Method and system for locating low-voltage cable leakage fault point, electronic equipment and medium

Abstract

The present application relates to the technical field of power system fault detection, and particularly relates to a low-voltage cable electric leakage fault point positioning method and system, electronic equipment and medium; the method comprises: in response to a trigger signal of an electric leakage fault, acquiring fault line section information of the electric leakage; injecting a target current signal into a fault cable corresponding to the fault line section information; after injecting the target current signal into the fault cable, using a non-contact sensor to collect a magnetic field signal along a path direction of the fault cable, and converting the magnetic field signal into an electric signal; determining the position of the low-voltage cable electric leakage fault point according to a signal strength mutation point of the electric signal. In this way, the technical problem of insufficient non-contact measurement accuracy in the existing electric leakage fault positioning technology is solved, and the accuracy, safety and efficiency of fault positioning in complex environments, especially in the dark cable laying scene, are improved.

Description

Technical Field

[0001] This invention relates to the field of power system fault detection technology, and in particular to a method, system, electronic device and medium for locating leakage faults in low-voltage cables. Background Technology

[0002] With the continuous expansion of low-voltage power distribution systems and the increasing complexity of laying environments, especially the widespread use of concealed cables, leakage faults caused by aging and damage to line insulation are frequent. These faults not only easily lead to safety accidents such as electric shock and fire, but also pose a serious threat to personal safety and the stable operation of equipment. While existing residual current devices (RCDs) can cut off the circuit when a leakage occurs, they can only isolate the fault and cannot accurately locate the fault point, greatly complicating subsequent troubleshooting and repair work.

[0003] In the field of leakage current fault location, existing technologies mainly rely on two types of methods: one is traditional manual inspection methods, such as manual line inspection and insulation resistance meter measurement. These methods are inefficient, experience-dependent, and almost ineffective for concealed wiring; the other is detection technology based on signal injection, which locates the fault by injecting a specific signal into the cable and tracking its changes. However, existing signal injection methods mostly use contact measurement, which requires disconnecting the line and connecting the equipment, making the operation complex and posing electrical safety risks. In addition, low-voltage cables are often surrounded by densely distributed metal materials such as steel bars, and the eddy current effect generated by these materials can seriously interfere with the magnetic field signal, leading to a decrease in the accuracy of non-contact measurement or even misjudgment.

[0004] Prior art document 1 (application publication number CN112034390A) discloses a method for monitoring leakage current faults in low-voltage power distribution systems based on Hausdorff distance. This method calculates the bidirectional Hausdorff distance between the residual current waveforms of adjacent monitoring nodes using edge terminals, constructing a mismatch matrix to identify fault sections. This method improves monitoring sensitivity by utilizing waveform difference characteristics, avoiding the malfunction problem caused by traditional single-end electrical quantity numerical coordination. However, prior art document 1 mainly focuses on macroscopic difference analysis of residual current waveforms, failing to effectively solve the problem of precise fault location. Specifically, this method relies on multi-terminal synchronous sampling and topology coordination, resulting in high deployment costs and insufficient flexibility in concealed or complex environments. Furthermore, its algorithm focuses on section-level fault identification, unable to directly locate leakage points with meter-level or even higher precision, and particularly struggles to suppress waveform distortion caused by on-site metal interference, making the location results susceptible to environmental specificities. Therefore, existing leakage fault location technologies suffer from insufficient non-contact measurement accuracy, limiting their practicality in complex scenarios such as concealed cabling and failing to meet the requirements of high-precision, rapid-response operation and maintenance. Summary of the Invention

[0005] In view of the above-mentioned shortcomings or disadvantages, the present invention provides a method, system, electronic device and medium for locating leakage faults in low-voltage cables, which can solve the technical problem of insufficient non-contact measurement accuracy in existing leakage fault location technology.

[0006] This invention provides a method for locating leakage faults in low-voltage cables, comprising:

[0007] In response to the trigger signal of a leakage fault, information about the faulty line section where the leakage occurred is obtained.

[0008] A target current signal is injected into the faulty cable corresponding to the faulty line section information. The target operating frequency of the target current signal is determined based on the cable distribution parameters and environmental interference parameters through a quantitative calculation model and a dynamic frequency adaptive adjustment mechanism.

[0009] After injecting the target current signal into the faulty cable, a non-contact sensor is used to collect the magnetic field signal along the path of the faulty cable and convert the magnetic field signal into an electrical signal.

[0010] The location of the low-voltage cable leakage fault can be determined based on the point of abrupt change in the signal strength of the electrical signal.

[0011] According to a second aspect, the present invention provides a system for locating leakage faults in low-voltage cables, comprising:

[0012] The faulty line section location module is used to obtain information about the faulty line section where leakage occurred when a trigger signal for a leakage fault is received.

[0013] The target current signal injection module is used to inject a target current signal into the faulty cable corresponding to the faulty line section information. The target operating frequency of the target current signal is determined based on the cable distribution parameters and environmental interference parameters through a quantitative calculation model and a dynamic frequency adaptive adjustment mechanism.

[0014] The non-contact signal acquisition module is used to acquire the magnetic field signal along the path of the faulty cable after injecting the target current signal into the faulty cable, and convert the magnetic field signal into an electrical signal.

[0015] The leakage fault location module is used to determine the location of low-voltage cable leakage faults based on the sudden change in the signal strength of the electrical signal.

[0016] According to a third aspect, the present invention provides an electronic device comprising:

[0017] At least one processor; and a memory communicatively connected to the at least one processor;

[0018] The memory stores instructions that can be executed by the at least one processor, which enables the at least one processor to perform any low-voltage cable leakage fault location method in the embodiments of the present invention.

[0019] According to another aspect of the present invention, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause a computer to execute a method for locating a low-voltage cable leakage fault point in any of the embodiments of the present invention.

[0020] The present invention provides a method for locating leakage faults in low-voltage cables. This method is achieved through four core steps: fault segment information acquisition, target current signal injection, magnetic field signal acquisition and conversion, and fault point location. Specifically, the method involves: responding to a leakage fault trigger signal and acquiring faulty line segment information to initially delineate the fault range; injecting a target current signal into the faulty cable based on cable distribution parameters and environmental interference parameters, using a quantitative calculation model and a dynamic frequency adaptive adjustment mechanism to determine the target operating frequency, thereby generating an optimal detection signal adapted to the specific cable structure and site environment; using a non-contact sensor to acquire magnetic field signals along the path and converting them into electrical signals for safe and efficient non-contact electromagnetic signal pickup; and determining the fault point location based on the signal strength abrupt change of the electrical signal to achieve precise location of the leakage point.

