matrix is ​​formed, which can characterize the extension direction and retention degree of the boundary conductive path, thereby improving the accuracy of identifying interference sources.

[0017] 3. This invention utilizes the pheromone matrix to calculate the node participation vector, and combines it with the loop node proximity matrix to obtain the loop pollution weight vector and the loop allowance vector. Then, it corrects the loop state vector formed by the real-time acquisition data of each branch loop, and outputs the real-time acquisition state vector of the low-voltage distribution box. This can reduce the influence of boundary conductivity paths on the original acquisition data, make the output results closer to the actual power supply state, and improve the accuracy of power distribution monitoring and control. Attached Figure Description

[0018] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings: Figure 1 This is a flowchart illustrating a method for real-time data acquisition from a low-voltage distribution box according to an embodiment of the present invention. Figure 2 This is a functional module diagram of a real-time data acquisition system for a low-voltage distribution box provided in an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0020] This embodiment provides a method for real-time data acquisition from low-voltage distribution boxes. (See also...) Figure 1 Specifically, including: S1. The boundary conductance matrix is ​​obtained based on the thin cavity region between the door panel lining of the low-voltage distribution box and the device mounting plate. In an embodiment of the present invention, a boundary surface conductivity matrix is ​​obtained based on the thin cavity region between the door panel liner of the low-voltage distribution box and the device mounting plate, including: Position the thin cavity area between the door panel lining of the low-voltage distribution box and the component mounting plate; The thin cavity area refers to the enclosed or semi-enclosed space formed between the inner lining of the door panel of the low-voltage distribution box and the device mounting plate. Air flow is restricted in this space and local humidity and temperature gradients are easily formed.

[0021] The door panel liner and the device mounting plate constitute the two sides of the internal space of the low-voltage distribution box. The door panel liner is a structural layer set inside the box door to enclose the internal space and isolate it from the external environment. The device mounting plate is a load-bearing structure set inside the box to fix electrical components and conductive parts. The two form a relatively closed gap area. Under the combined effects of temperature changes, restricted air flow, and differences in surface conditions, this gap area is prone to uneven local humidity distribution and changes in boundary conductivity, thereby affecting the potential distribution and current conduction in this area.

[0022] First, open the door of the low-voltage distribution box to expose the inner structure of the door panel and the installation location of the internal components. Identify the inner surface boundary of the door panel lining and the outer surface boundary of the component mounting plate facing the door panel. Observe whether there is a continuous gap space between the door panel lining and the component mounting plate along the edge of the door panel lining. Then, use a ruler or feeler gauge to measure the distance between the inner surface of the door panel lining and the outer surface of the component mounting plate at the top, bottom, left, right, and middle positions. Based on the result that the distance of each measuring point is within the same continuous interlayer space, determine that the interlayer is a spatially connected thin cavity region. Subsequently, form boundary markers at the corresponding positions of the door panel lining or the component mounting plate along the boundary contour of the thin cavity region, so that the starting edge, ending edge, lateral edge, and coverage area of ​​the thin cavity region all have clear positional orientations.

[0023] A microelectrode array is disposed in the thin cavity region; wherein, the microelectrode array is composed of multiple sets of grid electrode pairs; A microelectrode array refers to a collection of multiple electrodes arranged in the thin cavity region to reflect the electrical state distribution at different locations; a grid electrode pair refers to electrode units arranged in pairs at corresponding locations to obtain the potential difference and current information at that location.

[0024] Based on the coverage area of ​​the thin cavity region with established boundary markings, horizontal and vertical reference lines are drawn along the side of the door panel liner facing the device mounting plate and the side of the device mounting plate facing the door panel liner, respectively. Multiple grid point positions are determined according to the intersection of the horizontal and vertical reference lines. At each grid point position, a sampling electrode is fixed on the side of the door panel liner and a reference electrode is fixed on the side of the device mounting plate directly opposite the grid point position. The sampling electrode and the reference electrode at the same grid point position form a grid electrode pair. Then, all grid electrode pairs are arranged sequentially in the thin cavity region in a manner that maintains a consistent arrangement direction between adjacent grid point positions, thereby forming a microelectrode array covering the thin cavity region. Each set of grid electrode pairs has a one-to-one correspondence in spatial position and a clear row and column distribution relationship.

[0025] Synchronous sampling is performed on each grid electrode pair to obtain the boundary potential difference signal and the boundary current signal; The boundary potential difference signal refers to the change in potential difference generated along the surface path between the door panel liner and the device mounting plate, which reflects the surface electric field distribution. The boundary current signal refers to the change in current flowing along the aforementioned surface path, which reflects the existence and strength of the surface conductive path. All grid electrode pairs are connected to the corresponding data acquisition channels according to their row and column positions in the thin cavity region, and all data acquisition channels share the same clock trigger signal. At the same trigger time, the potential difference data between the sampling electrode and the reference electrode in each grid electrode pair and the current data through the surface conductive path of the grid electrode pair are read simultaneously. Then, all potential difference data and all current data obtained at the same trigger time are written into the corresponding sampling record sequence, thereby obtaining the boundary potential difference signal and boundary current signal corresponding one-to-one with each grid position.

[0026] The boundary potential difference signals are arranged into a matrix to obtain the boundary potential difference matrix; Specifically, first, the row and column position numbers of all grid electrode pairs within the thin cavity region are read. Then, the boundary potential difference signals corresponding to each grid electrode pair are filled into a two-dimensional table consistent with the grid distribution of the thin cavity region according to their row and column positions. This ensures that the boundary potential difference signals corresponding to grid electrode pairs in the same row are arranged in the same row of the two-dimensional table, and that the boundary potential difference signals corresponding to grid electrode pairs in the same column are arranged in the same column of the two-dimensional table. After filling in all grid positions, a boundary potential difference matrix covering the spatial distribution relationship of the entire thin cavity region is formed.

