A circuit protection method and system triggered by meter wiring error

Abstract

The application provides a circuit protection method and system triggered by meter wiring errors, and relates to the technical field of circuit protection. The method comprises the following steps: obtaining a real-time state feature set sampled by a meter in real time, generating an abnormal trigger signal if an abnormal index exceeds a preset abnormal trigger threshold; performing iterative probability fusion reasoning layer by layer according to error evidence until a target error state node is locked, and outputting a corresponding target wiring error type; determining a static risk weight according to the target wiring error type, determining a dynamic stress weight according to the real-time state feature set, and evaluating a real-time danger level to map and generate a corresponding target protection strategy; performing a protection action according to the target protection strategy, and recording the target wiring error type and the real-time state feature set in association. The application realizes accurate identification and risk assessment of meter wiring errors, generates a dynamic protection strategy and quickly executes a protection action, and improves the technical effects of power supply system safety and response accuracy.

Description

Technical Field

[0001] This application relates to the field of circuit protection technology, and in particular to a circuit protection method and system for a meter wiring error triggering a circuit. Background Technology

[0002] With the rapid development of smart grids and modern power distribution systems, electricity meters are increasingly used in monitoring energy consumption, ensuring metering accuracy, and assisting in power distribution management. During actual operation, electricity meters need to continuously collect electrical parameters such as voltage, current, and power, and identify and record abnormal states to ensure the safe and stable operation of the power supply system. However, during the meter wiring process, wiring errors, misconnections, or short circuits are still relatively common. These wiring errors can not only lead to abnormal metering data but also potentially cause overcurrent, equipment damage, or electrical safety accidents, posing a potential threat to the operational safety of the power supply system.

[0003] Currently, most existing methods for detecting and protecting against electrical meter anomalies rely on monitoring a single parameter or simple threshold judgments, triggering protection actions by detecting instantaneous current, voltage deviations, or power anomalies. These methods typically lack sophisticated mechanisms for identifying wiring errors, failing to differentiate between different types of errors, and struggling to assess the cumulative effects of abnormal states under time and load conditions. This leads to frequent malfunctions or delayed protection actions. Especially under conditions of significant load fluctuations or short-lived abnormal signals, existing technologies are prone to misjudgments, causing protection actions to be executed prematurely or delayed, further impacting power supply safety and equipment reliability.

[0004] In summary, the existing technology suffers from a lack of accurate identification and risk assessment mechanisms for wiring errors. This results in the meter being unable to accurately determine the type and severity of wiring errors under abnormal conditions, further affecting the safety of the power supply system, the stability of equipment operation, and the accuracy and timeliness of protection actions. Summary of the Invention

[0005] The purpose of this application is to provide a circuit protection method and system for electricity meter wiring errors, in order to solve the technical problem in the prior art that the lack of an accurate identification and risk assessment mechanism for wiring error types leads to the inability of electricity meters to accurately determine the type and degree of danger of wiring errors under abnormal conditions, which further affects the safety of the power supply system, the stability of equipment operation, and the accuracy and timeliness of protection actions.

[0006] In view of the above problems, this application provides a circuit protection method and system for electricity meter wiring errors.

[0007] In a first aspect, this application provides a circuit protection method triggered by a meter wiring error, implemented through a circuit protection system triggered by a meter wiring error, comprising: acquiring a real-time state feature set sampled in real time from the meter and calculating an anomaly index; if the anomaly index exceeds a preset anomaly trigger threshold, generating an anomaly trigger signal and mapping the real-time state feature set as error evidence; in a hierarchical state space of wiring errors, performing iterative probabilistic fusion reasoning layer by layer based on the error evidence until a target error state node is locked, and outputting the corresponding target wiring error type; determining a static risk weight based on the target wiring error type, determining a dynamic stress weight based on the real-time state feature set, and evaluating the real-time hazard level, mapping and generating a corresponding target protection strategy; executing protection actions according to the target protection strategy, and associating and recording the target wiring error type with the real-time state feature set.

[0008] Preferably, the circuit protection method triggered by meter wiring error further includes: extracting a reference state feature vector based on a reference state feature set, extracting a real-time state feature vector based on the real-time state feature set, and calculating the Mahalanobis distance between the reference state feature vector and the real-time state feature vector as the anomaly index.

[0009] Preferably, the circuit protection method triggered by a wiring error in an electricity meter further includes: the wiring error hierarchical state space contains an error state tree; if the target error state node that meets the convergence condition cannot be locked at the first level based on the error evidence, then a high-suspicion node is selected based on the first-level error confidence of the first-level state node; the error confidence of the high-suspicion node and the high-suspicion sub-node is aggregated using the error evidence until the target error state node that meets the convergence condition is locked.

[0010] Preferably, the circuit protection method for triggering meter wiring errors further includes: the error state tree includes a first level up to the Nth level, wherein the first level includes a first level state node, the first level state node corresponds to a single wiring error state, the Nth level includes an Nth level state node formed by coupling at least two single wiring error states, and the Nth level state node is a multiple coupled error state.

