Link bar current and voltage measuring system based on wireless transmission

Abstract

The invention relates to the technical field of electrical measurement and wireless communication, in particular to an insulating rod current and voltage measurement system based on wireless transmission, and aims to solve the problems of low efficiency, limited range and high safety risk of existing single-phase grounding fault troubleshooting. The system comprises a portable measurement and acquisition subsystem and a handheld terminal analysis subsystem; the measurement and acquisition subsystem integrates high-precision synchronous sensing, electromechanical driving and wireless communication and can synchronously acquire current and voltage in a non-intrusive manner; and a multi-feature fusion and space-time association algorithm is embedded in the terminal analysis subsystem and is used for fault diagnosis and accurate positioning. The system can accurately measure and analyze the current and the voltage of the distribution line under the non-power-off and non-intrusive conditions, can quickly and accurately position the single-phase earth fault, remarkably shortens the troubleshooting time, and reduces the economic loss and the safety risk.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of electrical measurement and wireless communication, and in particular, relates to a Ling rod current and voltage measurement system based on wireless transmission. BACKGROUND

[0002] The stable operation of the power grid system is the core guarantee for modern social industrial production and resident life, and among them, the power distribution network as a key link directly facing the end user, its power supply reliability is of vital significance. In the operation process of the power distribution network, various types of electrical faults are difficult to completely avoid, according to relevant industry statistics, single-phase grounding fault accounts for the vast majority of the total number of power distribution network faults, and usually accounts for about 80%. Unlike other serious fault types, when a single-phase grounding fault occurs, the system line voltage can still maintain basic symmetry in most cases, and does not constitute an immediate and interrupted impact on the normal power consumption of the user side. Based on this characteristic, the relevant operation regulations allow the line carrying the single-phase grounding fault to continue to operate with faults within a certain time limit (for example, 1 to 2 hours), which to some extent avoids large-scale power outages caused by instantaneous tripping, thereby improving the overall reliability of power supply.

[0003] However, the fault operation is essentially a makeshift, and it hides significant safety hazards and equipment risks behind it. In a small current grounding system, single-phase grounding will cause the voltage of the non-fault phase to ground to suddenly rise to 1.73 times the normal phase voltage, i.e. the level of the line rated line voltage. If there is an intermittent arc at the fault point, it may cause more complex resonant overvoltage, whose peak value can far exceed the limit that the device insulation can withstand, posing a serious threat to the relatively weak insulation performance of the power grid, and is extremely easy to induce insulation breakdown. More critically, if the single-phase grounding fault is not handled and isolated in time, its existence itself will destroy the insulation balance of the entire system, significantly increasing the possibility of the fault evolving into a more serious two-phase or multi-phase short circuit, and further leading to catastrophic equipment damage and large-scale power outage accidents. Therefore, although the regulations allow short-time fault operation, quickly and accurately locating and eliminating the single-phase grounding fault point is always the core task and technical challenge of power grid operation and inspection work.

[0004] To address this challenge, those skilled in the art have developed and implemented various fault troubleshooting and location methods. In practice, a more traditional approach is the "two-way splitting method." This method, based on logical inference, isolates the faulty line by operating the line's sectionalizers, one by one, splitting the faulty line in two. The fault's location is determined by whether the fault disappears after isolation. While this method is straightforward, its efficiency is significantly reduced when the number of sectionalizers is limited or when the fault occurs behind a branch fuse without a switch. Each operation also results in a short power outage for downstream users. Failure of the switch mechanism itself can even cause a prolonged outage, defeating the purpose of improving power supply reliability. To address the shortcomings of these operational methods, the industry has also deployed automated monitoring systems such as "low-current grounding line selection devices." These devices are typically installed at the outgoing line of a substation. At the initial stage of a fault, they automatically identify the specific line experiencing the fault by analyzing characteristic quantities such as the zero-sequence current of each outgoing line circuit. However, their functionality is limited to "line selection"—determining which feeder the fault belongs to—and cannot "select" the specific section of the line to locate the fault. Furthermore, due to complex factors such as unbalanced system currents and changes in transition resistance, such devices still have a certain probability of misselection and omission in practical applications. To further improve positioning accuracy, the deployment of "fault indicators" along the line has become a technological evolution. By distributing multiple fault indicators on line towers, when a fault current flows through them, the indicators flip or emit a light signal, thereby localizing the fault range between two adjacent indicators.

[0005] However, with the expansion of power grids and increasingly stringent requirements for fault handling efficiency, the aforementioned technical solutions have gradually exposed their inherent and systemic limitations in practice. These limitations do not exist in isolation, but rather collectively point to a deeper technical contradiction: the difficulty in achieving an effective balance between diagnostic accuracy, efficiency, operational impact, and economic cost. Specifically, the "two-way pull-through method" sacrifices the normal operation of the line, and its diagnostic process itself interferes with power supply reliability. While "low-current grounding line selection devices" and "fault indicators" avoid power outages, their diagnostic capabilities inherently rely on a static, pre-deployed monitoring architecture. For grounding line selection devices, their monitoring points are fixed at the line start, resulting in limited information dimensionality and inability to meet the precise positioning requirements for wide-area, long-distance lines. For fault indicators, there is an inherent and irreconcilable contradiction between diagnostic accuracy and investment cost. High-precision positioning requires high-density deployment. This, for distribution lines stretching tens or even hundreds of kilometers, implies enormous equipment investment and ongoing maintenance costs, making them economically unaffordable. Conversely, if sparse deployment is adopted to control costs, the fault zone that the indicator can locate is still too large, requiring extensive manual inspections, especially during inclement weather such as thunderstorms. This work is not only inefficient but also carries significant risks to personnel safety. The root cause lies in the lack of a dynamic diagnostic tool that combines flexibility, accuracy, and cost-effectiveness—a means of accurately collecting and analyzing electrical signatures on demand and in real time at any location on the line, without power outages or restrictions on the layout of pre-set monitoring points. This lack of capability forces maintenance personnel to face a difficult trade-off between power outages, rough location, and high investment when dealing with single-phase grounding faults. This often results in troubleshooting time stretching for hours, far exceeding the safe operating window permitted by regulations.

[0006] Therefore, how to develop a method that can perform real-time and accurate measurement of key electrical parameters such as current and voltage at any location on the distribution line in a mobile and flexible manner without interrupting power supply, thereby breaking the inherent bottlenecks of existing fault location technology in terms of accuracy, efficiency, cost and safety, has become a key challenge and technical problem that technicians in this field are currently facing and need to solve urgently. Summary of the Invention

[0007] The purpose of the present invention is to overcome the technical contradictions existing in the prior art in that it is difficult to effectively balance the diagnostic accuracy, diagnostic efficiency, operational impact and economic cost. Specifically, it aims to solve the problems of low positioning efficiency, limited diagnostic range and high safety risks caused by the existing single-phase grounding fault troubleshooting methods due to reliance on power outage operations, fixed monitoring points or high-cost deployment. In order to achieve the above-mentioned purpose of the invention, the present invention provides a linker rod current and voltage measurement system based on wireless transmission. The system constructs a set of portable electrical status diagnostic equipment that integrates high-precision synchronous sensing, electromechanical automatic drive, real-time data processing and wireless communication functions, and is combined with a set of fault diagnosis methods based on multi-feature fusion and spatiotemporal correlation analysis deployed on a handheld terminal. Therefore, it is possible to accurately collect and intelligently analyze key electrical parameters such as current and voltage at any position of the distribution line on demand and in real time without interrupting the line power supply and without being restricted by the preset monitoring point layout, thereby realizing rapid and accurate positioning of single-phase grounding faults.