[0027] The boundary current signals are arranged into a matrix to obtain the boundary current matrix; The boundary potential difference matrix refers to a two-dimensional data set formed by arranging the boundary potential difference signals at each grid point according to their spatial positions, used to characterize the potential distribution of the entire thin cavity region; the boundary current matrix refers to a two-dimensional data set formed by arranging the boundary current signals at each grid point according to their spatial positions, used to characterize the current distribution of the entire thin cavity region.

[0028] Specifically, the row and column positions of each grid electrode pair within the thin cavity region are read. The boundary current signals obtained by each grid electrode pair at the same sampling time are filled into a two-dimensional table consistent with the grid distribution of the thin cavity region according to their respective row and column positions. This ensures that the boundary current signals at the same row position are located in the same row of the two-dimensional table, and the boundary current signals at the same column position are located in the same column of the two-dimensional table. After filling in all grid positions, a boundary current matrix corresponding one-to-one with the spatial position of the boundary potential difference matrix is ​​obtained.

[0029] The boundary potential difference matrix and the boundary current matrix are calculated element by element to obtain the boundary conductance matrix.

[0030] The boundary conductivity matrix refers to the two-dimensional distribution of conductivity at each location through the correspondence between boundary potential difference and boundary current. It is used to characterize the strength of the ability to form a conductive path at different locations within a thin cavity region.

[0031] Specifically, a one-to-one correspondence is established between the elements of the boundary potential difference matrix and the elements of the boundary current matrix according to the same row and column positions. The absolute value of the boundary current value at each corresponding position is taken, and the absolute value of the boundary potential difference value at the corresponding position is also taken. The absolute value of the boundary current is then divided by the absolute value of the boundary potential difference to obtain the boundary conductance value at that position. The boundary conductance values ​​obtained at all positions are then written into a two-dimensional table of the same dimension as the boundary potential difference matrix and the boundary current matrix according to their original row and column positions, thereby obtaining the boundary conductance matrix.

[0032] S2. Obtain the stitching texture matrix based on the capillary channel region and boundary conductivity matrix, and construct the adjacency matrix based on the stitching texture matrix; In embodiments of the present invention, the stitching texture matrix is ​​obtained based on the capillary channel region and the boundary conductivity matrix, including: The narrow slit region, the recessed region, and the region covered by the rough insulating coating within the thin cavity region are defined as the capillary channel region; Narrow slit regions refer to elongated channels formed by structural gaps within thin cavity regions. These channels have small cross-sectional dimensions and a distinct extension direction, making it easy to maintain a continuous liquid medium distribution under surface tension. Recessed regions refer to localized depressions within thin cavity regions, which can accumulate liquid or contaminants and create a locally high-humidity environment. Rough insulating coating regions refer to areas of insulating material with microscopically uneven morphology covering the inner lining of door panels or the surface of device mounting plates. The rough surface structure of these regions enhances liquid adhesion and promotes liquid spreading on the surface. Capillary channel regions refer to the spatial regions formed by the aforementioned narrow slit regions, recessed regions, and rough insulating coating regions, which can maintain the continuous presence of liquid and form boundary conductive paths.

[0033] Specifically, the surfaces of the door panel liner facing the device mounting plate and the device mounting plate facing the door panel liner are inspected area by area along the determined thin cavity region boundary. The gap between the two surfaces that narrows significantly and extends continuously along the length direction is identified as the narrow slit region. The parts of the surface that are locally concave and can accommodate liquid retention are identified as the recessed region. The parts of the surface with an insulating coating that has a continuous rough undulating morphology are identified as the rough insulating coating coverage region. The spatial positions of the narrow slit region, recessed region and rough insulating coating coverage region in the thin cavity region are recorded one by one, and the union range of the three types of regions is determined as the capillary channel region.

[0034] Based on the capillary channel region, the grid positions corresponding to each grid electrode pair in the thin cavity region are marked and assigned values ​​to obtain the structural mask matrix. The structural mask matrix refers to the two-dimensional distribution formed by marking each discrete position in the thin cavity region, which is used to distinguish between capillary channel regions and non-capillary channel regions.

[0035] Specifically, the row and column positions of each grid electrode pair in the microelectrode array are read, and the correspondence between each grid position and the actual spatial position of the thin cavity region is established. Grid positions located in the capillary channel region are assigned channel label values, and grid positions located in the non-capillary channel region are assigned non-channel label values. All label values ​​are then written into a two-dimensional table according to the original row and column order of each grid position in the microelectrode array, thereby obtaining a structure mask matrix that is consistent with the spatial distribution of the thin cavity region and corresponds one-to-one with the position of each grid electrode pair.

[0036] The capillary conduction matrix is ​​obtained by multiplying the boundary conduction matrix and the structure mask matrix element by element. Specifically, first, the boundary conductance values ​​corresponding to each row and column position in the boundary conductance matrix are read. Then, the marker values ​​corresponding to each row and column position in the structural mask matrix are read. The boundary conductance value at each position is multiplied with the marker value at the same position, so that the corresponding position in the capillary channel region retains the original boundary conductance value, and the corresponding position in the non-capillary channel region is converted to zero value. Then, all the product results are written into a two-dimensional table with the same row and column distribution as the boundary conductance matrix and the structural mask matrix according to the original row and column order of each position, so as to obtain the capillary conduction matrix corresponding to the spatial position of the thin cavity region.

[0037] The stitching texture matrix is ​​obtained by performing row and column differences on the capillary conduction matrix.

