Distributed traveling wave distance measurement system, method and device and storage medium

Abstract

The invention discloses a distributed traveling wave distance measurement method, equipment and a storage medium. The system is composed of monitoring terminal equipment arranged along a power transmission line, an APN data transmission network and a central station system. The monitoring terminal acquires a traveling wave signal through a Rogowski coil and calibrates time through a GPS synchronous clock, and data is encrypted and then transmitted to the central station; the central station adopts a distributed cluster architecture, analyzes multi-manufacturer data through a unified equipment protocol, calculates a fault position by using a double-end positioning method in combination with a wave velocity self-learning technology, and identifies a fault type based on wave tail time characteristics. The method comprises the steps of monitoring point arrangement, data encryption transmission, waveform feature extraction, fault positioning, graded early warning and the like. According to the system and the method, the problems of poor compatibility, low positioning precision and low operation and maintenance efficiency of equipment of multiple manufacturers are solved, and high-precision positioning and intelligent diagnosis of power transmission line faults are realized.

Description

Technical Field

[0001] This invention relates to the field of intelligent management technology for power systems, specifically to a distributed traveling wave ranging system method, equipment, and storage medium. Background Technology

[0002] With the expansion of power transmission lines, tripping accidents caused by lightning strikes, pollution, and other factors are becoming increasingly frequent, making rapid fault location crucial for operation and maintenance. Traditional traveling wave (TW) positioning technology is significantly affected by terrain and sag in long lines. Increased TW transmission distance leads to wavefront attenuation and deformation, resulting in large errors in wavefront timing. For complex network structures such as 3T connections, TW reflection interference renders positioning ineffective. While the first phase of the distributed TW ranging master station has achieved data access and unified display, the lack of unified diagnostic standards for equipment from multiple manufacturers results in high operation and maintenance costs and insufficient positioning accuracy for complex networks and long lines. Existing technologies suffer from inconsistent data formats from different manufacturers, making efficient parsing and processing by the central station impossible. Uncertain wave velocity leads to large positioning errors, and the operation and maintenance platform has poor compatibility, making it difficult to adapt to the growing equipment demands. Therefore, a distributed TW ranging system with unified management and high-precision positioning is urgently needed. Summary of the Invention

[0003] This invention discloses a distributed traveling wave ranging system, which consists of monitoring terminal equipment deployed along the transmission line, an APN data transmission network module, and a central station system. The monitoring terminal acquires traveling wave signals via Rogowski coils and calibrates the time using a GPS-synchronized clock. The data is encrypted using AES-256 and transmitted to the central station. The central station adopts a distributed cluster architecture, parsing data from multiple manufacturers using a unified equipment protocol, calculating fault locations using a two-end positioning method combined with wave velocity self-learning technology, and identifying fault types based on wave tail time characteristics.

[0004] This invention provides a distributed traveling wave ranging system, comprising monitoring terminal equipment, a data transmission network module, and a central station system. The monitoring terminal equipment is deployed along the transmission line at predetermined intervals, and each device integrates a traveling wave ranging device for collecting traveling wave signals, power frequency fault current, equipment self-test information, and operating condition data. The data transmission network module uses an APN network channel to encrypt and transmit the data collected by the monitoring terminal equipment to the central station system. The central station system includes a data front-end receiving server, a data processing server, and a database server, used to uniformly receive, parse, store, and analyze data from equipment from multiple manufacturers, and generate fault diagnosis results based on a traveling wave positioning algorithm.

[0005] In one embodiment, the data receiving module of the central station system is deployed on the data front-end receiving server. It identifies terminal devices from different manufacturers through a unified device protocol and establishes a standardized communication protocol to receive raw data. The data parsing module runs on the data processing server and parses the Southern Power Grid protocol-encoded data into business data containing timestamps with a timestamp accuracy of microseconds.

[0006] In one embodiment, the waveform processing module of the central station system performs feature marking on the waveforms in the service data and extracts the tail time, amplitude and frequency parameters of the fault waveform; the automatic diagnosis module adopts the dual-end positioning method and combines wave speed self-learning technology to calculate the fault location. The wave speed self-learning technology determines the equivalent wave speed of the interval by the time difference between non-fault traveling waves and adjacent monitoring points.