[0008] To achieve the aforementioned objectives, the technical solution employed by the present invention specifically includes a measurement and acquisition subsystem and a terminal and analysis subsystem. The measurement and acquisition subsystem is designed as a portable, maneuverable pole-like structure, whose core function is to physically contact or near-field couple with high-voltage overhead conductors and synchronously acquire current and voltage information from the conductors in a non-invasive manner. The terminal and analysis subsystem is designed as a handheld smart device, whose core function is to receive real-time electrical data wirelessly transmitted by the measurement and acquisition subsystem, execute a set of preset fault diagnosis algorithms, and ultimately provide operators with clear fault location guidance.

[0009] Specifically, the measurement and acquisition subsystem consists of a multi-modal synchronous sensing module, an electromechanical drive and locking module, a data processing and communication module, an integrated power management module and a modular high-voltage insulating operating rod body.

[0010] The multimodal synchronous sensing module is located at the forefront of the measurement and acquisition subsystem and integrates a current sensing unit and a voltage sensing unit. The current sensing unit utilizes a high-precision, open-and-close Rogowski coil with an air core structure, designed to resemble a jaw that can be opened and closed by the electromechanical drive and locking module. This Rogowski coil is connected to the analog-to-digital conversion channel of the data processing and communication module via a dedicated hardware integrator circuit. This hardware integrator integrates the induced voltage signal output by the Rogowski coil to restore a voltage signal proportional to the measured conductor current. This design ensures high linearity and high-precision measurement over a wide frequency range, particularly for fault currents containing high-frequency transient components. The voltage sensing unit utilizes a non-contact voltage sensor array based on the electric field coupling principle. This array consists of multiple concentric rings of metal sensing electrodes integrated into the inner surface of the jaw structure. The outermost sensing electrode serves as a shielding electrode and is grounded to eliminate interference from external stray electric fields. The inner sensing electrodes serve as signal pickup electrodes and are connected to another analog-to-digital conversion channel of the data processing and communication module via an ultra-high-impedance preamplifier with an input impedance greater than 10 gigahertz. This sensor array indirectly measures the conductor's voltage relative to ground by measuring the displacement current generated by the coupling capacitance formed between the sensing electrodes and the conductor being measured. Crucially, the multimodal synchronous sensing module incorporates a shared high-frequency clock source driven by a temperature-compensated crystal oscillator (TCXO). This clock source provides synchronized sampling clock signals for the analog-to-digital converters of the current and voltage sensing units and adds microsecond-accurate timestamps to all collected data. This synchronized sampling mechanism is fundamental to implementing subsequent advanced diagnostic algorithms, particularly spatiotemporal correlation analysis based on traveling wave theory, ensuring absolute time-base consistency of the collected current and voltage waveform data.

[0011] The electromechanical drive and locking module is used to drive the jaw structure of the multi-modal synchronous sensing module to open, close and lock. The core of this module is a brushless DC motor, which is connected to a worm gear transmission mechanism through a multi-stage planetary gear reducer. The output worm of the worm gear transmission mechanism directly drives the opening and closing connecting rod of the jaws. The use of the worm gear transmission mechanism and its self-locking characteristics ensure that after the jaws are closed and clamped to the measured wire, they can still maintain a stable clamping force even when the motor is powered off, without the need for continuous energy consumption. The brushless DC motor is equipped with a Hall effect position sensor for feeding back the motor's speed and angle information to the data processing and communication module, thereby achieving precise control of the jaw opening and closing angle. In addition, a current monitoring loop based on a sampling resistor is integrated in the drive circuit of the motor, which monitors the load current of the motor in real time. When the jaws are fully closed and the clamping force reaches a preset threshold, the load current will rise sharply. After the data processing and communication module detects this sudden change in current, it immediately stops the motor drive, thereby achieving torque limitation and preventing damage to the measured wire or sensor body due to excessive clamping force.

[0012] The data processing and communication module serves as the control and information hub for the measurement and acquisition subsystem. Its core processor utilizes a dual-core heterogeneous microcontroller unit (MCU), for example, comprising a high-performance core (such as an ARM Cortex-M7) and a low-power core (such as an ARM Cortex-M4). The high-performance core runs a real-time operating system (RTOS) dedicated to executing high-precision, synchronized data acquisition tasks, digital filtering algorithms, and a high-bandwidth data transmission protocol stack with the terminal and analysis subsystems. The low-power core manages the motion control logic, power management status monitoring, and low-power standby and wake-up functions of the electromechanical drive and locking module. The module integrates a hybrid wireless communication unit, comprising a Bluetooth Low Energy (BLE) transceiver and a Wi-Fi transceiver supporting peer-to-peer (P2P) mode. During system initialization, the measurement and acquisition subsystem establishes a connection with the terminal and analysis subsystem via BLE for authentication, status exchange, and command handshaking. This process consumes minimal power. Once the operator issues the measurement start command via the terminal, the system immediately switches to Wi-Fi P2P mode, establishing a high-bandwidth direct data link. This allows for the real-time, uninterrupted transmission of synchronized and time-stamped raw current and voltage waveform data at a high sampling rate (e.g., 25.6 kilosamples per second) to the terminal and analysis subsystem in the form of a data stream. The data transmission protocol is defined as a customized data frame structure. Each frame includes a frame header, device ID, a high-precision synchronized timestamp, a three-phase current waveform data block, a three-phase voltage waveform data block, a device status word (including battery level, GPS location information, and sensor operating temperature), and a CRC checksum.

[0013] The integrated power management module provides stable and reliable power for the entire measurement and acquisition subsystem. This module houses a high-energy-density lithium iron phosphate (LiFePO4) battery pack, chosen for its excellent thermal stability and long cycle life. The battery pack is equipped with a dedicated battery management system (BMS), which monitors the voltage and temperature of each cell string in real time and performs functions such as charge balancing, overcharge protection, over-discharge protection, overcurrent protection, and short-circuit protection. The BMS transmits its monitored status data to the data processing and communication module via an internal communication bus (such as I2C or SMBus), enabling the terminal device to display the precise remaining power at the measurement end in real time. The charging port uses a magnetic waterproof connector, ensuring safe and convenient charging in harsh outdoor environments.

[0014] The modular high-voltage insulating operating rod body is a physical structure that carries all the above-mentioned functional modules and ensures the safety of operators. The rod body is composed of multiple insulating pipe sections that can be plugged and locked into each other and made of epoxy glass fiber cloth or epoxy resin material. The surface of each insulating pipe section is integrally formed with multiple axially distributed umbrella skirt structures, namely rainproof insulator structures. The purpose of this design is to significantly increase the creepage distance of the pole surface. In humid or rainy and snowy weather conditions, it can effectively prevent the continuous water film formed along the pole surface, thereby preventing surface flashover and ensuring insulation safety under all-weather conditions. Its design standards comply with IEC 60855 or equivalent level insulation tool safety specifications.

[0015] In conjunction with the aforementioned measurement and acquisition subsystem, the terminal and analysis subsystem is typically implemented as a ruggedized industrial-grade tablet or smartphone. This device runs a dedicated application (APP), which forms another core component of the present invention. This application's functionality extends beyond data display, embedding a comprehensive set of multi-feature fusion and spatiotemporal correlation diagnostic algorithms.