[0038] The capillary conduction matrix refers to a two-dimensional set that retains only the conduction capability of the capillary channel region based on the boundary conduction distribution, and is used to characterize the spatial distribution of continuous conductive paths within the capillary channel; The stitching texture matrix refers to a two-dimensional distribution that characterizes the continuity and transition relationship of the capillary conduction state in the thin cavity region in space. This matrix is ​​used to reflect the degree of change in conductivity from strong to weak or from weak to strong between adjacent positions and the tightness of the connection between different conduction regions. When the value corresponding to certain positions in the matrix is ​​large, it indicates that the conduction state changes significantly and the connection relationship is relatively loose near that position. When the value is small, it indicates that the conduction state remains continuous between adjacent regions and the connection relationship is relatively stable. Thus, it reflects the splicing and extension state of the conductive path in the capillary channel in space.

[0039] Specifically, first, the values ​​of adjacent columns are read sequentially along each row of the capillary conduction matrix and the difference between them is calculated. The differences of all adjacent columns in the same row are written into the row difference result table in the original row order. Then, the values ​​of adjacent rows are read sequentially along each column of the capillary conduction matrix and the difference between them is calculated. The differences of all adjacent rows in the same column are written into the column difference result table in the original column order. Then, the absolute values ​​of the row difference and column difference at each corresponding position are taken and added together. The sum is written into a two-dimensional table according to the spatial arrangement relationship of the capillary conduction matrix, thus obtaining the stitching texture matrix used to characterize the spatial change relationship of the capillary conduction state.

[0040] It should be noted that the variation of boundary conductivity along space reflects the continuity and connection state of the surface conductive path at different locations. According to the relationship between current continuity and conductivity distribution, when the conductivity change between adjacent locations is gradual, the current can be stably distributed on the surface and form a continuous conductive path. However, when the conductivity change between adjacent locations is significant, the current distribution will be redistributed and a transition region will be formed at the connection. By calculating the difference between adjacent locations along the row and column directions of the capillary conductivity matrix, the conductivity change in each direction can be obtained. The absolute value of this change represents the degree of abrupt change in conductivity at that location. By superimposing the row and column changes, the intensity of conductivity change at that location in two-dimensional space can be comprehensively reflected, thereby characterizing the splicing degree and transition state between different conductive regions. Therefore, the results calculated by row and column differences can reflect the connection relationship and spatial extension between capillary conductive paths and form a stitching texture matrix.

[0041] In an embodiment of the present invention, constructing an adjacency matrix based on the stitching texture matrix includes: Based on the index relationship of each grid point position in the thin cavity region, the boundary potential difference matrix, capillary conduction matrix and stitch texture matrix are flattened and arranged sequentially to obtain the node sequence; A node sequence refers to an ordered set formed by unfolding the electrical states of each spatial location within a thin cavity region according to their spatial distribution relationship. Each node corresponds to a specific location within the thin cavity region and carries the potential distribution and conduction state information of that location.

[0042] Specifically, first, the row and column positions of all grid points within the thin cavity region are read in the microelectrode array. The row and column positions corresponding to each grid point are combined to form a unique index for that grid point. Then, an index table covering all grid point positions is built, with row positions increasing sequentially and column positions increasing sequentially within the same row. Subsequently, based on this index table, the matrix elements corresponding to each grid point position in the boundary potential difference matrix, capillary conduction matrix, and stitch texture matrix are read one-to-one, ensuring that the corresponding elements in the three matrices maintain consistent positions under the same index order. Finally, the boundary potential difference matrix... The boundary potential difference data corresponding to each index position, the capillary conduction data corresponding to each index position in the capillary conduction matrix, and the suture texture data corresponding to each index position in the suture texture matrix are extracted sequentially according to the same index order. The three types of data corresponding to the same index position are combined and written into the same node recording unit, so that each node recording unit corresponds to a unique grid point position in the thin cavity region and simultaneously contains the boundary potential difference information, capillary conduction information, and suture texture information of that grid point position. Then, all node recording units are arranged continuously according to the arrangement order of the index table to obtain the node sequence.

[0043] Based on the node sequence, establish adjacent node pairs; Specifically, the grid position index corresponding to each node record unit in the node sequence is read, and the row and column positions of each node in the thin cavity region are recovered based on the grid position index. Then, taking each node as the reference node, the nodes in the same row and column position that differ from the reference node by one unit, as well as the nodes in the same column and row position that differ from the reference node by one unit, are retrieved one by one. The nodes that satisfy the above positional relationship are paired with the reference node to form adjacent node pairs. All adjacent node pairs are registered in sequence according to the index order in the node sequence, thereby obtaining a set of adjacent node pairs that correspond one-to-one with the spatial adjacency relationship of the thin cavity region.

[0044] Calculate the edge weights of adjacent node pairs; Adjacent node pairs refer to a combination of two nodes that are directly adjacent in space, used to describe the connection relationship between adjacent positions of the conduction path; edge weights refer to the numerical values ​​used to quantify the strength of the conductive connection between adjacent nodes, reflecting the combined influence of potential changes, conduction distribution and conduction continuity between adjacent positions.

[0045] Specifically, when calculating the edge weights of adjacent node pairs, the boundary potential difference data, capillary conduction data, and suture texture data corresponding to the two node record units in each adjacent node pair are read. The average value of the capillary conduction data of the two nodes in the adjacent node pair is calculated to obtain the average conduction value. The average value of the suture texture data of the two nodes is calculated to obtain the average texture value. The difference between the boundary potential difference data of the two nodes is taken and the absolute value is obtained to obtain the change in potential difference. The result of dividing the average conduction value by the average texture value and adding it to the result is then divided by the change in potential difference to obtain the edge weight value of the adjacent node pair. The edge weight values ​​corresponding to all adjacent node pairs are written into the edge weight record table one by one according to the registration order of the adjacent node pairs.