[0011] Preferably, the circuit protection method triggered by meter wiring error further includes: performing a breadth-first traversal fusion evaluation at the first level to obtain the first-level error confidence level, and sorting them to obtain the first-level error confidence level sequence; if there is no node in the first-level error confidence level sequence whose error confidence level is greater than the first error confidence level threshold and whose difference with the adjacent error confidence level is greater than the second error confidence level threshold, then it is determined that the error evidence cannot lock the target error state node that meets the convergence condition at the first level.

[0012] Preferably, the circuit protection method for meter wiring error triggering further includes: for the high-suspicion node, generating a high-suspicion child node of the high-suspicion node at the Nth level in the error state tree, wherein the high-suspicion child node represents the coupling between a single wiring error state corresponding to the high-suspicion node and at least another single wiring error state; forming a local space with the high-suspicion node and the high-suspicion child node, and re-aggregating the error confidence of the high-suspicion node and the high-suspicion child node using the error evidence to obtain an updated error confidence, until the target error state node that meets the convergence condition is locked.

[0013] Preferably, the circuit protection method triggered by meter wiring error further includes: determining the static risk weight by the physical damage attributes of the target wiring error type; determining the dynamic stress weight by the current amplitude and abnormal duration in the real-time load characteristics of the real-time status feature set; generating a dynamic hazard index by weighted summing of the static risk weight and the dynamic stress weight; and classifying the real-time hazard level according to the dynamic hazard index.

[0014] Preferably, the circuit protection method triggered by meter wiring error further includes: the real-time danger level includes at least a first level, a second level, and a third level, wherein the third level is lower than the second level, and the second level is lower than the first level; when the real-time danger level is at the first level, an immediate trip command is generated; when the real-time danger level is at the second level, a current-limiting operation and delayed trip command is generated; when the real-time danger level is at the third level, an alarm signal is generated and the current power supply state is maintained.

[0015] Preferably, the circuit protection method triggered by the meter wiring error further includes: after the protection action is completed, entering a safety lockout state; in the safety lockout state, the safety lockout state is released only when the abnormal index is determined to have returned to the normal range based on the real-time status feature set re-acquired after on-site correction, and an external authorized reset command is received.

[0016] Secondly, this application also provides a circuit protection system triggered by a meter wiring error, used to execute a circuit protection method triggered by a meter wiring error as described in the first aspect, comprising: an abnormal trigger signal generation module 1, used to acquire a real-time state feature set sampled by the meter in real time, and calculate an abnormal index; if the abnormal index exceeds a preset abnormal trigger threshold, an abnormal trigger signal is generated, and the real-time state feature set is mapped to error evidence; a target wiring error type output module 2, used to perform iterative probabilistic fusion reasoning layer by layer in the wiring error hierarchical state space based on the error evidence until the target error state node is locked, and output the corresponding target wiring error type; a target protection strategy generation module 3, used to determine a static risk weight based on the target wiring error type, determine a dynamic stress weight based on the real-time state feature set, and evaluate the real-time hazard level, and map to generate a corresponding target protection strategy; and a protection action execution module 4, used to execute protection actions according to the target protection strategy, and associate and record the target wiring error type with the real-time state feature set.

[0017] The technical solution provided in this application has at least the following technical effects or advantages: by achieving the technical goal of accurately classifying and identifying abnormal wiring status of electricity meters and assessing the risk level in real time, it can generate dynamic protection strategies based on the type of wiring error and real-time load characteristics, and execute protection actions such as tripping, current limiting or alarm in a timely and accurate manner, thereby improving the safety of the power supply system, the reliability of equipment operation, and the accuracy and response speed of protection actions under abnormal conditions.

[0018] The above description is merely an overview of the technical solution of this application. To enable a clearer understanding of the technical means of this application and to facilitate its implementation according to the description, and to make the above and other objects, features, and advantages of this application more apparent, specific embodiments of this application are described below. It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent through the following description. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this application 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 merely exemplary. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating a circuit protection method for an electricity meter wiring error triggered according to this application.

[0021] Figure 2 This paper presents the relationship between the error state tree hierarchy and error coupling complexity in a circuit protection method for meter wiring errors triggered by an error in this application.

[0022] Figure 3 This is a schematic diagram of the circuit protection system triggered by a wiring error of an electricity meter, as described in this application.