[0007] In one embodiment, the fault early warning module of the central station system presets the tail time thresholds for lightning strike faults and non-lightning strike faults. When the tail time in the monitoring data is less than 20μs, a lightning strike early warning is triggered, and when it is greater than 40μs, a non-lightning strike fault early warning is triggered. The Web display module deploys intelligent diagnostic programs through the intranet to visually present equipment ledgers, operating data, and fault diagnosis reports.

[0008] In one embodiment, the data transmission network uses the AES-256 encryption algorithm to encrypt the raw data uploaded by the monitoring terminal device in groups, and the encryption key is updated regularly by the key management module of the central station system to ensure the security of data transmission.

[0009] In one embodiment, the database server adopts a distributed cluster architecture, builds a historical monitoring data storage cluster based on the HBase storage engine, and realizes distributed storage and fast retrieval of multi-source heterogeneous data by dividing the data into segments according to the transmission line sections.

[0010] Secondly, the present invention also provides a distributed traveling wave ranging method based on any one of the claims, comprising: deploying monitoring terminal equipment along the transmission line at preset intervals; the equipment acquiring traveling wave current signals through Rogowski coils and using a GPS synchronous clock to achieve microsecond-level time calibration; encapsulating the acquired raw data according to a unified equipment protocol; the monitoring terminal equipment encrypting the raw data in groups using the AES-256 encryption algorithm and transmitting it to the central station data front-end receiving server through the APN network channel; the server identifying terminals from different manufacturers based on the equipment protocol and establishing a standardized communication link; the central station data processing server decrypting the received encrypted data and parsing it into business data; using a Kalman filter algorithm to denoise the traveling wave signal; and using a slope detection algorithm to mark fault waveforms and extract characteristic parameters such as wave tail time and rise time. The central station system uses a wave velocity self-learning module to calculate the equivalent wave velocity between adjacent monitoring points using small-amplitude traveling waves during non-fault periods and updates the database. Based on the dual-end positioning method and the updated wave velocity, it calculates the fault location and identifies lightning strike and non-lightning strike fault types according to the wave tail time threshold. The central station fault early warning module generates graded early warning information based on the fault type and location results, and simultaneously pushes a diagnostic report containing the fault location, type, and handling suggestions through SMS platform and Web interface. The report uses the HBase distributed storage engine to achieve rapid retrieval and related display of historical data.

[0011] In one embodiment, the central station system uses a wave velocity self-learning module to calculate the equivalent wave velocity between adjacent monitoring points using small-amplitude traveling waves during non-tripped faults, and establishes a line section wave velocity database; it calculates the fault location based on the double-ended positioning formula L=(T2-T1)×V / 2, where T2 and T1 are the time for the traveling waves to reach the two monitoring points, and V is the section equivalent wave velocity.

[0012] Thirdly, the present invention also provides a fault location device for a distributed traveling wave ranging system, comprising: one or more processors; and a memory storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement any of the distributed traveling wave ranging systems described above.

[0013] Fourthly, the present invention provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to execute any of the distributed traveling wave ranging systems described above.

[0014] Beneficial effects

[0015] This invention effectively addresses the technical pain points of existing distributed traveling wave ranging systems through multi-dimensional technological innovation. By strategically deploying monitoring terminal equipment along transmission lines and combining it with advanced wave velocity self-learning technology, fault location accuracy is significantly improved, enabling precise fault point localization and providing more accurate guidance for emergency repairs, thereby reducing line outage time and maintenance costs. A unified access and processing mechanism for data from multiple manufacturers' equipment is established, achieving seamless integration and sharing of monitoring data from distributed ranging devices from different manufacturers. This provides comprehensive and accurate data support for joint and unified fault diagnosis, fully leveraging the advantages of online transmission line devices, improving the accuracy and timeliness of fault diagnosis, and providing strong evidence for power departments to assess the safety operation level of lines and formulate effective protective measures. The optimized web display platform provides an intuitive and convenient user interface and operating experience, enabling operation and maintenance personnel to more easily manage and monitor the distributed traveling wave ranging system. Simultaneously, by establishing unified management standards and operation and maintenance methods, efficient resource utilization is achieved, significantly reducing system operation and maintenance costs, effectively improving operation and maintenance management efficiency, and ensuring the long-term stable operation of the system. The system adheres to a unified interface standard and coding system, and reserves standard interfaces for third-party applications, possessing excellent compatibility and scalability. It can easily integrate new manufacturers' equipment and functional modules, adapting to the evolving monitoring needs of transmission lines and providing strong support for the intelligent operation and maintenance of power systems. The newly added rapid fault early warning module can monitor the operating status of transmission lines in real time, promptly capture fault symptoms, and quickly generate early warning information. It notifies relevant personnel through multiple methods, enabling maintenance personnel to take timely measures in the early stages of a fault, preventing further escalation and significantly improving the operational reliability and power supply stability of transmission lines. Attached Figure Description