[0046] It should be noted that the boundary potential difference data, capillary conduction data, and suture texture data correspond to the matrix element values ​​at each grid point position in the boundary potential difference matrix, capillary conduction matrix, and suture texture matrix, respectively.

[0047] Construct an adjacency matrix based on adjacent node pairs and edge weights.

[0048] An adjacency matrix is ​​a two-dimensional distribution constructed based on the connection relationships between nodes and their corresponding edge weights. The rows and columns of the matrix correspond to the positions of each node, and the matrix elements are used to represent whether there is a conductive connection between nodes and the strength of the connection, thereby describing the spatial connection structure and conduction relationship of the boundary conduction path in the thin cavity region as a whole.

[0049] Specifically, first, the arrangement order of all node record units in the node sequence is read, and the row and column indices of the adjacency matrix are determined according to this arrangement order, so that each row and each column in the adjacency matrix corresponds to a node in the node sequence. Then, all matrix elements of the adjacency matrix are initialized to zero. Subsequently, the indices of the two nodes corresponding to each pair of adjacent nodes in the set of adjacent node pairs and the edge weights corresponding to the adjacent node pairs are read one by one. The edge weights are written into the row and column intersection positions corresponding to the two node indices in the adjacency matrix, and the same edge weights are synchronously written into the symmetrical positions corresponding to the two node indices after their order is swapped in the adjacency matrix, so that two nodes with an adjacency relationship form a pair of symmetrical matrix elements with the same value in the adjacency matrix. At the same time, the remaining matrix elements that have not been written with edge weights are kept to zero, thus obtaining an adjacency matrix based on the spatial adjacency relationship between nodes and reflecting the strength of the conductive connection between each adjacent node.

[0050] S3. Based on the stitching texture matrix, determine the pheromone of each pair of adjacent nodes in the adjacency matrix; In an embodiment of the present invention, determining the pheromone of each pair of adjacent nodes in the adjacency matrix based on the stitching texture matrix includes: The initial pheromone intensity of each adjacent node pair in the adjacency matrix is ​​determined based on the capillary conduction matrix and the stitching texture matrix. In the adjacency matrix, each pair of adjacent nodes refers to a combination of nodes that are directly adjacent in space within the thin cavity region and can form a local conductive connection. It is used to describe whether there is a connection between the nodes and the strength of the connection, thus representing the overall spatial extension state of the capillary conduction path within the thin cavity region. The initial pheromone intensity refers to the pre-assigned connection strength between each pair of adjacent nodes, which is used to indicate the degree to which the adjacent node pair is preferentially passed during the formation of the conductive path.

[0051] Specifically, the capillary conduction data of the two nodes corresponding to each adjacent node pair in the capillary conduction matrix and the stitch texture data in the stitch texture matrix are read one by one. The average value of the capillary conduction data of the two nodes is calculated as the conduction average of the adjacent node pair. The average value of the stitch texture data of the two nodes is calculated as the texture average of the adjacent node pair. Then, the conduction average is used as the numerator, and the texture average is added to one as the denominator to calculate the ratio. The obtained ratio is determined as the initial pheromone intensity of the adjacent node pair. Subsequently, according to the row and column corresponding positions of the adjacent node pairs in the adjacency matrix, the initial pheromone intensity of each adjacent node pair is written into the initial pheromone record table one by one.

[0052] Based on the initial pheromone intensity, the pheromone of each pair of adjacent nodes in the adjacency matrix is ​​determined.

[0053] Pheromones refer to the connection weights continuously assigned to adjacent node pairs during path evolution, reflecting the degree of participation and retention of different adjacent node pairs in the overall boundary conduction path. Specifically, the initial pheromone intensity corresponding to each adjacent node pair in the initial pheromone record table is read, and the initial pheromone intensity of each adjacent node pair is directly assigned to that adjacent node pair as the current pheromone value. Then, according to the node index correspondence of each adjacent node pair in the adjacency matrix, the current pheromone value of each adjacent node pair is written to the row and column intersection position and the symmetrical position corresponding to that adjacent node pair, so that nodes with an adjacency relationship form a pheromone distribution with the same value, while the positions that do not form an adjacent node pair keep the value zero, thus obtaining the pheromone distribution result of adjacent node pairs consistent with the spatial connection relationship of the adjacency matrix.

[0054] S4. Obtain the target path based on the adjacency matrix, and construct the pheromone matrix based on the pheromone of the target path and the adjacent node pairs; In an embodiment of the present invention, obtaining the target path based on the adjacency matrix includes: Based on the correspondence between the grid points within the thin cavity region and the reference regions on the door panel side and the mounting plate side, determine the starting node set and the ending node set; The door panel side region refers to the set of spatial locations within the thin cavity region closest to the door panel liner. This region reflects the area where the external environment has a strong influence and where moisture accumulation is likely to occur. The mounting plate side reference region refers to the set of spatial locations within the thin cavity region closest to the device mounting plate and corresponding to the electrical reference position. This region reflects the stable position range related to electrical connection and reference potential. The start node set refers to the set of nodes corresponding to the door panel side region, which is used to represent the distribution of the starting positions of the boundary surface conductive paths. The end node set refers to the set of nodes corresponding to the mounting plate side reference region, which is used to represent the distribution of the ending positions of the boundary surface conductive paths.