[0023] Explanation of reference numerals in the attached diagram: 1. Abnormal trigger signal generation module; 2. Target wiring error type output module; 3. Target protection strategy generation module; 4. Protection action execution module. Detailed Implementation

[0024] This application provides a circuit protection method and system for electricity meter wiring errors, solving the technical problem in existing technologies where the lack of a precise identification and risk assessment mechanism for wiring error types leads to the inability to accurately determine the type and severity of wiring errors in abnormal conditions, further affecting the safety of the power supply system, the stability of equipment operation, and the accuracy and timeliness of protection actions. The method achieves the technical goal of accurately classifying and identifying abnormal wiring states of electricity meters and assessing their real-time hazard levels. It enables the generation of dynamic protection strategies based on wiring error types and real-time load characteristics, and timely and accurately executes protection actions such as tripping, current limiting, or alarms, thereby improving the safety of the power supply system, the reliability of equipment operation, and the accuracy and response speed of protection actions in abnormal conditions.

[0025] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. It should be understood that this application is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application. It should also be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all of them.

[0026] Example 1, please refer to Figure 1 and Figure 2 This application provides a circuit protection method triggered by a wiring error in an electricity meter, applied to a circuit protection system triggered by a wiring error in an electricity meter, specifically including the following steps:

[0027] S1: Obtain the real-time status feature set of the meter in real time and calculate the anomaly index. If the anomaly index exceeds the preset anomaly trigger threshold, generate an anomaly trigger signal and map the real-time status feature set as erroneous evidence.

[0028] Furthermore, this application also includes: extracting a baseline state feature vector based on the baseline state feature set, extracting a real-time state feature vector based on the real-time state feature set; and calculating the Mahalanobis distance between the baseline state feature vector and the real-time state feature vector as the anomaly index.

[0029] Specifically, during operation, the meter continuously acquires and records a set of parameters reflecting the current operating status of the power supply circuit according to a preset sampling period, thus obtaining a real-time status feature set. The real-time status feature set includes at least one or more of the following: voltage amplitude, current amplitude, active power, reactive power, power factor, frequency, phase angle, phase sequence relationship, zero-sequence current, harmonic components, and changes in energy metering.

[0030] Furthermore, the reference state feature set refers to a standard operating state data set acquired and established through continuous sampling under the condition that the meter wiring is correct and the power supply circuit is operating normally. Specifically, after the meter is installed, calibrated, and wiring confirmed, a preset acquisition period with correct wiring and normal power supply circuit operation is selected as the reference acquisition phase. During the reference acquisition phase, the meter continuously acquires one or more operating state parameters from the following categories according to a preset sampling frequency: voltage amplitude, current amplitude, active power, reactive power, power factor, frequency, phase angle, phase sequence relationship, and harmonic parameters. Outlier removal, noise filtering, and data standardization are performed on the acquired multiple sets of operating state parameters to obtain a standard state data set reflecting normal operating conditions. This standard state data set is then used as the reference state feature set. Further, according to preset feature composition rules, multiple state parameters reflecting the operating state of the power supply circuit are selected from the reference state feature set and constructed into a multi-dimensional numerical vector according to a unified arrangement order. Furthermore, based on the same feature selection and arrangement rules as the baseline state feature vector, corresponding state parameters are extracted from the real-time state feature set, and a multi-dimensional numerical vector with the same dimension as the baseline state feature vector is constructed to obtain the real-time state feature vector.

[0031] Furthermore, Mahalanobis distance refers to a multidimensional statistical distance index established based on the covariance relationship of feature variables. Calculating the Mahalanobis distance between the baseline state feature vector and the real-time state feature vector involves simultaneously considering the numerical differences between each feature dimension and the correlation between different feature dimensions to quantify the overall deviation between the real-time state feature vector and the baseline state feature vector. A larger distance value indicates a more significant difference between the real-time operating state and the normal operating state, while a smaller distance value indicates a higher degree of similarity between the real-time operating state and the normal operating state. For example, the baseline state feature vector is the residual vector Δ=X calculated from the mean μ of the real-time state feature vector X and the baseline state feature vector. μ. Then, obtain the covariance matrix Σ of the baseline state feature set, and calculate its inverse matrix Σ. 1 The covariance matrix Σ contains the variance of each feature dimension and the covariance between different feature dimensions. Based on formula D... M = Calculate the Mahalanobis distance D M ; where, by multiplying by the inverse matrix Σ 1 This method eliminates dimensional differences and correlation coupling between feature dimensions, zeroes the residuals generated by normal linkage fluctuations, and retains only the abnormal residuals reflecting substantial topological changes, thus obtaining a comprehensive anomaly index characterizing the degree to which the real-time state deviates from the center of the normal state. Furthermore, Mahalanobis distance is used to characterize the anomaly index, ensuring that it reflects not only the magnitude of changes in state parameter values ​​but also the degree of change in the correlation between multiple state parameters. A higher anomaly index value indicates a greater likelihood of wiring errors or operational anomalies, while a lower anomaly index value indicates a state closer to normal operating conditions.