[0021] In this technical solution, the present invention addresses the problems of coarse positioning granularity and low investigation efficiency mentioned in the background technology. By first acquiring information on the faulty line section where leakage occurred, the investigation scope is narrowed from the entire power distribution system to a specific section, providing a clear target for subsequent precise positioning. This solves the technical defects of traditional manual line inspection or section identification technology, which cannot quickly narrow down the fault range. Addressing the technical problems of low accuracy and weak anti-interference capability of non-contact measurement, the invention injects a current signal with a target operating frequency determined by a quantitative calculation model and a dynamic frequency adaptive adjustment mechanism. This allows the injected signal to actively avoid strong power frequency interference and suppress the eddy current effect of surrounding metals, while optimizing the signal transmission characteristics in specific cables, thereby significantly improving the signal-to-noise ratio and anti-interference capability of the detection signal. Addressing the safety risks and operational complexity of contact measurement, the invention uses a non-contact sensor to collect magnetic field signals along a preset path, achieving contactless and uninterrupted safe detection of concealed cables. Finally, addressing the technical bottleneck of insufficient final positioning accuracy, the invention locates the fault by analyzing the intensity abrupt changes of the converted electrical signal. This allows for sensitive identification of magnetic field abrupt changes caused by current leakage at the leakage point, thereby achieving meter-level or even higher spatial positioning accuracy of the fault point. Therefore, the technical solution of the present invention solves the technical problem of insufficient non-contact measurement accuracy in existing leakage fault location technology, and improves the accuracy, safety and efficiency of fault location in complex environments, especially in the case of concealed cables. Attached Figure Description

[0022] Figure 1 This is a flowchart of a method for locating leakage faults in low-voltage cables according to an embodiment of the present invention;

[0023] Figure 2 This is a complete operation flowchart of maintenance personnel performing on-site fault diagnosis based on the positioning method according to another embodiment of the present invention;

[0024] Figure 3 This is an example diagram of the core calculation process for determining the operating frequency of the target current signal in another embodiment of the present invention;

[0025] Figure 4 This is an example diagram of a hardware implementation architecture for generating and precisely controlling a target current signal in another embodiment of the present invention;

[0026] Figure 5 This is an example diagram of a hardware system architecture for implementing magnetic field signal acquisition and processing in another embodiment of the present invention;

[0027] Figure 6 This is an example diagram of key hardware components used to achieve high-sensitivity magnetic field sensing in another embodiment of the present invention;

[0028] Figure 7This is a measured data curve of signal strength changing with the measurement path in another embodiment after applying the method of the present invention;

[0029] Figure 8 This is a schematic diagram of the structure of a low-voltage cable leakage fault location system according to an embodiment of the present invention;

[0030] Figure 9 This is a block diagram of an electronic device used to implement embodiments of the present invention. Detailed Implementation

[0031] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention, including various details to aid understanding. These details should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope of the invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0032] During the development of this invention, the inventors, through extensive experiments and data analysis, discovered the intrinsic relationship between cable distribution parameters (such as burial depth, soil moisture, and conductor radius) and environmental interference parameters (such as surrounding metal density and power frequency interference). These parameters collectively determine the signal transmission attenuation characteristics in low-voltage cables. Distributed inductance, distributed capacitance, and distributed resistance are influenced by the combined effects of soil dielectric constant, temperature, and metal eddy current effects. The optimal frequency must balance transmission loss and anti-interference capability. Based on this relationship, the inventors innovatively proposed this technical solution. Utilizing a multi-parameter coupled quantitative calculation model, and through a dynamic frequency adaptive adjustment mechanism, combined with non-contact magnetic field signal acquisition and gradient analysis, meter-level precise location of leakage fault points is achieved, embodying the core concept of "computational" precise frequency matching and non-contact tracing.

[0033] Specifically, through comparative experiments, the invention team discovered that traditional manual line inspection or fixed-frequency signal injection methods suffer from technical defects such as low efficiency, high safety risks, and weak anti-interference capabilities: manual line inspection relies on experience and is ineffective for concealed cables; contact measurement requires power-off operation, which is complex and dangerous; non-contact measurement is susceptible to interference from power frequency harmonics and surrounding metal eddy currents, leading to signal distortion and misjudgment of location. These technical defects result in long fault diagnosis cycles and poor location accuracy, making it difficult to meet the high-efficiency operation and maintenance requirements of modern power distribution systems. However, the non-contact positioning method based on signal tracing proposed in this invention can improve positioning accuracy to the meter level and significantly enhance anti-interference capabilities; through a dynamic frequency adaptive adjustment mechanism (such as theoretical calculation, eddy current correction, and on-site calibration), signal transmission loss can be minimized and environmental specificity can be adapted; through a composite magnetic core sensor and gradient analysis algorithm, the signal-to-noise ratio of magnetic field signal acquisition can be improved by more than 45 dB, and the sudden change characteristics of fault points can be accurately identified.

[0034] Therefore, this invention provides a method for locating low-voltage cable leakage faults according to the first aspect, which can be applied to a comprehensive intelligent power distribution operation and maintenance system (hereinafter referred to as the "system"). This system can operate in a power distribution IoT environment through edge computing and cloud collaboration or local independent operation to complete the entire operation and maintenance task from leakage fault early warning to precise fault location. Specifically, this system can be deployed in various hardware environments, including but not limited to: edge gateways deployed in power distribution transformer areas, portable mobile terminals used by maintenance personnel (such as industrial tablets, dedicated handheld devices), and cloud data center servers. This flexible deployment architecture enables the system to meet both the requirements of high-precision, low-latency fault detection and location on-site and the application scenarios of large-scale power distribution network remote monitoring and big data analysis.

[0035] like Figure 1 As shown, the method may include:

[0036] Step S110: In response to the trigger signal of the leakage fault, obtain the information of the faulty line section where the leakage occurred.

[0037] Among them, the trigger signal refers to the start command generated by the monitoring system when it detects an abnormal leakage current event, which is used to activate this positioning process; the fault line section information refers to the identification data that can narrow down the leakage fault range from the entire power distribution network to a specific physical section.

[0038] Specifically, the system can use a residual current monitoring platform deployed in the distribution transformer area to compare the residual current value with a preset threshold (e.g., 30 mA) in real time. When the threshold is exceeded, a trigger signal is automatically generated. Alternatively, it can be manually triggered by maintenance personnel using clamp meters to detect an anomaly on-site. For example, if the system detects that the residual current value at the main incoming line of a residential building exceeds 50 mA for 5 seconds, the platform immediately generates a trigger signal and, based on the action logs of the multi-level residual current devices (RCDs) (e.g., the RCD in the floor distribution box acts before the RCD in the main cabinet), analyzes the action sequence and outputs the fault section as "the lighting circuit on the east side of the fifth floor of the west unit of Building 3".

[0039] Step S120: Inject the target current signal into the faulty cable corresponding to the faulty line section information.

[0040] The target operating frequency of the target current signal is determined based on the cable distribution parameters and environmental interference parameters through a quantitative calculation model and a dynamic frequency adaptive adjustment mechanism. The quantitative calculation model refers to a set of mathematical relationships that map physical parameters such as cable structure and soil characteristics to the theoretical optimal frequency. The dynamic frequency adaptive adjustment mechanism refers to the optimization process of fine-tuning the theoretical frequency in a closed loop based on the measured signal strength on site.

[0041] Specifically, the system can first execute a quantitative calculation model through the main controller of the signal generator: inputting parameters such as cable burial depth (0.8 meters), soil moisture (35%), and surrounding metal density (120 kg / m³), and calculating distributed inductance and distributed capacitance based on transmission line theory, and then solving for the theoretical frequency that minimizes signal transmission attenuation. (e.g., 8.5 kHz). Subsequently, a dynamic frequency adaptive adjustment mechanism is activated: with... Using the initial value, a small-range frequency scan is performed on-site with a step size of 200 Hz to measure the signal strength at each frequency point. Finally, the frequency with the strongest signal strength (such as 8.62 kHz) is selected as the target operating frequency. For example, based on calculation and adaptive adjustment, the system determines the final target operating frequency to be 8.62 kHz, and the signal generator then generates and injects a sinusoidal current signal with an amplitude of 100 mA at this frequency into the faulty cable.