[0055] Specifically, first, a thickness direction from the door panel liner towards the device mounting plate is established within the thin cavity region. The two sides corresponding to this thickness direction are defined as the side boundaries of the door panel liner and the side boundaries of the device mounting plate, respectively. Then, the spatial position record of each grid point within the thin cavity region is read. The distance from the grid point to the side boundary of the door panel liner is compared with the distance from the grid point to the side boundary of the device mounting plate along the thickness direction. When the distance from the grid point to the side boundary of the door panel liner is less than the distance to the side boundary of the device mounting plate, the grid point is determined to be a grid point closer to the door panel side. When the interval distance of the side boundary of the panel is less than the interval distance to the side boundary of the inner lining of the door panel, the position of the grid point is determined to be a grid point position close to the side of the mounting panel. Then, the node record units in the node sequence corresponding to the grid point position within the coverage area of ​​the side of the door panel that is determined to be close to the side of the door panel are sequentially assigned to the starting node set. The node record units in the node sequence corresponding to the grid point position within the coverage area of ​​the reference area of ​​the mounting panel that is determined to be close to the side of the mounting panel are sequentially assigned to the ending node set. The original index order of each node record unit in the node sequence is retained, thus obtaining the starting node set and the ending node set.

[0056] In each iteration of the ant colony algorithm, a target starting node is selected from the set of starting nodes; Specifically, first, the original index order of all node record units in the starting node set in the node sequence is read, and a starting node selection table is built according to the original index order. Then, the round number corresponding to the current iteration round is read, and the round number is matched sequentially with the node arrangement order in the starting node selection table. The node record unit corresponding to the current round number is determined as the target starting node of this iteration round. When the round number exceeds the total number of node record units in the starting node set, the matching continues from the beginning according to the arrangement order of the starting node selection table to ensure that each iteration round can determine a unique target starting node from the starting node set. The node index, grid position, and arrangement position of the target starting node in the starting node set are written into the path record table of this round, thereby completing the selection of the target starting node.

[0057] Based on the adjacency matrix, a path is constructed from the set of starting nodes to ending nodes of the target to obtain the target path.

[0058] The target starting node refers to the specific node position selected from the set of starting nodes for path construction; the target path refers to the node connection sequence that starts from the target starting node and extends continuously in space to any node in the set of ending nodes. This path reflects the possible extension paths of boundary conductivity in the thin cavity region and its spatial distribution.

[0059] Specifically, first, the corresponding row position of the target starting node in the adjacency matrix is ​​read, and the column indices corresponding to all non-zero matrix elements in that row are extracted as the current reachable node set. Then, the edge weights and pheromone values ​​corresponding to each reachable node are read, and the edge weights and pheromone values ​​are registered in the candidate node record table according to the node correspondence. The reachable node with the highest comprehensive connection strength is selected from the candidate node record table as the next node. The node indices of the target starting node and the next node are written into the path record table in connection order. Then, the next node is updated as the current node. Continue to read the column indices corresponding to all non-zero matrix elements in the adjacency matrix corresponding to the current node's row position. After removing the node indices already written into the path record table, a new reachable node set is obtained. Then, a new next node is selected according to the correspondence between edge weights and pheromone values ​​and written into the path record table. The process of updating the current node, extracting reachable nodes, registering candidate nodes, and selecting the next node is repeated until the current node in the path record table belongs to any node in the termination node set. The path extension ends when the current node in the path record table belongs to any node in the termination node set. The node indices in the path record table arranged in connection order are determined as the target path.

[0060] In an embodiment of the present invention, constructing a pheromone matrix based on the pheromones of the target path and adjacent node pairs includes: After each iteration, the pheromones of adjacent node pairs are incrementally updated according to the target path to obtain the updated pheromones. Incremental update refers to increasing the connection strength of adjacent nodes along the target path, thereby strengthening the priority of the path in subsequent propagation; updated pheromone refers to the distribution of node connection strength after the path strengthening is completed.

[0061] Specifically, first, all node indices in the target path are read in connection order. Then, adjacent node pairs along the target path are extracted sequentially according to the indexes of adjacent nodes. Next, the pheromone values ​​of each adjacent node pair before the start of the current iteration and all edge weights of the target path are read. The sum of edge weights of each adjacent node pair in the target path is calculated and used as the total path connectivity. Then, the ratio of the edge weight of each pair of adjacent node pairs in the target path to the total path connectivity is calculated to obtain the path proportion of the adjacent node pair in the target path. Then, the original pheromone value of the adjacent node pair is added to the path proportion to obtain the updated pheromone value of the adjacent node pair. At the same time, the original pheromone values ​​of the remaining adjacent node pairs that do not appear in the target path are kept unchanged. The updated pheromone values ​​are written into the pheromone update record table one by one according to the registration order of all adjacent node pairs to obtain the updated pheromone.

[0062] After each iteration, the updated pheromone is evaporated to obtain the evaporated pheromone. Volatilization update refers to the overall attenuation of the connection strength of all nodes, so that the connections that have not been continuously strengthened are gradually weakened in order to maintain the dynamic adjustment capability of the conduction path; post-volatile pheromone refers to the distribution of node connection strength after the attenuation process is completed.

[0063] Specifically, first, the updated pheromone values ​​of all adjacent node pairs in the pheromone update record table are read. Then, the traversal records of all adjacent node pairs in the current iteration round in the target path are read one by one. Adjacent node pairs not traversed by the target path are marked as non-enhanced node pairs, and adjacent node pairs traversed by the target path are marked as enhanced node pairs. Then, a uniform decay process is performed on all adjacent node pairs. That is, based on the updated pheromone value of each adjacent node pair, a portion of the updated pheromone value is deducted as the evaporation loss, so that the pheromone value of each adjacent node pair decreases. At the same time, the difference in pheromone size between enhanced node pairs and non-enhanced node pairs after incremental update is retained. The pheromone values ​​of each adjacent node pair after decay processing are written into the evaporation update record table one by one according to the registration order of adjacent node pairs, thus obtaining the evaporated pheromone.