[0032] Furthermore, based on historical normal operation data statistics, equipment operation standards, or on-site operation experience, pre-set anomaly judgment boundary values ​​are obtained to obtain preset anomaly trigger thresholds. When the anomaly index is lower than the preset anomaly trigger threshold, the current operating state is determined to be within the normal range. When the anomaly index reaches or exceeds the preset anomaly trigger threshold, the current operating state is determined to have an anomaly risk, thereby triggering an anomaly trigger signal. The anomaly trigger signal can be represented in the form of logical status flags, event numbers, anomaly tag data packets, or control commands.

[0033] Furthermore, based on a pre-established rule base for wiring error features, an error feature association model, or a state feature mapping relationship, information that reflects wiring anomalies in the real-time state feature set is converted into a set of evidence for error reasoning.

[0034] S2: In the hierarchical state space of wiring errors, iterative probabilistic fusion reasoning is performed layer by layer based on the error evidence until the target error state node is locked and the corresponding target wiring error type is output.

[0035] Furthermore, this application also includes: the wiring error hierarchical state space contains an error state tree; if the target error state node that meets the convergence condition cannot be locked at the first level based on the error evidence, then a high-suspicion node is selected based on the first-level error confidence of the first-level state node; the error confidence of the high-suspicion node and the high-suspicion sub-node is aggregated using the error evidence until the target error state node that meets the convergence condition is locked.

[0036] Furthermore, this application also includes: the error state tree includes a first level up to the Nth level, wherein the first level includes a first level state node, the first level state node corresponds to a single wiring error state, the Nth level includes an Nth level state node formed by coupling at least two single wiring error states, and the Nth level state node is a multi-coupled error state.

[0037] Furthermore, this application also includes: performing a breadth-first traversal fusion evaluation at the first level to obtain the first-level error confidence score, and sorting them to obtain the first-level error confidence score sequence; if there is no node in the first-level error confidence score sequence whose error confidence score is greater than the first error confidence score threshold and whose difference with the adjacent error confidence score is greater than the second error confidence score threshold, then it is determined that the erroneous evidence cannot lock the target erroneous state node that meets the convergence condition at the first level.

[0038] Furthermore, this application also includes: for the highly suspicious node, generating a highly suspicious child node of the highly suspicious node at the Nth level in the error state tree, wherein the highly suspicious child node represents the coupling between a single wiring error state corresponding to the highly suspicious node and at least another single wiring error state; forming a local space with the highly suspicious node and the highly suspicious child node, and re-aggregating the error confidence of the highly suspicious node and the highly suspicious child node using the error evidence to obtain an updated error confidence, until the target error state node that satisfies the convergence condition is locked.

[0039] Specifically, the hierarchical state space for wiring errors refers to a hierarchical state description structure constructed for different types of meter wiring errors. The hierarchical state space is organized hierarchically according to the complexity, coupling degree, and combination relationships of the wiring errors, describing the progressive relationship from single wiring errors to multiple wiring errors. Each level in the hierarchical state space corresponds to a set of error states of different complexity. This hierarchical organization achieves an ordered expression of wiring error states, providing a structured search range for subsequent error reasoning and state localization. Furthermore, the error state tree refers to a hierarchical tree-shaped state model constructed for meter wiring error types and the combination relationships between different errors. Each node in the error state tree represents a wiring error state, and each level represents a set of error states of different complexity. The error state tree establishes the association path between single and multiple wiring error states through tree-like topological relationships, enabling the wiring error identification process to unfold the reasoning and analysis layer by layer from simple to complex and from basic to combined, thereby achieving a structured expression and ordered search of wiring error states. Furthermore, levels one through N refer to multiple analysis levels within the error state tree, divided according to the complexity of the error. Level one is the foundational level of the error state tree, representing the most basic wiring error state. As the level increases, the coupling between error states gradually strengthens. Level N is located in the higher-level region of the error state tree, representing complex error states formed by the coexistence of multiple wiring errors. The number of levels N is set based on the preset number of wiring error types and the allowed depth of analysis combinations, thus forming a complete hierarchical structure of error states.

[0040] Furthermore, such as Figure 2As shown, the first level contains first-level state nodes, which means that multiple state nodes are set in the basic layer of the error state tree to represent basic wiring error states. The first-level state nodes are independent of each other, and each state node corresponds to an independent wiring error form. The first-level state nodes serve as the initial analysis objects in the error identification process, used to prioritize the determination of whether a single wiring error state exists, thereby improving error identification efficiency and reducing unnecessary complex combination analysis processes. A single wiring error state refers to an error state where only one wiring relationship abnormality exists without other wiring errors occurring simultaneously. A single wiring error state includes at least one of the following: current transformer polarity reverse connection state, voltage circuit reverse connection state, phase sequence wiring error state, phase loss wiring state, and phase line misconnection state. Further, the Nth level contains Nth-level state nodes formed by the coupling of at least two single wiring error states, meaning that the state nodes in the higher-level regions of the error state tree are constructed from multiple basic error states according to combination relationships. Each Nth-level state node corresponds to an operating state where at least two single wiring error states exist simultaneously. In coupled states, the abnormal characteristics generated by different wiring errors may superimpose, amplify, cancel each other out, or cross-influence each other, thus causing the overall operating state to exhibit comprehensive characteristics that differ from any single wiring error state. For example, the coexistence of current reverse connection and phase sequence error states forms a combined error state, or the coexistence of voltage reverse connection and phase loss states forms a combined error state. The state nodes constructed through these combined relationships can describe the actual operating conditions in complex wiring error scenarios.