[0042] In another embodiment, Figure 3 This demonstrates the core calculation step in the aforementioned positioning method used to determine the operating frequency of the target current signal—"calculation of the theoretical optimal frequency with minimal transmission attenuation." This step corresponds to the step S120 above, "calculating the theoretical target operating frequency based on cable distribution parameters and environmental interference parameters using a quantitative calculation model." Its function is to transform the collected physical parameters into key frequency values ​​for guiding signal injection. The input to this step is the basic parameters obtained in the preceding steps, including cable burial depth (…). (meters), soil moisture ( ), cable conductor radius ( (millimeters) and cable cross-sectional area ( (square millimeters), etc. The calculation process follows three key technical steps, as shown in bold black text in the figure. First, a transmission attenuation coefficient model is established. Specifically, the system is based on transmission line theory and uses input parameters to calculate the distributed inductance per unit length of cable. Distributed capacitance With distributed resistance The formula for calculating distributed inductance is as follows: The calculation of distributed capacitance requires first obtaining the relative permittivity based on soil moisture. Then substitute into the formula Distributed resistance is given by the formula... Calculation, where To account for the resistivity of the copper conductor at ambient temperature T, a characterization of signal attenuation as a function of angular frequency is then constructed. Mathematical model of change: ,in The value of the dielectric loss tangent depends on the characteristics of the cable insulation material and can usually be obtained from a material handbook. Next, the theoretically optimal angular frequency is solved using a model. Specifically, the system uses the aforementioned transmission attenuation coefficient model... Defined as the objective function to be optimized, a one-dimensional search algorithm (such as the golden section method) is used to find the optimal function within a preset frequency band (e.g., the angular frequency range corresponding to 1 kHz to 20 kHz). Angular frequency that achieves minimum value Ultimately, the theoretically optimal frequency value was obtained. Specifically, the system uses the formula... Optimal angular frequency Convert to the theoretical optimal frequency in Hertz The calculation is then completed. For example, after calculation, the result might be: kilohertz. The output of this stage, i.e., the theoretically optimal frequency. This will serve as the direct input for the subsequent "environmental interference correction and frequency band constraint verification" stage. Figure 3 With a clear logic diagram and blue connecting arrows, the complete calculation chain from the original parameters to the core frequency result is vividly illustrated, highlighting the cornerstone role of this step in achieving "quantitative calculation" and "frequency adaptation".

[0043] In another embodiment, Figure 4This demonstration showcases the hardware architecture for generating and precisely controlling the target current signal in the aforementioned positioning method—a signal generation and closed-loop gain control system. This system specifically implements the step of "injecting the target current signal into the faulty cable" and ensures stable signal strength through an "automatic gain control loop." Its physical structure and data flow visually demonstrate the complete process from digital instructions to stable physical signal output. The core of the system is the main controller (STM32F103, a 32-bit microcontroller based on the ARM Cortex-M3 core designed and manufactured by STMicroelectronics). As the top-level decision-making unit, it is responsible for generating the corresponding frequency control word based on the calculated target operating frequency and sending it to the Direct Digital Synthesis (DDS) module via the SPI (Serial Peripheral Interface) bus. Upon receiving the instruction, the DDS module generates a high-precision, low-phase-noise sinusoidal analog signal of the corresponding frequency. This signal is then amplified by a power amplifier to meet the signal strength requirements for long-distance transmission and detection. The amplified signal enters the Automatic Gain Control (AGC) module, which is crucial for the system's stable output. The AGC module not only drives the final signal output but also forms a closed-loop control through a feedback loop: its output signal is connected to the faulty line and ground via the output interface to form an injection loop; simultaneously, a current detection module connected in series in the loop monitors the loop current in real time and sends this feedback signal back to the AGC module. The system's workflow is a complete closed-loop control: the main controller sets the target frequency and current amplitude → the DDS generates the signal → power amplification → AGC output → real-time feedback from current detection → the AGC compares the feedback value with the target value and dynamically adjusts its gain → ultimately stabilizing the output current amplitude within the preset range. For example, when the grounding resistance increases, causing the loop current to decrease, the current detection module's feedback value decreases, and the AGC module accordingly increases its gain to compensate for the current decrease, maintaining a constant signal strength. Therefore, Figure 4 It not only demonstrates the specific hardware components of the signal generating device, but also vividly explains how the technical feature of "dynamically adjusting the output amplitude" in the above method can be accurately realized through an electronic system by clearly showing the signal flow and feedback loop, thus ensuring the reliability and environmental adaptability of this positioning method in practical applications.

[0044] Step S130: After injecting the target current signal into the faulty cable, a non-contact sensor is used to collect the magnetic field signal along the path of the faulty cable and convert the magnetic field signal into an electrical signal.

[0045] Non-contact sensors refer to devices that can detect the magnetic field strength around a conductor without electrical contact, based on the principle of electromagnetic induction; electrical signals refer to voltage or current signals that are easy to process and analyze later.

[0046] Specifically, the system allows an operator to handhold a data acquisition device with a built-in composite magnetic core sensor and move it along the path of a suspected faulty concealed cable (such as a wall). The sensor senses a magnetic field and generates a weak induced potential (typically in the millivolt range). This signal is then filtered (to remove out-of-band interference such as power frequency), amplified (adjustable gain, e.g., 40 dB), and converted to digital signal (ADC, sampling rate 100 kHz) by a signal conditioning circuit, ultimately yielding a digital electrical signal. For example, when the sensor moves 5 cm from the cable, it acquires an initial induced potential of 3 millivolts, which is then conditioned and converted into a digital signal with an amplitude of 1.5 volts. The sampling sequence is as follows: (Unit: Volt), for further analysis.

[0047] In another embodiment, Figure 5 This demonstrates the hardware system architecture for magnetic field signal acquisition and processing in the aforementioned positioning method—the magnetic signal detection and processing system. This system specifically implements step S130, and its modular design clearly illustrates the signal chain from physical field sensing to digital information generation and distribution. The system's signal sensing originates from a magnetic rod coil sensor, whose core is a high-permeability magnetic core. This sensor is responsible for non-contactly sensing the alternating magnetic field generated by the target current signal around the faulty cable and outputting a weak, raw induced electromotive force signal. This raw signal then enters the signal conditioning circuit for processing. This circuit integrates two key functions: filtering and variable gain amplification. The filtering unit (usually a bandpass filter) suppresses out-of-band interference such as power frequency; the variable gain amplification unit dynamically adjusts the amplification factor according to the signal strength, ensuring that the output signal amplitude remains stable within a level range suitable for subsequent processing. After conditioning, the signal is converted into a regular analog electrical signal. This analog electrical signal is then sent to a high-performance microcontroller (such as an STM32F407) for core processing. The microcontroller's built-in analog-to-digital converter (ADC) discretizes the analog signal into a high-precision digital sequence. Subsequently, the microcontroller performs two parallel operations: first, it wirelessly transmits the digital data stream to a terminal (such as a tablet or mobile phone used by maintenance personnel) via an integrated Bluetooth module, enabling remote monitoring and analysis of the data; second, it generates drive signals to control a local display module (such as an OLED screen, short for Organic Light-Emitting Diode), displaying the signal strength in real time in graphical or numerical form, providing immediate feedback to on-site operators. Therefore, Figure 5With clear module division and signal flow, it fully illustrates the physical implementation of non-contact signal acquisition, conditioning, digitization, display and transmission, forming an indispensable hardware foundation and data source in the above positioning method.

[0048] Step S140: Determine the location of the low-voltage cable leakage fault point based on the signal strength change point of the electrical signal.

[0049] Among them, the signal strength mutation point refers to the local feature point in the digital signal sequence collected along the path where the amplitude drops or rises sharply. This point corresponds to the location where the injected current flows into the ground through the leakage point, causing a sudden change in the current in the cable.

[0050] Specifically, the system can be implemented using a positioning algorithm in host computer software or an embedded controller. This algorithm first calculates the envelope or RMS value of the digital signal sequence as the signal strength sequence, then performs gradient calculation (e.g., first-order difference) on this strength sequence, and searches for gradient values ​​that exceed a preset threshold (e.g., ...). A continuous point (per meter) is identified as a point of inflection.

