A power-off and power-on alarm active reporting system and method

Abstract

This invention discloses a proactive reporting system and method for power outage and restoration alarms. The system includes: a Terminal Sensing Unit (STA), deployed in low-voltage terminal equipment, for real-time acquisition of power grid signals and local detection and reporting of power outage events; a Regional Management Node (PCO), deployed at low-voltage branch boxes or meter boxes, for receiving events reported by subordinate Terminal Sensing Units, performing regional aggregation and branch-level analysis; and a Core Master Node (CCO), deployed at distribution transformer terminals (TTUs) or concentrators, for receiving events reported by Terminal Sensing Units, performing multi-source verification across the entire network, and generating alarm information to report to the master station. The Terminal Sensing Units, Regional Management Nodes, and Core Master Nodes are sequentially connected to form a three-level collaborative edge analysis architecture. Implementing this invention can improve the timeliness and reliability of distribution network fault detection, as well as the efficiency of proactive repair.

Description

Technical Field

[0001] This invention relates to the field of power outage and restoration monitoring technology in power distribution networks, and in particular to a system and method for actively reporting power outage and restoration alarms. Background Technology

[0002] In the traditional low-voltage distribution area power outage and restoration monitoring model, centralized analysis by the master station has long been the mainstream solution. In this model, the terminal devices are only responsible for collecting raw data such as voltage and current; all event judgment, logical analysis, and scope definition rely on the master station system. This architecture has the following problems: First, the communication link between the terminal devices and the master station is susceptible to power grid fluctuations and signal attenuation, resulting in high data transmission latency and delayed alarm response; second, uploading all the raw data from a massive number of terminals to the master station overloads its computing resources, leading to low analysis efficiency; third, relying solely on data from a single terminal lacks multi-dimensional verification, resulting in significant false alarms and missed alarms, making it difficult to meet the real-time and reliability requirements of proactive emergency repairs in the distribution network. Summary of the Invention

[0003] The present invention aims to solve the above-mentioned technical problems and provide a system and method for proactively reporting power outage and restoration alarms, thereby improving the timeliness and reliability of power distribution network fault detection and the efficiency of proactive emergency repairs.

[0004] The present invention adopts the following technical solution. As one aspect of the present invention, it provides a power outage and restoration alarm active reporting system, which includes: The Terminal Sensing Unit (STA) is deployed in low-voltage terminal equipment to collect power grid signals in real time and perform local detection and reporting of power outage events. The regional management node (PCO) is deployed at the low-voltage branch box or meter box to receive events reported by subordinate end sensing units and perform regional aggregation and branch-level analysis. The core master node (CCO) is deployed in the intelligent distribution transformer terminal (TTU) or concentrator in the distribution area. It is used to receive events reported by the end sensing units, perform multi-source verification across the entire network, and generate alarm information to report to the master station. The terminal sensing unit, regional management node, and core master node are sequentially connected to form a three-level collaborative edge analysis architecture.

[0005] Preferably, the end-sensing unit includes: The power supply module uses a supercapacitor backup power supply and a bidirectional DC-DC converter to achieve microsecond-level power supply switching when the power grid fails, and maintain operation for at least 5 seconds. The programmable logic device module is used to acquire AC voltage zero-crossing pulse signals in real time and trigger a preliminary alarm when no valid signal is detected for a continuous preset period. The level detection module is used to detect the level of the plugged-in and unplugged pins of the terminal sensing unit to distinguish between power grid outages and terminal faults. The voltage RMS monitoring module is used to generate a formal power outage event when the voltage is lower than a preset threshold for a set period of time. The lightweight model module is used to dynamically adjust the detection threshold based on historical data and combine multi-dimensional features to perform power outage event fusion judgment.

[0006] Preferably, the area management node includes: The regional event cache table module is used to record power outage event information reported by subordinate end-point sensing units; The regional topology relationship table module is used to clarify the subordinate branches and table box levels of the subordinate end sensing units; The branch-level power outage assessment module is used to initiate a branch-level power outage assessment when the number or proportion of end sensing units reporting power outages in the same meter box or branch exceeds a preset threshold. The abnormal event identification module is used to distinguish between single-household faults and single-point grounding events of the line by combining historical fault records, status of surrounding nodes, meteorological and load data.

[0007] Preferably, the core master node includes: The event time verification module is used to verify the integrity of the event reporting timestamp; The multi-source data cross-validation module is used to integrate terminal operating status, real-time meter voltage, marketing records and topology data to perform network-wide event verification. The structured alarm generation module is used to organize alarm data according to the dual topology model and report it to the main station; The power restoration verification module is used to combine the power restoration signals, repair work order progress, and load trends reported by the end sensing units / regional management nodes to judge and warn of the power restoration status of the entire network.

[0008] Preferably, it further includes: The automatic topology identification module is deployed in the regional management node and the core master node. It is used to automatically construct and dynamically update the four-level topology relationship of "transformer-branch-meter box-user" based on feature signal injection, dual feature matching and multi-dimensional verification. The automatic topology identification module supports three triggering mechanisms: new equipment coming online, line modification, and periodic inspection, and has conflict resolution and closed-loop verification functions.

[0009] As another aspect of the present invention, a method for actively reporting power outage and restoration alarms is also provided, which includes the following steps: The terminal sensing unit (STA) performs local power outage detection, uses a multi-dimensional fusion judgment mechanism to generate power outage events and reports them to the regional management node (PCO). The regional management node receives power outage events reported by its subordinate STAs, performs regional aggregation and branch-level analysis, and generates an aggregated event report to be reported to the core master node (CCO). The core master node receives aggregated events reported by the regional management nodes, performs multi-source verification across the entire network, generates structured alarm information, and reports it to the master station. During the power restoration phase, the terminal sensing unit, regional management node, and core master node work together to collect power restoration signals, perform regional pre-judgment, and verify the entire network to achieve accurate judgment of the power restoration status.

[0010] Preferably, the step of the terminal sensing unit performing local power outage detection includes: Real-time acquisition of AC voltage zero-crossing pulse signals; triggering a preliminary alarm when no valid signal is detected continuously. The system detects the voltage level of the STA's own plugged-in / plugged-out pins. If the voltage level is lower than the preset threshold, it is confirmed that the power grid is out of service. Monitor the effective value of the voltage. When the voltage is lower than the danger threshold and remains below it for a set time, generate an early warning. When the voltage returns to zero and remains below it for a set time, generate a formal power outage event. The detection threshold is dynamically adjusted by combining a lightweight model, and zero-crossing signals and harmonic features are integrated for multi-dimensional judgment.