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0017] Figure 1 A schematic diagram of a distributed traveling wave ranging system module provided for the implementation of this invention;

[0018] Figure 2 This is a flowchart illustrating the distributed traveling wave ranging method provided in an embodiment of the present invention.

[0019] Figure 3 This is a schematic diagram of the structure of the distributed traveling wave ranging device provided in an embodiment of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0021] It should be noted that if the embodiments of the present invention involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a specific posture. If the specific posture changes, the directional indicators will also change accordingly.

[0022] Furthermore, if the embodiments of this invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Thus, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the use of "and / or" or "and / or" throughout the text implies three parallel solutions. For example, "A and / or B" includes solution A, solution B, or a solution where both A and B are satisfied. Furthermore, the technical solutions of the various embodiments can be combined, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0023] With the continuous expansion of power transmission lines, their safe and stable operation is increasingly crucial for power supply. However, transmission lines often traverse complex terrain, making them highly susceptible to tripping accidents caused by various natural factors such as lightning, pollution, vegetation, wind, rain, and icing. Each tripping accident not only impacts the power system but also damages insulators, conductors, and other facilities, creating potential safety hazards for system operation. Therefore, timely and accurate fault location and repair have become critical tasks in line operation and maintenance. Traveling wave localization technology, as an effective fault monitoring method, can quickly locate fault points, which is of great significance for improving the safety and reliability of line operation.

[0024] Traditional traveling wave (TW) positioning technology has many shortcomings in practical applications. For long lines, TW propagation is significantly affected by factors such as terrain, sag, and wave velocity, making positioning unreliable and inaccurate. As the TW propagation distance increases, the wavefront will attenuate and deform, which will cause a large error in determining the wavefront time, thus affecting the positioning accuracy. For complex network structures with branching structures, such as 3T wiring networks, traditional TW fault location technology is no longer applicable due to the reflection of the TW.

[0025] Building upon the first phase of the distributed traveling wave ranging master station construction, while functions such as data access from distributed ranging devices for transmission lines, independent analysis, processing, and diagnosis of equipment from different manufacturers, and unified data display have been achieved, initially meeting the online monitoring and early warning requirements of various bureaus' transmission lines, the master station has gradually revealed problems such as a lack of unified diagnostic standards, unified management standards, and unified operation and maintenance methods as the coverage and installation volume of distributed equipment and the number of equipment manufacturers increase year by year. These problems lead to increased system operation and maintenance costs and reduced operation and maintenance efficiency. Therefore, there is an urgent need for a distributed traveling wave ranging system and method that can solve the above problems.

[0026] refer to Figure 1 This invention provides a distributed traveling wave ranging system, including monitoring terminal equipment, a data transmission network, and a central station system. The monitoring terminal equipment is deployed at preset intervals along the transmission line, and each equipment integrates a traveling wave ranging device for collecting traveling wave signals, power frequency fault current, equipment self-test information, and operating condition data. The data transmission network uses an APN network channel to encrypt and transmit the data collected by the monitoring terminal equipment to the central station system. The central station system includes a data front-end receiving server, a data processing server, and a database server for uniformly receiving, parsing, storing, and analyzing data from equipment from multiple manufacturers, and generating fault diagnosis results based on a traveling wave positioning algorithm.

