A method for reconstructing the topology of a circular pavement in the case of missing drawings of a grounding grid

Abstract

The application relates to the technical field of circumferential road paving topology reconstruction, and particularly discloses a circumferential road paving topology reconstruction method for a grounding grid drawing missing working condition, which injects a pulse sequence signal carrying a unique pseudo-random code feature, accurately extracts a target response from a strong interference background by using cross-correlation operation, and improves detection anti-interference capability; meanwhile, a conductor intersection point or a branch point is pre-judged by using external stray current information, and the requirement for detection equipment resolution is reduced; a preliminary conductor path diagram is generated by connecting path tracking coordinate points, and a topology node to be verified is identified based on an interference field intensity diagram; finally, a branch path is confirmed by multi-directional detection, and a complete grounding grid topology structure diagram is generated; the method aims to solve the problems of grounding grid drawing missing or inconsistency with the actual due to historical reasons or poor data management, and has high precision, high efficiency and high safety, and provides a solid data basis for grounding grid operation and maintenance.

Description

Technical Field

[0001] This invention relates to the field of circumferential paving topology reconstruction technology, and more specifically, to a method for circumferential paving topology reconstruction in the case of missing grounding grid drawings. Background Technology

[0002] As a critical infrastructure for the safe operation of power systems, the integrity and accuracy of the underground grounding network's topology are of paramount importance. However, due to historical reasons or poor data management, many original drawings of grounding networks for in-service substations and other facilities are missing or do not match reality, posing significant safety hazards and technical challenges to daily operation and maintenance, expansion and renovation, and fault diagnosis. In complex industrial electromagnetic environments, how to reconstruct the actual routing and connection relationships of underground metallic conductors with high precision and without excavation is an urgent challenge currently facing the industry.

[0003] Currently, the commonly used methods for grounding grid detection in the industry mainly include direct excavation, high-current injection, and ground-penetrating radar (GPR). While direct excavation is intuitive, it is costly, inefficient, and highly destructive to the site, limiting its application to small-scale verification. High-current injection involves injecting a large current at power frequency or a specific frequency into the grounding grid and measuring the potential difference or magnetic field distribution at the surface to roughly determine the conductor's location; this is a widely used non-destructive detection technology. Ground-penetrating radar (GPR) utilizes the principle of electromagnetic wave reflection to image underground targets.

[0004] However, these traditional methods have significant drawbacks. The high-current injection method is highly susceptible to strong power frequency and harmonic interference within substations, resulting in a low signal-to-noise ratio and insufficient positioning accuracy, particularly in distinguishing complex node and branch structures. This method typically requires power outages for safety and to reduce interference, impacting the normal operation of the power grid. Ground-penetrating radar (GPR) detection effectiveness heavily relies on soil conditions, experiencing severe attenuation in highly conductive soils, and cannot effectively distinguish target grounding conductors from other underground metal pipelines, making it difficult to form a continuous topology network. Therefore, existing technologies cannot fully meet practical requirements in terms of anti-interference capability, detection accuracy, and topology identification completeness. Summary of the Invention

[0005] In view of this, in order to solve the problems mentioned in the background technology, a method for reconstructing the topology of a circular paving road in the case of missing grounding grid drawings is proposed.

[0006] The objective of this invention can be achieved through the following technical solution: This invention provides a method for reconstructing the topology of a circular paving road when the grounding grid drawing is missing, including the following steps: S1, generating and applying an excitation signal: generating a pulse sequence signal with an identification identifier according to a preset pseudo-random code with low correlation, and applying the pulse sequence signal to a known access point of the grounding grid to form an excitation current carrying a unique pseudo-random code feature in the underground conductor.

[0007] S2. Hybrid Magnetic Field Signal Acquisition and Processing: Acquire the hybrid magnetic field signal generated by the combined action of the excitation current carrying a unique pseudo-random code and the external stray current, and digitize the hybrid magnetic field signal to generate a time-domain data stream containing the target response and environmental interference.

[0008] S3. Target Response Separation and Localization: Perform cross-correlation operation on the time-domain data stream containing target response and environmental interference and a preset pseudo-random code with low correlation to separate the target response component and generate a path tracking coordinate point sequence that locks the contribution of the excitation source.

[0009] S4. Preliminary conductor path diagram generation: Connect the path tracing coordinate point sequence to draw the extended path of a single conductor, generating a preliminary conductor path diagram.

[0010] S5. Generation of Topology Nodes to be Verified: Based on the time-domain data stream containing the target response and environmental interference, the common-mode interference field component is obtained, an interference field intensity map is generated, and special locations where local intensity peaks of the common-mode interference field component appear are identified on the preliminary conductor path map to generate topology nodes to be verified.