[0011] Preferably, the steps for the regional management node to perform regional aggregation and branch-level analysis include: Establish a regional event cache table to record events reported by subordinate end-point sensing units; When the number or proportion of end-sensing units reporting power outages within the same meter box or branch exceeds a preset threshold, branch-level power outage analysis is initiated. Actively scan the end sensing units that have not reported events. If there is no response or the returned voltage is within the power outage determination range, then the branch is confirmed to be out of power. By combining historical fault records, the status of surrounding nodes, and meteorological and load data, abnormal events can be identified and the distinction between individual household faults and line problems can be made.

[0012] Preferably, the core master node performs multi-source verification across the entire network, including: Verify the event reporting timestamp, and replace it with the current system time in case of an anomaly; Integrate terminal operating status, real-time meter voltage, marketing records, and topology data for multi-dimensional cross-validation; By combining horizontal comparison with vertical penetration analysis, the scope of the power outage can be accurately defined. By combining structured and unstructured data, fault cause analysis and optimal repair plan generation are performed.

[0013] Preferably, it also includes an automatic topology identification and update step: The core master node sends a clock synchronization signal to the regional management node, and the regional management node generates a dual characteristic current pulse to inject into the branch line; The end-sensing unit captures feature pulses and extracts feature parameters, which are then reported to the regional management node for dual feature matching and multi-dimensional verification. The regional management node determines the branch affiliation of the end sensing unit, and the core master node integrates and constructs a four-level topology table and synchronizes it to the master station. When the network structure changes, a topology update process is triggered to compare old and new data, resolve conflicts, and perform closed-loop verification.

[0014] Implementing the embodiments of the present invention has the following beneficial effects: This invention provides a proactive reporting system and method for power outage and restoration alarms. It adopts an "edge collaboration + intelligent judgment" model. Specifically, it uses a three-level architecture of "STA (Terminal Sensing Unit) - PCO (Regional Management Node) - CCO (Core Master Node)" to realize local detection, regional aggregation and network-wide verification of power outage events. Combined with power restoration judgment and automatic topology identification, it forms a complete, accurate and efficient proactive reporting system for power outages and restorations.

[0015] In this invention, a three-level edge collaborative architecture is implemented: the traditional centralized judgment of the main station is decentralized to the three-level nodes of STA, PCO and CCO, so as to realize local second-level perception, regional aggregated judgment and network-wide multi-source verification, which greatly reduces the burden on the main station and communication latency.

[0016] It can realize an intelligent power outage judgment mechanism: STA adopts a multi-dimensional fusion judgment of "zero crossing signal + plug-in / plug-out pin level + voltage threshold + lightweight model", combined with dynamic threshold adjustment and abnormal event recognition, to reduce false alarms from the source.

[0017] And to achieve hierarchical and progressive verification of power restoration: By combining the multi-dimensional power restoration signals collected by STA / PCO, and through PCO regional pre-judgment and CCO full-network multi-source verification, accurate judgment and early warning of power restoration status can be achieved.

[0018] It can automatically identify and dynamically update the topology: based on feature signal injection, dual feature matching, multi-dimensional verification and conflict resolution, it can automatically construct and dynamically update the four-level topology of "transformer-branch-meter box-user", and support adaptive network structure changes.

[0019] This enables multi-source data fusion and intelligent analysis: CCO integrates structured and unstructured data (such as weather, work orders, and inspection reports), and combines large models and causal reasoning algorithms to achieve advanced functions such as fault cause analysis and optimal repair plan generation. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, obtaining other drawings based on these drawings without creative effort still falls within the scope of the present invention. Figure 1 This is a schematic diagram of the structure of an embodiment of a power outage / restoration alarm active reporting system provided by the present invention; Figure 2 for Figure 1 A schematic diagram of the mid-end sensing unit (STA); Figure 3 for Figure 1 A schematic diagram of the structure of the regional management node (PCO); Figure 4 for Figure 1 A schematic diagram of the structure of the core master node (CCO); Figure 5 This is a schematic diagram of the main flow of an embodiment of the active reporting method for power outage and restoration alarms provided by the present invention; Figure 6 This is a flowchart illustrating the overall power outage alarm process involved in the method provided by the present invention. Figure 7 A flowchart illustrating the lightweight model detection process used in the method provided by this invention; Figure 8 This is a flowchart illustrating the process of determining the cause of a power outage in the method provided by the present invention. Figure 9 This is a flowchart illustrating the intelligent identification process for abnormal events in the method provided by the present invention. Figure 10 A flowchart is generated for the optimal emergency repair scheme involved in the method provided by this invention. Figure 11 This is a flowchart illustrating the power restoration judgment process used in the method provided by the present invention. Figure 12 This is a flowchart illustrating the initial topology construction process involved in the method provided by the present invention; Figure 13 This is a flowchart of the multi-parameter acquisition and interference filtering of the terminal signal involved in the method provided by the present invention; Figure 14 The flowchart of dual feature matching and multidimensional verification judgment involved in the method provided by the present invention; Figure 15 This is a flowchart illustrating the dynamic topology update process involved in the method provided by the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings.

[0022] like Figure 1 The diagram shown illustrates a structural schematic of an embodiment of a power outage / restoration alarm proactive reporting system provided by the present invention. (In conjunction with...) Figures 2 to 4 As shown, in this embodiment, the power outage / restoration alarm proactive reporting system includes: The Terminal Sensing Unit (STA) 1 is deployed in low-voltage terminal equipment to collect power grid signals in real time and perform local detection and reporting of power outage events. It serves as the original sensing unit for power outage events. The regional management node (PCO)2 is deployed at the low-voltage branch box or meter box to receive events reported by subordinate end sensing units and perform regional aggregation and branch-level analysis. Core Master Node (CCO) 3 is deployed in the intelligent distribution transformer terminal (TTU) or concentrator in the distribution area. It is used to receive events reported by the end sensing unit, perform multi-source verification across the entire network, and generate alarm information to report to the master station. It can be understood that as the main communication node of the entire network, Core Master Node (CCO) 3 is responsible for uplink connection to the master station and downlink management area management node (PCO) / end sensing unit (STA).