[0051] For example, the system processes and obtains a signal strength sequence along the path from 2 meters to 8 meters. (Unit: dB / µV). The gradient sequence is calculated as follows: At 5 meters along the path (corresponding to the gradient) The system detected a sudden change in signal strength from 67 dB / µV to 25 dB / µV, indicating that the location below this point was the leakage fault. The location accuracy was [not specified]. rice.

[0052] In another embodiment, Figure 2 This demonstrates the complete operational process for maintenance personnel to troubleshoot on-site using the aforementioned location method. Specifically, this process is a closed-loop, iterative on-site operation guidance logic. The process begins with external input, namely "discovery of leakage / platform alarm," which corresponds to "responding to the trigger signal of the leakage fault" in step S110 above. Subsequently, the process enters the decision-making and execution phase. The first phase is coarse fault location, corresponding to "obtaining information on the faulty line section where leakage occurred." The diagram provides two parallel technical paths: "using a three-level RCD" or "using a clamp meter." If the faulty section is successfully determined by analyzing the operating timing of the multi-level residual current device or measuring the current distribution of each branch, the process proceeds to "isolate the faulty line and inject the optimal frequency." The first stage involves a "signal" step. If the initial assessment is that "there is no fault in this section," the operator is instructed to "continue searching forward," returning to the previous stage to reselect the section, demonstrating the iterative nature of the method. The second stage is precise location implementation. After isolating the line and injecting the target current signal, the operator "uses the acquisition device to non-contactly scan and measure the magnetic field signal along the path." This step integrates signal injection, acquisition, and conversion. Subsequently, the system or host computer performs "signal strength analysis" on the data. If "a sudden change in signal strength is found," the process leads to "precisely locating the fault point," and finally "repairing and verifying" to complete the closed loop. If the analysis does not find an obvious sudden change, the instruction to "continue searching forward" is returned to eliminate misjudgments or find other potential fault points. This flowchart graphically clarifies the temporal relationship, decision logic, and backoff mechanism between the steps in the method, emphasizing the sequential nature of on-site operations and the feedback-based iterative optimization process. It is a visual representation of how this method transforms from a theoretical solution into a standardized and repeatable operating procedure.

[0053] Therefore, according to the above implementation method, the system achieves its purpose through four core steps: fault section information acquisition, target current signal injection, magnetic field signal acquisition and conversion, and fault point location. Specifically, in response to the trigger signal of the leakage fault, the system acquires information about the faulty line section to initially delineate the fault range; a target current signal is injected into the faulty cable based on cable distribution parameters and environmental interference parameters, and the target operating frequency is determined through a quantitative calculation model and a dynamic frequency adaptive adjustment mechanism to generate an optimal detection signal adapted to the specific cable structure and site environment; a non-contact sensor is used to acquire the magnetic field signal along the path and convert it into an electrical signal for safe and efficient non-contact electromagnetic signal pickup; and the fault point location is determined based on the signal strength abrupt change point of the electrical signal to achieve precise location of the leakage point.

[0054] Specifically, in this implementation, the technical solution addresses the problems of coarse positioning granularity and low investigation efficiency mentioned in the background technology. By first acquiring information about the faulty line section where leakage occurred, the investigation scope is narrowed from the entire power distribution system to a specific section, providing a clear target for subsequent precise positioning. This solves the technical deficiency of traditional manual line inspection or section identification technologies in quickly narrowing down the fault range. Regarding the technical problems of low accuracy and weak anti-interference capability of non-contact measurement, a current signal with a target operating frequency determined by a quantitative calculation model and a dynamic frequency adaptive adjustment mechanism is injected, enabling the injected signal to actively avoid strong power frequency interference. By suppressing and mitigating eddy current effects in surrounding metals and optimizing signal transmission characteristics in specific cables, the signal-to-noise ratio and anti-interference capability of the detection signal are significantly improved. Addressing the safety risks and operational complexity of contact measurements, a non-contact sensor is used to collect magnetic field signals along a preset path, enabling contactless and uninterrupted safe detection of concealed cables. To overcome the technical bottleneck of insufficient final location accuracy, fault location is achieved by analyzing abrupt changes in the intensity of the converted electrical signal. This allows for sensitive identification of magnetic field abrupt changes caused by current leakage at the leakage point, achieving meter-level or even higher spatial positioning accuracy for the fault point. Therefore, this technical solution solves the technical problem of insufficient non-contact measurement accuracy in existing leakage fault location technologies, improving the accuracy, safety, and efficiency of fault location in complex environments, especially in concealed cable scenarios.

[0055] In some embodiments, the trigger signal is generated by the residual current monitoring platform when the residual current monitoring platform detects that the residual current value exceeds a preset threshold; the step of obtaining information on the faulty line section where leakage has occurred includes:

[0056] The system obtains the operating status information of the multi-stage residual current device, performs timing analysis on the operating status information, and outputs the information of the faulty line section where leakage occurred.

[0057] Among them, the operation status information refers to the switching status (e.g., opening or closing) of the multi-stage residual current protection device and the timestamp information of the operation; the operation timing analysis refers to analyzing the sequence of operation of the multi-stage residual current protection device based on the timestamp in the operation status information, so as to infer the section where the leakage fault occurred.

[0058] Specifically, the system reads the status registers of each level of residual current protection device through a communication interface (such as RS-485 or a wireless module) to obtain its current switching status and the most recent action timestamp. Then, the system compares the action time sequence of each level of protection device. If a certain level of protection device acts before its superior protection device, the system determines that the fault point is located downstream of the line section protected by that level of protection device. For example, in a three-level residual current protection system with a preset threshold of 30 mA, when a leakage fault occurs, the second-level protection device acts (opens) at timestamp T1, while the first-level protection device acts at timestamp T2 (T2>T1). The system then determines, through action timing analysis, that the fault section is the branch under the jurisdiction of the second-level protection device. RS-485 is a standard serial communication interface defined by the Electronic Industries Alliance and widely used in industrial environments. Alternatively, clamp meters can be used to measure the current in each distribution branch of the low-voltage cable, and distribution anomaly analysis can be performed based on the measured current values ​​to output information about the faulty line section.

[0059] Among them, distribution anomaly analysis refers to identifying branches whose current values ​​deviate significantly from the normal range by comparing the measured current values ​​of each distribution branch, thereby determining the fault section; the normal range is set based on historical data or system reference values.

[0060] Specifically, operators use clamp meters to sequentially clamp onto each branch cable, measuring and recording the current value. The system compares the measured value with a preset threshold (e.g., 1 ampere) or the average current of branches of the same level. If the current value of a branch consistently exceeds the threshold or deviates from the average by a certain percentage (e.g., 50%), it is determined that the branch has a leakage current abnormality. For example, when measuring the current of each branch in a residential building's distribution box, the current of the lighting branch is measured to be 5 amperes, while the currents of other branches are all below 1 ampere. Through distribution anomaly analysis, the system determines that the lighting branch is the faulty section.

[0061] Therefore, according to the above implementation method, the system can quickly and accurately delineate the leakage fault section, providing a basis for subsequent precise location.

[0062] In some embodiments, before injecting a target current signal into the faulty cable corresponding to the faulty line segment information, the method further includes:

[0063] Obtain the cable distribution parameters of the faulty cable and the environmental interference parameters of the site environment.

[0064] Among them, cable distributed parameters refer to physical quantities used to describe the electrical transmission characteristics of cables, including distributed inductance, distributed capacitance and distributed resistance; environmental interference parameters refer to external environmental factors that affect signal transmission, including soil moisture, surrounding metal density and ambient temperature.