[0011] S6. Topology Integration and Generation: Using the topology node to be verified as the center, multi-directional detection is performed to confirm and draw branch paths. Finally, the preliminary conductor path diagram and all branch paths are integrated to generate a complete grounding network topology diagram.

[0012] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention greatly improves the anti-interference capability of the detection signal by injecting a pulse sequence signal carrying a unique identifier and using cross-correlation operation technology to accurately extract the target response from a strong interference background. Even in extremely complex electromagnetic environments such as substations, it can effectively suppress interference fields generated by power frequency, harmonics and other stray currents, realize accurate and stable tracking of the target conductor, and ensure the reliability of topology reconstruction.

[0013] (2) This invention uses the interference field distribution characteristics of the conductor under test as the identification basis and cleverly utilizes the external stray current information that was originally regarded as noise to achieve effective prediction of the intersection or branch point of underground conductors. This method does not rely on complex signal feature changes, reduces the stringent requirements on the resolution of the detection equipment, and provides an innovative technical path for the complete reconstruction of complex network topology.

[0014] (3) This invention achieves refined and integrated reconstruction of the grounding grid topology. It can not only accurately draw the physical path of a single conductor, but also completely identify all branch paths by performing multi-directional detection at key nodes, ultimately generating a complete topological structure diagram that reflects the actual connection relationship between conductors. The entire process is trenchless and requires no power outage, taking into account high precision, high efficiency and high safety, providing a solid data foundation for the digital asset management and intelligent operation and maintenance of the grounding grid. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the method steps of the present invention.

[0017] Figure 2 This is a schematic diagram of the interference field intensity of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see Figure 1 The present invention provides a method for reconstructing the topology of a circular paving road when the grounding grid drawing is missing, including: S1, generating and applying an excitation signal: generating a pulse sequence signal with an identification identifier according to a preset pseudo-random code with low correlation, and applying the pulse sequence signal to a known access point of the grounding grid to form an excitation current carrying a unique pseudo-random code feature in the underground conductor.

[0020] In a specific embodiment of the present invention, the method for generating a pulse sequence signal with identification based on a preset pseudo-random code with low correlation is as follows: the binary code bits of the preset pseudo-random code with low correlation are mapped to preset positive and negative voltage levels to generate a pulse sequence signal with a specific timing.

[0021] It should be noted that a 7-bit pseudo-random code with low autocorrelation is first pre-defined as the identifier, specifically the binary sequence 1110010. The low autocorrelation of this pseudo-random code means that when the code stream is shifted and compared with itself, it shows extremely high similarity only when perfectly aligned, and extremely low similarity at any other shift position, ensuring the uniqueness and accuracy of subsequent detection. Subsequently, this pseudo-random code is converted into a pulse sequence signal with a specific timing. The operation process is as follows: each code bit corresponds to a duration of 1 millisecond, and a binary "1" is mapped to a +5 volt DC voltage output, and a "0" is mapped to a -5 volt DC voltage output. This generates a pulse sequence signal with a total duration of 7 milliseconds, where the voltage changes in the order of "+5V, +5V, +5V, -5V, -5V, +5V, -5V".

[0022] It should also be noted that after the pulse sequence signal is generated, this identified pulse sequence signal is applied to a known connection point in the grounding grid using an excitation device. This excitation device consists of a signal generator and a power amplifier. The signal generator generates the aforementioned pulse sequence signal, while the power amplifier amplifies the signal energy sufficiently to drive the low-impedance grounding grid. During operation, the output of the excitation device is clamped to a ground down conductor, identified as being connected to an underground conductor, using a special clamp. This ground down conductor is the known connection point. When the pulse sequence signal is applied, it acts as a probe signal source, propagating through the underground conductor network and generating an excitation current with a waveform identical to the original pulse sequence signal. This excitation current carries the unique pseudo-random code 1110010 and diffuses along the underground conductor throughout the grounding grid.

[0023] The pulse sequence signal with identification is a time-varying electrical signal whose voltage or current transition pattern is determined by a specific digital code, i.e., an identification identifier. Its function is to act as a precisely identifiable detection signal in complex electromagnetic environments. The pulse sequence signal forms the basis of the aforementioned signal; it consists of a series of pulses switching between different levels, forming a waveform with a time-sequential pattern. The known access point is a location on the ground that can be physically connected and is clearly part of the target grounding network, such as a substation grounding terminal or a lightning arrester down conductor of a building. The excitation current carrying the unique pseudo-random code flows in an underground conductor, and its intensity and direction variations reproduce the pseudo-random code pattern carried by the injected pulse sequence signal, distinguishing it from other currents. The pseudo-random code is a binary digital sequence that appears random but is actually generated by a deterministic algorithm. Its characteristic is extremely low autocorrelation. The code length is set to be greater than 63 bits to ensure a sufficient signal-to-noise ratio under typical electromagnetic interference environments; here, it is set to 127 bits. An excitation device is a set of equipment that can generate and inject a specified electrical signal. It typically includes a signal source and a power amplifier circuit. Its output power is set according to the size of the grounding grid and the soil resistivity, and the setting range is 50 to 200 watts.