[0023] In this invention, a step-by-step reporting path of STA→PCO→CCO is adopted. STA events are first aggregated by PCO and then forwarded to CCO.

[0024] like Figure 2 As shown, in a specific example, the end sensing unit (STA) 1 includes: Power supply module 10 uses a supercapacitor backup power supply and a bidirectional DC-DC converter to achieve microsecond-level power supply switching when the power grid fails, and maintain operation for at least 5 seconds. Programmable logic device module 11 is used to acquire AC voltage zero-crossing pulse signals in real time and trigger a preliminary alarm when no valid signal is detected for a continuous preset period. Level detection module 12 is used to detect the level of the plugged-in and unplugged pins of the terminal sensing unit to distinguish between power grid outages and terminal faults; The voltage RMS monitoring module 13 is used to generate a formal power outage event when the voltage is lower than a preset threshold and continues for a set time. The lightweight model module 14 is used to dynamically adjust the detection threshold based on historical data and combine multi-dimensional features to perform power outage event fusion judgment.

[0025] like Figure 3 As shown, in a specific example, the area management node (PCO) 2 includes: The regional event cache table module 20 is used to record power outage event information reported by subordinate end sensing units; The regional topology relationship table module 21 is used to clarify the subordinate branches and table box levels of the subordinate end sensing units; The branch-level power outage judgment module 22 is used to initiate the branch-level power outage judgment when the number or proportion of end sensing units reporting power outages in the same meter box or branch exceeds a preset threshold. The abnormal event identification module 23 is used to distinguish between single-household faults and single-point grounding events of the line by combining historical fault records, status of surrounding nodes, meteorological and load data.

[0026] like Figure 4 As shown, in a specific example, the core master node (CCO) 3 includes: Event time verification module 30 is used to verify the integrity of the event reporting timestamp; The multi-source data cross-validation module 31 is used to integrate terminal operating status, real-time meter voltage, marketing records and topology data to perform network-wide event verification. The structured alarm generation module 32 is used to organize alarm data according to the dual topology model and report it to the main station; The power restoration verification module 33 is used to combine the power restoration signals, emergency repair work order progress, and load trends reported by the end sensing unit / regional management node to judge and warn of the power restoration status of the entire network.

[0027] Furthermore, this system also includes: The automatic topology identification module is deployed in the regional management node and the core master node. It is used to automatically construct and dynamically update the four-level topology relationship of "transformer-branch-meter box-user" based on feature signal injection, dual feature matching and multi-dimensional verification. The automatic topology identification module supports three triggering mechanisms: new equipment coming online, line modification, and periodic inspection, and has conflict resolution and closed-loop verification functions.

[0028] like Figure 5 The diagram illustrates the main flow of an embodiment of a power outage / restoration alarm proactive reporting method provided by the present invention. In this embodiment, it employs the following... Figures 2 to 4 To implement the described system, the method includes the following steps: Step S10: The terminal sensing unit (STA) performs local power outage detection, generates a power outage event using a multi-dimensional fusion judgment mechanism, and reports it to the regional management node (PCO). Step S11: The regional management node receives the power outage events reported by its subordinate STAs, performs regional aggregation and branch-level analysis, and generates an aggregated event report to be reported to the core master node (CCO). Step S12: The core master node receives the aggregated events reported by the regional management node, performs multi-source verification across the entire network, generates structured alarm information, and reports it to the master station. In step S13, during the power restoration phase, the terminal sensing unit, regional management node, and core master node work together to collect power restoration signals, perform regional pre-judgment, and verify the entire network to achieve accurate judgment of the power restoration status.

[0029] In a specific example, step S10, in which the end sensing unit performs local power outage detection, includes: Real-time acquisition of AC voltage zero-crossing pulse signals; triggering a preliminary alarm when no valid signal is detected continuously. The system detects the voltage level of the STA's own plugged-in / plugged-out pins. If the voltage level is lower than the preset threshold, it is confirmed that the power grid is out of service. Monitor the effective value of the voltage. When the voltage is lower than the danger threshold and remains below it for a set time, generate an early warning. When the voltage returns to zero and remains below it for a set time, generate a formal power outage event. The detection threshold is dynamically adjusted by combining a lightweight model, and zero-crossing signals and harmonic features are integrated for multi-dimensional judgment.

[0030] In a specific example, step S11, where the regional management node performs regional aggregation and branch-level analysis, includes the following steps: Establish a regional event cache table to record events reported by subordinate end-point sensing units; When the number or proportion of end-sensing units reporting power outages within the same meter box or branch exceeds a preset threshold, branch-level power outage analysis is initiated. Actively scan the end sensing units that have not reported events. If there is no response or the returned voltage is within the power outage determination range, then the branch is confirmed to be out of power. By combining historical fault records, the status of surrounding nodes, and meteorological and load data, abnormal events can be identified and the distinction between individual household faults and line problems can be made.

[0031] In a specific example, step S12, in which the core master node performs multi-source verification across the entire network, includes: Verify the event reporting timestamp, and replace it with the current system time in case of an anomaly; Integrate terminal operating status, real-time meter voltage, marketing records, and topology data for multi-dimensional cross-validation; By combining horizontal comparison with vertical penetration analysis, the scope of the power outage can be accurately defined. By combining structured and unstructured data, fault cause analysis and optimal repair plan generation are performed.

[0032] Furthermore, this method also includes an automatic topology identification and update step: The core master node sends a clock synchronization signal to the regional management node, and the regional management node generates a dual characteristic current pulse to inject into the branch line; The end-sensing unit captures feature pulses and extracts feature parameters, which are then reported to the regional management node for dual feature matching and multi-dimensional verification. The regional management node determines the branch affiliation of the end sensing unit, and the core master node integrates and constructs a four-level topology table and synchronizes it to the master station. When the network structure changes, a topology update process is triggered to compare old and new data, resolve conflicts, and perform closed-loop verification.

[0033] To further understand the system and method provided by this invention, the following will be combined with Figures 6 to 15 This invention provides a detailed description of each branch process and its corresponding deployment.