[0065] Specifically, the system can obtain geometric parameters such as cable burial depth, conductor radius, and cross-sectional area through on-site measurements or by consulting construction drawings, and use sensors (such as soil moisture sensors, metal detectors, and temperature sensors) to collect environmental parameters such as soil moisture, surrounding metal density, and ambient temperature. For example, the system can obtain cable burial depth... Rice, soil moisture Surrounding metal density kilograms per cubic meter, cable cross-sectional area square millimeter, conductor radius millimeters, ambient temperature Celsius.

[0066] Based on cable distribution parameters and environmental interference parameters, the theoretical target operating frequency is calculated using a quantitative calculation model.

[0067] The quantitative calculation model refers to a set of mathematical formulas based on electromagnetic transmission line theory, which are used to derive the theoretical frequency that minimizes signal transmission attenuation based on cable distribution parameters and environmental interference parameters.

[0068] Specifically, the system first calculates the distributed inductance based on the cable geometry and environmental parameters (Formula 1: Distributed capacitance (Formula 2:) , Formula 3: ) and distributed resistance (Formula 4: , Formula 5: Then, by optimizing the attenuation coefficient model (Equation 6: Solve for the theoretically optimal angular frequency (Formula 7: ), which is ultimately converted into the theoretical target operating frequency (Formula 8: ).

[0069] For example, substituting parameters rice, millimeters , , Square millimeters, calculated distributed inductance microhenry per meter, distributed capacitance Pifael per meter, distributed resistivity Ohms per meter, and then the theoretical target operating frequency is calculated using Formula 8. kilohertz.

[0070] Environmental interference correction and frequency band constraint verification are performed on the theoretical target operating frequency to obtain the adjusted frequency.

[0071] Among them, environmental interference correction reduces the frequency by using the eddy current correction coefficient to suppress metal eddy current interference; frequency band constraint verification ensures that the frequency is within the sensor's operating frequency band and avoids power frequency harmonics.

[0072] Specifically, the system first calculates the eddy current correction coefficient (Formula 9: Correction to theoretical frequency (Formula 10: Then verify whether the frequency meets the sensor frequency band (1.2 kHz to 18.5 kHz) and power frequency harmonic avoidance conditions. , (where the integer is an integer), and if it does not meet the requirements, it is adjusted through a penalty function.

[0073] For example, if kilograms per cubic meter Meters, calculation , kHz; since 5.4 kHz is within the sensor's frequency band and far from power frequency harmonics, no further adjustment is needed. The adjusted frequency... kilohertz.

[0074] Based on the adjusted frequency, the target operating frequency of the target current signal is determined through a preset on-site adaptive calibration mechanism.

[0075] Among them, the on-site adaptive calibration mechanism refers to an optimization process that uses measured signal strength to fine-tune the frequency in a closed loop in order to eliminate model errors.

[0076] Specifically, the system injects a signal with the adjusted frequency as the initial value and measures the signal strength; then it scans the neighboring frequencies with a preset step size (e.g., 200 Hz) and selects the frequency with the strongest signal strength as the candidate value; finally, it iterates and optimizes with a smaller step size (e.g., 100 Hz) until the signal strength improvement is lower than the threshold (e.g., 0.5 dB / µV).

[0077] For example, system initial injection kilohertz, measuring signal strength decibels and microvolts; scanned at 5.2 kHz and 5.6 kHz, and measured... decibels decibels and microvolts; selecting 5.6 kHz corresponding to S3 as a candidate frequency, and further scanning in 100 Hz steps to finally determine the target operating frequency. kilohertz.

[0078] Therefore, according to the above implementation method, the system can dynamically generate the optimal frequency that matches the environment through parameterized calculation and adaptive calibration, which significantly improves the anti-interference capability and accuracy of leakage current location.

[0079] In some embodiments, a non-contact sensor is used to acquire a magnetic field signal along the path of the faulty cable, and the magnetic field signal is converted into an electrical signal, including:

[0080] By inducing magnetic field signals and outputting induced potential through a composite magnetic core structure, the composite magnetic core structure is made of materials with different magnetic permeability characteristics to achieve broadband magnetic field induction.

[0081] Among them, the composite magnetic core structure refers to a multi-layer magnetic core design that uses manganese-zinc ferrite as the inner layer material to improve low-frequency sensitivity and nanocrystalline alloy as the outer layer material to enhance high-frequency anti-saturation capability; induced electromotive force refers to the voltage signal induced in the sensor coil by an alternating magnetic field based on the principle of electromagnetic induction.

[0082] Specifically, the system uses a composite magnetic core structure to concentrate and couple the magnetic field around the cable to an induction coil. The coil inductance is proportional to the rate of change of the magnetic field, thus outputting an AC voltage signal proportional to the magnetic field strength. For example, when the target operating frequency is 8 kHz, the sensor can sense an induced potential of 3 millivolts at a distance of 5 cm from the cable, with its frequency components concentrated around 8 kHz.

[0083] In another embodiment, Figure 6 This diagram illustrates a detailed structure of the composite magnetic core sensor, a key hardware component used in the positioning method to achieve high-sensitivity magnetic field sensing. The diagram specifically explains the physical realization of the feature described above: "the composite magnetic core structure is composed of materials with different permeability characteristics to achieve broadband magnetic field sensing." The diagram clearly reveals its geometric parameters, material composition, and assembly relationship with the induction coil through a split-type illustration. Figure 6 The left side shows the independent front and side views of the composite magnetic core. As indicated by the label, the core is an elongated cylinder, with key geometric parameters including a total length L (e.g., 50 mm) and a diameter W (e.g., 8 mm). More importantly, its cross-sectional schematic reveals the composition of the "composite" material: the core layer is a material with high initial permeability (such as manganese-zinc ferrite). This is used for efficient magnetic focusing in low-frequency bands (such as 1~10 kHz) to enhance signal sensitivity; the outer layer is coated with a material with high saturation magnetic induction intensity (such as nanocrystalline alloys). Tesla (Tesla) is used to resist magnetic saturation and maintain linear response at high frequencies or in strong fields. This composite structure of "high internal conductance and high external saturation" is the physical basis for achieving stable magnetoelectric conversion over a wide frequency band (e.g., 1 kHz to 20 kHz). Figure 6 The right side illustrates the assembly and application of this composite magnetic core in a real sensor. For example... Figure 6As shown, a magnetic core is precisely threaded into the center of a multi-layered induction coil, with signal lines leading out from both ends of the coil. Its working principle is as follows: when the target current signal in the faulty cable generates an alternating magnetic field, this magnetic field is efficiently collected and concentrated by the high-permeability composite magnetic core, causing a corresponding change in the magnetic flux inside the core. According to Faraday's law of electromagnetic induction, this changing magnetic flux will generate a proportional induced electromotive force in the external induction coil, i.e., the output signal. The diagram illustrates the process of the magnetic field being concentrated by the magnetic core and passing through the coil using magnetic field lines. Therefore, Figure 6 Through specific dimension markings, material specifications, and assembly diagrams, a clear and feasible physical example is provided for the overarching concept of "composite magnetic core structure," demonstrating the feasibility and superiority of this design in improving sensor performance and achieving broadband non-contact measurement. It is one of the core hardware guarantees supporting the high precision and high environmental adaptability of the entire positioning method.

[0084] The induced potential is filtered to suppress out-of-band interference.

[0085] Out-of-band interference refers to noise signals whose frequency is outside the target operating frequency range, including 50 Hz power frequency and its harmonics, environmental electromagnetic noise, etc.; filtering refers to selectively retaining the target frequency band signal through a bandpass filter.