[0064] A pheromone matrix is ​​constructed based on the pheromone after evaporation and the adjacency matrix.

[0065] The pheromone matrix refers to a two-dimensional distribution formed by arranging the connection strength of each pair of adjacent nodes according to the node index, based on the connection relationship between nodes. It is used to describe the degree of preservation and distribution of conductive paths in space within a thin cavity region.

[0066] Specifically, first, the arrangement order of all node record units in the node sequence is read, and the row and column indices of the pheromone matrix are determined based on this arrangement order, so that each row and column in the pheromone matrix corresponds to a node in the node sequence. Then, the pheromone values ​​after evaporation corresponding to all adjacent node pairs in the evaporation update record table and the two node indices corresponding to each adjacent node pair are read. At the same time, the distribution of non-zero elements in each row and column position in the adjacency matrix is ​​read to determine the node index combinations with adjacency relationships. Then, all adjacent node pairs are traversed one by one, and the pheromone value after evaporation corresponding to each adjacent node pair is written into the pheromone matrix at the row and column intersection position corresponding to the two node indices. The same pheromone value after evaporation is synchronously written into the symmetrical position corresponding to the two node indexes after their order is swapped. For node combinations in the adjacency matrix that do not have non-zero elements, the zero value is kept unchanged. Thus, the positions in the pheromone matrix with adjacency relationships are stored with evaporation pheromone values, and the positions without adjacency relationships are kept in an empty connection state. In this way, a pheromone matrix that is consistent with the spatial connection relationship of the adjacency matrix and reflects the connection strength distribution of each adjacent node pair is obtained.

[0067] S5. Obtain the loop allowance vector based on the pheromone matrix, and generate the real-time acquisition status vector of the low-voltage distribution box based on the loop allowance vector.

[0068] In an embodiment of the present invention, the loop permissibility vector is obtained based on the pheromone matrix, including: Calculate the node participation vector based on the pheromone matrix; The node participation vector refers to a one-dimensional data set obtained by aggregating the connection strengths of each node in the pheromone matrix, which reflects the degree of participation and importance of each node in the overall conductive path.

[0069] Specifically, first, read the node index order corresponding to all rows and columns in the pheromone matrix, and make each row and each column correspond to a node in the node sequence. Then, read all matrix elements in each row of the pheromone matrix in turn, and sum the values ​​of each matrix element in the same row to obtain the total amount of pheromone connected to the node corresponding to that row. This total amount of pheromone is determined as the node participation value of that node. Then, according to the node index order corresponding to each row in the pheromone matrix, write the node participation value of each node into a one-dimensional table in turn, so that each position in the one-dimensional table corresponds to a node and stores the total amount of pheromone of that node, thus obtaining a node participation vector that is consistent with the node sequence index order.

[0070] Based on the branch circuits and thin cavity regions of the low-voltage distribution box, a circuit-node proximity matrix is ​​constructed; The loop-node proximity matrix refers to a two-dimensional data set that quantifies the spatial proximity relationship between each branch loop of a low-voltage distribution box and the nodes within the thin cavity area, where the range of nodes that may be affected by the conductive path of each branch loop is included.

[0071] Specifically, first, the wiring positions, terminal positions, and corresponding acquisition positions of all branch circuits in the low-voltage distribution box are read. Then, the index positions and spatial positions of all nodes in the thin cavity area in the node sequence are read. Next, the relative proximity relationships between the wiring positions, terminal positions, and acquisition positions of each branch circuit and the spatial positions of each node in the thin cavity area are compared one by one, taking each branch circuit as a unit. The nodes that are spatially adjacent to the branch circuit are determined as the neighboring nodes corresponding to the branch circuit. The proximity relationship between the branch circuit and its corresponding neighboring nodes is assigned and written into a two-dimensional table. Each row of the two-dimensional table corresponds to each branch circuit, and each column corresponds to each node in the thin cavity area. For positions with proximity relationships, a proximity mark value is written, and for positions without proximity relationships, a non-neighboring mark value is written. The writing of all positions is completed according to the arrangement order of each branch circuit and the index order of each node in the node sequence, thereby obtaining the circuit node proximity matrix.

[0072] Perform matrix multiplication on the loop-node proximity matrix and the node participation vector to obtain the loop pollution weight vector; Specifically, first, read the data of each row corresponding to all branch loops and the data of each column corresponding to all nodes in the loop node proximity matrix, and read the node participation value corresponding to each node in the node participation vector. Then, taking each branch loop as a unit, according to the one-to-one correspondence between the column position in that row and the position in the node participation vector, multiply the proximity relationship value of each node in that row with the node participation value one by one, and accumulate all the product results in the row corresponding to the same branch loop. The accumulated result is determined as the loop contamination weight value of that branch loop. Then, according to the row order of each branch loop in the loop node proximity matrix, write the loop contamination weight values ​​corresponding to each branch loop into a one-dimensional table, thereby obtaining the loop contamination weight vector corresponding to each branch loop.

[0073] The loop contamination weight vector is transformed element by element to obtain the loop permissibility vector.

[0074] The loop tolerance vector refers to a one-dimensional data set obtained after transforming the loop contamination weights, which reflects the degree to which each branch loop can maintain stable operation under the current conductive environment.

[0075] Specifically, first, read the pollution weight values ​​corresponding to each branch loop in the loop pollution weight vector. Then, perform a reciprocal transformation on each pollution weight value, that is, use the result of adding the pollution weight value to one as the denominator and use one as the numerator to perform division. The result is determined as the loop allowance value of the corresponding branch loop. Then, according to the original arrangement order of each branch loop in the loop pollution weight vector, write all the loop allowance values ​​into a one-dimensional table in sequence, thereby obtaining the loop allowance vector corresponding to each branch loop.