[0034] like Figure 6 The diagram shown illustrates the overall flowchart of a power outage alarm in an example. Wherein: I. Power Outage Alarm The STA features localized detection and utilizes a built-in supercapacitor backup power supply. A bidirectional DC-DC converter enables a rapid 10μs switching between grid power and backup power, ensuring at least 5 seconds of operation after a power outage to complete event encoding and reporting, preventing event loss due to terminal power failure. After reporting, the STA automatically enters a low-power sleep state, maximizing backup power efficiency.

[0035] Method 1: Rapid Initial Screening of Zero-Crossing Signals: The STA has a built-in programmable logic device that collects the zero-crossing pulse signal of AC voltage in real time. The periodic zero-crossing characteristic of AC power is a core indicator of normal grid operation. When no valid zero-crossing pulse is detected for a consecutive preset period, an abnormal voltage is immediately determined, triggering the initial alarm process.

[0036] Pin level fault isolation: After initially determining an abnormal voltage, the STA checks the voltage level of its own plugged-in / plugged-out pins. If the pin level is lower than a preset threshold (e.g., 1.5V), it is confirmed that the external power grid is down; if the level is normal, it is determined to be an internal problem such as poor module contact or its own fault, and the event is directly filtered out without being reported to the superior. This effectively distinguishes between "power grid outage" and "terminal fault," reducing false alarms at the source.

[0037] Final confirmation of effective voltage threshold: For the initially screened effective abnormal events, the STA further monitors the effective value of the A-phase voltage. When the voltage is lower than the preset danger threshold (e.g., 150V) for 3 seconds, it is marked as a "high-risk power outage state" and an early warning message is pushed; when the voltage returns to zero and lasts for 200ms, a formal power outage event is generated, and key data such as the event occurrence time, unique equipment identifier, and voltage drop curve are recorded simultaneously.

[0038] For the threshold, the system learns the characteristics of power outages under different operating conditions based on historical data (such as voltage fluctuation patterns during peak load periods in rural power grids and harmonic interference characteristics in urban power grids) and automatically adjusts the detection threshold.

[0039] The STA collects two types of core data and binds them to operating condition / scenario labels: first, operating condition data such as voltage, harmonics, and load; second, tagged data such as actual power outages and misjudged events. Simultaneously, it extracts "operating condition identification features" and "power outage judgment features" to provide data support for model learning. Cloud-based pre-training combined with edge incremental learning utilizes a large cloud-based model pre-trained on full-network data to establish general operating condition-threshold mapping rules, such as lowering peak thresholds at the end of rural power grids and maintaining thresholds for harmonic scenarios in urban power grids with enhanced verification. These rules are then distributed to the STA. During STA operation, incremental learning is initiated for misjudged or new operating condition events to optimize and adapt threshold parameters to the personalized operating conditions of the local distribution area. The lightweight STA model dynamically adjusts thresholds and verifies multiple features. It first identifies real-time operating conditions (such as peak hours at the end of rural power grids and harmonic interference in urban power grids), then retrieves the corresponding optimal threshold; subsequently, it performs multi-dimensional fusion judgment by combining voltage thresholds, zero-crossing signals, and harmonic features.

[0040] To avoid threshold adjustment deviations in individual STAs, the PCO periodically summarizes the threshold adjustment records and judgment effects of its subordinate STAs. If the misjudgment rate of a certain STA is significantly higher than that of other STAs in the same branch, the CCO will trigger collaborative calibration. The CCO will send the optimal threshold reference value under the same operating conditions to that STA to help it optimize model parameters and ensure the consistency of threshold adjustment within the region.

[0041] Method 2: Collect basic data such as zero-crossing signals and RMS voltage values, as well as multi-dimensional features such as current waveforms, harmonic content, and temperature, and input them into a lightweight model. The model automatically distinguishes between real power outages, instantaneous voltage dips, harmonic interference, and module faults using a pre-trained power grid fault feature library, outputting accurate event determination results. Specifically... Figure 7 As shown.

[0042] PCO (Power Control Center) regional analysis: As a regional management node deployed at branch boxes and meter boxes, the PCO aggregates and analyzes event information from multiple subordinate STAs to determine branch-level power outages. Furthermore, the PCO is also equipped with a supercapacitor backup power supply, enabling it to maintain operation and continue event aggregation and forwarding even after a power outage in its assigned area, ensuring uninterrupted edge-side analysis.

[0043] Multi-STA event batch aggregation: The PCO receives power outage events from all subordinate STAs in real time, establishes a regional event cache table, and records information such as the event occurrence time, equipment location, and voltage status for each STA.

[0044] Branch-level power outage threshold determination: The PCO has a built-in regional topology table that clearly defines the branches and meter box levels to which subordinate STAs belong. When the number of STAs reporting power outages in the same meter box exceeds a preset number, or when the proportion of STAs reporting power outages in the same branch exceeds 80%, the PCO automatically initiates branch-level power outage analysis. At this time, the PCO actively retrieves voltage data from STAs in that branch that have not reported events. If there is no response or the returned voltage value is within the power outage determination range of 0-132V, then a regional power outage is confirmed to have occurred in that branch, and an aggregated event report is generated.

[0045] The PCO forwards the aggregated event report (including branch number, outage range, event start time, number of affected STAs, etc.) to the CCO, along with the call results of STAs that did not report, providing complete data support for the CCO's network-wide verification.

[0046] It is understood that the method provided in this invention has the following extension point: Data such as the reporting time series, voltage drop curves, and topological locations of STAs within the input area are combined with pre-trained fault type-feature maps (e.g., a line short circuit manifests as multiple STAs simultaneously losing power and the voltage instantly dropping to zero; a switch tripping manifests as a batch of STAs within a branch losing power and the voltage steadily decreasing) to preliminarily determine the cause of the power outage, such as "branch line short circuit," "branch switch tripping," or "meter box incoming line fault," and the inference results are synchronized to the CCO. Please refer to [link / reference] for details. Figure 8 The flowchart shown illustrates the process of determining the cause of a power outage.