[0086] Specifically, the system filters the induced electromotive force using a fourth-order Butterworth active bandpass filter. The center frequency of this filter is set to the target operating frequency (e.g., 8 kHz), and the passband bandwidth is set to... The signal has a range of frequencies from 7.5 kHz to 8.5 kHz, with a stopband attenuation greater than 40 dB. For example, if the signal before filtering contains 50 Hz power frequency interference (amplitude 1 mV) and an 8 kHz target signal (amplitude 3 mV), after filtering, the power frequency interference is suppressed to below 0.1 mV, while the target signal amplitude remains at 3 mV.

[0087] Gain adjustment is performed on the filtered signal to make the signal amplitude match the input range of the analog-to-digital converter.

[0088] Among them, gain adjustment processing refers to dynamically adjusting the signal amplification factor through a programmable gain amplifier so that the signal amplitude matches the full-scale input voltage of the analog-to-digital converter; the input range of the analog-to-digital converter refers to the range of analog voltages that it can quantize, such as 0 to 3.3 volts.

[0089] Specifically, the system outputs digital control signals through a microcontroller (such as an STM32F407) to adjust the gain value of a variable gain amplifier (such as an AD8361) to stabilize the signal amplitude between 1 volt and 3 volts, avoiding saturation or excessive weakness. For example, if the filtered signal amplitude is 3 millivolts, and the system is set to a gain of 40 dB (100 times), the output signal amplitude becomes 300 millivolts, which is then amplified two stages to 1.5 volts, adapting to a 3.3-volt full-scale analog-to-digital converter.

[0090] The signal with gain adjustment is subjected to analog-to-digital conversion to obtain a digital electrical signal.

[0091] Analog-to-digital conversion refers to the process of discretizing a continuous analog voltage signal into a digital sequence; digital electrical signals refer to signal amplitude time sequences represented by binary values.

[0092] Specifically, the system samples the amplified signal using a 16-bit analog-to-digital converter (ADC) at a sampling rate of 100 kHz, with a quantization precision of [missing value]. This generates a digital sequence of length 1024 points. For example, an input 1.5-volt analog signal, after analog-to-digital conversion, outputs a digital sequence. (Unit: ADC code value), corresponding voltage value .

[0093] Therefore, according to the above implementation method, the system can convert weak magnetic field signals into digital signals with high fidelity, providing an accurate data basis for subsequent fault location.

[0094] In some embodiments, determining the location of a low-voltage cable leakage fault point based on abrupt changes in the signal strength of the electrical signal includes:

[0095] The electrical signal is processed to calculate the signal strength, and the signal strength sequence distributed along the path of the faulty cable is obtained.

[0096] Among them, the signal strength sequence refers to the set of signal amplitude values ​​obtained by digital signal processing technology and arranged sequentially along the measurement path, which is used to characterize the trend of magnetic field strength with spatial location.

[0097] Specifically, the system samples the conditioned analog signal at a sampling rate of 100,000 times per second using the built-in ADC (analog-to-digital converter) of a microprocessor (such as an STM32F407) to obtain a digital sequence; then it calls... The FFT (Fast Fourier Transform) function in the ARM library (a standardized digital signal processing software library developed and maintained by ARM and optimized for its Cortex-M series processor cores) performs spectral analysis on each 1024-point data block, extracts the squared magnitude of the frequency point corresponding to the target operating frequency (e.g., 8 kHz) as the signal strength, and stores it as a sequence in chronological order of sampling time. For example, the system moves 2 meters along a path, recording a signal strength value every 0.1 meters to obtain the sequence. (Unit: decibel microvolt), where each value corresponds to a specific location on the path.

[0098] In another embodiment, Figure 7 This figure displays a measured data curve showing the signal strength variation along the measurement path when the above-mentioned positioning method is applied in actual measurement. The graph visually verifies and illustrates the results and effects of the two technical steps: "performing signal strength calculation processing on the digital electrical signal to obtain the signal strength sequence distributed along the path of the faulty cable" and "identifying the location of abrupt changes in signal strength." Figure 7 As shown, the horizontal axis represents the "measurement path direction (distance in meters)," ranging from 0 meters to 10 meters, representing the movement trajectory of the sensor along the suspected faulty cable. The vertical axis represents the "signal strength (dB)," with values ​​ranging from... The range from decibels to 0 decibels reflects the amplitude of the electrical signal received and converted by the sensor (usually expressed in decibel-microvolts, simplified to decibels in the diagram). Figure 7 The light purple broken line clearly depicts the characteristics of signal strength variation with spatial location. Along the measurement path from 0 meters to approximately 4.8 meters, the signal strength is relatively stable, reaching approximately... decibels to The signal strength fluctuates smoothly within a range of decibels, indicating that the current in the cable remains essentially constant and the resulting magnetic field strength is stable before the point of leakage fault. The critical abrupt change occurs at approximately 5 meters along the path, where the signal strength drops sharply over a very short distance, from approximately... The decibel level quickly dropped to approximately [number] decibels. Decibels. This abrupt drop, a "cliff-like" plunge, precisely corresponds to the physical location where the current in the cable suddenly decreases due to leakage into the ground at the leakage point. Along the path 5 meters further, the signal strength stabilizes at a new, lower value (approximately...). decibels to (decibels), indicating that after current leakage occurs, the residual current value decreases significantly and remains stable. Therefore, Figure 7Visualized experimental data directly illustrates the core principle of the above method: acquiring signal strength sequences through non-contact measurement and identifying abrupt changes to determine the fault location. The significant signal strength abrupt change at 5 meters in the figure is the "abrupt change point location" that the algorithm can automatically and accurately identify through "gradient analysis processing," thus precisely locating the fault point 5 meters from the measurement starting point. This figure strongly supports the technical effectiveness of this method in achieving meter-level precision positioning.

[0099] Gradient analysis is performed on the signal intensity sequence to generate a gradient sequence of the rate of change of signal intensity.

[0100] The gradient sequence refers to the first-order difference sequence of the signal strength sequence, which is used to quantify the rate at which the signal strength changes with unit distance.

[0101] Specifically, the system performs point-by-point difference calculations on the signal strength sequence using the arithmetic logic unit in the microprocessor: gradient value ,in For the first Signal strength values ​​at each location, For sequence indexes; gradient values ​​are in decibels per microvolt per meter. For example, for signal strength sequences... Perform gradient calculation to obtain the gradient sequence. (Unit: decibels microvolts per meter).

[0102] Based on the continuously changing gradient values ​​in the gradient sequence, identify the locations of abrupt changes in signal intensity.

[0103] The mutation point location refers to the path location index corresponding to the continuous gradient values ​​in the gradient sequence that meet the preset mutation conditions. The mutation conditions include gradient values ​​that are continuously lower than the negative threshold and have significant changes.

[0104] Specifically, the system presets a mutation detection threshold as follows: The algorithm uses a sliding traversal of the gradient sequence, with a consecutive point count condition of 3. When three consecutive gradient values ​​are detected to be lower than 1000 microvolts per meter, the algorithm will stop the flow of gradients. When the density is 1 dB / µV per meter, the starting position index of the segment is recorded as a candidate location for abrupt change. For example, gradient sequences. In the middle, from the 4th gradient value Three consecutive values All below The system determined that the fourth location was a mutation point, which was 5 meters away on the path.

[0105] The location of the mutation point is mapped to the corresponding geographical location of the non-contact sensor in the spatial movement path to determine the location of the low-voltage cable leakage fault.

[0106] Mapping refers to the process of converting sequence indexes into actual physical coordinates through path calibration relationships, which are established based on the sensor's starting point position, direction of movement, and sampling interval.