[0027] The distributed traveling wave ranging system adopts a three-layer distributed architecture, consisting of a field monitoring layer, a network transmission layer, and a central management layer from bottom to top. This architecture design offers excellent scalability and stability, meeting the monitoring needs of transmission lines of varying sizes. The field monitoring layer, acting as the system's sensing front end, deploys monitoring terminal equipment along the transmission line at specific intervals, forming a high-density monitoring network to achieve real-time acquisition of traveling wave signals and equipment operating conditions. The network transmission layer constructs a secure and reliable data transmission channel, employing APN encryption to ensure that monitoring data is transmitted to the central management layer in real-time, stably, and completely. The central management layer, as the core of the system, is deployed in the power dispatch center and consists of a cluster of multiple servers. It undertakes key tasks such as data processing, storage, diagnosis, and display, achieving accurate fault location and intelligent diagnosis through in-depth analysis of the acquired data. The three layers interact and transmit commands through standardized interfaces. This design allows each part of the system to work independently yet collaborate closely, while also supporting hot-swappable expansion, effectively adapting to the ever-expanding scale of transmission lines.

[0028] The monitoring terminal equipment is a core component of the field monitoring layer. Its hardware composition has been carefully designed and selected to meet the reliable operation requirements in complex field environments. The equipment is enclosed in a high-protection metal enclosure, which meets the IP68 protection standard and can effectively resist the effects of rain, dust, and harsh weather. The enclosure surface is coated with an anti-salt spray coating, further improving the equipment's corrosion resistance in coastal or industrially polluted areas.

[0029] The core components of the equipment include a traveling wave acquisition module, a synchronization clock module, a data processing unit, and a communication module. The traveling wave acquisition module uses a Rogowski coil, which features wide bandwidth and high precision, enabling accurate capture of traveling wave current signals on transmission lines. The synchronization clock module employs a GPS / BeiDou dual-mode receiver, ensuring high-precision time synchronization and guaranteeing accurate timing of the traveling wave signal. The data processing unit is built on a high-performance processor and integrates a high-speed ADC, enabling high-speed digitization of the traveling wave signal. The communication module uses an industrial-grade, fully network-compatible module, supporting APN leased line access and featuring a built-in encryption chip to ensure the security and reliability of data transmission.

[0030] The installation quality of the monitoring terminal equipment directly affects the monitoring effect of the system, therefore strict installation specifications must be followed. The equipment is installed below the crossarm of the transmission line tower and secured with U-shaped clamps to ensure good electrical insulation between the equipment and the tower. The Rogowski coil needs to pass through the phase conductor of the transmission line; during installation, the coil plane should be kept perpendicular to the conductor to reduce measurement errors.

[0031] The power supply scheme employs a hybrid approach combining solar energy and lithium batteries, adaptable to environments without mains power access. High-efficiency monocrystalline silicon solar panels are used, with the installation tilt angle optimized based on local latitude to maximize solar energy collection efficiency. The lithium battery pack utilizes lithium iron phosphate batteries, characterized by high energy density and long cycle life. Equipped with an intelligent battery management system, it provides charge and discharge protection and management, ensuring normal operation even during prolonged periods of cloudy or rainy weather.

[0032] To ensure reliable equipment operation, the monitoring terminal incorporates comprehensive self-testing and operational condition monitoring functions. The equipment includes built-in temperature, humidity, and vibration sensors to monitor internal and surrounding environmental parameters in real time. The self-test module periodically performs functional tests, including Rogowski coil impedance testing, ADC channel calibration, and GPS signal strength assessment, ensuring the proper functioning of all equipment modules. Self-test data and traveling wave signals are synchronously uploaded to the central station, allowing maintenance personnel to monitor the equipment's operating status in real time.

[0033] The data transmission network adopts an APN leased line network, constructing a complete communication protocol and encryption mechanism to ensure the security, reliability, and efficiency of data transmission. The communication protocol is comprehensively designed from the physical layer, link layer, to the application layer. The physical layer automatically switches between 4G / 5G frequency bands based on signal strength to ensure the stability of the communication link; the link layer uses PPP protocol encapsulation and supports IPSec VPN tunnel encryption to ensure the security of data transmission; the application layer uses the MQTT protocol to achieve reliable data transmission and efficient distribution.

[0034] The encryption mechanism uses the AES-256 algorithm to encrypt data in blocks, ensuring that the data is not stolen or tampered with during transmission. The encryption key is updated regularly by the key management module of the central station system, using a secure key exchange protocol to guarantee the security and reliability of the key.