[0047] like Figure 9 The diagram illustrates the intelligent anomaly event identification flowchart of the present invention. Specifically, the second extension point here is intelligent anomaly event identification: for isolated STAs reporting power outages, the system combines the STA's historical fault records and the status of surrounding nodes to determine whether it is a single-household equipment fault or a single-point grounding issue such as poor contact at the branch end, avoiding invalid alarms caused by a single terminal anomaly. The analysis is performed from four dimensions: first, the voltage of surrounding nodes; if the surrounding voltage is normal, it tends to be a single-household fault; if there is a slight drop, it tends to be a single-point grounding issue; second, historical fault characteristics, combining the STA's past fault patterns to increase the confidence level of the judgment; third, meteorological and line environment; in thunderstorms and old line scenarios, line grounding is prioritized; fourth, load current data; a surge in load causing a trip points to a single-household overload, while a stable load causing a power outage points to a line problem. For high-confidence judgments of single-household faults, the user is notified to check themselves, and emergency repairs are not triggered; for judgments of single-point grounding, a special emergency repair work order is generated; in low-confidence scenarios, a secondary screening and user verification are initiated to avoid misjudgments and omissions.

[0048] CCO full-network verification: As the core master node of the transformer area communication network, CCO integrates multi-dimensional data to perform full-network verification of regional events reported by PCO and single-point events directly connected to STA, and finally generates accurate and reliable alarm information to report to the master station, completely eliminating false alarms and missed alarms.

[0049] Event time validity verification: After receiving an event, the CCO first verifies the timestamp of the event report. If the timestamp is not empty and is for the current day, it is used directly; if the timestamp is empty or abnormal, it is automatically replaced with the current system time to ensure the accuracy of the event time and provide a reliable basis for subsequent fault tracing.

[0050] Multi-dimensional data cross-validation: The CCO integrates three types of core data for comprehensive analysis: First, terminal operation status data to confirm whether the PCO and STA are in normal communication status and to rule out false events caused by communication interruption; second, real-time voltage data of the electricity meter to conduct secondary testing on key nodes in the PCO aggregated events to verify the consistency of abnormal voltage status; and third, marketing file and topology relationship data to map device IDs to specific transformer areas, branches, and users, clarify the spatial location of events, and distinguish different fault types such as "single household power outage", "meter box power outage", "branch power outage", and "transformer area power outage".

[0051] Precise definition of network-wide event boundaries: Through dual-dimensional analysis of "horizontal comparison" and "vertical penetration," the precise boundaries of the power outage area are delineated. Horizontal comparison of STA event status within the same branch and the same meter box confirms the consistency of regional power outages; vertical penetration, from user meters to branches and to transformer substations, determines the specific location of the fault point (such as branch switch tripping, transformer substation failure, etc.).

[0052] Once the CCO completes full network verification and confirms the validity of the event, it immediately organizes structured alarm data according to the dual topology models of "transformer area-line-substation" and "transformer area-community-building" and pushes it to the main station system via 4G / 5G or fiber optic channel.

[0053] It is understood that, in the embodiments of this invention, there is an extension point: structured and unstructured multi-source data can be integrated to achieve more comprehensive cross-validation. Structured data includes: transformer area load data, switch action records, equipment ledgers, and historical fault data; unstructured data includes: text reports from inspection personnel, on-site photos, video surveillance footage, and meteorological data (such as extreme weather events like typhoons, heavy rain, and blizzards). The large model uses Natural Language Processing (NLP) technology to analyze unstructured data. For example, it associates "line aging at branch box A" in the inspection report with the current power outage area to enhance the credibility of the "line fault" determination; it combines "typhoon passing through" in the meteorological data with the geographical information of the transformer area to predict the power outage cause of "tree obstruction touching the line." The final output is a structured result consisting of the power outage fact, confidence level, and cause analysis.

[0054] Meanwhile, the second expansion point is: based on the network-wide verification results and historical fault case database, using causal reasoning algorithms, the fault point and root cause are located from multiple dimensions such as power outage range, voltage characteristics, equipment status, and weather conditions. Combining information such as fault cause, power outage impact range, user type (e.g., hospitals, schools, residents), repair team location, and spare parts inventory, the optimal repair plan is automatically generated. For example... Figure 10 The diagram shows a flowchart of an optimal emergency repair scheme generation method provided by the present invention.

[0055] Understandably, compared to the traditional centralized analysis mode at the main station, the analysis pressure shifts from the main station to the edge nodes. The PCO's regional analysis does not require waiting for instructions from the main station, and the STA's local detection achieves second-level awareness. The PCO's event aggregation reduces the amount of data in uplink communication, and the CCO's multi-source verification filters out invalid events, preventing the main station from being overwhelmed by massive data processing and significantly reducing the main station's computational load and communication bandwidth usage. The combined strategy of three-level progressive verification, multi-source data cross-checking, and multi-layer confirmation after power restoration effectively filters out interference factors such as terminal failures and voltage fluctuations, providing a reliable basis for emergency repair decisions.

[0056] II. Power Restoration Judgment like Figure 11 The diagram shows a flowchart of the power restoration judgment process involved in the method provided by the present invention.

[0057] After the CCO completes the full network verification, it is classified into "confirmed power restoration, suspected power restoration, and no power restoration". The status of confirmed power restoration is synchronized to the main station, and a power restoration notification is generated (SMS push to users, GIS topology map updated); suspected power restoration starts continuous monitoring every 5 minutes until the status is clear; no power restoration is combined with the fault cause analysis and pushed to the emergency repair system to investigate the cause of no power restoration.

[0058] Multi-dimensional power restoration signal acquisition (STA / PCO end): The STA simultaneously acquires three types of core signals: first, grid-side signals (AC zero-crossing pulse recovery, A / B / C three-phase voltage RMS values ​​stabilizing within the rated range, and voltage phase returning to normal); second, equipment-side signals (its own operating power supply switching from supercapacitor back to grid power, and communication module reconnecting to the carrier network); and third, derived signals (power outage duration, cumulative power loss, and instantaneous current surge value upon power restoration). The STA integrates these three types of signals to generate a preliminary power restoration judgment information packet containing "signal acquisition time, characteristic parameters, and confidence level." The confidence level is scored based on signal integrity (100% confidence level if all three types of signals are acquired, and 60% confidence level if only voltage is restored).

[0059] PCO-side regional power restoration signal aggregation: The PCO receives power restoration initial judgment information packets from all subordinate STAs in real time, aggregates data by box / branch dimension, and calculates "the percentage of STAs that have been restored, the average confidence level of the power restoration signal, and the consistency of power restoration time". At the same time, it collects the total current and total voltage recovery status of the branch lines and generates a "branch-level power restoration characteristic table" to mark the coverage and signal reliability of power restoration within the branch.