[0076] In an embodiment of the present invention, generating a real-time acquisition status vector for the low-voltage distribution box based on the loop tolerance vector includes: Based on the real-time data collected from each branch circuit in the low-voltage distribution box, a circuit state vector is generated. Real-time acquired quantities refer to the instantaneous electrical quantities obtained by measuring current, voltage, or power in each branch circuit of the low-voltage distribution box under the current operating state, which reflect the actual operating load of each branch circuit; the circuit state vector refers to a one-dimensional data set formed by arranging the real-time acquired quantities of each branch circuit in the order of circuit number, which is used to characterize the overall distribution of the operating state of each branch circuit.

[0077] Specifically, first, the circuit number records of all branch circuits in the low-voltage distribution box and the real-time acquisition data corresponding to each branch circuit are read, and a unique correspondence is established between each real-time acquisition data and the circuit number of the corresponding branch circuit. Then, the corresponding real-time acquisition data is extracted sequentially according to the circuit number order of each branch circuit. The real-time acquisition data corresponding to each branch circuit is written into the corresponding position in a one-dimensional table, so that the arrangement order of each position in the one-dimensional table is consistent with the circuit number order of each branch circuit, thereby forming a circuit state vector obtained by continuously arranging the real-time acquisition data of all branch circuits in a unified order.

[0078] The reliable loop state vector is obtained by multiplying the loop permissibility vector and the loop state vector element by element. Specifically, first, read the loop allowance values ​​corresponding to each branch loop in the loop allowance vector, and then read the loop state values ​​corresponding to each branch loop in the loop state vector. Next, establish a positional correspondence according to the same arrangement order of each branch loop in the two vectors, so that the loop allowance value and loop state value corresponding to the same branch loop are located in the same vector position. Then, taking the position corresponding to each branch loop as a unit, multiply the loop allowance value and loop state value at that position one by one. Determine the product result obtained at each position as the reliable loop state value of the corresponding branch loop, and write all the product results into a one-dimensional table according to the arrangement order of each branch loop in the original vector, thereby obtaining the reliable loop state vector corresponding to each branch loop.

[0079] The reliable loop state vector is used as the real-time acquisition state vector of the low-voltage distribution box.

[0080] The trusted loop state vector refers to a one-dimensional data set obtained by combining the loop tolerance and the loop state. It reflects the actual effective operating state of each branch loop after considering the influence of boundary conductivity. The real-time acquired state vector refers to a one-dimensional data set with the trusted loop state vector as the final output. It is used to represent the distribution of the effective operating state of the low-voltage distribution box at the current moment.

[0081] After obtaining the reliable loop state vector, it can be used as a unified input for the current operating status of the low-voltage distribution box. It can be used to evaluate the operating status of each branch loop, determine the load distribution, and identify abnormal loops. By comparing and analyzing the changing trends of each component in the reliable loop state vector, it can be determined whether there is a load shift, local anomaly, or uneven power supply. Based on this, operations such as loop switching, load adjustment, or alarm output can be performed. At the same time, the vector can also be used as the data basis for remote power distribution scheduling and energy consumption management to achieve stable operation control and refined management of the low-voltage power distribution system.

[0082] It should be noted that the reliable loop state vector is the result obtained by adding loop tolerance to the real-time acquisition data of each branch loop. The loop tolerance reflects the degree of influence of the boundary conduction path on the measurement results of each branch loop. By weighting the original loop state, the electrical interference caused by boundary conduction, humid environment and surface contamination can be weakened, making the obtained loop state values ​​closer to the actual operating state of each branch loop. Therefore, using the corrected reliable loop state vector as the real-time acquisition state vector of the low-voltage distribution box can improve the effectiveness and reliability of the acquisition results while maintaining real-time performance, thereby more accurately reflecting the current overall operating status of the low-voltage distribution box.

[0083] It should be noted that the capillary retention boundary surface conductive path network refers to the narrow cavity area between the inner lining of the low-voltage distribution box door panel and the device mounting plate, where the narrow slit structure, the recessed structure, and the rough insulating coating work together to cause moisture and contaminants to be retained on the surface and continuously distributed along the solid interface. This results in a set of interconnected boundary surface conductive paths at multiple discrete locations. This set of paths is spatially distributed in a network shape and can conduct charges between different locations and affect the local potential distribution and current path.

[0084] like Figure 2 The diagram shown is a functional block diagram of a real-time data acquisition system for a low-voltage distribution box provided in an embodiment of the present invention.

[0085] In this embodiment, the functions of each module / unit are as follows: The boundary conductivity generation module obtains the boundary conductivity matrix based on the thin cavity region between the door panel lining of the low-voltage distribution box and the device mounting plate. The stitch texture mapping module obtains the stitch texture matrix based on the capillary channel region and the boundary conductivity matrix, and constructs an adjacency matrix based on the stitch texture matrix; The initial information setting module determines the pheromone of each pair of adjacent nodes in the adjacency matrix based on the stitching texture matrix. The path information generation module obtains the target path based on the adjacency matrix and constructs a pheromone matrix based on the pheromone of the target path and adjacent node pairs. The status output module obtains the loop allowance vector based on the pheromone matrix and generates the real-time status vector of the low-voltage distribution box based on the loop allowance vector.

