Method for network coverage of overhead transmission line in unpopulated areas

Abstract

The application provides a kind of unmanned area overhead transmission line network coverage method, along the line deployment multiple as intelligent spacer intelligent network node, node uses modular hot plug structure, equipped with super capacitor and solid-state battery hybrid energy storage system;Through LoRa communication to build distributed wireless mesh ad hoc network, combined with TDMA time division multiple access and AODV adaptive routing protocol;Utilize the power supply of at least two different principle of multi-source fusion self-powered module power supply;Node collects line monitoring data and carries out edge computing processing, and the processed data is transmitted through multi-hop relay transmission of ad hoc network, and then transmitted to the center master station through the main and standby dual-link redundant transmission architecture.The application can realize long-term stable self-power supply and reliable communication of unmanned transmission line, improve the real-time performance of monitoring data transmission and network invulnerability.

Description

Technical Field

[0001] This invention relates to the field of power transmission and distribution technology, specifically to a method for covering an overhead transmission line network in uninhabited areas, and more particularly to a method for covering an overhead transmission line network in uninhabited areas based on intelligent spacers. Background Technology

[0002] Monitoring the condition of overhead transmission lines, especially those traversing uninhabited areas such as mountains and deserts, presents significant challenges. Existing monitoring solutions suffer from numerous shortcomings because public grid signals typically cannot cover these areas.

[0003] A common existing technology involves deploying monitoring terminals with wireless communication capabilities along power transmission lines. Data is transmitted back to the monitoring center via multi-level relays, and the equipment is powered by the induced current within the power transmission lines themselves. However, this type of technology suffers from two core reliability flaws: First, the power supply reliability is insufficient. It relies entirely on induced current from the transmission lines for power. If the lines are shut down due to maintenance, faults, or other reasons, the induced current disappears, and the entire monitoring system will fail, unable to perform its monitoring function during power outages. Furthermore, when the lines are under light load or no load, the weak induced current is insufficient to meet the power supply requirements of the equipment, especially high-power communication modules.

[0004] Secondly, data transmission reliability is insufficient. Long-distance data backhaul typically relies on a single communication link, whether fiber optic or wireless, which is susceptible to single-point failures due to natural disasters, physical damage, or signal interference. Once this backbone link is interrupted, all front-end monitoring data will be lost, resulting in monitoring "blindness" and an inability to promptly grasp line status and fault information. Therefore, existing technologies struggle to provide a monitoring network capable of long-term autonomous operation with high power supply and data transmission reliability in harsh, uninhabited environments. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method for covering overhead power transmission line networks in uninhabited areas.

[0006] A method for covering an overhead transmission line network in an uninhabited area according to the present invention includes the following steps: Multiple smart network nodes are deployed along the overhead transmission line; each smart network node is equipped with a hybrid energy storage system consisting of supercapacitors and solid-state batteries, and a distributed wireless mesh self-organizing network is constructed among the multiple smart network nodes through LoRa wireless communication; the distributed wireless mesh self-organizing network combines TDMA time division multiple access technology and AODV adaptive routing protocol. The intelligent network node is powered by a multi-source fusion self-powered module, which includes at least two energy harvesting units based on different physical principles. The intelligent network node collects monitoring data of the overhead transmission line and performs edge computing processing on the collected monitoring data; the intelligent network node is an intelligent spacer bar, and the intelligent spacer bar adopts a modular structure that supports hot-swappable modules; The monitoring data processed by edge computing is transmitted via the wireless ad hoc network through multi-hop relay and then aggregated to the central master station via a dual-link redundant remote transmission architecture. The dual-link redundant remote transmission architecture includes a primary backbone link and a backup backbone link.

[0007] Preferably, the multi-source fusion self-powered module includes at least two of the following: a CT sensing energy harvesting unit, a solar energy harvesting unit, and a vibration energy harvesting unit.

[0008] Preferably, the primary backbone link is an OPGW fiber optic link, and the backup backbone link is a 4G or 5G public network wireless link.

[0009] Preferably, the primary backbone link is a long-distance microwave link, and the backup backbone link is a satellite communication link.

[0010] Preferably, the edge computing processing includes filtering, compressing, and identifying abnormal events in the monitoring data.

[0011] Preferably, the abnormal event identification is achieved through an artificial intelligence model deployed on the intelligent network node, used to identify abnormal intruders in the overhead transmission line or its surrounding environment; the artificial intelligence model is a deep learning model or a machine learning model; the deep learning model is a CNN module or a YOLO model.

[0012] Preferably, the intelligent spacer includes: a shell, a main control unit, a multi-source sensor assembly, a length adjustment mechanism, and a power supply module; The outer casing includes a first housing portion and a second housing portion that cooperate with each other, and a mounting cavity is formed between the first housing portion and the second housing portion; The main control unit is located inside the mounting cavity and is connected to the multi-source sensor assembly, the length adjustment mechanism, the power supply module, the edge processing module, and the communication module, respectively, for receiving, processing, and transmitting monitoring data; The multi-source sensor assembly includes at least three of the following: an image acquisition module, an electrical parameter sensor, an environmental sensor, and an attitude sensor. The image acquisition module is disposed on the second housing portion, and the other sensors are disposed inside the mounting cavity or outside the housing. The multi-source sensor assembly is used to collect multi-dimensional monitoring information of the power transmission line and its surroundings. The length adjustment mechanism is disposed between the first housing part and the second housing part, and is used to adjust the extension distance of the second housing part relative to the first housing part, thereby adjusting the installation position and monitoring field of view of the image acquisition module; The power supply module includes an inductive power extraction module, which is used to obtain electrical energy from the transmission line to provide working power for all components of the spacer bar.

[0013] Preferably, the smart spacer further includes a communication module and an edge processing module; The antenna of the communication module is located outside the housing and is used to enable data interaction between the main control unit and an external terminal or platform. The edge processing module is integrated with the main control unit or is set independently in the housing, and is used to process the monitoring data collected by the multi-source sensor components.

[0014] Preferably, the length adjustment mechanism is a set of flanges with different preset lengths that can be replaced, or a threaded telescopic sleeve mechanism. And / or, the image acquisition module includes a visible light camera and an infrared camera, used to acquire visible light images and infrared thermal images of the transmission line, respectively; And / or, the electrical parameter sensor includes at least one of a wire temperature sensor, a wire current sensor, and a fault waveform sensor; And / or, the environmental sensor includes at least one of a rainfall, wind speed and wind direction sensor, a sunshine sensor, a temperature and humidity sensor, and a barometric pressure sensor; And / or, the attitude sensor is used to monitor the installation attitude and displacement of the spacer itself; And / or, the inductive power-gathering module is disposed in an integrated acquisition unit separate from the main control unit, and the integrated acquisition unit also integrates at least one electrical parameter sensor.

[0015] Preferably, the smart spacer also includes a BeiDou RTK antenna, which is disposed outside the housing and connected to the main control unit for acquiring the spacer's position information; And / or, the communication module supports at least two of the following communication methods: 4G, 5G, LoRa, Wi-Fi, and Bluetooth; And / or, the power supply module further includes a solar charging module, which is disposed outside the housing and connected to the main control unit for auxiliary power supply and energy storage; And / or, the edge processing module can perform abnormal data identification, feature extraction and data compression processing, and transmit the monitoring data to an external terminal or platform through the communication module.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention achieves effective energy complementarity by integrating current transformer induction power, solar power, and vibration energy harvesting into a multi-source self-powering scheme. This ensures that the monitoring nodes can work continuously and stably under various extreme conditions, including power outages, continuous rain, and no wind. It solves the reliability shortcomings of the single power supply method in the existing technology, realizes true long-term autonomous operation, and has extremely high power supply reliability.