[0016] The execution flow of the diagnostic algorithm is as follows: First, during the data reception and preprocessing phase, the application receives synchronized waveform data streams from the measurement and acquisition subsystem in real time via a Wi-Fi P2P link. The application verifies the integrity and correctness of the data frames. It then uses the high-precision timestamps embedded in the frames to align and buffer small packet delays that may be caused by wireless channel jitter, ensuring that the data streams used for subsequent analysis are fully synchronized and continuous in time. A digital finite impulse response (FIR) filter is then applied to the raw waveform data to remove high-frequency noise introduced by the sensor or the environment.

[0017] Secondly, in the multi-dimensional feature extraction stage, the algorithm performs parallel calculations on the preprocessed waveform data to extract electrical feature quantities in multiple dimensions.

[0018] The first dimension is the fundamental frequency steady-state characteristic quantity. The algorithm uses discrete Fourier transform (DFT) or the more efficient Goertzel algorithm to accurately calculate the fundamental frequency (50Hz or 60Hz) effective value (RMS) and phase angle of current and voltage. Based on the three-phase measurement data (obtained through three independent single-phase measurements or through three parallel measurement systems), the algorithm further synthesizes and calculates the zero-sequence current. and zero sequence voltage In a low-current grounding system, the magnitude of the zero-sequence current is the most direct basis for determining whether the fault point is upstream or downstream of the measurement point.

[0019] The second dimension is harmonic and transient characteristics. The algorithm performs a Fast Fourier Transform (FFT) on the waveform data to obtain a complete harmonic spectrum, paying particular attention to the content of odd-order harmonic components such as the 3rd, 5th, and 7th harmonics. For high-impedance grounding or intermittent arc-grounding faults, the current waveform is often severely distorted, producing specific harmonic characteristics. The algorithm also applies a wavelet transform to perform time-frequency analysis on the waveform. The wavelet transform effectively captures and characterizes singular points in the current waveform, which are extremely short-duration transient traveling wave signals generated by arc reignition or extinction. The algorithm extracts transient characteristic parameters such as the amplitude, steepness (rise time), and time of occurrence of the traveling wave.

[0020] The third dimension is the correlation feature. When an operator performs measurements at two different geographic locations (for example, points A and B), the algorithm stores the feature vectors extracted from both measurements. Specifically for transient traveling wave signals, the algorithm calculates the difference (Δt) in the timestamps of the same transient event captured in the two measurements.

[0021] Finally, in the intelligent diagnosis and location decision stage, the algorithm inputs the extracted multi-dimensional features into a rule- and model-based decision engine to perform fault location.

[0022] The decision engine first applies a set of rules based on expert knowledge. For example, Rule 1: For high-current grounding systems, the line is selected when the current in the fault phase of the grounding line (the collected voltage is 0 phase) increases; the line and section are selected when the current in the fault phase increases before the fault point and the current after the fault point is normal. Rule 2: For systems with an ungrounded neutral point, the zero-sequence current of the non-fault line decreases as it moves away from the busbar. The zero-sequence current of the fault line first increases, suddenly jumps, and then gradually decreases, and the line and section are selected. Rule 3: For systems grounded by arc suppression coils, the transient mode is enabled and traveling wave ranging is performed. Rule 4: If a signal with typical arc grounding characteristics (such as high-frequency transients and specific harmonic components) is detected, the confidence level of the fault judgment is enhanced.

[0023] For complex fault conditions with insignificant features, or to achieve more accurate section positioning, the decision engine will start the spatiotemporal correlation analysis model. When the operator completes the measurement at two points A and B with a known distance L between them according to the instructions of the application, the algorithm uses the difference Δt between the arrival timestamps of the transient traveling waves recorded in the two measurements, combined with the propagation speed v of electromagnetic waves on the transmission line (usually about 80%-95% of the speed of light, which can be preset), to calculate the distance from the fault point to one of the measurement points. For example, if the traveling wave is detected at point A before point B, the fault point is located downstream of point B, and its distance d from point B can be calculated by the formula This principle, based on traveling wave ranging, improves positioning accuracy from the "segment" level to the "meter" level.

[0024] The working method of the present invention, i.e., the method for locating a single-phase ground fault based on the system, comprises the following specific steps: The first step is system initialization. Operators assemble a modular high-voltage insulated operating pole of appropriate length based on the voltage level of the line to be measured and the tower height. The measurement and acquisition subsystem and the terminal and analysis subsystem are powered on. The two automatically pair via Bluetooth Low Energy. The terminal application interface indicates that the measurement system is ready and provides status information such as battery charge and GPS signal strength.

[0025] The second step involves line identification and preliminary measurement. If no fault indication is available on-site, the operator first measures each phase conductor sequentially at the substation outlet or at the beginning of the main line. The electromechanical drive and locking module opens the sensor jaws, hooks them onto the conductor, and then actuates them to close. The system automatically switches to Wi-Fi P2P high-bandwidth mode, transmitting waveform data in real time. The terminal application's diagnostic algorithm calculates the zero-sequence current to quickly identify the faulty feeder.

[0026] The third step is bisection segment location. After locating the faulty line, the operator drives to a point approximately halfway along the line, selects a suitable tower location, and repeats the measurement process. The terminal application's diagnostic algorithm, based on the rules in its rule base, instantly provides clear graphical and textual indications of whether the fault is in the first half of the segment or the second half of the segment. This process does not require the coordination of line section switches and does not cause any power outages.

[0027] The fourth step is iterative approximation and precise location. Following the instructions from the previous step, the operator continues to use the binary method to measure within the identified fault section, gradually reducing the search range by half. After several iterative measurements, the fault point can be located between two adjacent towers.

[0028] Step 5: High-precision distance measurement (optional advanced feature). Once the fault is localized to a specific section, if further precise positioning is required (for example, in difficult-to-access areas such as forested or mountainous areas), the operator can activate advanced diagnostic mode. Following the application's instructions, measurements are taken at the pole towers at the beginning and end of the section. The terminal application's diagnostic algorithm automatically switches to a spatiotemporal correlation analysis model. By analyzing the time difference of transient traveling waves, it calculates and displays the specific physical distance from the fault point to one of the measurement points, providing repair personnel with precise coordinates for their work.

[0029] Step 6: Data Archiving and Report Generation. After all measurements are complete, the application automatically generates a detailed diagnostic report containing fault line information, the locations of each measurement point (GPS coordinates), measured electrical characteristic data, waveform screenshots, location conclusions, and operation time records. This report can be directly exported or sent to the operation and maintenance management center via the network, providing first-hand data support for fault analysis and asset management.

[0030] In summary, the present invention provides a link rod current and voltage measurement system based on wireless transmission, which fundamentally solves the inherent contradictions existing in the background technology by deeply integrating high-precision synchronous sensing technology, electromechanical automation technology and intelligent diagnostic algorithms into a portable, non-invasive measurement system. The present invention enables operation and maintenance personnel to perform "surgical" precise diagnosis of the electrical status of any position in the distribution line in a mobile, flexible and efficient manner without power outages, greatly shortening the time for troubleshooting single-phase grounding faults, reducing the economic losses and safety risks caused by power outages or fault deterioration, and avoiding the high investment and maintenance costs required for large-scale deployment of fixed monitoring equipment. It has significant technological progress and important engineering application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a schematic diagram of the overall architecture of the system of the present invention; Figure 2 It is a schematic structural diagram of the measurement and acquisition subsystem of the present invention; Figure 3 Schematic diagram of the structure of the multi-modal synchronous sensing module in the present invention; Figure 4 It is a functional module block diagram of the measurement and acquisition subsystem of the present invention; Figure 5 It is a flow chart of the fault diagnosis algorithm of the present invention; Figure 6 It is a flow chart of a single-phase ground fault locating method of the present invention; Figure 7 This is a diagram showing the installation structure of the link rod of the present invention; Figure 8 This is a diagram showing the state of the link rod of the present invention being used to measure a cable; Figure 9 This is a link rod measurement circuit diagram of the present invention.