[0041] Furthermore, the convergence condition is used to measure the degree of distinction between different erroneous state nodes and the credibility of the target erroneous state node. When the error confidence corresponding to a certain erroneous state node reaches a preset credibility level and forms a sufficiently obvious difference with other competing nodes, the error inference result is determined to meet the convergence condition; when the error confidence corresponding to multiple erroneous state nodes is close and cannot form a clear distinction, the error inference result is determined to not meet the convergence condition. Specifically, all first-level state nodes in the first level of the error state tree are taken as the analysis object, and evidence matching calculation is performed sequentially according to the access method of nodes at the same level first. Then, the supporting information corresponding to multiple erroneous evidences is uniformly processed, and the support degree of erroneous evidences for each state node is calculated. Erroneous evidences include at least one or more of the following: voltage phase anomaly information, current direction anomaly information, power factor anomaly information, phase sequence anomaly information, zero-sequence current anomaly information, and metering deviation anomaly information. This avoids the deviation of the identification result caused by a single erroneous evidence, improves the stability and accuracy of the wiring error identification result, and obtains the first-level error confidence. Breadth-first search (BFS) is a horizontal traversal strategy within tree-structured search. During the analysis, it first visits and calculates all state nodes at the current level before deciding whether to proceed to subsequent levels. Furthermore, a higher error confidence value at the first level indicates a higher consistency between the corresponding single wiring error state and the current operating state; conversely, a lower error confidence value indicates a weaker correlation between the corresponding single wiring error state and the current operating state. For example, the first level contains M state nodes, and each first-level state node is denoted as S. i Let i = 1, 2, ..., M, and each erroneous piece of evidence be denoted as E. j j=1,2,...,K. Then each first-level state node S i The corresponding error confidence level C i The weighted fusion formula can be used to calculate C as follows: i = f(S i E j ), where w j Let f(S) be the weight of the j-th erroneous evidence, used to represent the importance of different erroneous evidences. i E j E is erroneous evidence. j With the first-level state node S i The matching function can quantify the degree of matching using methods such as cosine similarity, Mahalanobis distance mapping function, or logistic regression probability output. By weighted summation, the error confidence C of each state node after comprehensively considering all erroneous evidence at the first level can be obtained. i .

[0042] Furthermore, the error confidence C of all first-level state nodes is...i Sort them in descending order to form the first-level error confidence sequence [C]. (1) C (2) ,...,C (M) ], where C (1) This represents the state node that receives the highest level of erroneous evidence. The sorting process can be implemented using standard sorting algorithms, such as quicksort or mergesort, to visually reflect the matching priority of each state node with erroneous evidence.

[0043] Furthermore, the first error confidence threshold refers to a preset judgment boundary used to evaluate whether the credibility of a state node meets the requirements for effective identification, and is customized by those skilled in the art according to actual circumstances. The first error confidence threshold is used to determine whether erroneous evidence sufficiently supports the corresponding state node. Adjacent error confidence refers to the error confidence in the first-level error confidence sequence that is adjacent to the position of the first-level error confidence extracted in real time. For example, when extracting the first-ranked error confidence in the first-level error confidence sequence, the adjacent error confidence is the second-ranked error confidence. Furthermore, the second error confidence threshold is used to evaluate whether the difference in error confidence between adjacent first-level state nodes reaches a preset difference boundary, and is customized by those skilled in the art according to actual circumstances.

[0044] Furthermore, if there are no nodes in the first-level error confidence sequence whose error confidence is greater than the first error confidence threshold and whose difference with the adjacent error confidence is greater than the second error confidence threshold, that is, any first-level error confidence is less than or equal to the wiring error confidence threshold, and there is no first-level error confidence that is significantly larger than the remaining first-level error confidence in the first-level error confidence sequence, it indicates that the error confidence of the first-level state nodes corresponding to the first-level error confidence sequence is not much different, and it is difficult to determine whether there is a wiring error in one step. Therefore, it is necessary to enter the high-suspicion node screening and higher-level combined error state analysis stage to further improve the ability to identify complex wiring errors.

[0045] Furthermore, state nodes with a high probability of error occurrence are selected based on the first-level error confidence results. The error confidence corresponding to high-suspicion nodes is ranked high in the first-level error confidence sequence. For example, the first-level error confidence of the top M sequences is selected as high-suspicion nodes. The error states corresponding to high-suspicion nodes have strong supporting evidence, but due to the existence of multiple competing states or insufficient evidence differentiation, they cannot be directly identified as the target error state node at this time.