[0024] For example, to detect a missing grounding grid in a substation's blueprints, a 127-bit pseudo-random code is selected as an identifier. This pseudo-random code is input into an excitation device, which generates a corresponding pulse sequence signal with the identifier. The signal's symbol width is set to 0.1 milliseconds, and the voltage amplitude is ±12 volts. The operator connects the excitation device's output clamp to the grounding down conductor on the substation's main transformer casing, which is a known access point. After the excitation device is activated, the pulse sequence signal is applied to the grounding grid, forming an excitation current carrying the unique pseudo-random code characteristic in the underground conductor. The peak value of this excitation current is approximately 5 amperes, measured based on the grounding grid impedance.

[0025] S2. Hybrid Magnetic Field Signal Acquisition and Processing: Acquire the hybrid magnetic field signal generated by the combined action of the excitation current carrying a unique pseudo-random code and the external stray current, and digitize the hybrid magnetic field signal to generate a time-domain data stream containing the target response and environmental interference.

[0026] In a specific embodiment of the present invention, the specific steps for generating a time-domain data stream containing target response and environmental interference include: continuously collecting time-varying information on the total magnetic field strength above the Earth's surface using a mobile magnetic field detection device to obtain a mixed magnetic field signal.

[0027] It should be noted that the operator holds a portable magnetic field detection device and moves slowly along the surface area near the known access point. This device has a built-in high-precision fluxgate sensor that can detect extremely weak magnetic field changes directly beneath it in real time. When an excitation current flows through an underground conductor, it generates a time-varying magnetic field based on the pulse pattern of the current; simultaneously, external stray currents from other industrial leaks or nearby power lines in the environment also create interfering magnetic fields underground. The magnetic field detection device collects the time-varying information of the total magnetic field strength resulting from the superposition of these two factors on the surface; this composite signal is the mixed magnetic field signal.

[0028] The mixed magnetic field signal is sampled and quantized to convert it into a time-domain data stream that includes the target response and environmental interference.

[0029] It should be noted that the acquired hybrid magnetic field signal is a continuously varying analog voltage signal, which is immediately transmitted to the digital signal processing unit inside the device. The analog-to-digital converter within the processing unit first samples the analog signal, capturing the instantaneous voltage value at a rate of 1 million times per second. Subsequently, each sample point is quantized, converting its voltage value into a 16-bit binary number. Through continuous sampling and quantization, the continuous analog signal is transformed into a discrete digital sequence. This sequence constitutes the time-domain data stream containing the target response and environmental interference, and is stored for subsequent calculation and analysis.

[0030] The mixed magnetic field signal refers to the total magnetic field signal in the surface space of the detection point, which is composed of the magnetic field generated by the target excitation current and the magnetic fields generated by all non-target sources. Its data structure is an analog voltage that varies with time. External stray currents refer to all non-target currents that intrude into the grounding grid and flow within it, excluding artificially applied excitation currents, such as ground potential rise from nearby substations and surge currents during the startup of large equipment. The time-domain data stream is a one-dimensional digital sequence generated by digitizing the mixed magnetic field signal. Each value in the sequence represents the magnetic field strength at a specific moment, and its data structure is a floating-point or fixed-point array indexed by time. The target response is the magnetic field signal component in the time-domain data stream generated by the excitation current carrying a unique pseudo-random code. Environmental interference includes all signal components in the time-domain data stream other than the target response, mainly originating from the interfering magnetic field generated by external stray currents. The time-varying information of the total magnetic field strength refers to the complete record of the change of the total magnetic field strength measured by the detection equipment at a fixed location over time.

[0031] For example, continuing from the previous example, an operator holds a magnetic field detection device with a sensitivity of 1 nanotesla and walks at a constant speed of 0.5 meters per second within a 2-meter radius around the grounding lead of the main transformer. During this process, the device continuously collects time-varying information on the total magnetic field strength above the ground surface, obtaining a mixed magnetic field signal that includes the magnetic field generated by the excitation current and the magnetic field generated by leakage current from surrounding factory equipment. The analog voltage peak of this signal is approximately ±50 millivolts. The device's built-in analog-to-digital converter samples this mixed magnetic field signal at a frequency of 2 MHz and quantizes it with 24-bit precision, generating a digital time-domain data stream that includes the target response and environmental interference. This time-domain data stream is recorded in real time at a rate of 2 megadata points per second.