[0060] Layered progressive power restoration verification (PCO / CCO end): PCO Area Power Restoration Pre-judgment: The PCO initiates pre-judgment logic based on the "Branch-level Power Restoration Feature Table": If more than 80% of STAs in a branch report high-confidence power restoration information (confidence ≥ 80%), and the total voltage / current of the branch returns to the normal range, then it is determined that "the branch has been initially restored", and the pre-judgment results and supporting data are reported to the CCO simultaneously; if the proportion of restored STAs is insufficient or the signal confidence is low, it is marked as "suspected power restoration", and active recall of STAs that have not reported is initiated to supplement the collection of power restoration signals.

[0061] CCO performs multi-source verification for full-network power restoration: The CCO receives the pre-judgment results from each PCO and integrates four types of data to conduct full-network verification: 1. Distribution area-level data (total voltage / load restoration status reported by distribution transformer terminals (TTUs) and switchgear closing signals); 2. Regional-level data (branch power restoration pre-judgment results from each PCO); 3. Terminal-level data (power restoration information packages directly reported by STAs); 4. Externally related data (repair work order completion status, on-site feedback from maintenance personnel, and weather restoration status). The CCO verifies each level sequentially: "Distribution Area - Branch - Meter Box - User". Area-level power restoration: If the TTU reports power restoration and all branch PCOs determine that power has been restored, the entire area is directly determined to be restored; Partial power restoration: If only some branch PCOs determine that power has been restored, the scope of power restoration is located based on the topology relationship, and "branch XX is restored, branch XX is not restored" is determined; Suspected power restoration: If there is a data conflict (such as the TTU reporting power restoration but most STAs not reporting it), a secondary call test and manual review are triggered.

[0062] Dynamic threshold scenario adaptation: CCO has a built-in scenario-based threshold library that automatically adjusts the verification threshold for different working conditions: for example, in rural power grid areas where users are scattered, the "power restoration STA ratio threshold" is lowered from 80% to 70%; in urban power grid areas with dense distribution of transformers, it remains at 80%; after emergency repairs in extreme weather, the weight of "external work order feedback" is temporarily increased, and the power restoration status is confirmed based on on-site feedback.

[0063] Power restoration prediction and early warning (CCO / Cloud): Power restoration prediction based on repair progress: The CCO connects to the emergency repair management system to obtain work order progress in real time (such as "fault point has been repaired, power is being restored"). Combined with historical power restoration time data for similar faults, the CCO predicts the power restoration time window, generates a "power restoration prediction reminder" and pushes it to maintenance personnel. At the same time, the STA / PCO signal acquisition frequency is started in advance to prepare for power restoration detection.

[0064] Power restoration prediction based on load trends: The CCO continuously monitors the load recovery trend of the transformer area / branch. If the load gradually recovers from 0 and conforms to the load growth curve after historical power restoration, it is marked as "high probability of power restoration" even if the power restoration judgment threshold is not reached, triggering the power restoration signal for key monitoring and shortening the power restoration confirmation delay.

[0065] 3. Automatic topology identification of "transformer-branch-meter box-user" When the network structure changes (such as the installation of new electricity meters or line renovation), the PCO automatically senses and updates the topology to ensure the accuracy of power outage location.

[0066] Initial topology construction phase: like Figure 12 The diagram shows a flowchart of the initial topology construction process involved in the method provided by the present invention.

[0067] Precise clock synchronization and multi-dimensional feature signal injection: The CCO (Center Control Center) of the distribution area sends a nanosecond-level high-precision clock synchronization signal to all PCOs (Programmable Centers) to unify the time base across the entire network and eliminate time errors in signal transmission. Each PCO generates a characteristic current pulse signal with dual unique identifiers: the first layer is a basic feature code of "amplitude-frequency-duration," and the second layer is an enhanced feature code of phase offset + pulse interval sequence. The combination of these two feature codes can completely avoid confusion between signals from different PCOs. The PCO injects the characteristic signal into the branch lines under its jurisdiction, and records the signal injection time, its own ID, dual feature codes, and injection power, forming an injection information table containing a "redundancy check field" stored locally, providing dual basis for subsequent matching.

[0068] Multi-parameter acquisition and intelligent interference filtering of terminal signals: The STAs, distributed across meter boxes / user sides, continuously monitor line current and voltage signals. After capturing characteristic pulses injected by the PCO, they extract the pulse amplitude, frequency, duration, and arrival timestamp, and simultaneously acquire enhanced feature parameters such as pulse phase offset and pulse interval sequence. The STA has a built-in lightweight interference identification model that learns the characteristic patterns of interference signals such as household appliance start-stop and line harmonics based on historical data. Through a dual comparison of "basic features + enhanced features," invalid interference signals are filtered out, retaining only valid signals that conform to the PCO feature format. These signals are then packaged into a data acquisition packet with the STA's own ID, meter box ID, and installation location coordinates to ensure the purity of the uploaded data. More details can be found in [link to relevant documentation]. Figure 13 The flowchart shown is a process for multi-parameter acquisition and interference filtering of terminal signals in the method provided by the present invention.

[0069] Dual feature matching and multidimensional verification to determine branch affiliation: The STA reports the collected information packet to the nearest PCO, which then initiates a dual feature matching mechanism: first, it compares the basic feature code, and second, it compares the enhanced feature code. Only when the two feature codes are completely identical will it proceed to the next verification stage.

[0070] The Power Control Center (PCO) conducts multi-dimensional cross-validation: First, it calculates the difference between the signal injection time and arrival time, and uses the power line transmission speed model to determine if the time difference is within a reasonable range. Second, it analyzes the signal attenuation level, and uses line impedance parameters to verify if the signal strength conforms to the transmission distance law. Third, it verifies the geographical matching degree between the STA installation location and the branch line to eliminate the possibility of cross-branch signal crosstalk. After all validations pass, the STA is determined to belong to the branch line of the current PCO, and a hierarchical relationship table of "branch-PCO-meter box-STA" containing "matching confidence" is generated. Records with confidence scores below the threshold will trigger secondary data acquisition and validation. More details can be found in [link to relevant documentation]. Figure 14 The flowchart shown is a process for dual feature matching and multidimensional verification determination involved in the method provided by the present invention.