[0046] Furthermore, high-suspicion nodes indicate that the evidence of errors has a similar degree of support for multiple individual wiring error states, suggesting the possibility of potential combinations or multiple couplings. High-suspicion nodes serve as the entry point for complex error analysis, further expanding the state space to identify multi-coupled wiring errors. High-suspicion child nodes are generated at level N in the error state tree. These high-suspicion child nodes are combined error state nodes formed by further expansion of the high-suspicion nodes; that is, composite wiring error states formed by the coupling of at least two individual wiring error states. Their state characteristics combine the anomalous features and matching rules of each individual wiring error state constituting the combination.

[0047] A local space, comprised of high-suspicion nodes and their child nodes, is used to limit the computational scope of error confidence aggregation, thereby improving analysis efficiency and reducing global search complexity. Within the local space, the error confidence of each node is calculated using a weighted fusion method for all relevant erroneous evidence. The error confidence of each node is then expressed as C. i = f(S i E j ) to obtain, where S i Update to a highly suspicious node or highly suspicious child node within the local space, E j The evidence is updated to false. Through weighted summation, supporting information from multiple false pieces of evidence is integrated into a comprehensive error confidence score for each node, thus quantifying the probability of the node's validity. After obtaining the updated error confidence score, a convergence condition is determined, i.e., whether the target error state node has been identified. The convergence condition considers both whether the node's own error confidence score exceeds a first error confidence score threshold and whether the difference in error confidence scores with other competing nodes exceeds a second error confidence score threshold. Once the target error state node meets the convergence condition, the corresponding error type identifier is read according to the pre-established node-error type mapping relationship, and the final identification result is generated according to a preset output format. The output content includes at least one or more of the following: target wiring error type name, error type number, error occurrence time, corresponding target error state node number, and error confidence score information.

[0048] S3: Determine the static risk weight based on the target wiring error type, determine the dynamic stress weight based on the real-time status feature set, evaluate the real-time hazard level, and map to generate the corresponding target protection strategy.

[0049] Furthermore, this application also includes: determining the static risk weight by the physical damage attributes of the target wiring error type; determining the dynamic stress weight by the current amplitude and abnormal duration in the real-time load characteristics of the real-time state feature set; generating a dynamic hazard index by weighted summing of the static risk weight and the dynamic stress weight; and classifying the real-time hazard level according to the dynamic hazard index.

[0050] Furthermore, this application also includes: the real-time hazard level includes at least a first level, a second level, and a third level, wherein the third level is lower than the second level, and the second level is lower than the first level; when the real-time hazard level is at the first level, an immediate trip command is generated; when the real-time hazard level is at the second level, a current-limiting operation and delayed trip command is generated; when the real-time hazard level is at the third level, an alarm signal is generated and the current power supply status is maintained.

[0051] Specifically, determining static risk weights based on the physical damage attributes of the target wiring error type refers to quantifying the risk impact according to the physical characteristics and potential hazard level corresponding to the target wiring error type. Physical damage attributes include factors such as the probability of current short circuits, abnormal voltage amplitudes, potential device damage caused by wiring loops, and threats to the safety of the power supply system. The static risk weight is a numerical indicator used to represent the degree of risk that the power supply system may experience under the current wiring error type, without external disturbances.

[0052] Load-related features are extracted using real-time collected meter status feature sets, including current amplitude, fluctuation trends, and duration of abnormal states. Dynamic stress weight is a numerical indicator used to reflect the system stress and hazard level caused by load fluctuations or persistent abnormalities under the current operating conditions. By combining current amplitude with abnormal duration, the immediate impact of wiring errors on system stability can be assessed, providing a dynamic reference for real-time hazard level classification. Specifically, current amplitude characterizes the instantaneous electrical stress level experienced by the power supply circuit under wiring error conditions. A larger current amplitude indicates a more pronounced conductor heating effect, faster insulation material aging, and stronger thermal and electrodynamic stresses on electrical equipment. This increases the risk of device damage, contact erosion, and protection failure due to wiring errors, thus resulting in a larger dynamic stress weight. Conversely, a smaller current amplitude indicates a lower electrical load on the power supply circuit, a weaker immediate impact of wiring errors on equipment operational stability, and thus a smaller dynamic stress weight. Furthermore, abnormal duration characterizes the cumulative effect of abnormal operating states on the power supply system. The longer the duration of the abnormality, the longer the abnormal current, abnormal phase relationship, or abnormal metering state continues to act on the equipment, the more obvious the heat accumulation effect, the higher the degree of insulation degradation, and the more serious the equipment fatigue loss. Therefore, the dynamic stress weight is greater. The shorter the duration of the abnormality, the less significant the cumulative damage caused by the abnormal state has yet to be formed, and the relatively weaker the long-term impact of wiring errors. Therefore, the dynamic stress weight is smaller.