[0032] The accompanying drawings are numbered as follows: 1. Measurement and acquisition subsystem; 2. Terminal and analysis subsystem; 10. Multimodal synchronous sensing module; 11. Open-close high-precision Rogowski coil; 12. Contactless voltage sensor array; 20. Electromechanical drive and locking module; 30. Data processing and communication module; 40. Integrated power management module; 50. Modular high-voltage insulating operating rod; 51. Insulated pipe section; 52. Rainproof insulator structure. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the scope of protection of the present invention.

[0034] Reference Figure 1 The present invention discloses a link rod current and voltage measurement system based on wireless transmission, which is divided into two core subsystems in terms of overall architecture: a measurement and acquisition subsystem 1 responsible for on-site electrical quantity acquisition, and a terminal and analysis subsystem 2 responsible for human-machine interaction and intelligent analysis. These two subsystems build a real-time, closed-loop diagnostic system through wireless communication. The measurement and acquisition subsystem 1 is designed as a portable rod-shaped device that can be operated by a single person on-site. Its main task is to directly or near-field couple to the high-voltage overhead conductor and synchronously capture the current and voltage waveforms of the line in a non-invasive manner. The terminal and analysis subsystem 2 is usually materialized as an industrial-grade handheld smart device running a specific application. It receives the raw data stream wirelessly sent by the measurement and acquisition subsystem 1, and uses the embedded diagnostic algorithm to perform real-time calculations, and finally presents clear fault location conclusions and guidance to the operator.

[0035] Now turn Figure 2 and Figure 4 The internal structure of the measurement and acquisition subsystem 1 is described in detail. The measurement and acquisition subsystem 1 is a highly integrated mechatronic device, with its physical structure and functional modules meticulously designed to ensure measurement accuracy, operational safety, and equipment reliability in high-voltage environments. From top to bottom, it consists of a multimodal synchronous sensing module 10, an electromechanical drive and locking module 20, a data processing and communication module 30, an integrated power management module 40, and a modular high-voltage insulated operating lever 50, all connected in series.

[0036] Specifically, refer to Figure 3At the forefront of the entire device is the multimodal synchronous sensing module 10, which performs the critical task of converting the electrical state of the high-voltage conductor into a precise digital signal. This module structurally integrates a current sensing unit with a voltage sensing unit. The current sensing unit is embodied as a retractable, high-precision Rogowski coil 11. This Rogowski coil 11 utilizes a non-ferromagnetic air-core bobbin, precisely machined into a jaw that opens and closes via an electromechanical drive and locking module 20. In this embodiment, the coil bobbin is integrally machined from polyetheretherketone (PEEK) using a five-axis CNC machine tool, ensuring dimensional stability and insulation performance within an operating temperature range of -40°C to +85°C. The coil's effective inner diameter is 150 mm, sufficient to accommodate large-section insulated or bare conductors commonly found in power distribution networks. The coil winding utilizes high-strength, 0.1 mm diameter enameled copper wire, evenly and densely wound with a winding density of 250 turns per centimeter. The induced voltage signal output by a Rogowski coil is extremely weak and a differential of the measured current. Therefore, its output is not connected directly to an analog-to-digital converter (ADC). Instead, it is connected to a dedicated hardware integrator circuit via a precision shielded coaxial cable. The core of this integrator circuit is an ultra-low-noise, low-bias-current precision operational amplifier, such as the AD8421 from Analog Devices. This circuit accurately integrates the induced voltage, outputting a voltage signal proportional to the original current wave flowing through the measured conductor. Its calibrated transfer function is 10 millivolts per ampere of current. This design, based on a Rogowski coil and hardware integrator, fundamentally avoids the magnetic saturation problem of traditional current transformers, ensuring measurement linearity better than 0.5% across a wide frequency range of 10 Hz to 100 kHz, for both steady-state power-frequency currents and transient traveling-wave currents generated at fault moments, which contain abundant high-frequency components.

[0037] Meanwhile, integrated on the inner surface of the same jaw structure is a non-contact voltage sensor array 12 for measuring voltage. The sensor array works on the principle of electric field coupling, and its structure is composed of three concentric ring-shaped metal sensing electrodes. These electrodes are manufactured by flexible printed circuit board (FPC) technology and firmly attached to the epoxy insulating layer on the inner wall of the jaw. The outermost sensing electrode is designed as a shield electrode, which is directly connected to the digital ground of the data processing and communication module 30 through an internal lead, to absorb and shield the stray electric field interference from other phase conductors or the environment, ensuring the purity of the measurement results. The two inner sensing electrodes act as signal pickup electrodes, which form a small and stable coupling capacitor with the measured high-voltage conductor. When the conductor voltage changes, a displacement current proportional to the rate of change of voltage is generated through the coupling capacitor. This displacement current flows into a preamplifier with extremely high input impedance. In this embodiment, the preamplifier is selected as ADA4530-1 from Analog Devices, with an input impedance as high as 20 Tera-Ohms , and a bias current as low as the fA level. Such high input impedance is the key to accurately measuring weak displacement current and accurately inverting the conductor voltage. The amplifier output signal then passes through an analog integration and calibration network, and is finally converted into a voltage signal proportional to the measured conductor-to-ground voltage waveform, and sent to the analog-to-digital conversion channel.

[0038] In order to realize the time reference unification necessary for the subsequent advanced diagnostic algorithms of the application, the multi-modal synchronous sensing module 10 is internally provided with a key common clock source. The clock source is a temperature-compensated crystal oscillator (TCXO), such as the SiT5356 series product from SiTime, which can provide a high-precision clock reference with a frequency of 25.6 MHz and a stability better than ±0.5 ppm within the entire operating temperature range. The clock signal is distributed to two independent 24-bit high-precision Sigma-Delta type analog-to-digital converters (ADCs) for current and voltage signal sampling, such as the ADS131E08 from Texas Instruments. It not only serves as the conversion clock of the ADC, ensuring that the sampling actions of the current and voltage channels are completely synchronized in time, but also drives a high-precision hardware timer inside the data processing and communication module 30. Whenever a data sampling point is collected, the timer will attach an absolute time stamp to it with a precision of nanoseconds. This hardware-based synchronous sampling and time stamping mechanism ensures the absolute alignment of current and voltage waveform data in the time dimension from the source, providing a solid and reliable data foundation for subsequent complex algorithms such as phase difference calculation, traveling wave arrival time difference analysis, etc.