[0035] The data transmission network employs a dual-link backup architecture, with the primary link being a carrier-provided APN leased line and the backup link being a BeiDou short message communication module. This design automatically switches to the backup link in the event of a primary link failure, ensuring continuous data transmission. The network management platform monitors the communication status of each terminal in real time, collecting network performance indicators to achieve real-time monitoring and optimization of the network status. When network anomalies occur, the link optimization process is automatically triggered to ensure reliable system operation.

[0036] The central station system adopts an advanced distributed cluster architecture, deployed in the power dispatch data center, and possesses powerful data processing, storage, and analysis capabilities. The hardware architecture includes a data front-end receiving server, data processing servers, a database server cluster, and application servers. Each server utilizes high-performance hardware configurations and is interconnected via a high-speed network to form a powerful computing cluster. The database server cluster employs a distributed storage architecture, capable of handling petabytes of massive data, supporting high-concurrency data read and write operations, and ensuring efficient storage and rapid retrieval of historical monitoring data. The entire hardware architecture incorporates a redundant design, improving system reliability and availability, and meeting the needs of large-scale transmission line monitoring.

[0037] The data front-end receiving server runs a data receiving service, supports multi-protocol adaptation, and can identify terminal devices from different manufacturers and automatically load the corresponding parser. The data parsing module decrypts, decodes, and timestamps the received data according to standard protocols, converting the raw data into standard format business data, which is then pushed to the data processing server via a message queue, providing high-quality data support for subsequent data processing and analysis.

[0038] The waveform processing service employs a streaming architecture to perform feature labeling and extraction on traveling wave waveforms in real-time streaming data. Through advanced signal processing algorithms, it extracts time-domain, frequency-domain, and time-frequency features of the waveform, providing rich feature parameters for fault diagnosis. The automatic diagnosis module, based on a two-end positioning method combined with wave velocity self-learning technology, achieves accurate calculation of fault location. Wave velocity self-learning technology can update the equivalent wave velocity of each section of the line in real time based on traveling wave data during non-fault periods, improving positioning accuracy.

[0039] The fault diagnosis model adopts a multi-layered architecture and utilizes machine learning algorithms such as SVM and BP neural networks to intelligently identify fault types. The model can accurately distinguish between lightning-induced and non-lightning-induced faults based on waveform characteristics, and further determine the type of lightning-induced fault. The early warning module implements a three-level early warning mechanism, generating graded early warning information based on the severity of the fault and pushing it to relevant personnel through various methods to ensure timely handling of the fault.

[0040] The web-based platform adopts a front-end and back-end separation architecture. The front-end provides an intuitive and user-friendly interface, including functional modules such as equipment ledger management, a fault diagnosis center, and a reporting system, facilitating real-time monitoring of equipment status and fault information by maintenance personnel. The back-end provides robust business logic support and data services, enabling functions such as equipment management, access control, and data sharing, ensuring efficient system operation and maintenance.

[0041] The deployment of monitoring points is fundamental to achieving high-precision fault location in the system and must adhere to strict principles and procedures. Before deployment, three-dimensional data of the line is acquired through UAV surveys, and key areas are analyzed to determine candidate locations for monitoring points. Based on the traveling wave positioning accuracy requirements, the reasonable spacing between monitoring points is calculated to ensure that the measurement error of the traveling wave transmission time difference between adjacent monitoring points is within acceptable limits.

[0042] During equipment installation, the Rogowski coil, terminal chassis, and GPS antenna were installed strictly in accordance with installation specifications to ensure secure installation and correct wiring. After installation, system debugging was conducted, including time synchronization testing, signal acquisition testing, and communication testing, to ensure that all equipment functions were normal, laying the foundation for subsequent monitoring work.

[0043] The monitoring terminal equipment employs a data acquisition mechanism that combines routine acquisition with fault-triggered acquisition. In routine acquisition mode, traveling wave signals and operating condition data are collected at a certain frequency. When a fault signal is detected, high-speed sampling is triggered to record detailed waveform data before and after the fault. Data transmission utilizes efficient compression algorithms and reliable transmission strategies to ensure that data is not lost or damaged during transmission, while simultaneously improving data transmission efficiency.