[0017] 2. This invention employs a dual-link redundant long-distance transmission architecture, primarily using OPGW optical fiber and supplemented by 4G or 5G public networks. When the primary link fails, it automatically switches to the backup link, fundamentally solving the problem of data loss across the entire network due to a single point of failure in the backbone transmission link. This ensures the continuity and integrity of critical monitoring data and provides extremely high data transmission reliability. By performing edge computing at the front end, the amount of invalid data transmitted is significantly reduced, effectively lowering the bandwidth pressure on the wireless ad hoc network and the communication power consumption of nodes. Combined with a highly reliable self-powered system, this significantly reduces operation and maintenance costs.

[0018] 3. Based on wireless self-organizing network technology, this invention can build a dedicated monitoring and communication network in a vast, uninhabited area without public network signals, realizing comprehensive and real-time perception of line status. Attached Figure Description

[0019] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a schematic diagram of the system architecture provided in an embodiment of the present invention; Figure 2 This is a block diagram of the intelligent spacer functional module provided in an embodiment of the present invention; Figure 3 A schematic diagram of the intelligent spacer structure provided in an embodiment of the present invention; Figure 4 A flowchart illustrating the method provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of signaling interaction timing provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of a system deployment scenario provided in an embodiment of the present invention; Figure 7 This is a schematic diagram of a power transmission line condition monitoring communication network provided in an embodiment of the present invention; Figure 8 This is a schematic diagram of the structure of a smart spacer. Figure 9 Layout diagram of external components of the main control unit; Figure 10This is a schematic diagram of the structure of a standard spacer bar; Figure 11 A partial decomposition diagram of the main control unit; Figure 12 This is a flowchart of the online monitoring method.

[0020] Explanation of reference numerals in the attached figures: 1-Integrated acquisition unit; 2-Split conductor; 3-Online monitoring spacer body; 31-Standard spacer; 32-Fixing frame; 33-Main control unit; 34-Rain, wind speed and direction sensor; 35-Sunlight sensor; 331-Face cover; 332-Bottom shell; 333-Adjusting flange; 334-Lower compartment; 335-BeiDou RTK antenna; 336-Communication antenna assembly; 337-Camera; 338-Infrared camera; 339-Temperature, humidity and air pressure sensor; S101 - Obtaining electrical energy through the inductive power extraction module; S102 - Acquiring electrical, image, and environmental data of the line; S103 - Processing and fusing data by the main control unit; S104 - Remotely transmitting data through the multi-mode communication module; S100 - Deploy smart spacer bars; S200 - Build a wireless self-organizing network; S300 - Collect multi-source monitoring data; S400 - Perform edge computing processing; S500 - Transmit data through the primary backbone link; S600 - Determine if the primary link is functioning correctly; S700 - Switch to the backup backbone link for transmission; S800 - The central master station receives and analyzes the data. Detailed Implementation

[0021] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the scope of protection of the present invention.

[0022] Example 1 This embodiment provides a specific implementation of a method for constructing a self-powered redundant communication transmission line network coverage in typical uninhabited environments (such as the Gobi Desert). The scheme demonstrates the complete process of deploying intelligent network nodes, constructing a wireless ad hoc network, achieving multi-source fusion self-powering, performing edge computing, and utilizing a dual-link redundancy architecture for highly reliable long-distance data transmission.

[0023] Please see Figure 6This figure is a schematic diagram of the system deployment scenario according to an embodiment of this application. In a vast uninhabited area, multiple transmission towers are distributed along the transmission line corridor. On the overhead transmission lines between these towers, multiple smart spacers serving as intelligent network nodes are installed. These smart spacers are interconnected via wireless communication links, forming a dedicated monitoring and communication network covering the entire line, and ultimately transmitting the collected and processed data to the central master station at the rear.

[0024] Figure 1 The system architecture of this application embodiment is shown in further detail. Logically, the architecture can be divided into three parts: the field network segment, the remote transmission network segment, and the central master station.

[0025] The field network segment is the core area for data generation and initial aggregation. This network segment is based on multiple intelligent network nodes deployed along the overhead transmission line; in this embodiment, these nodes are specifically intelligent spacers. Depending on their role in the network, these intelligent spacers can be divided into ordinary relay nodes and more powerful regional gateways. The main task of relay nodes is to collect data and relay it as a link in the network. Regional gateways, in addition to possessing all the functions of relay nodes, also integrate communication modules for accessing backup backbone links. Various monitoring sensors on the line, such as those monitoring conductor temperature, vibration, and micro-meteorological parameters, transmit raw monitoring data to the nearest intelligent spacer (relay node or regional gateway) via short-range wireless communication methods (such as Bluetooth or low-power wireless technology). The intelligent spacers communicate with each other via a long-range wireless communication technology; in this embodiment, LoRa technology in the 1.4 GHz band is used to construct a distributed wireless self-organizing network. It can be understood that this network is a decentralized mesh network that supports multi-hop relay transmission of data between nodes.

[0026] The long-distance transmission network segment is responsible for transmitting data aggregated from the field network to the central master station over long distances with high reliability. As an optional implementation, this embodiment employs a dual-link redundant long-distance transmission architecture to address potential single-point failures in the backbone link. This architecture includes one primary backbone link and one backup backbone link. Specifically, the primary backbone link is preferably an OPGW fiber optic link laid along the transmission line, which has advantages such as high bandwidth, stable transmission, and strong anti-interference capabilities. At designated transmission towers (e.g., Figure 1 At the end closest to the central master station, a special intelligent spacer with optical access capability is deployed. This node integrates an optoelectronic conversion unit, which can convert electrical signal data in the wireless ad hoc network into optical signals and connect them to the OPGW fiber optic link. The backup backbone link uses a 4G or 5G public network link. At locations farther from the fiber optic access point or at key locations in the network topology, a regional gateway is deployed, which integrates a 4G or 5G communication module.

[0027] The central master station is the core of the entire monitoring system and is typically deployed in a monitoring center or substation. It consists of high-performance servers, large-capacity storage devices, and professional monitoring and analysis software. It is responsible for receiving, storing, processing, and displaying all monitoring data transmitted from the front-end network, and providing a human-machine interface for maintenance personnel. It supports remote configuration, status monitoring, fault diagnosis, and software upgrades of front-end devices.

[0028] Figure 4 The specific execution steps of the method provided in the embodiments of this application are clearly illustrated in the form of a flowchart.

[0029] Step S100: Deploy Smart Spacer Bars. On a 500 kV four-split overhead transmission line traversing the Gobi Desert, suitable installation locations are selected based on the site survey results. To ensure network connectivity and signal strength, a smart spacer bar is typically installed on the conductor every 3 to 5 towers (in this embodiment, every 4 towers, with a physical distance of approximately 2 kilometers). All deployed smart spacer bars must meet stringent industrial-grade standards, such as having an IP67 protection rating, being able to operate stably in a wide temperature range of -40℃ to 85℃, and being able to withstand wind speeds of at least 35 m / s.

[0030] Step S200: Construct a wireless ad hoc network. After all smart spacers are powered on, their internal communication aggregation modules (see...) Figure 2 The network automatically initiates the networking process. In this embodiment, the communication aggregation module uses LoRa technology as the basis for the physical and link layers, operating in the licensed 1.4 GHz frequency band to reduce interference. To efficiently utilize limited channel resources and avoid data collisions, the network employs TDMA (Time Division Multiple Access) technology. Specifically, the system divides time into several time slots and allocates fixed transmission time slots to each node, ensuring that only one node transmits data on a specific channel at any given time. Furthermore, to achieve network flexibility and robustness, the network layer adopts the AODV (Adaptive On-Demand Distance Vector) routing protocol. When a node needs to transmit data, it broadcasts a routing request. Other nodes in the network dynamically calculate the optimal path to the destination based on the request and their own routing table information. This protocol supports the automatic discovery of new available paths when a node fails or link quality degrades, thereby achieving network fault self-healing and dynamic topology reconfiguration. Experimental data shows that the network's self-healing and reconfiguration time after a single point of failure is less than 30 seconds.