[0071] Full network topology integration and 3D visualization construction: The CCO aggregates all branch-STA relationship tables reported by all PCOs, binding its associated transformer IDs to the branch IDs of each PCO. It also integrates marketing archive data, line GIS data, and equipment ledger data to construct a four-level topology tree structure: "Transformer (CCO) - Branch (PCO) - Meter Box - User (STA)". This structure not only includes the hierarchical relationships of equipment but also integrates attribute information such as line length, conductor type, and equipment commissioning time, converting it into a standardized topology relationship table and synchronizing it to the main station. Based on this table and combined with a 3D GIS map engine, the main station generates a 3D visualized topology map, intuitively displaying the physical location of equipment, line routing, and operating status. It supports zooming, rotating, and detailed querying of the topology structure, providing maintenance personnel with an immersive topology viewing experience. More details can be found in [link to documentation]. Figure 15 The diagram illustrates the topology dynamic update process involved in the method provided by this invention.

[0072] Real-time detection of incremental device / structural changes using multiple triggering mechanisms: In this embodiment of the invention, a triple triggering mechanism is set to ensure real-time perception of network structure changes: (1) Active registration trigger after a new STA goes online. After the new STA connects to the line, it automatically sends a registration request containing its own ID, box ID and installation location to the surrounding PCOs, triggering the characteristic signal re-injection process of the PCOs; (2) Work order linkage trigger after line modification. When the master station issues a line modification work order, it simultaneously sends a topology update instruction to the corresponding PCO, triggering the full branch signal re-acquisition; (3) Periodic inspection trigger. The PCO automatically calls up the online status and signal characteristics of all subordinate STAs every preset period, and promptly discovers hidden changes such as equipment offline and migration.

[0073] Comparison of old and new topology data and conflict resolution: The PCO performs a full-field comparison between the newly collected STA matching results and the local historical topology table to identify "new STA records, invalid STA records, and branch affiliation change records". For records of branch affiliation changes, conflict resolution logic is initiated: The signal feature matching confidence level and geographical matching level before and after the change are compared. The historical signal feature matching confidence level (calculated based on historical feature code matching consistency, time difference rationality, etc.) and geographical matching level (based on parameters such as line connection relationships and physical distances between historical topology substations) of the STA are retrieved. The values ​​of the two newly matched indicators are then calculated and compared using a set quantization threshold. If the newly matched signal feature and geographical matching levels are significantly higher than historical records, it is determined to be a genuine topology change caused by line modification, equipment relocation, etc. If the difference between the two indicators is below the threshold and the confidence levels are close and difficult to distinguish, the system automatically marks the record as "pending review," triggering a manual review process. Maintenance personnel further verify the record using on-site work orders, line ledgers, and other information to eliminate matching deviations caused by signal crosstalk, harmonic interference, etc., avoiding erroneous topology updates. If the confidence level of the new matching result is higher, it is determined to be a genuine change; if the confidence levels are close, a manual review process is triggered to avoid erroneous updates caused by signal interference. Finally, the PCO generates a topology increment table containing "reason for change, confidence level, and handling recommendations" and reports it to the CCO.

[0074] Network-wide topology synchronization and multi-level closed-loop verification: The CCO merges the incremental topology tables of all PCOs and updates the entire network topology relationship table. New records are directly added and marked "Pending Verification," expired records are marked "Offline / Removed" with historical data retained, and changed records modify hierarchical relationships and record the change trajectory. The CCO initiates multi-level closed-loop verification: the first layer is reverse recall verification, randomly selecting 20% ​​of STAs and recalling their current PCO information, comparing it with the updated topology table; the second layer is cross-system comparison verification, cross-comparing the updated topology table with user files in the marketing system and line ledgers in the GIS system to verify the consistency of device affiliation; the third layer is on-site spot check verification, automatically generating spot check work orders for topology changes in key branches and pushing them to maintenance personnel to verify the authenticity of the changes on-site. Only after all verifications pass is the topology table marked as "valid," and the 3D visualization topology map of the main station is refreshed.

[0075] Topology identification model self-optimization iteration: Establish a data feedback and model optimization mechanism: The results of each topology identification and update, including successful matching cases, interference signal cases, and mismatch cases, are fed back to the topology identification model training library in the cloud. The cloud model continuously learns based on the new cases, optimizes the feature matching algorithm and interference identification rules, and distributes the optimized algorithm parameters and rules to all PCOs and STAs to achieve a closed-loop iteration of "identification-update-optimization".

[0076] Implementing the embodiments of the present invention has the following beneficial effects: This invention provides a proactive reporting system and method for power outage and restoration alarms. It adopts an "edge collaboration + intelligent judgment" model. Specifically, it uses a three-level architecture of "STA (Terminal Sensing Unit) - PCO (Regional Management Node) - CCO (Core Master Node)" to realize local detection, regional aggregation and network-wide verification of power outage events. Combined with power restoration judgment and automatic topology identification, it forms a complete, accurate and efficient proactive reporting system for power outages and restorations.

[0077] In this invention, a three-level edge collaborative architecture is implemented: the traditional centralized judgment of the main station is decentralized to the three-level nodes of STA, PCO and CCO, so as to realize local second-level perception, regional aggregated judgment and network-wide multi-source verification, which greatly reduces the burden on the main station and communication latency.

[0078] It can realize an intelligent power outage judgment mechanism: STA adopts a multi-dimensional fusion judgment of "zero crossing signal + plug-in / plug-out pin level + voltage threshold + lightweight model", combined with dynamic threshold adjustment and abnormal event recognition, to reduce false alarms from the source.

[0079] And to achieve hierarchical and progressive verification of power restoration: By combining the multi-dimensional power restoration signals collected by STA / PCO, and through PCO regional pre-judgment and CCO full-network multi-source verification, accurate judgment and early warning of power restoration status can be achieved.

[0080] It can automatically identify and dynamically update the topology: based on feature signal injection, dual feature matching, multi-dimensional verification and conflict resolution, it can automatically construct and dynamically update the four-level topology of "transformer-branch-meter box-user", and support adaptive network structure changes.

[0081] This enables multi-source data fusion and intelligent analysis: CCO integrates structured and unstructured data (such as weather, work orders, and inspection reports), and combines large models and causal reasoning algorithms to achieve advanced functions such as fault cause analysis and optimal repair plan generation.

[0082] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 Units that specify functions within one or more boxes.