[0039] In order to reliably open, close and clamp the multimodal synchronous sensing module 10, the present invention further provides an electromechanical drive and locking module 20. The power source of this module is a high-performance brushless DC motor, such as Maxon's EC-4pole 22 motor, which has the advantages of fast response speed and long life while providing sufficient torque. The output shaft of the motor is connected to a multi-stage planetary gear reducer, and its reduction ratio is set to 128:1, which is used to convert the high speed and low torque of the motor into a low speed and high torque output. The output end of the reducer is then connected to a worm gear transmission mechanism through a coupling. The output worm of the worm gear transmission mechanism directly drives a sophisticated four-bar linkage, ultimately achieving the smooth opening and closing of the jaws of the Rogowski coil 11. The worm gear transmission mechanism is a key design feature. Its inherent self-locking feature ensures that once the jaws are fully closed and clamped onto the conductor under test, the worm prevents the worm gear from reversely rotating, even when the motor is completely powered off. This maintains a constant clamping force, eliminating the need to continuously consume precious battery energy to maintain the clamping state. This is crucial for extending the device's single-charge battery life. To achieve precise control of the jaw opening and closing process, the brushless DC motor integrates three Hall-effect position sensors, which provide real-time feedback of the motor rotor's precise angular position and speed to the data processing and communication module 30. The control system uses this information to calculate the jaws' real-time opening and closing angles, enabling smooth acceleration and deceleration control. Furthermore, a key safety and protection feature is the inclusion of a low-resistance precision sampling resistor in series with the motor driver circuit, along with a dedicated current sensing amplifier (such as the INA240) to monitor the motor's load current in real time. When the jaws close fully and begin applying clamping force to the conductor, the motor's load increases rapidly, causing its operating current to rise sharply. The control algorithm within the data processing and communication module 30 continuously monitors this current. Once it detects that the current exceeds a preset threshold (for example, 150% of the normal operating current), the system determines that the jaws are securely clamped and immediately cuts off the drive voltage to the motor. This closed-loop control method based on torque limitation ensures sufficient clamping force to withstand external disturbances such as wind, while effectively preventing damage to the wire insulation or the delicate structure of the sensor body due to excessive clamping force.

[0040] As the "brain" of the entire measurement and acquisition subsystem 1, the data processing and communication module 30 is responsible for all data processing, motion control, communication, and system management functions. The module's hardware core utilizes a dual-core heterogeneous microcontroller unit (MCU), specifically the STMicroelectronics STM32H755II. This MCU comprises a high-performance ARM Cortex-M7 core running at up to 480 MHz and a low-power ARM Cortex-M4 core running at 240 MHz. This heterogeneous design allows for refined task allocation: the high-performance Cortex-M7 core runs an embedded real-time operating system (RTOS), such as FreeRTOS, dedicated to handling computationally intensive tasks. These include driving the ADC for high-speed, simultaneous data acquisition at 25.6 kilosamples per second, executing digital filtering algorithms (such as finite impulse response filters) on the acquired raw data, and managing the high-bandwidth Wi-Fi data transmission protocol stack between the terminal and analysis subsystem 2. At the same time, the Cortex-M4 core with lower power consumption is responsible for handling control tasks with high real-time requirements but low computational intensity, such as executing the PID motion control logic of the electromechanical drive and locking module 20, periodically querying the status of the integrated power management module 40, and managing the low-power wake-up and sleep strategies of the entire system in standby mode.

[0041] The module 30 also integrates a hybrid wireless communication unit, consisting of a Bluetooth Low Energy (BLE 5.0) transceiver and a Wi-Fi (IEEE 802.11n) transceiver supporting point-to-point (P2P) direct connection mode. Both are managed by a dedicated communication coprocessor (such as the ESP32-WROOM-32E). This dual-mode communication strategy optimizes the balance between power consumption and performance. During system startup and standby states, the measurement and acquisition subsystem 1 establishes a connection with the terminal and analysis subsystem 2 via BLE. This phase involves only device authentication, low-rate exchange of status information (such as battery level, GPS signal quality, and device temperature), and handshaking for operational commands, all while consuming extremely low power. Once the operator issues the "start measurement" command through the terminal application, the system seamlessly and automatically switches to Wi-Fi P2P mode. A high-bandwidth, direct data link (theoretically up to 150 Mbps) is now established between the two subsystems. Through this link, the raw current and voltage waveform data, which has been synchronously sampled and time-stamped with high precision, can be transmitted to the terminal and analysis subsystem 2 in real-time, unbuffered, and uninterrupted form as a data stream. To ensure reliable and efficient data transmission, the present invention defines a customized data frame structure. Each data frame is fixed at 8192 bytes in length, and its internal fields are: a 4-byte frame start synchronization header, a 6-byte device unique MAC address, an 8-byte 64-bit high-precision synchronized timestamp (indicating the time of the first sample point in the frame), a data block containing 2048 16-bit sample points of the current of a single phase in the three-phase measurement, a data block containing 2048 16-bit sample points of the corresponding voltage, a 32-byte device status word (including the remaining battery capacity, the temperature reported by the BMS, and the latitude and longitude coordinates output by the GPS module), and a 4-byte CRC32 cyclic redundancy check code. After receiving each frame, the terminal first performs a CRC check to ensure that no errors occurred during data transmission.

[0042] Providing long-lasting and stable power to the entire high-power measurement and acquisition subsystem 1 is an integrated power management module 40. At its core is a high-energy-density lithium iron phosphate (LiFePO4) battery pack. This battery chemistry was chosen for its excellent thermal stability and safety (relatively low risk of thermal runaway), as well as its long lifespan of over 2,000 deep charge and discharge cycles, making it ideal for industrial-grade equipment requiring long-term, reliable operation. In this embodiment, the battery pack utilizes a 4-series-2-parallel (4S2P) configuration with a nominal voltage of 12.8V and a total capacity of 6,000 mAh, sufficient to support over eight hours of continuous measurement on a full charge. The battery pack is equipped with a dedicated, highly intelligent battery management system (BMS), whose core chip is the Texas Instruments BQ76920. This BMS monitors the voltage and temperature of each cell in the battery pack in real time, down to the millisecond level, through multiple sampling channels. It also actively performs charge balancing between cells to maximize the battery pack's available capacity and overall lifespan. The BMS also integrates comprehensive protection mechanisms, including overcharge protection, over-discharge protection, overcurrent protection, and short-circuit protection. The BMS transmits all monitored status data (such as total voltage, total current, remaining capacity percentage, maximum / minimum cell temperature, etc.) in real time to the low-power core of the data processing and communication module 30 via an I2C internal communication bus. This allows operators to clearly and accurately view the remaining power of the measuring device on the remote terminal application interface, allowing them to plan their work appropriately. To accommodate use in harsh outdoor environments, the module's charging port utilizes a magnetic waterproof connector, which is not only easy to plug and unplug, but also has an IP67 protection rating that ensures safe charging even in rainy weather.

[0043] The modular high-voltage insulated operating rod 50 houses all of the aforementioned precision electronic and mechanical modules and provides absolute operator safety. This rod is constructed from multiple (usually three to five) interlocking insulating tube segments 51 locked by spring pins. Operators can flexibly add or reduce the number of segments to create the desired operating length, depending on the actual tower height of the line being tested. Each insulating tube segment 51 is constructed from a specially formulated epoxy fiberglass cloth. The fiberglass cloth is impregnated with epoxy resin under constant tension, then rolled onto a core mold and heat-cured, ensuring exceptional mechanical strength and excellent insulation performance. Its design fully complies with the International Electrotechnical Commission's IEC 60855-1 standard, "Insulated Tubular Tools for Live Working," and its leakage current per 300 mm length at 100 kV is less than 100 μA. A significant innovation lies in the fact that the outer surface of each insulating tube segment 51 is integrally molded with multiple shed-like structures 52 evenly distributed along its axial direction. This rainproof insulator structure, modeled after high-voltage insulators, significantly increases the creepage distance along the pole surface. In humid, rainy, or snowy weather, these sheds effectively block and segment the continuous water film that forms along the pole surface, preventing the water from flowing in a straight line and reducing the insulation distance. This effectively avoids surface flashover accidents and ensures the system's operational safety in all-weather conditions.