[0031] TDMA (Time Division Multiple Access) technology: After a node successfully joins the network, it receives a time slot allocation response data packet broadcast by the gateway. This packet contains the time slot period T, the time slot start point t0, the time slot length l, and the static time slot number i assigned to the node. Therefore, the node's transmission time t in the k-th period...i It can be calculated using a specific formula: t i =t0+(i-1)*2l+k*T. This formula ensures that each node wakes up and sends data precisely within its own time window. AODV (Adaptive Routing Virtualization) protocol: Nodes on active routes periodically broadcast Hello messages to their neighbors to confirm link connectivity. If a node continuously loses Hello messages or receives a link-layer transmission failure report, it determines that the link is broken. This node generates a routing error message and sends it to all potentially affected "predecessor nodes" that depend on this link. Upon receiving a RERR (Redirect Error Response), the source node will re-initiate the route discovery process to find a new available path.

[0032] Step S300: Collect multi-source monitoring data. Multi-source sensing modules deployed on smart spacers (see...) Figure 2 The module begins operation. In this embodiment, the module integrates at least three types of sensors: an infrared sensor for non-contact measurement of the temperature of the conductor or clamp; a six-axis attitude sensor for real-time monitoring of the conductor's vibration frequency, amplitude, and galloping trajectory to provide early warning of conductor fatigue and galloping risks; and a visible light camera for periodically capturing images of the transmission line or its surrounding environment or taking pictures upon receiving instructions, allowing for manual assessment of any abnormalities such as external damage or hanging objects. The data collected by these sensors forms the basis for a comprehensive evaluation of the line's condition.

[0033] Step S400: Perform edge computing processing. The raw monitoring data collected, especially continuous temperature, vibration, and image data, is typically very large. To reduce the bandwidth consumption of the wireless ad hoc network and the communication power consumption of the nodes, the edge computing module built into the smart spacer performs localized preprocessing on this data. This process mainly includes: 1. Data filtering: filtering out obviously invalid or redundant data. For example, for temperature data, if the values ​​collected multiple times are within the normal range and the changes are minimal (e.g., less than 0.1℃), they are not recorded; 2. Data compression: using efficient compression algorithms to process the valid data (such as images) that need to be uploaded to reduce its size; 3. Abnormal event identification: the edge computing module has preset judgment thresholds and logical models for various abnormal events. For example, when the temperature of the wire clamp detected by the infrared sensor exceeds the preset threshold of 80℃, or when the temperature change rate exceeds 5℃ / minute in a short period of time, the system determines it as a "temperature abnormality" event. At this time, the edge computing module generates a structured alarm data, which includes core information such as event type, occurrence time, node location, and key values. Thus, compared to transmitting massive amounts of raw data streams, this solution only uploads refined event information when an anomaly occurs, thereby reducing the amount of data transmitted by several orders of magnitude.

[0034] Edge computing processing includes filtering, compressing, and identifying abnormal events in monitoring data, specifically: The data filtering algorithm performs noise reduction and cleaning on two types of data: time-series sensing data and image data. For time-series data, a combination of moving average, median filtering, and 3σ threshold filtering is used to remove electromagnetic interference, pulse spikes, and extreme invalid values. For image data, a 3×3 lightweight Gaussian filter is used to remove noise while retaining core features such as circuits and hardware. The overall filtering efficiency is ≥95%, and the execution time per run is ≤5ms with almost no additional computing power overhead.

[0035] The data compression algorithm is a hierarchical adaptive design that balances data availability and compression ratio. Time-series numerical data uses differential coding + lightweight Huffman coding to achieve lossless compression with a compression ratio of ≥60%. Image / video data uses JPEG-LS near-lossless compression + ROI region of interest cropping to remove redundant background data, reducing the data volume by more than 70%. The compression ratio can also be dynamically adjusted according to the energy storage capacity and network signal to adapt to narrowband transmission requirements.

[0036] The abnormal event recognition algorithm is based on lightweight edge AI inference. Temporal numerical anomalies are detected by the 3σ criterion + isolated forest algorithm to identify sudden changes in parameters such as temperature, vibration, and current. Visual image anomalies are inferred using the YOLO model after improved INT8 quantization to identify problems such as foreign objects hanging on wires and hardware failures. The confidence threshold is ≥0.85. In low power mode, visual recognition can be turned off and the inference frequency can be reduced.

[0037] Step S500: Transmit data via the primary backbone link. Data processed by edge computing (whether regular status data packets or high-priority alarm data) is transmitted tier by tier to the preset fiber optic access node via a wireless ad hoc network, using the path selected by the AODV protocol. At this node, the data is converted into optical signals and transmitted at high speed and stably to the central master station via the OPGW fiber optic link.

[0038] Step S600: Determine if the primary link is functioning correctly. The fiber optic access node periodically communicates with the central master station via heartbeat to confirm the connectivity of the OPGW fiber optic link. If no confirmation response is received from the central master station within a preset time (e.g., 30 seconds), or if data transmission fails continuously, the system determines that the primary backbone link has failed.

[0039] Step S700: Switch to backup backbone link transmission. Once the primary link is determined to be faulty, the routing protocol of the wireless ad hoc network will automatically reconfigure, and the data stream will be directed to the smart spacer acting as the area gateway. This area gateway will immediately activate its built-in 4G or 5G communication module, establish a connection with the central master station through the 4G or 5G public network link, and upload the cached and subsequently received data through this backup link.

[0040] Step S800: The central master station receives and analyzes the data. After receiving the data, the central master station decodes and stores it, and displays it in real time on the monitoring interface. For alarm data, the system will automatically trigger an audible and visual alarm and push notifications to relevant maintenance personnel.

[0041] To support the long-term autonomous operation of the above method, the smart spacer in this embodiment adopts a multi-source fusion self-powering scheme. Please refer to... Figure 2 The self-powered module of the intelligent spacer is its core component, which integrates three energy harvesting units based on different physical principles: CT Inductive Power Supply Unit: The core of this unit is an open-type current transformer, which is directly attached to the transmission line. When alternating current flows through the line, this unit utilizes the principle of electromagnetic induction to extract energy from the alternating magnetic field surrounding the line. To adapt to the significant current variations in transmission lines from light to heavy loads, this unit has been specially optimized to effectively extract power across a wide current range from 5 amps to 1000 amps, serving as the primary power source for the equipment.

[0042] Solar power harvesting unit: within the main casing of the smart spacer (see...) Figure 3 The device is equipped with high-efficiency photovoltaic panels. In this embodiment, the photovoltaic panels used have a photoelectric conversion efficiency of not less than 18%. Under good daylight conditions, the solar power unit can independently power the equipment and charge excess electrical energy into the energy storage system, serving as an important energy supplement during power outages or at night.

[0043] Vibration / Grace Energy Harvesting Unit: Under wind conditions, conductors experience high-frequency light vibrations or low-frequency, large-amplitude galloping. This unit incorporates a piezoelectric or electromagnetic energy harvesting device to convert this mechanical vibration energy into electrical energy. While its power output is typically lower than the former two, in extreme conditions of no light and power outages (i.e., no induced current), it can provide the basic power needed to maintain minimum standby and communication capabilities, provided there is wind.

[0044] The electrical energy obtained from these three energy harvesting methods is uniformly dispatched by a single intelligent energy management unit and stored in a hybrid energy storage system composed of supercapacitors and solid-state batteries. The supercapacitors provide power for scenarios requiring instantaneous high current, such as communication module startup, while the solid-state batteries handle long-term energy storage, and their excellent low-temperature performance ensures normal operation even at extreme temperatures of -40°C. This "three-source complementary" energy harvesting scheme, combined with the hybrid energy storage system, ensures a continuous and reliable power supply for the intelligent spacer under various foreseeable operating conditions, including normal line operation, power outage maintenance, continuous rain, and windless weather. This achieves the design goal of continuous operation for over 30 days without external power, and the system's mean time between failures (MTBF) exceeds 10,000 hours.