[0044] The central station data processing server preprocesses the received data, including noise reduction and synchronization correction, to improve data quality. The wave velocity self-learning module periodically updates the equivalent wave velocity of each section of the line, providing accurate wave velocity parameters for fault location. The fault location calculation module, based on the dual-end positioning method and the updated wave velocity, achieves precise calculation of the fault location. The fault type identification module accurately determines the fault type based on waveform characteristics, providing a basis for fault handling. The early warning and handling module generates tiered early warning information based on the fault type and location results, guiding maintenance personnel in fault handling.

[0045] System operation and maintenance (O&M) and optimization are crucial for ensuring the long-term stable operation of the system. The O&M management module enables real-time monitoring of equipment status, data quality assessment, and system performance optimization. By monitoring indicators such as equipment online rate and data integrity rate in real time, it can promptly detect equipment anomalies; regularly assess data quality to ensure data accuracy and integrity; and automatically optimize algorithms and hardware resource configuration based on system operating status to improve system performance and reliability.

[0046] refer to Figure 2 Secondly, the present invention also provides a distributed traveling wave ranging method based on any one of the claims, comprising:

[0047] S1. Monitoring terminal equipment is deployed along the transmission line at preset intervals. The equipment collects traveling wave current signals through Rogowski coils and uses a GPS synchronous clock to achieve microsecond-level time calibration. The collected raw data is packaged according to a unified equipment protocol.

[0048] S2. The monitoring terminal equipment uses the AES-256 encryption algorithm to encrypt the original data packets and transmits them to the central station data front-end receiving server through the APN network channel. The server identifies terminals from different manufacturers based on the device protocol and establishes a standardized communication link.

[0049] S3. The central station data processing server decrypts the received encrypted data and parses it into business data. It uses a Kalman filter algorithm to denoise the traveling wave signal and a slope detection algorithm to mark fault waveforms and extract characteristic parameters such as wave tail time and rise time. The central station system, through a wave velocity self-learning module, calculates the equivalent wave velocity between adjacent monitoring points using small-amplitude traveling waves during non-fault periods and updates the database. Based on the dual-end positioning method and the updated wave velocity, it calculates the fault location and identifies lightning strike and non-lightning strike fault types according to the wave tail time threshold. The central station fault early warning module generates tiered early warning information based on the fault type and location results, and simultaneously pushes a diagnostic report containing the fault location, type, and handling suggestions via SMS platform and Web interface. The report uses the HBase distributed storage engine to achieve rapid retrieval and related display of historical data.

[0050] In one embodiment, the central station system uses a wave velocity self-learning module to calculate the equivalent wave velocity between adjacent monitoring points using small-amplitude traveling waves during non-tripped faults, and establishes a line section wave velocity database; it calculates the fault location based on the double-ended positioning formula L=(T2-T1)×V / 2, where T2 and T1 are the time for the traveling waves to reach the two monitoring points, and V is the section equivalent wave velocity.

[0051] Thirdly, the present invention also provides a fault location device for a distributed traveling wave ranging system, comprising: one or more processors; and a memory storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the distributed traveling wave ranging system as described in any one of claims 1-6.

[0052] Fourthly, the present invention provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to execute any of the distributed traveling wave ranging systems described above.

[0053] refer to Figure 3 This is a schematic diagram of the structure of the distributed traveling wave ranging device provided in the embodiments of this application, with reference to... Figure 3The distributed traveling wave ranging device includes a processor 31, a memory 32, a communication device 33, an input device 34, and an output device 35. The number of processors 31 in the distributed traveling wave ranging device can be one or more, and the number of memories 32 in the monitoring and positioning device of the distributed traveling wave ranging system can also be one or more. The processor 31, memory 32, communication device 33, input device 34, and output device 35 of the monitoring and positioning device of the distributed traveling wave ranging system can be connected via a bus or other means.

[0054] The memory 32, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as program instructions / modules corresponding to the distributed traveling wave ranging system in any embodiment of this application. The memory 32 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the device. Furthermore, the memory 32 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0055] The communication device 33 is used for data transmission.

[0056] The processor 31 executes various functional applications and data processing of the device by running software programs, instructions and modules stored in the memory 32, thereby realizing the above-mentioned distributed traveling wave ranging system.