[0032] S3. Target Response Separation and Localization: Perform cross-correlation operation on the time-domain data stream containing target response and environmental interference and a preset pseudo-random code with low correlation to separate the target response component and generate a path tracking coordinate point sequence that locks the contribution of the excitation source.

[0033] In a specific embodiment of the present invention, the specific steps of separating the target response component and generating a path tracking coordinate point sequence that locks the excitation source contribution include: performing sliding cross-correlation calculation on the time-domain data stream containing the target response and environmental interference and a preset pseudo-random code with low correlation, and generating cross-correlation calculation results.

[0034] It's important to note that the core of the sliding cross-correlation calculation is to use the locally stored original pseudo-random code, which serves as an identifier, as a matching template. This template is then used for point-by-point sliding comparison on the real-time acquired time-domain data stream. Specifically, the system aligns a 7-millisecond original pseudo-random code template with the latest 7-millisecond data segment of the time-domain data stream and calculates the sum of the products of corresponding points in these two sequences. Subsequently, the template is slid forward by one data point, and the product accumulation calculation is repeated with the new 7-millisecond data segment. This sliding and calculation process continues continuously, generating a continuous sequence of cross-correlation results. Due to the extremely low autocorrelation of the original pseudo-random code, when the template is not aligned with the target response generated by the excitation current in the time-domain data stream, the sum of the products will be very small and chaotic. However, once the template and the target response are perfectly aligned in time, their waveforms are highly matched, and the sum of the products will instantly produce a unique, sharp peak value far exceeding the background noise.

[0035] It should also be noted that the core of this step is the calculation of sliding cross-correlation, and its discrete calculation formula is as follows: ,in, For the summation variable; The sliding cross-correlation operation has a time delay of The result at that time; It is a real-time acquired time-domain data stream, representing the data acquired in real time. The magnetic field strength at any given time, measured in nanoteslas; It is the locally stored original pseudo-random code, which is a dimensionless numerical sequence with a value of +1 or -1, representing the polarity of the signal. The time delay or sliding step is set based on the sampling period and can be a fraction of a second. The entire formula calculates the similarity between two signals under different time delays, and the result... The unit remains nanotesla.

[0036] The sharp peaks in the cross-correlation results are identified, and the geographic coordinates of the strongest sharp peaks are continuously recorded to form a sequence of path tracking coordinate points.

[0037] It should be noted that the peak detection algorithm within the system identifies and extracts sharp peaks from the cross-correlation results in real time. The specific amplitude of this sharp peak is separated and recorded as a target response component, which quantitatively represents the magnetic field strength generated by the excitation current detected at that location. Simultaneously, the system queries GPS data associated with the timing of this sharp peak, generating a path-tracking coordinate point from the geographic coordinates of the magnetic field detection device at that time, such as 39.9 degrees North latitude and 116.3 degrees East longitude, thus pinpointing the specific geographic location of the excitation source's contribution.

[0038] For example, continuing from the previous example, the processing system performs a sliding cross-correlation calculation on the time-domain data stream of 2 trillion data points generated per second and the locally stored 127-bit raw pseudo-random code. When the operator moves to a certain position, a sharp peak with an amplitude of 15.2 nanotesla appears in the cross-correlation result, far exceeding the background-result average of 0.5 nanotesla. The system immediately extracts and records this value of 15.2 nanotesla as the current target response component. At the same time, the system retrieves the reading from the built-in GPS module of the detection device at that moment, obtaining the geographical coordinates of 22.54 degrees north latitude and 114.05 degrees east longitude, and generates a path tracking coordinate point from these coordinates.

[0039] S4. Preliminary conductor path diagram generation: Connect the path tracing coordinate point sequence to draw the extended path of a single conductor, generating a preliminary conductor path diagram.

[0040] In a specific embodiment of the present invention, the specific steps for generating a preliminary conductor path map include: moving the magnetic field detection device so that the sharp peak amplitude in the cross-correlation calculation result remains at a local maximum value.