[0045] A multi-source fusion self-powered scheme is adopted to power the intelligent network nodes. This scheme integrates at least two energy harvesting units based on different physical principles, including electromagnetic induction, light energy, and mechanical energy harvesting. The electrical energy from these harvesting units is stored in the hybrid energy storage system after being scheduled by the intelligent energy management unit. The algorithm first collects energy harvesting, energy storage, load, and environmental parameters at different levels through a condition perception layer. After noise reduction via moving average filtering, it provides basic data for decision-making. The energy harvesting decision layer first determines the effectiveness of each unit's power supply, defaulting to CT induction as the primary power source. Then, it dynamically adjusts the priority of energy harvesting units based on special conditions such as line outages / light loads, continuous rain, and conductor vibration. The energy scheduling layer follows the principles of direct supply priority and storage-use balance, with three modes: direct energy harvesting, combined energy harvesting and storage, and energy storage-only supply. When the power supply is insufficient, a three-level low-power mode is triggered, shutting down non-core modules step by step and prioritizing core monitoring and communication functions. The energy storage management layer sets differentiated charging and discharging thresholds based on the characteristics of hybrid energy storage, monitors the health status in real time, and provides lifespan warnings. The fault tolerance layer achieves self-detection of energy harvesting / storage unit faults through continuous threshold determination. When a fault occurs, the module is quickly isolated, alarms are sent, and emergency power supply schemes are switched to avoid system paralysis caused by a single point of failure.

[0046] Figure 3 The physical structure of the intelligent spacer in this embodiment is shown. Its main outer shell is made of a high-strength, corrosion-resistant alloy material, and integrates all the aforementioned functional modules. Four wire clamps securely mount the device onto the four-split wires while maintaining the spacing between the split wires. Heat sinks designed on the outer shell utilize air convection to effectively dissipate heat generated by the internal electronic components, ensuring stable operation even under high temperatures and direct sunlight in summer. Furthermore, as a preferred implementation, the internal structure of the intelligent spacer can adopt a modular design. For example, self-powered modules and communication aggregation modules can be designed as independent units supporting hot-swapping, thereby simplifying on-site maintenance. When a module fails, maintenance personnel only need to replace the corresponding module.

[0047] Figure 5 The sequence diagram vividly illustrates a typical alarm reporting interaction process. When a smart spacer initiates a data collection request to the monitoring sensor and receives the raw data, its internal edge computing module processes it. If an anomaly is detected, an alarm message is generated. This message is transmitted via LoRa multi-hop, passing through other smart spacers, and finally reaches the area gateway. Depending on the link status, if the main link (OPGW) is normal, the area gateway uploads the data to the central master station via the OPGW fiber optic link; if the main link is abnormal, it automatically switches to a 4G or 5G public network link for uploading. Upon receiving the data, the central master station returns a data confirmation, thus completing a full alarm reporting process.

[0048] Reference Figure 3 The intelligent spacer in this embodiment mainly comprises two functional parts: an integrated acquisition unit 1 and an online monitoring spacer body 3. In actual deployment, the integrated acquisition unit 1 and the online monitoring spacer body 3 are securely mounted on one or more split conductors 2 of the power transmission system via their respective clamps (not shown in the figure). Split conductors 2 are a common conductor configuration in high-voltage or ultra-high-voltage transmission lines, consisting of multiple sub-conductors; the device in this application is designed to adapt to such line environments. The integrated acquisition unit 1 and the online monitoring spacer body 3 are electrically connected via a cable with good insulation and shielding performance for transmitting electrical energy and data signals. It is understood that this split design physically separates the part responsible for inductive power extraction and high-voltage signal acquisition from the main control part responsible for precision monitoring and data processing, thereby helping to reduce electromagnetic interference and improve the stability and safety of the entire system.

[0049] Further reference Figure 8 This figure shows a detailed structural diagram of the main body 3 of the online monitoring spacer. The core structure of the main body 3 of the online monitoring spacer includes a standard spacer 31, a fixing frame 32, and a main control unit 33. The standard spacer 31 serves as the mechanical foundation of the device and possesses the functions of a traditional spacer, namely, maintaining a fixed safe distance between the split conductors 2 to prevent short circuits caused by wind-induced vibrations. The standard spacer 31 is typically made of metal or composite materials, possessing sufficient mechanical strength and weather resistance. The fixing frame 32 is a specially designed clamp or support structure, its function being to securely mount the main control unit 33 at the center or predetermined position of the standard spacer 31. The design of the fixing frame 32 must ensure that the main control unit 33 remains stable even under harsh environments such as long-term wind vibration and icing. The main control unit 33, as the "brain" of the entire monitoring system, integrates data processing, communication, and multiple sensing functions.

[0050] The intelligent spacer also includes a communication module and an edge processing module; the main control unit is connected to the edge processing module and the communication module; the antenna of the communication module is located outside the housing to enable data interaction between the main control unit and external terminals or platforms; the edge processing module is integrated with the main control unit or is set independently inside the housing to process the monitoring data collected by the multi-source sensor components.

[0051] An edge processing module typically consists of a main control chip, a storage unit, and a signal conditioning circuit, working with built-in algorithms to perform data preprocessing and intelligent recognition. The edge processing module is a unit that performs real-time processing of raw data such as images, meteorological data, and electrical parameters directly on the spacer bar, without uploading everything to the backend. It primarily performs anomaly detection, feature extraction, data compression, and filtering, only transmitting key alarms and valid data through the communication module, thereby reducing transmission pressure, power consumption, and improving response speed.

[0052] To further clarify the core innovations of this application, the following will combine... Figure 9 , Figure 10 , Figure 11 Please provide an explanation. Figure 9 The layout of the external components of the main control unit 33 is shown, and Figure 11 Its key adjustable structure is clearly revealed in the form of an exploded diagram.

[0053] The main control unit 33 has a robust and sealed housing, which is precisely assembled from multiple parts, including a front cover 331, a bottom cover 332, and a lower compartment 334. In the context of this application, the bottom cover 332 can be understood as the first housing part, and the lower compartment 334 as the second housing part. As a preferred embodiment, these housing components can be made of high-strength, corrosion-resistant metal materials (such as aluminum alloy) or engineering plastics, and are fastened with screws. Silicone sealing rings are used at the joints to achieve a high protection rating, such as IP67 or IP68, ensuring that the internal precision electronic components are protected from rain, dust, and moisture.

[0054] A key technical feature of this embodiment lies in the length adjustment mechanism disposed between the first housing portion (bottom shell 332) and the second housing portion (lower compartment 334). Specifically, this length adjustment mechanism can be embodied as a set of interchangeable adjusting flanges 333 with different preset lengths. Figure 11As shown, the adjusting flange 333 is an annular or cylindrical connector. This application provides various specifications with different axial lengths, such as a short adjusting flange with a length of 30 mm and a long adjusting flange with a length of 70 mm. During actual installation, on-site technicians can select the most suitable adjusting flange length based on the diameter of the standard spacer 31 to be installed and the required field of vision. For example, if the standard spacer 31 is thick, it may obstruct the view below. In this case, a long adjusting flange can be used and installed between the bottom shell 332 and the lower compartment 334. This causes the lower compartment 334 to extend downwards relative to the bottom shell 332, allowing the image acquisition module mounted on the lower compartment 334 to move downwards as well. Its monitoring field of vision can then completely extend beyond the lower edge of the standard spacer 31, providing unobstructed observation of icing, foreign object suspension, or hardware conditions below the conductor. Conversely, if the spacer is thin, or to reduce the windward area and avoid corona discharge, a short adjusting flange can be used. Understandably, this modular and replaceable design greatly improves the device's versatility in installation and the effectiveness of monitoring.