[0053] According to preset weighting coefficients, static risk weights and dynamic stress weights are linearly weighted to obtain an index that comprehensively reflects the overall risk level of the system. The weighting coefficients can be adjusted based on system operating experience, engineering safety standards, or historical accident statistics to ensure that the dynamic hazard index accurately reflects the true risk of the system. Using pre-set hazard level classification standards, the obtained dynamic hazard index is mapped to different levels of hazard states. Real-time hazard levels include multiple grades to guide the formulation and implementation of protection strategies. By classifying hazard levels, quantitative values ​​can be transformed into operational guidelines, providing a clear decision-making basis for wiring error protection control.

[0054] Furthermore, the real-time hazard level includes at least a first level, a second level, and a third level. The first level represents the operating state with the highest degree of danger, the second level represents the operating state with a medium degree of danger, and the third level represents the operating state with a low degree of danger. By setting multiple hazard levels, different levels of danger can correspond to different protection strengths, enabling differentiated execution of wiring error protection strategies.

[0055] Furthermore, the hierarchy of hazard levels—third level lower than second level, and second level lower than first level—indicates a progressive relationship between different hazard levels based on the degree of danger. A higher hazard level indicates a greater likelihood that a wiring error, under current operating conditions, will cause equipment damage, electrical fires, insulation aging, power supply anomalies, or electric shock to personnel. Conversely, a lower hazard level indicates that although a wiring error has occurred, the likelihood of it causing serious damage to the power supply system in the short term is lower. This progressive relationship between hazard levels ensures that protective actions are consistent with the level of risk.

[0056] Furthermore, a hazard level mapping rule is established based on the dynamic hazard index value range. When the dynamic hazard index reaches the first hazard range, it corresponds to the first level; when it reaches the second hazard range, it corresponds to the second level; and when it reaches the third hazard range, it corresponds to the third level. The boundary values ​​of the hazard ranges can be set based on the equipment's tolerance capabilities, protection coordination requirements, historical fault statistics, and operational safety specifications, thereby ensuring that the hazard level classification results meet actual operational needs. Furthermore, when the real-time hazard level is at the first level, after determining that the current operating state has reached a high-hazard level, a power-off control command is immediately output to the actuator. The immediate trip command is a protection control command without setting an additional waiting time, used to drive the circuit breaker, load switch, or protection actuator to quickly disconnect the power supply circuit. Application scenarios corresponding to the immediate trip command include situations where wiring errors have caused serious overcurrent, serious metering anomalies, or significant equipment damage risks, reducing the probability of accident escalation by quickly isolating the faulty circuit.

[0057] Furthermore, when the real-time hazard level is at Level 2, the current operating status is determined to be at a medium hazard level. The operating load is then reduced, and after the delayed observation period, a decision is made on whether to execute power outage protection based on changes in the hazard status. Current-limiting operation is used to keep the control circuit current within a safe range, and delayed tripping is used to reserve fault buffer time to avoid malfunctions due to short-term fluctuations or transient disturbances. The delay time can be set according to the degree of hazard, equipment capacity, and on-site operating requirements. During the delay period, changes in the dynamic hazard index are continuously monitored. Tripping is executed when the hazard persists or worsens; the tripping action is canceled when the hazard returns to normal. The delayed tripping command is used to balance power supply continuity and operational safety.

[0058] Furthermore, when the real-time danger level is at level three, the current operating status is determined to be at a low danger level. Instead of immediately cutting off power or limiting current, a risk warning is issued to maintenance personnel or the monitoring system, and the power supply circuit remains operational. Although the wiring error state corresponding to level three already exhibits abnormal characteristics, it has not yet reached the point of immediate intervention under the current load conditions. Furthermore, alarm signals can be implemented through audible and visual alarms, display interface prompts, SMS notifications, remote monitoring platform push notifications, or event log reporting. Alarm signals must include at least one or more of the following: error type, danger level, occurrence time, and handling suggestions, to remind maintenance personnel to promptly investigate and handle abnormal states.

[0059] S4: Execute protection actions according to the target protection strategy, and associate the target wiring error type with the real-time status feature set.

[0060] Furthermore, this application also includes: after the protection action is completed, entering a safety lockout state; in the safety lockout state, the safety lockout state is released only when the abnormal index is determined to have recovered to the normal range based on the real-time status feature set re-acquired after on-site correction, and an external authorized reset command is received.

[0061] Specifically, based on the target protection strategy, specific control measures are implemented for abnormal operating states in the power supply system caused by wiring errors. Protection actions include, but are not limited to, tripping control, current limiting operation, delayed tripping, and alarm signal output, to reduce the risks that wiring errors may pose to equipment, lines, and personnel safety. Furthermore, systematically storing the target wiring error type along with the real-time status feature set collected at the time can form a complete protection action execution log, providing data support for subsequent anomaly analysis, fault reproduction, operation optimization, and safety assessment. The recorded content includes the protection action trigger time, the target wiring error type identifier, the real-time status feature vector, and related control parameters.