[0057] Input device 34 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the device. Output device 35 may include display devices such as a display screen.

[0058] The distributed traveling wave ranging device provided above can be used to perform the distributed traveling wave ranging system provided in the above embodiments, and has the corresponding functions and beneficial effects.

[0059] This application embodiment also provides a storage medium containing computer-executable instructions. When executed by a computer processor, the computer-executable instructions are used to execute a distributed traveling wave ranging system, including monitoring terminal equipment, a data transmission network, and a central station system. The monitoring terminal equipment is deployed along the transmission line at preset intervals, and each equipment integrates a traveling wave ranging device for collecting traveling wave signals, power frequency fault current, equipment self-test information, and operating condition data. The data transmission network adopts an APN network channel to encrypt and transmit the data collected by the monitoring terminal equipment to the central station system. The central station system includes a data front-end receiving server, a data processing server, and a database server for uniformly receiving, parsing, storing, and analyzing data from equipment from multiple manufacturers, and generating fault diagnosis results based on the traveling wave positioning algorithm.

[0060] Storage medium – any type of memory device or storage apparatus. The term “storage medium” is intended to include: mounting media, such as CD-ROMs, floppy disks, or magnetic tape devices; computer system memory or random access memory, such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory, such as flash memory, magnetic media (e.g., hard disks or optical storage); registers or other similar types of memory elements, etc. Storage media may also include other types of memory or combinations thereof. Furthermore, storage media may reside in a first computer system in which a program is executed, or may reside in a different second computer system connected to the first computer system via a network (such as the Internet). The second computer system can provide program instructions to the first computer for execution. The term “storage medium” can include two or more storage media residing in different locations (e.g., in different computer systems connected via a network). Storage media may store program instructions (e.g., specifically implemented as a computer program) executable by one or more processors.

[0061] Of course, the computer-executable instructions provided in the embodiments of this application are not limited to the distributed traveling wave ranging system described above, but can also execute related operations in the distributed traveling wave ranging system provided in any embodiment of this application.

[0062] The distributed traveling wave ranging system device provided in the above embodiments can execute the distributed traveling wave ranging system provided in any embodiment of this application. For technical details not described in detail in the above embodiments, please refer to the distributed traveling wave ranging system provided in any embodiment of this application.

[0063] This invention effectively addresses the technical pain points of existing distributed traveling wave ranging systems through multi-dimensional technological innovation. By strategically deploying monitoring terminal equipment along transmission lines and combining it with advanced wave velocity self-learning technology, fault location accuracy is significantly improved, enabling precise fault point localization and providing more accurate guidance for emergency repairs, thereby reducing line outage time and maintenance costs. A unified access and processing mechanism for data from multiple manufacturers' equipment is established, achieving seamless integration and sharing of monitoring data from distributed ranging devices from different manufacturers. This provides comprehensive and accurate data support for joint and unified fault diagnosis, fully leveraging the advantages of online transmission line devices, improving the accuracy and timeliness of fault diagnosis, and providing strong evidence for power departments to assess the safety operation level of lines and formulate effective protective measures. The optimized web display platform provides an intuitive and convenient user interface and operating experience, enabling operation and maintenance personnel to more easily manage and monitor the distributed traveling wave ranging system. Simultaneously, by establishing unified management standards and operation and maintenance methods, efficient resource utilization is achieved, significantly reducing system operation and maintenance costs, effectively improving operation and maintenance management efficiency, and ensuring the long-term stable operation of the system. The system adheres to a unified interface standard and coding system, and reserves standard interfaces for third-party applications, possessing excellent compatibility and scalability. It can easily integrate new manufacturers' equipment and functional modules, adapting to the evolving monitoring needs of transmission lines and providing strong support for the intelligent operation and maintenance of power systems. The newly added rapid fault early warning module can monitor the operating status of transmission lines in real time, promptly capture fault symptoms, and quickly generate early warning information. It notifies relevant personnel through multiple methods, enabling maintenance personnel to take timely measures in the early stages of a fault, preventing further escalation and significantly improving the operational reliability and power supply stability of transmission lines.