[0044] Working closely with the measurement and acquisition subsystem 1 is the terminal and analysis subsystem 2. Physically, this subsystem is typically an industrial-grade tablet computer with an IP67 rating and a high-brightness, anti-glare screen, such as the Panasonic Toughbook FZ-G2. It runs an application (APP) developed specifically for this invention, another key component of intelligent fault diagnosis. This application's capabilities extend far beyond simple data display, incorporating a comprehensive and efficient set of multi-feature fusion and spatiotemporal correlation diagnostic algorithms.

[0045] Reference Figure 5The execution flow of this diagnostic algorithm is analyzed. First, during the data reception and preprocessing phase, the application receives a synchronized waveform data stream from the measurement and acquisition subsystem 1 in real time via a previously established Wi-Fi P2P link. The application's underlying data reception thread first performs a CRC32 check on each frame and discards any corrupted frames. It then uses the nanosecond-precision timestamp embedded in the data frame, generated by the source hardware, to precisely align and buffer minute packet arrival time differences caused by wireless channel transmission jitter. Using a sophisticated jitter buffer, the application reconstructs a continuous, time-synchronized current and voltage data stream that is identical to the source acquisition instant. Next, a digital finite impulse response (FIR) filter is applied to the raw waveform data stream. In this embodiment, the filter is designed as a 128-order low-pass filter with a cutoff frequency of 5 kHz. This filter removes high-frequency white noise introduced by the sensor itself or the electromagnetic environment, while preserving all valuable frequency components of the fault transient.

[0046] Secondly, entering the multi-dimensional feature extraction stage, the algorithm performs parallel and in-depth calculations on the pre-processed pure waveform data to extract multi-dimensional electrical feature quantities that can characterize the line status.

[0047] The first dimension is the fundamental frequency steady-state characteristic quantity. The algorithm starts a processing thread and applies a sliding window technique to continuous waveform data. Within each window (for example, a length of 40 milliseconds, which just contains two power frequency cycles), the efficient Goertzel algorithm is used instead of a complete discrete Fourier transform (DFT) to specifically calculate the effective value (RMS) of the fundamental frequency (50 Hz) component of the current and voltage, as well as the phase angle of the current relative to the voltage. The Goertzel algorithm is much more computationally efficient than FFT when only a single frequency point information needs to be calculated. After completing the measurement of the three phases of the same line (A, B, and C phases, obtained through three independent single-phase measurements or possible three-phase integrated measurement equipment in the future), the algorithm further synthesizes and calculates the zero-sequence current through vector addition based on Kirchhoff's law. and zero sequence voltage In a low-current grounding system in a distribution network, the zero-sequence current in a non-fault state is extremely small (typically less than 300 mA), caused solely by three-phase load imbalance or line parameter asymmetry. However, after a single-phase grounding fault occurs, the fault point becomes a large zero-sequence current source. Consequently, significant zero-sequence current can be measured on the line between the fault point and the substation. The magnitude and direction (phase) of the zero-sequence current are the most direct and reliable basis for determining whether the fault point is upstream or downstream of the measurement point.

[0048] The second dimension is the harmonic and transient features. Another parallel thread of the algorithm performs a Fast Fourier Transform (FFT) on the same waveform data, resulting in a full spectrum of harmonics up to several kilohertz. The algorithm pays special attention to the amplitudes of odd harmonics (3rd, 5th, 7th, etc.) and their proportions to the fundamental component. In particular, for high impedance or intermittent arc ground faults, the fault current waveform often experiences severe non-sinusoidal distortion, resulting in a unique and identifiable harmonic "fingerprint" in the frequency spectrum. At the same time, in order to capture those transient signals with extremely short duration and energy concentrated in an instant, the algorithm also applies a Wavelet Transform. Unlike the FFT which provides global frequency information, the Wavelet Transform can provide time-frequency localized analysis of the signal. In this embodiment, "Daubechies 4" (db4) is used as the mother wavelet for multi-layer decomposition of the current waveform. The Wavelet Transform can effectively capture and characterize the transient traveling wave signals caused by arc reignition or extinction, which are manifested as abrupt points in the waveform. The algorithm extracts key transient feature parameters from the traveling wave signal, such as peak amplitude, wave front steepness (defined as the time taken to rise from 10% amplitude to 90% amplitude), and the exact time of occurrence of the traveling wave on the absolute time axis.

[0049] The third dimension is the correlation feature. The extraction of this feature is not done in a single measurement, but requires the operator to perform measurements at two different geographical points (e.g., tower A and tower B) in succession. The application stores all the above feature vectors extracted from the two measurements, along with the GPS coordinates of the measurement points, in the internal database. In particular, for the transient traveling wave signals, the algorithm automatically compares the transient events captured in the two measurements that may have been generated by the same fault source. After confirming their common origin through cross-correlation calculation of the waveform patterns, the algorithm calculates the difference (Δt) in the high-precision time stamps of the two common transient events. This microsecond-level time difference directly reflects the time taken by the traveling wave to propagate from one measurement point to another on the transmission line.

[0050] Finally, in the intelligent diagnosis and location decision stage, the algorithm feeds all the multi-dimensional feature quantities extracted in the previous stage as a comprehensive input vector into a hybrid decision engine based on rules and models to perform the final fault location. The decision engine first starts a rule base built based on the knowledge of domain experts. For example, rule one: for a large current grounding system, the fault phase (the collected voltage is the 0 phase) current increases to select the line; the fault phase current increases before the fault point and the current is normal after the fault point, to select the line and section. Rule two: for a neutral point ungrounded system, the zero sequence current of the non-fault line far from the bus decreases, the zero sequence current of the fault line first increases, suddenly jumps, and then gradually decreases, to select the line and section. Rule three: for a grounding system through an arc extinction coil, a transient mode is enabled to perform traveling wave distance measurement; rule four: if a signal with typical arc grounding characteristics (such as high-frequency transient, specific harmonic component) is detected, the overall confidence of the fault judgment is improved to 99.9%.

[0051] For some complex fault conditions with insignificant features (such as high impedance, small current, and metallic grounding), or in order to achieve more accurate "point" positioning beyond the "section" level, the decision engine prompts and starts the space-time correlation analysis model. When the operator follows the graphical interface guidance of the application program and completes the measurement at two points A and B with a known distance L (the distance can be automatically calculated from the GPS coordinates of two measurements, or the tower spacing can be manually input by the operator), the algorithm calls the previously stored correlation feature quantities. It uses the difference Δt between the arrival time stamps of the homologous transient traveling waves recorded in the two measurements, and combines the propagation speed v of the electromagnetic wave on the transmission line (the speed is close to the speed of light, and for common overhead lines, the value can be preset as m / s), to accurately calculate the physical distance from the fault point to one of the measurement points. For example, assuming that the time of detecting the traveling wave at point A is earlier than that at point B, it can be determined that the fault point is located somewhere downstream of point B. At this time, the distance from the fault point to the closer point A , can be obtained by solving the equation set , and the solution is . This principle based on double-end traveling wave distance measurement can improve the theoretical accuracy of fault location from the tower spacing level of hundreds of meters to the meter level of ten meters or less, providing unprecedented accurate guidance for repair work.

[0052] Referring to Figure 6 , a complete working method for finding a single-phase grounding fault based on the system provided by the application is described, and a neutral point ungrounded substation is taken as an example. The specific steps are as follows: The first step is system initialization and preparation. Based on the typical tower height of the 10 kV distribution line being tested, on-site maintenance personnel remove three modular high-voltage insulated operating poles 50 from the equipment box and securely plug them together, assembling a pole approximately 4.5 meters long. They then power on the measurement and acquisition subsystem 1 at the top of the pole and the terminal and analysis subsystem 2 in their hands. Within 10 seconds, the two automatically pair via Bluetooth Low Energy. The terminal application's main interface displays "Device Connected," and a dashboard displays real-time status information, including the measurement terminal's battery level (showing 98%), GPS signal strength (displayed as 5 / 5 bars), and internal operating temperature (displayed as 25°C), indicating system readiness.