[0041] It should be noted that after successfully locking down the contribution of the excitation source through cross-correlation calculations, the operator moves the handheld magnetic field detector along the ground to map the extended path of a single underground conductor. During this movement, the operator observes the target response component value displayed on the device's screen in real time. The goal of the movement is to keep this value consistently at a local maximum within a small surrounding area. For example, if the current target response component is 15.2 nanotesla, the operator will fine-tune the position in several directions (forward, backward, left, and right) to find a new position where the reading reaches its peak, such as 15.5 nanotesla. Once this local maximum point is found, it means the detector is directly above the underground conductor. At this point, the device automatically records the path-tracking coordinates of that location. The operator then moves forward a small step, repeating the process of finding and locating the next local maximum point and recording its corresponding path-tracking coordinates. Through this gradual approach of continuously tracking the local maximum of the target response component, the device continuously records a series of closely connected path-tracking coordinates.

[0042] Connect the sequence of path tracking coordinates recorded during the movement in the geographic information system to generate a preliminary conductor path map.

[0043] It should be noted that, finally, all the recorded path tracking coordinate point sequences are imported into a geographic information system. The computer system software automatically connects these discrete coordinate points in the order they were recorded using straight lines or smooth curves, ultimately forming a clear trajectory line on an electronic map. This line visually represents the physical direction of this underground conductor, thus generating a preliminary conductor path map.

[0044] For example, continuing from the previous example, after recording the first path-tracking coordinate point, 22.54 degrees North latitude and 114.05 degrees East longitude, the operator began to move slowly. He observed that after moving approximately 0.5 meters due north, the target response component displayed by the device increased from 15.2 nanoteslas to 15.6 nanoteslas, but the value decreased upon further forward or to the sides. Therefore, the device automatically recorded this new path-tracking coordinate point. The operator continued walking for 50 meters along the direction where this target response component remained at a local maximum, in steps of approximately 0.5 meters. During this process, the device recorded a total of 101 path-tracking coordinate points, forming a sequence of path-tracking coordinate points. Subsequently, this sequence data file containing 101 coordinate points was imported into a geographic information system. The system connected these points on a satellite map of the substation, drawing a straight path extending 50 meters northward from the main transformer grounding lead. This constitutes a preliminary conductor path map.

[0045] S5. Generation of Topology Nodes to be Verified: Based on the time-domain data stream containing the target response and environmental interference, the common-mode interference field component is obtained, an interference field intensity map is generated, and special locations where local intensity peaks of the common-mode interference field component appear are identified on the preliminary conductor path map to generate topology nodes to be verified.

[0046] In a specific embodiment of the present invention, the specific steps of obtaining the common-mode interference field component and generating the interference field intensity map include: subtracting the target response component identified by sliding cross-correlation calculation from the time-domain data stream containing the target response and environmental interference.

[0047] Please see Figure 2 The residual signal after subtraction is used as the common-mode interference field component. The intensity of the common-mode interference field component is calculated and associated with the geographical location information to generate an interference field intensity map.

[0048] It should be noted that the system retrieves and processes all time-domain data streams previously collected and stored during the initial conductor path mapping process. For each path-tracking coordinate point on the path, the system possesses its corresponding original time-domain data stream segment and the target response component waveform accurately identified through cross-correlation calculations. The first step in processing is to perform a subtraction operation, that is, subtracting the corresponding target response component waveform from the original time-domain data stream segment corresponding to each coordinate point, point by point. For example, at a certain moment, the magnetic field strength value of the original time-domain data stream is 17.3 nanotesla, and the known contribution value of the target response component at that moment is 15.2 nanotesla, then the subtraction yields 2.1 nanotesla. This subtraction operation is performed continuously on the entire time-domain data stream, and the residual signal obtained after the operation is the common-mode interference field component generated purely by external stray currents, after eliminating the influence of artificially injected signals. Next, the system calculates the intensity of the common-mode interference field component segment corresponding to each geographical location, usually by calculating its root mean square value within a certain time window, to obtain a stable value that represents the average interference level at that location. Finally, the system correlates these calculated intensity values ​​with their respective geographical locations and performs visualization rendering on a geographic information system, generating an interference field intensity map reflecting the distribution of external stray currents. On this map, different colors represent the common-mode interference field intensity at different locations.

[0049] It should also be noted that this step involves calculating the intensity of the interference field, which is usually quantified using the root mean square value. The calculation formula is as follows: ,in, The value represents the intensity of the common-mode interference field component, measured in nanotesla. It is the residual signal obtained after the subtraction operation, that is, the first common-mode interference field component. The value of each sampling point is expressed in nanotesla. It is the total number of sampling points within the time window used to calculate the intensity. It is a dimensionless integer, and its setting is based on the shortest signal duration that needs to ensure statistical stability. It is usually taken as the length covering several pseudo-random code periods, and can be set to 1000 sampling points.