[0055] The main control unit 33 integrates an image acquisition module for visual monitoring of the transmission line and its surrounding environment. Specifically, this image acquisition module includes a camera 337 mounted on the lower compartment 334 and an infrared camera 338 mounted on the bottom shell 332. Camera 337 is typically a visible light camera with a resolution of 1080P or higher, used to acquire clear color images during the day to observe the detailed condition of components such as conductors, insulators, and fittings. The infrared camera 338 is used for imaging at night or in low-light conditions. More importantly, it can sense temperature distribution by detecting infrared radiation from object surfaces, thus enabling non-contact detection of abnormal heating caused by poor contact at line connection points, clamps, etc., achieving early warning of faults. Mounting camera 337 on the adjustable lower compartment 334 ensures that its critical observation view below the line is not obstructed.

[0056] The device's energy supply is ensured by an inductive power extraction module located inside the integrated acquisition unit 1. Its working principle involves using an open or closed current transformer fitted onto the transmission line 2. When alternating current flows through the line 2, the secondary coil of the transformer induces a current according to the principle of electromagnetic induction. This current is then rectified, regulated, and stored in a circuit (typically including a power board and a backup battery) to generate a stable and reliable DC power supply for the main control unit 33 and all sensors. It should be noted that this method of obtaining energy from the transmission line itself solves the power supply problem for field monitoring devices, thus ensuring long-term, maintenance-free operation of the system.

[0057] As an optional implementation, the integrated acquisition unit 1 can also integrate other sensors for monitoring line electrical parameters, in addition to the inductive power extraction module. For example, a conductor temperature sensor can be integrated to directly measure the operating temperature of the conductor; a conductor current sensor can also be integrated to accurately measure the load current of the conductor. These data are crucial for assessing the line's load level and safety margin.

[0058] Reference Figure 12 This figure is a flowchart of an online monitoring method provided in an embodiment of this application, showing the complete working process of the device. The process begins with step S101: obtaining electrical energy through the inductive power extraction module. Once the device is installed on the energized transmission line 2, the inductive power extraction module in the integrated acquisition unit 1 starts working, continuously inductively extracting electrical energy from the line 2 to power the entire system. Subsequently, step S102 is executed: acquiring line electrical, image, and environmental data. After obtaining a stable power supply, the main control unit 33 is activated and begins to schedule the various sensors integrated on it to work. The line temperature sensor and line current sensor in the integrated acquisition unit 1 begin to measure the real-time temperature and current values ​​of the line and transmit the data to the main control unit 33 through the cable. At the same time, the image acquisition module on the main control unit 33 starts working, and the camera 337 and infrared camera 338 acquire visible light images and infrared thermal images of the line according to preset strategies such as timed snapshots, event triggering, or remote commands. Next, step S103 is executed: the main control unit processes and fuses the data. The main control unit 33 contains a high-performance integrated control board, including a microprocessor and memory. This control board receives data from all sensors, performs preliminary processing, formatting, timestamping, and data fusion on this multi-source heterogeneous data. For example, it can correlate temperature, current, visible light images, and infrared images from the same moment to form a complete data packet. Finally, step S104 is executed: data is remotely transmitted via a multi-mode communication module. The processed and packaged data is wirelessly transmitted to a remote monitoring center server via the communication board inside the main control unit 33 and the external communication antenna assembly 336. Personnel at the monitoring center can then monitor the line's operating status in real time and perform remote inspections.

[0059] In summary, this embodiment solves the problem of camera field of view being obstructed by spacers of different specifications by adopting a replaceable adjustable flange 333 structure, realizes effective monitoring of key areas under the line, and achieves long-term stable energy self-sufficiency through inductive power supply, providing a reliable technical means for intelligent operation and maintenance of transmission lines.

[0060] This embodiment integrates multiple micro-meteorological sensors. An integrated rainfall, wind speed, and wind direction sensor 34 and a solar radiation sensor 35 can be installed on the upper structure of the standard spacer bar 31. These sensors are used to measure wind speed, wind direction, rainfall, and solar radiation intensity around the line, respectively. These are key parameters for analyzing conductor deflection, galloping, and assessing the impact of severe weather. Additionally, a compact temperature, humidity, and air pressure sensor 339 can be integrated on the side of the main control unit 33's base shell 332 or lower compartment 334 to measure the ambient temperature, relative humidity, and atmospheric pressure around the equipment.

[0061] Example 2 This embodiment provides a method for network coverage of overhead transmission lines in uninhabited areas based on intelligent spacers. It solves the problem of how to build a fully covered, highly reliable, and self-powered transmission line monitoring and communication network in complex terrain environments of uninhabited areas using intelligent spacers, so as to realize real-time perception of line status, rapid fault location, and remote operation and maintenance management.

[0062] Overhead power transmission lines in uninhabited areas often traverse complex terrains such as mountains, deserts, and Gobi, where public network communication signal coverage is completely lacking. Traditional monitoring equipment faces the following prominent problems: a) High operation and maintenance costs: Traditional monitoring equipment relies on independent 4G channels, requiring high data traffic fees, and equipment fault location is difficult, resulting in high on-site inspection and maintenance costs; b) Poor link reliability: Single communication links are susceptible to interference in extreme environments, leading to unstable data transmission and the risk of losing critical monitoring data; c) Difficulty in ensuring power supply: Uninhabited areas lack mains power supply, and traditional battery-powered solutions experience a sharp decline in performance at temperatures as low as -40℃, making it difficult to meet the requirements for long-term stable operation; d) Limited monitoring dimensions: Existing monitoring methods mainly target single parameters such as conductor temperature and icing, lacking the comprehensive perception capability of multi-dimensional information such as conductor galloping, micro-meteorology, and channel visualization.

[0063] This embodiment is based on a multi-technology integrated network coverage scheme using intelligent spacers, which integrates OPGW fiber optics, wireless communication, self-powering and other technologies to achieve full-scene monitoring and data transmission of lines in uninhabited areas, effectively solving the above-mentioned technical problems.

[0064] The implementation objectives of this embodiment are shown in Table 1.

[0065] Table 1 Core Technical Indicators

[0066] I. Core Functional Design of Intelligent Spacer Bars

[0067] This embodiment uses intelligent spacers as the core nodes for network coverage, integrating four core functions: communication aggregation, sensing and monitoring, self-powering, and edge computing.

[0068] This embodiment adopts an integrated structure resistant to extreme environments. Designed for high-altitude, coastal, and windy regions, it incorporates a spacer bar body structure with anti-icing, corrosion resistance, and strong vibration resistance functions, as detailed below: a. Modular cavity design: Optimizes the bonding method between the integrated acquisition unit and the wire, improves stability under heavy loads, and adapts to the modification needs of different types of spacers.

[0069] b. Drawer-type modular structure: Sensors, communication modules, and energy storage components can be independently hot-swapped, and the cavity sealing and electromagnetic shielding structure are optimized to reduce the difficulty of on-site operation and maintenance.

[0070] c. Integrated anti-fighting and spacing functions: It integrates a double-pendulum anti-fighting device and a star-shaped damping device, which improves anti-fighting performance and energy harvesting efficiency while ensuring the basic functions of the spacer bar.

[0071] d. Extreme environment sealing protection: It adopts waterproof silicone rings and corrosion-resistant coatings, combined with fin design and hollow sunshade to optimize heat dissipation path, meet IP67 protection level, and is suitable for operation in a wide temperature range of -40℃ to 85℃.

[0072] II. Design of multi-source sensing capabilities.

[0073] This embodiment integrates multiple types of sensors to construct a multi-dimensional perception system of "line status - environmental parameters - potential faults", as shown in Figure 2.