[0053] The second step is identifying the faulty feeder. The operation and maintenance team received a dispatch instruction regarding a ground fault on phase A of a low-current grounded substation. A ground fault occurred on the outgoing line side of the substation, but the specific feeder could not be determined. The operator arrived at the substation's exit structure and, following the instructions in the application, measured the phase A conductors of the three outgoing feeders labeled "Line 1," "Line 2," and "Line 3," in sequence. During operation, a virtual button on the terminal app activated the electromechanical drive and locking module 20 at the measurement end to open the jaws, which were then placed on the conductor. The button was then pressed again to close the jaws. The system automatically switched from Bluetooth Low Energy (BLE) to Wi-Fi P2P high-bandwidth mode, with real-time waveforms and calculation results instantly displayed on the terminal screen. Measurements of Line 1 and Line 2 showed a gradual decrease in zero-sequence current as the measurement location moved away from the busbar. However, when measuring Line 3, the zero-sequence current gradually increased as the measurement location moved away from the busbar, indicating that this line was the faulty phase. At this point, it only took about 5 minutes to accurately identify the faulty feeder as "Line Three".

[0054] The third step involved binary segment location. After determining that the faulty line was "Line 3," a 12-kilometer-long section, the operator drove along the patrol route to a conveniently located tower approximately 6 kilometers (the midpoint of the line). The measurement procedure from step 2 was repeated, measuring the Phase A conductor at that location. The results showed that the zero-sequence current at this point was 3.9 amperes, still increasing. The terminal application's diagnostic algorithm, based on the "zero-sequence current direction method," immediately provided a clear graphical and textual indication: "The fault point is downstream of the current location," indicating that the fault occurred in the second half of the line, between 6 and 12 kilometers. This process was completely independent of the operation of the line section switches and did not cause any power outages to any customers on the line.

[0055] The fourth step involved iterative approximation and precise location. Following the instructions from the previous step, the operator drove to the midpoint of the second half of the targeted section, approximately 9 kilometers from the substation, and repeated the measurement. This time, the zero-sequence current suddenly dropped to 1.0 amperes. The application immediately indicated, "The fault is upstream of the current location." Combining these two measurements, the fault location was quickly narrowed to between 6 and 9 kilometers. The operator continued the binary approach within this 3-kilometer section, measuring again at approximately 7.5 kilometers and finding a zero-sequence current of 4.8 amperes (a downstream fault). A further measurement at 8.25 kilometers revealed a zero-sequence current of 1.2 amperes (an upstream fault). After these four measurements, totaling approximately 40 minutes, the fault was precisely located between tower N56 at 7.5 kilometers and tower N61 at 8.25 kilometers.

[0056] The fifth step is high-precision traveling wave ranging. Since there is a forest between the N56 tower and the N61 tower, visual line inspection is difficult. The operator decided to enable the advanced diagnostic mode. Following the instructions of the application, first measure under the N56 tower and save data point A. Then, drive to the N61 tower, take a second measurement, and save it as data point B. The GPS coordinates of the two measurements automatically calculate the line distance L between the two points to be approximately 750 meters. The diagnostic algorithm of the terminal application automatically switches to the spatiotemporal correlation analysis model. By comparing and analyzing the homologous transient traveling wave signals generated by intermittent grounding arcs captured in the two measurements, it is calculated that the timestamp of the traveling wave detected at point B is 1.72 microseconds later than that at point A (Δt = 1.72μs). The algorithm then substitutes the formula to calculate: The distance from the fault point to the N56 tower (point A) is The app pinpointed the fault on a map, approximately 126 meters along the line from tower N56. Using these precise coordinates, repair crews entered the forested area and quickly discovered a branch, broken by the strong wind, that had become lodged in the conductor, causing the ground fault.

[0057] Step 6: Data Archiving and Report Generation. After troubleshooting, the operator clicks "End Diagnosis" in the app. The app automatically generates a complete diagnostic report in PDF format. This report details the faulty line name, diagnosis date and time, and the final location (ground fault caused by a tree barrier, 126 meters downstream of tower N56). It also includes detailed data for each measurement, including GPS coordinates, zero-sequence current / voltage values, transient waveform screenshots, and the operator's name. This report can be directly sent to the operation and maintenance management center's server via the device's mobile network, providing valuable first-hand data support for subsequent fault statistical analysis and line health assessment.

[0058] For single-phase grounding of outgoing lines of large-current grounding substations (mainly small-resistance grounding substations), the large-current grounding mode can be selected. It is only necessary to directly measure the current of the grounding phase fault (voltage is 0 phase) for judgment. The current of the fault phase in front of the fault point is very large. It can also be used as a small-current grounding system to collect zero-sequence voltage and current to determine the production direction.

[0059] This device can also be used in conjunction with the "small current grounding line selection device" and "fault indicator" to complete the final section selection.

[0060] In order to further demonstrate the beneficial effects of the technical solution of the present invention, a comparative analysis of an embodiment and a comparative example is provided below.

[0061] Example 1: The wireless transmission-based Linker rod current and voltage measurement system described in the present invention was used to investigate a single-phase high-impedance grounding fault (grounding resistance of approximately 800 ohms, with the fault point located 11.3 kilometers away from the substation) occurring on a 10kV, 18-kilometer-long overhead distribution line at a low-current grounding substation.

[0062] The measurement took 5 minutes at two locations: one at the outgoing line of the substation (0.2 km) and another at a distance (0.5 km). By measuring the zero-sequence current of the three parallel feeders, the fault line was accurately identified.

[0063] Using the binary method, measurements were taken at 9 km, 13.5 km, and 11.25 km in sequence, taking a total of 45 minutes, and the fault was located in the section between 11.25 km and 13.5 km.

[0064] Double-end traveling wave measurements were conducted on the first and last two towers in this section (N78 and N85, about 2.2 kilometers apart). It took 15 minutes and calculated that the fault point was 58 meters away from the N78 tower.

[0065] The emergency repair personnel arrived at the scene directly based on precise positioning and found that a string of insulators there had deteriorated and there was hidden discharge.

[0066] The entire process, from identifying the line to precise positioning, took about 65 minutes. No power outage was required and no impact was caused to users.

[0067] Comparative Example 1: The same fault as in Example 1 was checked by using the conventional method of power-on test and manual line inspection.

[0068] The substation's backend system triggered an alarm, indicating a ground fault, but the specific line could not be identified. Dispatchers ordered a brief power outage and reclosing of the three feeder lines under the busbar. This process took approximately 20 minutes and caused three instantaneous power outages for all users on the three lines. The faulty line was eventually identified.

[0069] Two line patrol personnel were dispatched to drive to the starting point of the faulty line and begin manual inspections along the line.

[0070] Because the line is high-impedance grounded, fault symptoms are not obvious (no obvious sparks, broken wires, etc.). Line patrol personnel need to use binoculars to carefully observe the equipment status of each tower. The line passes through farmland and hills, so the inspection speed is slow, averaging about 20 minutes per kilometer.

[0071] After spending nearly 4 hours, the line patrol personnel arrived near the N78 tower at 11.3 kilometers. Using an infrared thermometer, they found an abnormal hot spot on the insulator there, and finally determined the fault point.