[0107] Specifically, the system records the sensor's movement distance in real time using a built-in displacement sensor (such as an encoder wheel) or an external positioning device (such as a UWB ultra-wideband module). Using the starting point of movement as the coordinate origin (0 meters), it marks the position coordinates along the path at fixed intervals (e.g., 0.1 meters). When a sudden change point index is identified, the system directly queries the pre-stored coordinate value corresponding to that index. For example, if the sudden change point index is 4, the sampling interval is 0.1 meters, and the starting point coordinate is 0 meters, then the fault location... Meters; combined with the path direction (e.g., horizontally eastward along the wall), the geographical coordinates of the fault point can be recorded as "0.4 meters from the starting point, eastward". Among them, UWB ( The module is used to transmit and receive extremely narrow pulse signals with nanosecond-level width, enabling real-time distance measurement and position calculation with centimeter-level accuracy.

[0108] Therefore, according to the above implementation method, the system can achieve meter-level accurate location of leakage fault points by quantifying the rate of change of signal strength and associating it with spatial location.

[0109] In some embodiments, the field adaptive calibration mechanism includes:

[0110] The adjusted frequency is used as the initial frequency for injection, and the corresponding first signal strength is obtained.

[0111] The adjusted frequency refers to the frequency value obtained after environmental interference correction and frequency band constraint verification; the first signal strength refers to the electrical signal amplitude measured and converted by a non-contact sensor when the initial frequency is injected, and the unit is decibel microvolt.

[0112] Specifically, the system injects a sinusoidal current signal at an initial frequency into the faulty cable through a signal generator, while simultaneously using a composite magnetic core sensor to collect the magnetic field signal. After processing by a conditioning circuit, the signal's spectral magnitude at the target frequency is calculated by a microprocessor (such as an STM32F407) and used as the first signal strength. For example, with an adjusted frequency of 5.4 kHz, the first signal strength measured after injection is 65 dB / µV.

[0113] The injection frequency is adjusted by a preset step size, and the second and third signal intensities corresponding to frequencies higher and lower than the initial frequency are obtained respectively.

[0114] The preset step size refers to a fixed interval value for frequency adjustment, used to scan near the initial frequency; the second signal strength and the third signal strength correspond to the signal amplitude measured at injection points that are higher and lower than the initial frequency, respectively.

[0115] Specifically, the system uses a direct digital frequency synthesis (DDS) module to generate signals with an initial frequency increased by 200 Hz and decreased by 200 Hz respectively, with a preset step size (e.g., 200 Hz), and injects them, simultaneously measuring and recording the corresponding signal strength values. For example, with an initial frequency of 5.4 kHz, injecting signals at 5.6 kHz and 5.2 kHz respectively, the measured second signal strength is 68 dB / µV, and the third signal strength is 63 dB / µV.

[0116] The maximum value is selected from the first, second, and third signal strengths, and the frequency corresponding to the maximum value is determined as the candidate frequency.

[0117] Among them, the candidate frequency refers to the frequency point with the strongest signal strength in the current scanning cycle, which serves as the benchmark for further optimization.

[0118] Specifically, the system compares the signal strength values ​​corresponding to three frequency points and uses a maximum value selection algorithm (such as simple comparison sorting) to mark the frequency corresponding to the maximum signal strength as a candidate frequency. For example, if the first signal strength is 65 dB / µV, the second signal strength is 68 dB / µV, and the third signal strength is 63 dB / µV, the maximum value of 68 dB / µV corresponds to a frequency of 5.6 kHz, so the candidate frequency is determined to be 5.6 kHz.

[0119] Using the candidate frequency as the center, repeat the above steps with a fine step size smaller than the preset step size until the increase in signal strength is lower than the preset threshold, and then determine the finally stable frequency as the target operating frequency.

[0120] Among them, the fine step size refers to the frequency adjustment interval that is smaller than the preset step size, which is used for local fine optimization; the preset threshold is the threshold value of the signal strength change, and optimization stops when the improvement is lower than this value.

[0121] Specifically, the system uses a candidate frequency as the new initial value, reduces the step size to 100 Hz, and repeats the injection-measurement-comparison process. After each iteration, it calculates the difference between the new signal strength and the previous signal strength. If the difference is less than a preset threshold (e.g., 0.5 dB / µV), the calibration terminates, and the current frequency is output as the target operating frequency. For example, using a candidate frequency of 5.6 kHz as the center, the system scans at 5.5 kHz, 5.6 kHz, and 5.7 kHz, obtaining signal strengths of 67 dB / µV, 68 dB / µV, and 69 dB / µV, respectively. The system selects 5.7 kHz, corresponding to 69 dB / µV, as the new candidate and continues scanning with a step size of 100 Hz. The measured signal strength at 5.7 kHz is 69.2 dB / µV, an increase of 0.2 dB / µV, which is below the threshold of 0.5 dB / µV. The calibration stops, and the target operating frequency is determined to be 5.7 kHz.

[0122] Therefore, according to the above implementation method, the system can dynamically adapt to changes in the field environment, eliminate model errors, and ensure that the injection frequency is always in the optimal state for signal transmission through the closed-loop scanning optimization mechanism.

[0123] In some embodiments, when injecting a target current signal into the faulty cable, the method further includes:

[0124] Detect the grounding resistance of the injection circuit.

[0125] Grounding resistance refers to the resistance value between the faulty cable and the earth, and its magnitude directly affects the current amplitude of the injected signal; the purpose of detecting grounding resistance is to provide feedback parameters for subsequent gain adjustment.

[0126] Specifically, the system connects a high-precision sampling resistor (1 ohm, 0.1% accuracy) in series in the output circuit of the power amplifier, and uses the built-in ADC (analog-to-digital converter) of a microcontroller (such as an STM32F103) to acquire the voltage across the sampling resistor at a sampling rate of 1 megahertz per second; according to Ohm's law ( The real-time output current value is calculated; then, combined with the preset voltage amplitude of the injected signal, the value is determined using the formula " "Indirectly calculate the grounding resistance. For example, when the injected voltage is 12 volts and the measured output current is 10 mA, the calculated grounding resistance is 1200 ohms; if the output current becomes 100 mA, the grounding resistance is 120 ohms."

[0127] Based on the grounding resistance, the output amplitude of the target current signal is dynamically adjusted through an automatic gain control loop to keep the signal strength within a preset range.

[0128] Among them, automatic gain control loop refers to a closed-loop feedback system that dynamically adjusts amplifier gain by comparing the deviation between measured value and target value in real time to stabilize the output signal amplitude; preset range refers to the current amplitude range set to ensure the reliability of signal detection, such as 50 mA to 150 mA.

[0129] Specifically, the system executes a PI (proportional-integral) regulation algorithm through a microcontroller: using the target current value (e.g., 100 mA) as the setpoint and the real-time measured output current as the feedback value, the deviation e is calculated as: target value - measured value; according to the formula " "(in This is the proportionality coefficient, taken as 0.5; The integral coefficient (taken as 0.1) is used to calculate the gain control voltage; this voltage is then output to a variable gain amplifier (such as AD8361, a variable gain amplifier integrated circuit manufactured by Analog Devices, featuring wide bandwidth and linear decibel control) via a DAC (Digital-to-Analog Converter) to adjust its gain value (adjustment range). decibels to (decibels), thereby changing the amplitude of the output current.

[0130] For example, when the grounding resistance suddenly increases from 100 ohms to 5000 ohms, the output current drops from 100 mA to 10 mA; the system detects the deviation. The gain adjustment is calculated using a PI algorithm, and the gain is increased to its maximum value within 100 milliseconds, so that the output current is restored to 95 mA, close to the target value.