[0074] Table 2 Multi-source sensing sensor configuration

[0075] III. Communication Capability Design.

[0076] This embodiment incorporates a multi-protocol adaptive communication module, supporting flexible networking in complex environments: a. Multi-protocol support: The device integrates 4G or 5G cellular communication, 1.4G (LoRa) low-power wide area network, and 2.4G, ZigBee, Wi-Fi, and Bluetooth short-range wireless communication protocols, making it compatible with multiple standards and adaptable to different monitoring scenarios.

[0077] b. TDMA (Time Division Multiple Access): Time division multiple access technology is used to achieve orderly communication among multiple nodes, avoid channel conflicts, and improve spectrum utilization efficiency.

[0078] c. Adaptive routing algorithm: dynamically adjusts the transmission path, supports low-latency multi-level relay, and the latency of a single-level relay is less than 10ms.

[0079] d. Flexible RF antenna: Optimize the installation position and shape of the flexible antenna to improve signal transmission stability, while adapting to the complex structure of the spacer bar.

[0080] IV. Self-powered capability design.

[0081] This embodiment integrates multiple energy harvesting technologies to achieve continuous power supply in extreme environments: a. CT induction power supply: CT induction power supply is adopted at the high-voltage conductor. The design features a wide-range induction structure and power compensation circuit, which is suitable for light load / no-load low current scenarios (5A~1000A).

[0082] b. Vibration Energy Harvesting: Utilizing the energy from conductor dancing or wind vibration, the energy harvester's mechanical transmission structure (gear transmission) is optimized to achieve efficient capture of vibration energy.

[0083] c. Solar power generation: Equipped with high-efficiency photovoltaic panels with a photoelectric conversion efficiency of ≥18%, forming a synergistic and complementary relationship with inductive power generation.

[0084] d. Intelligent energy management: Based on the power consumption requirements of the sensing module and communication module, the energy allocation priority is dynamically adjusted to extend the device's battery life and the lifespan of energy storage components.

[0085] V. Three-layer network architecture design.

[0086] like Figure 7 As shown, this embodiment adopts a three-layer architecture of "field network segment - remote transmission network segment - central master station" to achieve full-link connectivity of data acquisition, transmission and processing.

[0087] 1. On-site network segment.

[0088] This embodiment uses smart spacers as communication aggregation nodes to construct a distributed self-organizing network: a. Node deployment: The monitoring equipment connects to the spacer via Wi-Fi / LoRa / ZigBee / Bluetooth, and one relay-type smart spacer is set up every 5 towers (approximately 2000 meters).

[0089] Phase 1: Data Acquisition and Access (Network Edge).

[0090] Various sensors deployed on power transmission lines (such as temperature, vibration, and image sensors) need to upload data.

[0091] Bluetooth / Wi-Fi is used for direct device connections over extremely short distances and with high bandwidth. For example, inspection personnel can use handheld terminals or drones near poles to quickly upload high-definition images or large amounts of data to the nearest smart spacer via Wi-Fi. The advantages are high speed and versatility; the disadvantages are extremely limited coverage (typically <200 meters) and high power consumption.

[0092] In this architecture, LoRa serves as one of the primary access protocols for field-organized networks. Distributed, low-power sensors can connect to smart spacers spanning several kilometers via LoRa. Its advantages include long transmission distance, extremely low power consumption, and strong anti-interference capabilities; its disadvantage is low data transmission rate.

[0093] At this stage, the system functions as a "multi-protocol access gateway." The multi-protocol module built into the smart spacer can simultaneously receive signals from Bluetooth / Wi-Fi (high-speed near-field) and LoRa (far-field low-power). This resolves the contradiction that a single protocol cannot simultaneously meet the access requirements of "high-speed near-field" and "low-power far-field."

[0094] The wireless mesh network uses 1.4G (LoRa) / 2.4G omnidirectional antennas to achieve multi-hop transmission, forming a wireless mesh network with a point-to-point single-hop communication distance of ≥4km (with clear line of sight).

[0095] Phase 2: Multi-level jump transmission along the line.

[0096] This is the core of the invention. The intelligent spacer relays the collected local sensor data and its own status data to the regional gateway node through a wireless mesh network constructed along the power transmission line.

[0097] One of the protocols uses LoRa (with an omnidirectional antenna) as the primary physical layer protocol for hop transmission. This allows the wireless signal of a single smart spacer to cover a 360-degree radius around it. As a direct result, each node can establish potential wireless connections with multiple neighboring nodes within line of sight (potentially including spacers in front, behind, to the left, right, and even across the line corridor), and the network topology evolves from a "chain" into a dynamic "net".

[0098] The multiple access and scheduling technology employs TDMA (Time Division Multiple Access). The system allocates specific communication time slots to each smart spacer on the line, and all nodes take turns transmitting data within a precise schedule. This avoids wireless collisions caused by multiple nodes transmitting simultaneously, ensuring determinism and real-time performance in long, chain-like networks.

[0099] The routing protocol uses AODV (Self-Organizing On-Demand Distance Vector) as its core intelligent routing technology. AODV is a typical on-demand routing protocol, and its workflow is as follows: (1) Route discovery (on demand): When a smart spacer needs to send data but there is no valid route, it will broadcast a route request packet.

[0100] (2) Path establishment: After receiving the message, the neighboring node either establishes a reverse path or continues broadcasting until the RREQ reaches the target node (such as the area gateway). The target node then unicasts a route reply through the established reverse path.

[0101] (3) Route maintenance: Nodes monitor the next hop of active routes through periodic "Hello" messages or link-layer notifications. If a link breaks, the upstream node will send a route error message and may trigger a new route discovery process.

[0102] The advantages of LoRa directional transmission are ultra-long distance, low power consumption, and strong diffraction, perfectly matching the characteristics of long-distance and terrain-crossing power transmission lines, and its cost is far lower than microwave. Its disadvantage is extremely low bandwidth, making it unsuitable for transmitting large amounts of data such as video.

[0103] The introduction of TDMA+AODV compensates for the shortcomings of LoRa, such as collisions and uncertain latency, after multi-hop networking, and upgrades a simple LoRa link into a controllable, reliable, and self-healing industrial-grade private network.

[0104] c. Data aggregation: Data from each monitoring node is aggregated to the relay-type intelligent spacer, preprocessed at the edge, and then uploaded in a unified manner.

[0105] 2. Remote transmission network segment.

[0106] This embodiment uses OPGW optical fiber as the backbone communication link to achieve reliable long-distance transmission.

[0107] a. Photoelectric conversion: An optical modem is installed at the OPGW opening connector of the pole to achieve photoelectric conversion, supporting active / passive optical network adaptation to different transmission needs.

[0108] b. Network access: Data is transmitted to the central main station via the power private network or 4G or 5G public network through the substation, achieving seamless coverage of the "last mile".

[0109] c. Redundancy backup: Supports dual-link redundancy of fiber optic and wireless links, automatically switching in case of single-link failure to ensure communication continuity.

[0110] Data is transmitted via multi-level LoRa hops and ultimately converges to several pre-selected "regional gateway" smart spacers. These gateway nodes need to transmit all the converged data back to the monitoring center hundreds or even thousands of kilometers away at high speed and reliably.

[0111] Data transmission: The regional gateway, which aggregates data along the route, packages the data and transmits it to the remote monitoring center via its built-in 4G module in the form of standard IP data packets, through the operator's base station and core network, via the Internet or APN leased line.

[0112] Advantages of 4G wireless backhaul: extremely fast and flexible deployment, high independence. The installation location of the area gateway depends only on the cellular network signal strength and power supply convenience, and it can be quickly deployed on poles or sites with basic conditions, greatly shortening the construction cycle.

[0113] Extensive network coverage: In remote areas with carrier cellular network coverage (even weak coverage), this solution can take effect immediately and enable rapid activation.