[0072] The entire process, from receiving the alarm to identifying the fault point, took more than 4.5 hours and caused substantial power supply disturbances to a large number of users.

[0073] Through the detailed description and data comparison of the above embodiments and comparative examples, it is clearly evident that the wireless transmission-based Linker rod current and voltage measurement system and method provided by the present invention organically integrates high-precision synchronous sensing, electromechanical automation, wireless communication, and advanced intelligent diagnostic algorithms to construct a portable, efficient, accurate, and secure single-phase grounding fault diagnosis solution for distribution networks. This system enables rapid troubleshooting and precise fault location without relying on line power outages or being restricted to fixed monitoring points, significantly shortening repair time, reducing economic losses, and improving power supply reliability and the intelligence level of operation and maintenance work. It represents a significant technological advancement and has broad prospects for engineering applications.

[0074] The above description is only a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention.

Claims

1. A linker rod current and voltage measurement system based on wireless transmission, characterized in that: include: a measurement and acquisition subsystem (1) configured to be held by an operator and brought into contact with or adjacent to a high-voltage overhead conductor to perform non-invasive measurements of electrical parameters of the conductor; as well as a terminal and analysis subsystem (2) configured to communicate wirelessly with the measurement and acquisition subsystem (1); Among them, the measurement and acquisition subsystem (1) includes: A multi-modal synchronous sensing module (10) is provided at a measuring end of the measurement and acquisition subsystem (1), wherein the multi-modal synchronous sensing module (10) integrates a current sensing unit for measuring the current in the conductor and a voltage sensing unit for measuring the voltage of the conductor to the ground, and is configured to synchronously sample the current and voltage under the drive of a common high-precision clock reference, and to attach a high-precision time stamp to each sampled data collected; a data processing and communication module (30) electrically connected to the multi-modal synchronous sensing module (10) for processing synchronously sampled current and voltage data and transmitting the data in real time to the terminal and analysis subsystem (2) via wireless means in a data frame format including a high-precision time stamp; and a modular high-voltage insulating operating rod body (50) serving as a physical structure for carrying the multi-modal synchronous sensing module (10) and the data processing and communication module (30), and providing high-voltage insulating protection for operators; The terminal and analysis subsystem (2) is configured as follows: receiving current and voltage data including high-precision time stamps sent by the measurement and acquisition subsystem (1); and A preset diagnostic algorithm is run, which locates the single-phase grounding fault of the line to which the conductor belongs by extracting and analyzing electrical characteristic quantities based on synchronized current and voltage data.

2. The system according to claim 1, wherein: In the multimodal synchronous sensing module (10), the current sensing unit is specifically an open-close high-precision Rogowski coil (11), which has a jaw structure that can be driven to open to hang on a wire and closed to surround the wire; the voltage sensing unit is specifically a non-contact voltage sensor array (12) based on the electric field coupling principle, which is integrated into the inner surface of the jaw structure.

3. The system according to claim 2, characterized in that The multi-mode extra synchronous sensing module (10) is internally provided with a common high-frequency clock source driven by a temperature-compensated crystal oscillator, and the clock signal generated by the clock source is simultaneously provided to a first analog-to-digital converter and a second analog-to-digital converter for digitizing the output signal of the current sensing unit and the output signal of the voltage sensing unit, respectively, as a synchronous sampling clock; and the data processing and communication module (30) is internally provided with a hardware timer driven by the high-frequency clock source, and the data processing and communication module (30) uses the hardware timer to add a synchronous time stamp accurate to the microsecond or nanosecond level to each sampling data point output by the first and second analog-to-digital converters.

4. The system according to claim 2 or 3, characterized in that The open-close high-precision Rogowski coil (11) has a non-ferromagnetic air core structure, and its output end is connected to a hardware integrator circuit. The hardware integrator circuit is configured to perform an integration operation on the voltage signal induced and output by the Rogowski coil (11) and proportional to the differential of the measured current, thereby restoring and outputting a voltage signal proportional to the original current wave in the wire for subsequent analog-to-digital conversion.

5. The system according to claim 2 or 3, characterized in that The non-contact voltage sensor array (12) is composed of a plurality of concentric ring-shaped metal sensing electrodes, wherein the sensing electrodes include at least one outer sensing electrode serving as a shielding electrode and at least one inner sensing electrode serving as a signal pickup electrode; the shielding electrode is connected to the circuit ground to eliminate interference from external stray electric fields; the signal pickup electrode is connected to the analog-to-digital conversion channel through an ultra-high impedance preamplifier with an input impedance greater than 10 gigahertz to measure the displacement current generated by the coupling capacitance formed between the signal pickup electrode and the measured conductor, and thereby invert the voltage of the conductor to the ground.

6. The system according to claim 1, wherein: The measurement and acquisition subsystem (1) further includes an electromechanical drive and locking module (20), which includes a brushless DC motor and a worm gear transmission mechanism connected to the output end of the motor; the output end of the worm gear transmission mechanism is connected to the jaw structure of the multi-modal synchronous sensing module (10) to drive it to open and close; the transmission self-locking characteristic of the worm gear transmission mechanism enables the jaw structure to maintain a stable clamping force after closing and clamping the wire even when the motor is powered off.

7. The system according to claim 6, characterized in that The electromechanical drive and locking module (20) further includes a current monitoring circuit for implementing torque limiting control on the jaw structure, wherein the current monitoring circuit is configured to monitor the load current of the brushless DC motor in real time; the data processing and communication module (30) is configured to immediately stop driving the motor when it is detected that the load current rises sharply due to the jaw structure being closed and exceeds a preset threshold value, so as to prevent excessive torque damage to the wire or the sensor module body.

8. The system according to claim 1, wherein: The modular high-voltage insulating operating rod body (50) is composed of a plurality of insulating pipe sections (51) that can be plugged and locked into each other. The base material of the insulating pipe section (51) is an epoxy glass fiber cloth tube or an epoxy resin material. The outer surface of each insulating pipe section (51) is integrally formed with a plurality of umbrella skirt-shaped structures distributed along its axial direction, namely, rainproof insulator structures (52). The rainproof insulator structures (52) are used to increase the creepage distance of the rod surface to prevent surface flashover in humid or rainy or snowy weather conditions.

9. The system according to claim 1, wherein: The diagnostic algorithm executed by the terminal and analysis subsystem (2) is configured to perform at least one of the following positioning modes: The first positioning mode is the zero-sequence current direction positioning mode. In this mode, the algorithm processes the synchronized current and voltage data to calculate the effective value of the zero-sequence current at the measurement point. By comparing the calculated zero-sequence current effective value with the values ​​at other points, it is determined whether the single-phase grounding fault point is located upstream or downstream of the measurement point.

10. The system according to claim 9, characterized in that The diagnostic algorithm run by the terminal and analysis subsystem (2) is also configured to perform the following second positioning mode: The second positioning mode is the transient traveling wave ranging positioning mode. In this mode, after the operator completes the measurement of the first and second measurement points on the line, the algorithm performs the following steps: Identifying and extracting a transient traveling wave signal generated by the same single-phase grounding fault event from the current data collected from the first measuring point and the second measuring point by wavelet transform or other time-frequency analysis methods; Using the high-precision timestamps added to the data, determine the time difference (Δt) between the arrival of the transient traveling wave signal of the same source at the first measurement point and the second measurement point; as well as Combining the preset electromagnetic wave propagation speed (v) on the conductor and the known line distance (L) between the first measuring point and the second measuring point, the specific physical distance between the single-phase grounding fault point and one of the measuring points is determined through time-space correlation calculation.

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