[0083] The above description is merely a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. Therefore, any equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A power outage / restoration alarm active reporting system, characterized in that, include: The Terminal Sensing Unit (STA) is deployed in low-voltage terminal equipment to collect power grid signals in real time and perform local detection and reporting of power outage events. The regional management node (PCO) is deployed at the low-voltage branch box or meter box to receive events reported by subordinate end sensing units and perform regional aggregation and branch-level analysis. The core master node (CCO) is deployed in the intelligent distribution transformer terminal (TTU) or concentrator in the distribution area. It is used to receive events reported by the end sensing units, perform multi-source verification across the entire network, and generate alarm information to report to the master station. The terminal sensing unit, regional management node, and core master node are sequentially connected to form a three-level collaborative edge analysis architecture.

2. The power outage / restoration alarm active reporting system according to claim 1, characterized in that, The end-sensing unit includes: The power supply module uses a supercapacitor backup power supply and a bidirectional DC-DC converter to achieve microsecond-level power supply switching when the power grid fails, and maintain operation for at least 5 seconds. The programmable logic device module is used to acquire AC voltage zero-crossing pulse signals in real time and trigger a preliminary alarm when no valid signal is detected for a continuous preset period. The level detection module is used to detect the level of the plugged-in and unplugged pins of the terminal sensing unit to distinguish between power grid outages and terminal faults. The voltage RMS monitoring module is used to generate a formal power outage event when the voltage is lower than a preset threshold for a set period of time. The lightweight model module is used to dynamically adjust the detection threshold based on historical data and combine multi-dimensional features to perform power outage event fusion judgment.

3. The power outage / restoration alarm active reporting system according to claim 2, characterized in that, The regional management node includes: The regional event cache table module is used to record power outage event information reported by subordinate end-point sensing units; The regional topology relationship table module is used to clarify the subordinate branches and table box levels of the subordinate end sensing units; The branch-level power outage assessment module is used to initiate a branch-level power outage assessment when the number or proportion of end sensing units reporting power outages in the same meter box or branch exceeds a preset threshold. The abnormal event identification module is used to distinguish between single-household faults and single-point grounding events of the line by combining historical fault records, status of surrounding nodes, meteorological and load data.

4. The power outage / restoration alarm active reporting system according to claim 3, characterized in that, The core master node includes: The event time verification module is used to verify the integrity of the event reporting timestamp; The multi-source data cross-validation module is used to integrate terminal operating status, real-time meter voltage, marketing records and topology data to perform network-wide event verification. The structured alarm generation module is used to organize alarm data according to the dual topology model and report it to the main station; The power restoration verification module is used to combine the power restoration signals, repair work order progress, and load trends reported by the end sensing units / regional management nodes to judge and warn of the power restoration status of the entire network.

5. The power outage / restoration alarm active reporting system according to any one of claims 1 to 4, characterized in that, Also includes: The topology auto-identification module is deployed in the regional management node and the core master node. It is used to automatically construct and dynamically update the four-level topology relationship of "transformer-branch-meter box-user" based on feature signal injection, dual feature matching and multi-dimensional verification. The automatic topology identification module supports three triggering mechanisms: new equipment coming online, line modification, and periodic inspection, and has conflict resolution and closed-loop verification functions.

6. A method for actively reporting power outage and restoration alarms, characterized in that, Includes the following steps: The terminal sensing unit (STA) performs local power outage detection, uses a multi-dimensional fusion judgment mechanism to generate power outage events and reports them to the regional management node (PCO). The regional management node receives power outage events reported by its subordinate STAs, performs regional aggregation and branch-level analysis, and generates an aggregated event report to be reported to the core master node (CCO). The core master node receives aggregated events reported by the regional management nodes, performs multi-source verification across the entire network, generates structured alarm information, and reports it to the master station. During the power restoration phase, the terminal sensing unit, regional management node, and core master node work together to collect power restoration signals, perform regional pre-judgment, and verify the entire network to achieve accurate judgment of the power restoration status.

7. The method according to claim 6, characterized in that, The steps for the end-sensing unit to perform local power outage detection include: Real-time acquisition of AC voltage zero-crossing pulse signals; triggering a preliminary alarm when no valid signal is detected continuously. The system detects the voltage level of the STA's own plugged-in / plugged-out pins. If the voltage level is lower than the preset threshold, it is confirmed that the power grid is out of service. Monitor the effective value of the voltage. When the voltage is lower than the danger threshold and remains below it for a set time, generate an early warning. When the voltage returns to zero and remains below it for a set time, generate a formal power outage event. The detection threshold is dynamically adjusted by combining a lightweight model, and zero-crossing signals and harmonic features are integrated for multi-dimensional judgment.

8. The method according to claim 7, characterized in that, The steps for the regional management node to perform regional aggregation and branch-level analysis include: Establish a regional event cache table to record events reported by subordinate end-point sensing units; When the number or proportion of end-sensing units reporting power outages within the same meter box or branch exceeds a preset threshold, branch-level power outage analysis is initiated. Actively scan the end sensing units that have not reported events. If there is no response or the returned voltage is within the power outage determination range, then the branch is confirmed to be out of power. By combining historical fault records, the status of surrounding nodes, and meteorological and load data, abnormal events can be identified and the distinction between individual household faults and line problems can be made.

9. The method according to claim 8, characterized in that, The steps for the core master node to perform multi-source verification across the entire network include: Verify the event reporting timestamp, and replace it with the current system time in case of an anomaly; Integrate terminal operating status, real-time meter voltage, marketing records, and topology data for multi-dimensional cross-validation; By combining horizontal comparison with vertical penetration analysis, the scope of the power outage can be accurately defined. By combining structured and unstructured data, fault cause analysis and optimal repair plan generation are performed.

10. The method according to claim 9, characterized in that, It also includes the steps of automatic topology identification and updating: The core master node sends a clock synchronization signal to the regional management node, and the regional management node generates a dual characteristic current pulse to inject into the branch line; The end-sensing unit captures feature pulses and extracts feature parameters, which are then reported to the regional management node for dual feature matching and multi-dimensional verification. The regional management node determines the branch affiliation of the end sensing unit, and the core master node integrates and constructs a four-level topology table and synchronizes it to the master station. When the network structure changes, a topology update process is triggered to compare old and new data, resolve conflicts, and perform closed-loop verification.

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