[0131] Therefore, according to the above implementation method, the system can ensure that the injected signal maintains a stable strength under different grounding conditions by monitoring the changes in grounding resistance in real time and automatically compensating for the gain, thereby improving the reliability and adaptability of leakage current location.

[0132] Figure 8 This is a structural block diagram of a low-voltage cable leakage fault location system according to an embodiment of the present invention.

[0133] like Figure 8 As shown, the system for locating the leakage fault point of the low-voltage cable includes:

[0134] The fault line section location module 210 is used to obtain information about the fault line section where leakage occurred when a trigger signal for a leakage fault is received.

[0135] The target current signal injection module 220 is used to inject a target current signal into the faulty cable corresponding to the faulty line section information. The target operating frequency of the target current signal is determined based on the cable distribution parameters and environmental interference parameters through a quantitative calculation model and a dynamic frequency adaptive adjustment mechanism.

[0136] The non-contact signal acquisition module 230 is used to acquire the magnetic field signal along the path of the faulty cable using a non-contact sensor after injecting the target current signal into the faulty cable, and convert the magnetic field signal into an electrical signal.

[0137] The leakage fault location module 240 is used to determine the location of the leakage fault point in the low-voltage cable based on the signal strength change point of the electrical signal.

[0138] The specific functions and examples of each module and submodule of the device in this embodiment of the invention can be found in the relevant descriptions of the corresponding steps in the above method embodiments, and will not be repeated here.

[0139] According to embodiments of the present invention, the above-described method of the present invention can be applied to an electronic device and a readable storage medium.

[0140] Figure 9 A schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0141] like Figure 9 As shown, the electronic device 600 includes a computing unit 601, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 603. The RAM 603 may also store various programs and data required for the operation of the electronic device 600. The computing unit 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0142] Multiple components in electronic device 600 are connected to I / O interface 605, including: input unit 606, such as keyboard, mouse, etc.; output unit 607, such as various types of displays, speakers, etc.; storage unit 608, such as disk, optical disk, etc.; and communication unit 609, such as network card, modem, wireless transceiver, etc. Communication unit 609 allows electronic device 600 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0143] The computing unit 601 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as a method for locating a low-voltage cable leakage fault. For example, in some embodiments, a method for locating a low-voltage cable leakage fault can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by the computing unit 601, one or more steps of the method for locating a low-voltage cable leakage fault described above can be performed. Alternatively, in other embodiments, the computing unit 601 may be configured by any other suitable means (e.g., by means of firmware) to perform a method for locating a low-voltage cable leakage fault.

[0144] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0145] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0146] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0147] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0148] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0149] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0150] It should be understood that the various forms of processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this invention can be achieved, and this is not limited herein.

[0151] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for locating leakage faults in low-voltage cables, characterized in that, include: In response to the trigger signal of a leakage fault, information on the faulty line section where leakage occurred is obtained; A target current signal is injected into the faulty cable corresponding to the faulty line section information. The target operating frequency of the target current signal is determined based on the cable distribution parameters and environmental interference parameters through a quantitative calculation model and a dynamic frequency adaptive adjustment mechanism. After injecting the target current signal into the faulty cable, a non-contact sensor is used to collect the magnetic field signal along the path of the faulty cable, and the magnetic field signal is converted into an electrical signal. The location of the low-voltage cable leakage fault is determined based on the signal strength abrupt change point of the electrical signal.

2. The method according to claim 1, characterized in that, The trigger signal is generated by the residual current monitoring platform when the residual current monitoring platform detects that the residual current value exceeds a preset threshold. The step of obtaining information about the faulty line section where leakage occurred includes: The system obtains the operating status information of the multi-stage residual current protection device, performs operating timing analysis on the operating status information, and outputs the information of the faulty line section where leakage occurred. Alternatively, a clamp meter can be used to measure the current in each distribution branch of the low-voltage cable, and distribution anomaly analysis can be performed based on the measured current values ​​to output the faulty line section information.

3. The method according to claim 1, characterized in that, Before injecting the target current signal into the faulty cable corresponding to the faulty line segment information, the method further includes: Obtain the cable distribution parameters and environmental interference parameters of the faulty cable in the field environment; Based on the cable distribution parameters and the environmental interference parameters, the theoretical target operating frequency is calculated using a quantitative calculation model. Environmental interference correction and frequency band constraint verification are performed on the theoretical target operating frequency to obtain the adjusted frequency. Based on the adjusted frequency, the target operating frequency of the target current signal is determined through a preset on-site adaptive calibration mechanism.

4. The method according to claim 1, characterized in that, The method of acquiring magnetic field signals along the path of the faulty cable using a non-contact sensor and converting the magnetic field signals into electrical signals includes: The magnetic field signal is sensed and an induced potential is output by a composite magnetic core structure. The composite magnetic core structure is made of materials with different magnetic permeability characteristics to achieve wideband magnetic field sensing. The induced potential is filtered to suppress out-of-band interference; Gain adjustment is performed on the filtered signal to make the signal amplitude match the input range of the analog-to-digital converter; The signal with gain adjustment is subjected to analog-to-digital conversion to obtain a digital electrical signal.

5. The method according to claim 1, characterized in that, The step of determining the location of the low-voltage cable leakage fault point based on the signal strength abrupt change point of the electrical signal includes: Perform signal strength calculation processing on the electrical signal to obtain the signal strength sequence distributed along the path of the faulty cable; Gradient analysis is performed on the signal intensity sequence to generate a gradient sequence of the rate of change of signal intensity; Based on the continuously changing gradient values ​​in the gradient sequence, identify the locations of abrupt change points where the signal intensity changes abruptly; The location of the mutation point is mapped to the corresponding geographical location of the non-contact sensor in the spatial movement path to determine the location of the low-voltage cable leakage fault point.

6. The method according to claim 3, characterized in that, The on-site adaptive calibration mechanism includes: The adjusted frequency is used as the initial frequency for injection, and the corresponding first signal strength is obtained. The injection frequency is adjusted by a preset step size, and the second signal strength and third signal strength corresponding to frequencies higher than and lower than the initial frequency are obtained respectively. The maximum value is selected from the first, second, and third signal strengths, and the frequency corresponding to the maximum value is determined as the candidate frequency. Centered on the candidate frequency, repeat the above steps with a fine step size smaller than the preset step size until the increase in signal strength is lower than the preset threshold, and then determine the finally stable frequency as the target operating frequency.

7. The method according to claim 1, characterized in that, When injecting a target current signal into the faulty cable, the method further includes: Detect the grounding resistance of the injection circuit; Based on the grounding resistance, the output amplitude of the target current signal is dynamically adjusted by an automatic gain control loop to keep the signal strength within a preset range.

8. A system for locating leakage faults in low-voltage cables, characterized in that, include: The fault line section location module is used to obtain information about the fault line section where leakage occurred when a trigger signal for a leakage fault is received. The target current signal injection module is used to inject a target current signal into the faulty cable corresponding to the faulty line section information. The target operating frequency of the target current signal is determined based on the cable distribution parameters and environmental interference parameters through a quantitative calculation model and a dynamic frequency adaptive adjustment mechanism. A non-contact signal acquisition module is used to acquire magnetic field signals along the path of the faulty cable using a non-contact sensor after injecting a target current signal into the faulty cable, and convert the magnetic field signals into electrical signals. The leakage fault location module is used to determine the location of the low-voltage cable leakage fault point based on the signal strength change point of the electrical signal.

9. An electronic device, characterized in that, include: At least one processor; and a memory that is communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, in, Computer instructions are used to cause a computer to perform the method according to any one of claims 1-7.

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