[0086] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for real-time data acquisition from a low-voltage distribution box, characterized in that, The steps include: S1. The boundary conductance matrix is ​​obtained based on the thin cavity region between the door panel lining of the low-voltage distribution box and the device mounting plate. S2. Obtain the stitching texture matrix based on the capillary channel region and boundary conductivity matrix, and construct the adjacency matrix based on the stitching texture matrix; S3. Based on the stitching texture matrix, determine the pheromone of each pair of adjacent nodes in the adjacency matrix; S4. Obtain the target path based on the adjacency matrix, and construct the pheromone matrix based on the pheromone of the target path and the adjacent node pairs; S5. Obtain the loop allowance vector based on the pheromone matrix, and generate the real-time acquisition status vector of the low-voltage distribution box based on the loop allowance vector.

2. The method for real-time data acquisition from a low-voltage distribution box according to claim 1, characterized in that, The boundary conductance matrix is ​​obtained based on the thin cavity region between the door panel lining and the device mounting plate of the low-voltage distribution box, including: Position the thin cavity area between the door panel lining of the low-voltage distribution box and the component mounting plate; A microelectrode array is disposed in the thin cavity region; wherein, the microelectrode array is composed of multiple sets of grid electrode pairs; Synchronous sampling is performed on each grid electrode pair to obtain the boundary potential difference signal and the boundary current signal; The boundary potential difference signals are arranged into a matrix to obtain the boundary potential difference matrix; The boundary current signals are arranged into a matrix to obtain the boundary current matrix; The boundary potential difference matrix and the boundary current matrix are calculated element by element to obtain the boundary conductance matrix.

3. The method for real-time data acquisition from a low-voltage distribution box according to claim 2, characterized in that, The stitching texture matrix is ​​obtained based on the capillary channel region and the boundary conductivity matrix, including: The narrow slit region, the recessed region, and the region covered by the rough insulating coating within the thin cavity region are defined as the capillary channel region; Based on the capillary channel region, the grid positions corresponding to each grid electrode pair in the thin cavity region are marked and assigned values ​​to obtain the structural mask matrix. The capillary conduction matrix is ​​obtained by multiplying the boundary conduction matrix and the structure mask matrix element by element. The stitching texture matrix is ​​obtained by performing row and column differences on the capillary conduction matrix.

4. The method for real-time data acquisition from a low-voltage distribution box according to claim 3, characterized in that, Constructing an adjacency matrix based on the stitched texture matrix includes: Based on the index relationship of each grid point position in the thin cavity region, the boundary potential difference matrix, capillary conduction matrix and stitch texture matrix are flattened and arranged sequentially to obtain the node sequence; Based on the node sequence, establish adjacent node pairs; Calculate the edge weights of adjacent node pairs; Construct an adjacency matrix based on adjacent node pairs and edge weights.

5. The method for real-time data acquisition from a low-voltage distribution box according to claim 3, characterized in that, Based on the stitched texture matrix, the pheromone of each pair of adjacent nodes in the adjacency matrix is ​​determined, including: The initial pheromone intensity of each adjacent node pair in the adjacency matrix is ​​determined based on the capillary conduction matrix and the stitching texture matrix. Based on the initial pheromone intensity, the pheromone of each pair of adjacent nodes in the adjacency matrix is ​​determined.

6. The method for real-time data acquisition from a low-voltage distribution box according to claim 1, characterized in that, The target path is obtained based on the adjacency matrix, including: Based on the correspondence between the grid points within the thin cavity region and the reference regions on the door panel side and the mounting plate side, determine the starting node set and the ending node set; In each iteration of the ant colony algorithm, a target starting node is selected from the set of starting nodes; Based on the adjacency matrix, a path is constructed from the set of starting nodes to ending nodes of the target to obtain the target path.

7. The method for real-time data acquisition from a low-voltage distribution box according to claim 1, characterized in that, Construct a pheromone matrix based on the pheromone content of the target path and adjacent node pairs, including: After each iteration, the pheromones of adjacent node pairs are incrementally updated according to the target path to obtain the updated pheromones. After each iteration, the updated pheromone is evaporated to obtain the evaporated pheromone. A pheromone matrix is ​​constructed based on the pheromone after evaporation and the adjacency matrix.

8. The method for real-time data acquisition from a low-voltage distribution box according to claim 1, characterized in that, The loop permissibility vector is obtained based on the pheromone matrix, including: Calculate the node participation vector based on the pheromone matrix; Based on the branch circuits and thin cavity regions of the low-voltage distribution box, a circuit-node proximity matrix is ​​constructed; Perform matrix multiplication on the loop-node proximity matrix and the node participation vector to obtain the loop pollution weight vector; The loop contamination weight vector is transformed element by element to obtain the loop permissibility vector.

9. The method for real-time data acquisition from a low-voltage distribution box according to claim 1, characterized in that, The real-time acquisition status vector of the low-voltage distribution box is generated based on the loop allowance vector, including: Based on the real-time data collected from each branch circuit in the low-voltage distribution box, a circuit state vector is generated. The reliable loop state vector is obtained by multiplying the loop permissibility vector and the loop state vector element by element. The reliable loop state vector is used as the real-time acquisition state vector of the low-voltage distribution box.

10. A system for real-time data acquisition of a low-voltage distribution box as described in any one of claims 1-9, characterized in that, The system includes: The boundary conductivity generation module obtains the boundary conductivity matrix based on the thin cavity region between the door panel lining of the low-voltage distribution box and the device mounting plate. The stitch texture mapping module obtains the stitch texture matrix based on the capillary channel region and the boundary conductivity matrix, and constructs an adjacency matrix based on the stitch texture matrix; The initial information setting module determines the pheromone of each pair of adjacent nodes in the adjacency matrix based on the stitching texture matrix. The path information generation module obtains the target path based on the adjacency matrix and constructs a pheromone matrix based on the pheromone of the target path and adjacent node pairs. The status output module obtains the loop tolerance vector based on the pheromone matrix and generates the real-time status vector of the low-voltage distribution box based on the loop tolerance vector.

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