[0064] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. All equivalent structural transformations made by using the contents of the present invention description and drawings under the inventive concept of the present invention, or direct / indirect application in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. A distributed traveling wave ranging system, characterized in that, This includes monitoring terminal equipment, data transmission network modules, and a central station system; The monitoring terminal equipment is deployed at preset intervals along the power transmission line. Each equipment integrates a traveling wave ranging device to collect traveling wave signals, power frequency fault current, equipment self-test information and operating condition data. The data transmission network module uses an APN network channel to encrypt and transmit the data collected by the monitoring terminal device to the central station system. The central station system includes a data front-end receiving server, a data processing server, and a database server, which are used to uniformly receive, parse, store, and analyze data from equipment from multiple manufacturers, and generate fault diagnosis results based on the traveling wave positioning algorithm.

2. The distributed traveling wave ranging system according to claim 1, characterized in that, The data receiving module of the central station system is deployed on the data front-end receiving server. It identifies terminal devices from different manufacturers through a unified device protocol and establishes a standardized communication protocol to receive raw data. The data parsing module runs on the data processing server and parses the protocol-encoded data into business data containing timestamps with a timestamp accuracy of microseconds.

3. The distributed traveling wave ranging system according to claim 2, characterized in that, The waveform processing module of the central station system marks the waveforms in the business data with features and extracts the tail time, amplitude and frequency parameters of the fault waveform; the automatic diagnosis module uses the dual-end positioning method and combines wave speed self-learning technology to calculate the fault location. The wave speed self-learning technology determines the equivalent wave speed of the interval by the time difference of the non-fault traveling wave at adjacent monitoring points.

4. The distributed traveling wave ranging system according to claim 3, characterized in that, The fault early warning module of the central station system presets the wave tail time thresholds for lightning strike faults and non-lightning strike faults. When the wave tail time in the monitoring data is less than 20μs, a lightning strike early warning is triggered, and when it is greater than 40μs, a non-lightning strike fault early warning is triggered. The web-based display module deploys intelligent diagnostic programs through the intranet, visually presenting equipment ledgers, operational data, and fault diagnosis reports.

5. The distributed traveling wave ranging system according to claim 1, characterized in that, The data transmission network uses the AES-256 encryption algorithm to encrypt the raw data uploaded by the monitoring terminal equipment in groups. The encryption key is updated regularly by the key management module of the central station system to ensure the security of data transmission.

6. The distributed traveling wave ranging system according to claim 1, characterized in that, The database server adopts a distributed cluster architecture, and builds a historical monitoring data storage cluster based on the HBase storage engine. By dividing the data into segments according to the transmission line sections, it realizes distributed storage and fast retrieval of multi-source heterogeneous data.

7. A distributed traveling wave ranging method based on any one of claims 1-6, characterized in that, include: Monitoring terminal equipment is deployed along the transmission line at preset intervals. The equipment collects traveling wave current signals through Rogowski coils and uses a GPS synchronous clock to achieve microsecond-level time calibration. The collected raw data is packaged according to a unified equipment protocol. The monitoring terminal equipment encrypts the original data packets according to the AES-256 encryption algorithm and transmits them to the central station's data front-end receiving server through the APN network channel. The server identifies terminals from different manufacturers based on the device protocol and establishes a standardized communication link. The central station fault early warning module generates tiered early warning information based on the fault type and location results, and simultaneously pushes a diagnostic report containing the fault location, type and handling suggestions through SMS platform and Web interface. The report is based on HBase distributed storage engine to realize fast retrieval and related display of historical data.

8. The distributed traveling wave ranging method as described in claim 7, characterized in that, include, The central station system uses a wave velocity self-learning module to calculate the equivalent wave velocity between adjacent monitoring points using small-amplitude traveling waves during non-tripped faults, and establishes a wave velocity database for line sections. The location of the fault point is calculated based on the dual-end positioning formula L=(T2-T1)×V / 2, where T is the time for the traveling wave to reach the two monitoring points, and V is the equivalent wave velocity of the interval.

9. A fault location device for a distributed traveling wave ranging system, characterized in that, include: One or more processors; A memory that stores one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the distributed traveling wave ranging method as described in any one of claims 7-8.

10. A storage medium containing computer-executable instructions, characterized in that, The computer-executable instructions, when executed by a computer processor, are used to perform the distributed traveling wave ranging method as described in any one of claims 7-8.

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