[0050] For example, continuing from the previous example, the system processes the time-domain data stream at 101 path tracking coordinate points recorded along a 50-meter path. At the 90th coordinate point, approximately 45 meters along the path, the system subtracts the known target response component from the original time-domain data stream. Subsequently, the system calculates the root mean square intensity of 1000 sampling points on the residual signal after the subtraction, i.e., the common-mode interference field component, yielding an interference intensity of 10.5 nanotesla at that point. At most other locations along the path, such as the 20th coordinate point, the interference intensity calculated using the same method is only 1.8 nanotesla. The system associates these 101 calculated interference intensity values ​​with their corresponding coordinate points to generate an interference field intensity map.

[0051] In a specific embodiment of the present invention, the specific steps for generating the topology node to be verified include: superimposing the interference field intensity map on the preliminary conductor path map.

[0052] Along the conductor path, geographical locations where there are significant bulges or abrupt changes in the interference field strength value are automatically searched and marked as topological nodes to be verified due to stray current accumulation or shunting.

[0053] It should be noted that the interference field intensity map generated in the previous step is precisely overlaid on the preliminary conductor path map as a semi-transparent layer. This allows operators to simultaneously observe the direction of the underground conductor and the distribution intensity of stray currents along the line in a single view. Subsequently, the system initiates an automatic search algorithm along the trajectory line of the preliminary conductor path map. This algorithm detects the interference field intensity value corresponding to each coordinate point on the path and identifies locations where the intensity value exhibits a significant local peak. A location is identified as a local peak if its interference field intensity value is significantly higher than the intensity values ​​of all points within a certain distance before and after it, forming a significant bulge or abrupt change. For example, if the interference intensity at a point on the path is 10.5 nanotesla, and the intensity of points within a 5-meter radius before and after it does not exceed 3 nanotesla, this point will be identified by the algorithm. These points are special because they typically correspond to the intersections of underground conductors, i.e., topological nodes. At these node locations, multiple conductors converge or branch, causing external stray currents to collect or shunt, thus generating a locally enhanced magnetic field on the ground, manifested as a local intensity peak in the common-mode interference field component. The system automatically marks these identified special locations on the map, for example, with a red star symbol, and stores them as topology nodes to be verified, awaiting further detection and confirmation in subsequent steps.

[0054] Among them, special location points are specific geographical locations on the preliminary conductor path diagram where the intensity of the corresponding common-mode interference field component exhibits a local peak. In terms of data, it is represented as a coordinate point with high interference intensity.

[0055] For example, continuing from the previous example, the system overlays the previously generated interference field strength map, which appears dark red at the 45-meter mark of the path, onto the preliminary conductor path map of 50 meters. The automatic search algorithm scans along this path, and when it reaches the 90th coordinate point, it detects an interference field strength of 10.5 nanotesla, while the strength values ​​at the 10 coordinate points before and after it are all between 1.5 and 2.5 nanotesla. The algorithm determines this point to be a significant local intensity peak, and therefore marks this special location, generating a topology node to be verified at coordinates 22.54045 degrees North latitude and 114.05 degrees East longitude. This node is highlighted on the map with a red star symbol, indicating to the operator that a conductor branch may exist at this location.

[0056] S6. Topology Integration and Generation: Using the topology node to be verified as the center, multi-directional detection is performed to confirm and draw branch paths. Finally, the preliminary conductor path diagram and all branch paths are integrated to generate a complete grounding network topology diagram.

[0057] In a specific embodiment of the present invention, the method of multi-directional detection centered on the topological node to be verified to confirm and draw the branch path is as follows: pause the tracking along a single path, take the marked topological node to be verified as the center, repeatedly collect magnetic field signals, perform cross-correlation calculations and identify path tracking coordinate points in different surrounding angles, determine whether there are other conductor branches besides the original path, record the other conductor branches besides the original path as branch paths, and draw all branch paths.

[0058] It should be noted that the operator moves to the location of the topological node to be verified marked on the map. Upon arrival, the previous single-path tracking operation is paused. Using this topological node to be verified, for example, 22.54045 degrees North latitude and 114.05 degrees East longitude, as the center, a small-scale fan-shaped probe is started in multiple directions. The operation procedure is as follows: first, the magnetic field detection device is positioned at a new angle outside the original path extension direction, such as a direction at a 30-degree angle to the original path. Then, the core steps S2 to S4 are repeated. That is, a short distance is moved in this direction, while continuously acquiring the mixed magnetic field signal generated by the combined action of excitation current and stray current, and digitizing it to generate a time-domain data stream. Next, the system performs cross-correlation calculations on this new time-domain data stream in real time, separating the target response component and searching for the existence of a clear path tracking coordinate point, that is, the location where the target response component reaches a local maximum. If a series of consecutive path-tracking coordinates are successfully identified in this new direction, the system will connect these points to draw a new conductor path, which is a branch path at that node. The operator will continue to use the topology node to be verified as the center, systematically changing the detection angle, for example, increasing it by 30 degrees each time, and repeating the above detection process until the 360-degree range has been scanned, thereby determining whether there are other conductor branches besides the original path, and drawing all detected branch paths.