[0114] The biggest drawback of 4G wireless backhaul is that bandwidth, latency, and stability are limited by the public network.

[0115] Ongoing operating costs: These generate continuous traffic charges, and for large amounts of sensor data, especially high-traffic services such as high-definition video, the long-term operating costs can be very considerable.

[0116] 3. Central Main Station.

[0117] It consists of a monitoring server and a decision server, enabling data storage, analysis, large-screen display, and command issuance.

[0118] a. Data storage: Supports long-term storage of massive monitoring data and historical data retrieval.

[0119] b. Intelligent analysis: Based on a multi-source data fusion analysis model, improve the accuracy of abnormal state judgment and reduce false alarms and missed alarms.

[0120] c. Remote operation and maintenance: Supports remote equipment configuration, parameter calibration, fault warning and software upgrade.

[0121] VI. Communication technology optimization scheme.

[0122] This embodiment configures a multi-mode communication strategy based on the characteristics of the uninhabited area environment.

[0123] 1. Static broadband self-organizing network.

[0124] Suitable for real-time broadband data transmission scenarios, such as high-definition video surveillance and online inspection. Nodes maintain a long-term connection, dynamically adjust the transmission path, support low-latency multi-level relay, and achieve bandwidths of 100-1000Mbps.

[0125] 2. Dynamic self-organizing network.

[0126] Nodes are normally in sleep mode, but are woken up dynamically by AI recognition or on-demand triggering to establish transmission links. This is suitable for non-real-time monitoring scenarios, such as timed status reporting and abnormal event-triggered reporting, and can significantly reduce system power consumption.

[0127] 3. Low-power multi-hop IoT communication.

[0128] Employing narrowband communication technologies such as LoRa, it transmits small to medium-sized data at regular intervals. With extremely low overall power consumption, it can operate solely by inductive power, making it suitable for low-frequency data acquisition scenarios such as micro-meteorological data and conductor temperature monitoring.

[0129] 4. Anti-interference design.

[0130] To address complex electromagnetic environments, the following anti-interference measures are adopted: a. OFDM modulation technology: It adopts orthogonal frequency division multiplexing modulation to improve spectral efficiency and anti-multipath interference capability.

[0131] b. End-to-end encryption: Employs a dedicated power encryption protocol and device authentication mechanism to ensure transmission and storage security.

[0132] c. Electromagnetic shielding: Optimize the circuit design of the sensing unit to suppress the interference of high voltage electric field and electromagnetic radiation on the acquired signal.

[0133] VII. Power Supply Guarantee Plan.

[0134] In view of the lack of mains power in uninhabited areas, this embodiment adopts a three-level power supply mode of "main supply + backup + energy storage".

[0135] 1. Main power supply.

[0136] The high-voltage conductor uses CT induction power extraction. To address the issue of low current when the transmission line is lightly loaded or unloaded, a wide-range induction power extraction structure is designed, which is paired with a power compensation circuit. The power extraction range covers 5A~1000A, improving the stability of power extraction.

[0137] 2. Backup power supply.

[0138] The system is equipped with solar photovoltaic panels to complement inductive power supply. When inductive power is insufficient (such as during power outages for maintenance), it automatically switches to solar power to ensure continuous operation of the equipment.

[0139] 3. Energy storage system High and low temperature resistant supercapacitors and solid-state batteries are selected, and a compact mounting structure and overcharge and over-discharge protection circuits are designed. a. Supercapacitor: Supports high-current charging and discharging, has a long cycle life, and is suitable for short-time high-power output scenarios; b. Solid-state batteries: high energy density, low self-discharge rate, suitable for long-term energy storage scenarios; c. Status monitoring: Real-time monitoring of energy storage element performance parameters, with fault early warning and remaining life prediction functions.

[0140] 4. Energy-saving strategies.

[0141] Employing a device sleep-wake mechanism, the wireless AP goes into sleep mode when there is no data transmission, with only the ultra-low power RF module operating, reducing overall power consumption by more than 50%. Power supply priority is dynamically allocated through an intelligent energy management algorithm, and the energy storage components have a lifespan of ≥8 years.

[0142] VIII. Data Processing and Security Solutions.

[0143] 1. Edge computing.

[0144] The intelligent spacer bar performs data filtering, noise reduction, and anomaly identification locally, uploading only critical fault data to reduce transmission bandwidth usage. Based on locally acquired current, attitude, and image data, it enables real-time identification and location of anomalies such as conductor faults, galloping, and icing.

[0145] 2. Data encryption.

[0146] Employing a power-specific encryption protocol and device authentication mechanism ensures the security of monitoring data during transmission and storage, and complies with smart grid data security standards. End-to-end encrypted transmission is supported to prevent data eavesdropping or tampering.

[0147] 3. Self-healing faults.

[0148] The network supports dynamic topology reconfiguration, automatically switching to a backup transmission path when a single node fails to avoid data loss. The self-organizing network reconfiguration time is less than 30 seconds, and the network self-healing success rate is greater than 99%.

[0149] 4. Data compression.

[0150] Data compression and anomaly filtering are implemented locally on the spacer bar. Edge-side data compression and preprocessing algorithms are used to reduce transmission bandwidth usage and improve data transmission efficiency.

[0151] IX. Implementation Steps and Key Control Points

[0152] 1. Preliminary preparation stage.

[0153] a. On-site survey: Verify the distribution of poles and towers, topography, and OPGW fiber optic layout, and determine the installation location of smart spacers and the location of repeater nodes (prioritize high-altitude locations to ensure visible transmission).

[0154] b. Equipment selection: Confirm that the intelligent spacer bar, optical modem, sensors and other equipment meet the requirements of wide temperature range (-40℃~85℃), electromagnetic interference resistance, IP67 protection and other requirements.

[0155] c. Solution refinement: Optimize the network topology based on the survey results, and clarify the configuration of communication protocol switching thresholds, energy management parameters, etc.

[0156] 2. Equipment deployment phase.

[0157] a. OPGW Optical Modem Installation: Secure the optical modem to the OPGW open junction box on the pole, ensuring proper sealing and protection, and a secure optical interface connection. Power is supplied by an inductive power supply combined with solar power. The optical modem uses industrial-grade optical communication equipment (such as industrial optical transceivers, industrial Ethernet switches, small ONUs, etc.), with signals extracted via T-connections or by using spare fiber cores within the junction box. The equipment is typically installed on a specially designed bracket or in an equipment box on the pole.

[0158] b. Installation of intelligent spacer: The spacer is installed by drone under power or by high-altitude operation, and fixed at the designated position on the conductor. The integrated acquisition unit is closely attached to the conductor, and the directional antenna is aligned with the direction of the adjacent relay node.

[0159] c. Monitoring equipment access: Wirelessly pair video surveillance, micro-meteorological sensors, tilt sensors and other equipment with the smart spacer to complete equipment registration and parameter configuration.

[0160] 3. Debugging and optimization phase.

[0161] a. Network Debugging: Activate the self-organizing network function, test node connection status, transmission latency, bandwidth, and other indicators, and adjust antenna angle and communication parameters. b. Power Supply Testing: Simulate extreme environments (low light, no vibration) to verify the continuous operation capability of the power supply system and the energy storage switching efficiency. c. Data Verification: Check the integrity and accuracy of various monitoring data acquisitions and transmissions, and test the response speed of commands issued by the central master station. d. Redundancy Testing: Artificially simulate a single node failure to verify network topology reconstruction and data redundancy backup functions.

[0162] 4. Trial operation phase.

[0163] a. Trial Operation Monitoring: A 30-day trial operation will be conducted, continuously monitoring network stability, equipment operating status, and power supply reliability. b. Parameter Optimization: Based on the trial operation data, parameters such as energy management algorithms and communication switching thresholds will be optimized to improve system adaptability.

[0164] 10. Quality control requirements.