[0059] Here, a branch path extends from a topology node and is one or more conductor paths that differ from the main path. Its data format is similar to that of the initial conductor path. Figure 1 All of them are line segments connected by a series of geographical coordinate points.

[0060] For example, continuing from the previous example, the operator moves to the location of the topological node to be verified, marked on the map at 22.54045 degrees North latitude and 114.05 degrees East longitude. He first adjusts the detection direction to due east at a 90-degree angle to the original path. Then he starts the device and repeats steps S2 to S4. The device begins to acquire new mixed magnetic field signals and performs cross-correlation calculations. As the operator moves due east, he observes a significant increase in the target response component, which can be continuously tracked to a continuous local maximum trajectory. Based on this, the system records a series of new path-tracking coordinates and plots a branch path extending eastward from this node on the map. Subsequently, the operator tests the due west and due south directions and finds that in these directions, no clear and continuous peaks can be found in the cross-correlation results; that is, the target response component is very weak and discontinuous, indicating that there is no conductor branch in these directions. Finally, it is confirmed that only one branch path extending eastward exists at the topological node to be verified.

[0061] In a specific embodiment of the present invention, the specific steps of integrating the preliminary conductor path diagram with all branch paths to generate a complete grounding grid topology diagram include: connecting all drawn branch paths with the main conductor path.

[0062] Assign unique identifiers to the initial conductor path diagram, all branch paths, and topology nodes to be verified.

[0063] Establish a logical association table to record the connection relationships between paths and nodes, so as to construct a graph data structure that can reflect the physical connection relationships between conductors, thereby generating a complete grounding network topology diagram.

[0064] It should be noted that, specifically, after all the aforementioned detection and identification steps are completed, the system enters the final integration phase to construct a complete grounding network topology diagram. First, the system retrieves the preliminary conductor path diagram generated in step S4 and uses it as the basic framework. Next, the system loads the branch paths detected and drawn around each confirmed topology node into the same geographic information system view. Since the starting point of each branch path is precisely located at a node on the preliminary conductor path diagram, the system can seamlessly connect these branch paths to the main conductor path, achieving graphical splicing. After splicing, the system performs a logical association operation. This operation establishes connections between all path segments and nodes at the data level, moving beyond mere graphical overlap. The system assigns a unique identifier to each node and each path and establishes a logical association table, explicitly recording which path connects which two nodes, or which node is the intersection of multiple paths. In this way, all discrete paths and nodes are integrated into a data model with a network structure. Ultimately, this comprehensive view, which includes all main paths, branch paths, and their precise connections, constitutes a complete grounding grid topology diagram that fully reflects the physical connections and distribution of conductors in the entire underground grounding grid.

[0065] For example, continuing from the previous example, the system uses the initial 50-meter-long conductor path from south to north as the backbone. Then, it loads the eastward-extending branch path detected at the node at 45 meters along the path, i.e., 22.54045 degrees North latitude and 114.05 degrees East longitude. In the GIS software, this branch path is automatically connected to the corresponding node on the backbone path. Subsequently, the system performs logical association, defining the backbone path as path 1 connected by the southern endpoint and the intersection node, and defining the branch path as path 2 connected by the intersection node and the eastern endpoint, explicitly identifying the intersection node as node A. The final generated complete grounding network topology map is displayed on the map as a T-shaped conductor network, with a data table explaining that node A is the connection point of path 1 and path 2, thus completely reconstructing the local grounding network topology of the area.