[0165] Table 3 Quality Control Indicators

[0166] The method in this embodiment has a good coverage effect. This technology aims to solve the coverage problem of specific "no signal areas". It can achieve "full coverage" within the project area, with no signal blind spots, and supports a decentralized self-organizing network with multiple nodes.

[0167] The method in this embodiment has high operating efficiency, real-time uploading of monitoring data, fault warning response time of less than 5 minutes, and a 50% extension of the line inspection cycle.

[0168] The method in this embodiment has low cost, saves public network traffic costs, reduces on-site maintenance workload by 80%, and extends equipment lifespan to ≥8 years.

[0169] The method in this embodiment has high reliability, with a mean time between failures (MTBF) of ≥10,000 hours and a network self-healing success rate of 100%.

[0170] The method in this embodiment enables regular monitoring, allowing users to view parameters such as equipment operating status, energy storage capacity, and communication quality through the central master station, and generate a monthly operation and maintenance report.

[0171] The method in this embodiment can handle faults in a timely manner. After receiving a fault warning, it prioritizes remote diagnosis and debugging. When on-site handling is required, it relies on mobile terminals to access the self-organizing network to carry out precise operation and maintenance.

[0172] The method in this embodiment can achieve periodic calibration, remotely calibrating the sensor accuracy and communication parameters every year, and performing performance testing on the energy storage components every 3 years.

[0173] The method in this embodiment enables remote upgrades and supports online debugging of spacer monitoring accuracy and communication parameters via a cloud platform, without the need for on-site equipment disassembly.

[0174] This invention provides a method for network coverage of overhead transmission lines in uninhabited areas, belonging to the field of power transmission and distribution and IoT monitoring technology. This method aims to solve the problems of insufficient power supply and data transmission reliability in existing transmission line monitoring systems in uninhabited areas. The method includes: deploying multiple intelligent network nodes along the overhead transmission line and constructing a distributed wireless ad hoc network; using a multi-source fusion self-powering scheme that integrates at least two different physical principle energy harvesting units to power the nodes; having the nodes collect monitoring data and perform edge computing processing to reduce data volume; and transmitting the processed data via multi-hop relay through the wireless ad hoc network and then via a dual-link redundant remote transmission architecture including primary and backup backbone links to the central master station. This invention significantly improves the power supply and data transmission reliability of the monitoring system in the extreme environment of uninhabited areas through multi-source fusion self-powering and dual-link redundant transmission, and reduces system power consumption and operation and maintenance costs through edge computing, achieving comprehensive and long-term autonomous monitoring of the line status.

[0175] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method for covering an overhead transmission line network in an uninhabited area, characterized in that, Includes the following steps: Multiple smart network nodes are deployed along the overhead transmission line; each smart network node is equipped with a hybrid energy storage system consisting of supercapacitors and solid-state batteries, and a distributed wireless mesh self-organizing network is constructed among the multiple smart network nodes through LoRa wireless communication; the distributed wireless mesh self-organizing network combines TDMA time division multiple access technology and AODV adaptive routing protocol. The intelligent network node is powered by a multi-source fusion self-powered module, which includes at least two energy harvesting units based on different physical principles. The intelligent network node collects monitoring data of the overhead transmission line and performs edge computing processing on the collected monitoring data; the intelligent network node is an intelligent spacer bar, and the intelligent spacer bar adopts a modular structure that supports hot-swappable modules; The monitoring data processed by edge computing is transmitted via the wireless ad hoc network through multi-hop relay and then aggregated to the central master station via a dual-link redundant remote transmission architecture. The dual-link redundant remote transmission architecture includes a primary backbone link and a backup backbone link.

2. The method for covering an overhead transmission line network in an uninhabited area according to claim 1, characterized in that, The multi-source fusion self-powered module includes at least two of the following: a CT sensing energy harvesting unit, a solar energy harvesting unit, and a vibration energy harvesting unit.

3. The method for covering overhead transmission line networks in uninhabited areas according to claim 1, characterized in that, The primary backbone link is an OPGW fiber optic link, and the backup backbone link is a 4G or 5G public network wireless link.

4. The method for covering an overhead power transmission line network in an uninhabited area according to claim 1, characterized in that, The primary backbone link is a long-distance microwave link, and the backup backbone link is a satellite communication link.

5. The method for covering overhead transmission line networks in uninhabited areas according to claim 1, characterized in that, The edge computing processing includes filtering, compressing, and identifying abnormal events in the monitoring data.

6. The method for covering an overhead transmission line network in an uninhabited area according to claim 5, characterized in that, The abnormal event identification is achieved through an artificial intelligence model deployed on the intelligent network node, used to identify abnormal intruders in or around the overhead transmission line.

7. The method for covering overhead transmission line networks in uninhabited areas according to claim 1, characterized in that, The intelligent spacer includes: a shell, a main control unit, a multi-source sensor assembly, a length adjustment mechanism, and a power supply module; The outer casing includes a first housing portion and a second housing portion that cooperate with each other, and a mounting cavity is formed between the first housing portion and the second housing portion; The main control unit is located inside the mounting cavity and is connected to the multi-source sensor assembly, the length adjustment mechanism, and the power supply module, respectively, for receiving, processing, and transmitting monitoring data; The multi-source sensor assembly includes at least three of the following: an image acquisition module, an electrical parameter sensor, an environmental sensor, and an attitude sensor. The image acquisition module is disposed on the second housing portion, and the other sensors are disposed inside the mounting cavity or outside the housing. The multi-source sensor assembly is used to collect multi-dimensional monitoring information of the power transmission line and its surroundings. The length adjustment mechanism is disposed between the first housing part and the second housing part, and is used to adjust the extension distance of the second housing part relative to the first housing part, thereby adjusting the installation position and monitoring field of view of the image acquisition module; The power supply module includes an inductive power extraction module, which is used to obtain electrical energy from the transmission line to provide working power for all components of the spacer bar.

8. The method for covering an overhead power transmission line network in an uninhabited area according to claim 7, characterized in that, The intelligent spacer also includes a communication module and an edge processing module; The main control unit is connected to the edge processing module and the communication module; The antenna of the communication module is located outside the housing and is used to enable data interaction between the main control unit and an external terminal or platform. The edge processing module is integrated with the main control unit or is set independently in the housing, and is used to process the monitoring data collected by the multi-source sensor components.

9. The method for covering an overhead power transmission line network in an uninhabited area according to claim 7, characterized in that, The length adjustment mechanism is a set of flanges with different preset lengths that can be replaced and installed, or a threaded telescopic sleeve mechanism. And / or, the image acquisition module includes a visible light camera and an infrared camera, used to acquire visible light images and infrared thermal images of the transmission line, respectively; And / or, the electrical parameter sensor includes at least one of a wire temperature sensor, a wire current sensor, and a fault waveform sensor; And / or, the environmental sensor includes at least one of a rainfall, wind speed and wind direction sensor, a sunshine sensor, a temperature and humidity sensor, and a barometric pressure sensor; And / or, the attitude sensor is used to monitor the installation attitude and displacement of the spacer itself; And / or, the inductive power-gathering module is disposed in an integrated acquisition unit separate from the main control unit, and the integrated acquisition unit also integrates at least one electrical parameter sensor.

10. The method for covering an overhead transmission line network in an uninhabited area according to claim 8, characterized in that, The intelligent spacer also includes a BeiDou RTK antenna, which is located outside the housing and connected to the main control unit to obtain the spacer's position information. And / or, the communication module supports at least two of the following communication methods: 4G, 5G, LoRa, Wi-Fi, and Bluetooth; And / or, the power supply module further includes a solar charging module, which is disposed outside the housing and connected to the main control unit for auxiliary power supply and energy storage; And / or, the edge processing module can perform abnormal data identification, feature extraction and data compression processing, and transmit the monitoring data to an external terminal or platform through the communication module.

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