[0066] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A method for reconstructing the topology of a circular paving road when grounding grid drawings are missing, characterized in that, Includes the following steps: S1. Excitation signal generation and application: Generate a pulse sequence signal with identification based on a preset pseudo-random code with low correlation, and apply the pulse sequence signal to a known access point of the grounding grid to form an excitation current carrying a unique pseudo-random code feature in the underground conductor. S2. Hybrid magnetic field signal acquisition and processing: Acquire the hybrid magnetic field signal generated by the combined action of the excitation current carrying a unique pseudo-random code and the external stray current, and digitize the hybrid magnetic field signal to generate a time-domain data stream containing the target response and environmental interference. S3. Target response separation and localization: Perform cross-correlation operation on the time-domain data stream containing target response and environmental interference and a preset pseudo-random code with low correlation to separate the target response component and generate a path tracking coordinate point sequence that locks the contribution of the excitation source. S4. Preliminary conductor path diagram generation: Connect the path tracing coordinate point sequence to draw the extended path of a single conductor and generate a preliminary conductor path diagram. S5. Generation of topology nodes to be verified: Based on the time-domain data stream containing the target response and environmental interference and the target response component, the common-mode interference field component is obtained, the interference field intensity map is generated, and the special location points where the common-mode interference field component has local intensity peaks are identified on the preliminary conductor path map to generate the topology nodes to be verified. S6. Topology Integration and Generation: Using the topology node to be verified as the center, multi-directional detection is performed to confirm and draw branch paths. Finally, the preliminary conductor path diagram and all branch paths are integrated to generate a complete grounding network topology diagram.

2. The method for reconstructing the topology of a circular paving road when grounding grid drawings are missing, as described in claim 1, is characterized in that: The specific method for generating a pulse sequence signal with identification based on a preset pseudo-random code with low correlation is as follows: the binary code bits of the preset pseudo-random code with low correlation are mapped to preset positive and negative voltage levels to generate a pulse sequence signal with a specific timing.

3. The method for reconstructing the topology of a circular paving road under the condition of missing grounding grid drawings as described in claim 1, characterized in that: The specific steps for generating a time-domain data stream containing the target response and environmental interference include: By continuously collecting time-varying information on the total magnetic field strength above the Earth's surface using mobile magnetic field detection equipment, a mixed magnetic field signal can be obtained. The mixed magnetic field signal is sampled and quantized to convert it into a time-domain data stream that includes the target response and environmental interference.

4. The method for reconstructing the topology of a circular paving road when grounding grid drawings are missing, as described in claim 1, is characterized in that: The specific steps for separating the target response components and generating a sequence of path tracking coordinate points that lock the excitation source contribution include: Sliding cross-correlation calculation is performed on the time-domain data stream containing the target response and environmental interference and a preset pseudo-random code with low correlation to generate cross-correlation calculation results; The sharp peaks in the cross-correlation results are identified, and the geographic coordinates of the locations where the sharpest peaks are strongest are continuously recorded to form a sequence of coordinate points for path tracking.

5. The method for reconstructing the topology of a circular paving road under the condition of missing grounding grid drawings as described in claim 4, characterized in that: The specific steps for generating the preliminary conductor path diagram include: The magnetic field detection device is moved to keep the sharp peak amplitude in the cross-correlation calculation results at a local maximum. Connect the sequence of path tracking coordinates recorded during the movement in the geographic information system to generate a preliminary conductor path map.

6. The method for reconstructing the topology of a circular paving road when grounding grid drawings are missing, as described in claim 4, is characterized in that: The specific steps for obtaining the common-mode interference field components and generating the interference field intensity map include: Subtract the target response component identified by sliding cross-correlation from the time-domain data stream containing the target response and environmental disturbances; The residual signal after subtraction is used as the common-mode interference field component. The intensity of the common-mode interference field component is calculated and associated with the geographical location information to generate an interference field intensity map.

7. The method for reconstructing the topology of a circular paving road under the condition of missing grounding grid drawings as described in claim 6, characterized in that: The specific steps for generating the topology node to be verified include: The interference field intensity map is overlaid on the preliminary conductor path map; Along the conductor path, geographical locations where there are significant bulges or abrupt changes in the interference field strength value are automatically searched and marked as topological nodes to be verified due to stray current accumulation or shunting.

8. The method for reconstructing the topology of a circular paving road under the condition of missing grounding grid drawings as described in claim 1, characterized in that: The specific method for multi-directional detection centered on the topology node to be verified to confirm and draw branch paths is as follows: pause the tracking along a single path, take the marked topology node to be verified as the center, repeatedly collect magnetic field signals, perform cross-correlation calculations and identify path tracking coordinate points in different surrounding angles, determine whether there are other conductor branches besides the original path, record the other conductor branches besides the original path as branch paths, and draw all branch paths.

9. The method for reconstructing the topology of a circular paving road when grounding grid drawings are missing, as described in claim 8, is characterized in that: The specific steps for integrating the preliminary conductor path diagram with all branch paths to generate a complete grounding grid topology diagram include: Connect all the drawn branch paths to the main conductor path; Assign unique identifiers to the initial conductor path diagram, all branch paths, and topology nodes to be verified; Establish a logical association table to record the connection relationships between paths and nodes, so as to construct a graph data structure that can reflect the physical connection relationships between conductors, thereby generating a complete grounding network topology diagram.

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