[0062] After completing the protection action, entering the safety interlock state means that after the power supply system completes protection actions such as tripping, current limiting, delayed tripping, or alarming according to the target protection strategy, the power supply circuit and related control units enter a controlled locked state. The safety interlock state is used to prevent malfunctions or power restoration under conditions where wiring errors or abnormal loads have not been eliminated, thereby ensuring the operational safety of equipment, lines, and personnel. In the safety interlock state, the power supply system continues to collect real-time status characteristic sets from field meters, including current amplitude, voltage amplitude, power characteristics, and abnormal duration. When the abnormal index falls below a preset normal threshold, it indicates that the wiring error risk has been effectively eliminated. Simultaneously, upon receiving an external authorized reset command from maintenance personnel or the control center, the safety interlock state is automatically released, allowing the power supply circuit to resume normal operation.

[0063] In summary, the circuit protection method for meter wiring error triggering provided in this application has the following technical effects: by achieving the technical goal of accurately classifying and identifying abnormal meter wiring status and assessing the real-time hazard level, it can generate dynamic protection strategies based on the wiring error type and real-time load characteristics, and execute protection actions such as tripping, current limiting, or alarms in a timely and accurate manner, thereby improving the safety of the power supply system, the reliability of equipment operation, and the accuracy and response speed of protection actions under abnormal conditions.

[0064] Example 2: Based on the same inventive concept as the circuit protection method triggered by meter wiring error in the foregoing examples, this application also provides a circuit protection system triggered by meter wiring error. Please refer to the appendix. Figure 3 The system includes: an abnormal trigger signal generation module 1, used to acquire the real-time state feature set of the meter in real time and calculate the abnormal index. If the abnormal index exceeds the preset abnormal trigger threshold, an abnormal trigger signal is generated, and the real-time state feature set is mapped to error evidence; a target wiring error type output module 2, used to perform iterative probabilistic fusion reasoning layer by layer in the wiring error hierarchical state space based on the error evidence until the target error state node is locked, and output the corresponding target wiring error type; a target protection strategy generation module 3, used to determine the static risk weight based on the target wiring error type, determine the dynamic stress weight based on the real-time state feature set, evaluate the real-time hazard level, and map and generate the corresponding target protection strategy; and a protection action execution module 4, used to execute protection actions according to the target protection strategy and associate the target wiring error type with the real-time state feature set.

[0065] Furthermore, the circuit protection system triggered by the meter wiring error is also used to: extract a reference state feature vector based on a reference state feature set, extract a real-time state feature vector based on the real-time state feature set, and calculate the Mahalanobis distance between the reference state feature vector and the real-time state feature vector as the anomaly index.

[0066] Furthermore, the circuit protection system triggered by the meter wiring error is also used in the following ways: the wiring error hierarchical state space includes an error state tree; if the target error state node that meets the convergence condition cannot be locked at the first level based on the error evidence, then a high-suspicion node is selected based on the first-level error confidence of the first-level state node; the error confidence of the high-suspicion node and the high-suspicion sub-node is aggregated using the error evidence until the target error state node that meets the convergence condition is locked.

[0067] Furthermore, the circuit protection system triggered by the meter wiring error is also used in that: the error state tree includes a first level up to the Nth level, wherein the first level includes a first level state node, the first level state node corresponds to a single wiring error state, the Nth level includes an Nth level state node formed by coupling at least two single wiring error states, and the Nth level state node is a multiple coupled error state.

[0068] Furthermore, the circuit protection system triggered by the meter wiring error is also used to: perform a breadth-first traversal fusion evaluation at the first level to obtain the first-level error confidence level, and sort them to obtain the first-level error confidence level sequence; if there is no node in the first-level error confidence level sequence whose error confidence level is greater than the first error confidence level threshold and whose difference with the adjacent error confidence level is greater than the second error confidence level threshold, then it is determined that the error evidence cannot lock the target error state node that meets the convergence condition at the first level.

[0069] Furthermore, the circuit protection system triggered by the meter wiring error is also used to: for the high-suspicion node, generate a high-suspicion child node of the high-suspicion node at the Nth level in the error state tree, wherein the high-suspicion child node represents the coupling between a single wiring error state corresponding to the high-suspicion node and at least another single wiring error state; form a local space with the high-suspicion node and the high-suspicion child node, and re-aggregate the error confidence of the high-suspicion node and the high-suspicion child node using the error evidence to obtain an updated error confidence, until the target error state node that meets the convergence condition is locked.

[0070] Furthermore, the circuit protection system triggered by the meter wiring error is also used to: determine the static risk weight by the physical damage attributes of the target wiring error type; determine the dynamic stress weight by the current amplitude and abnormal duration in the real-time load characteristics of the real-time state feature set; generate a dynamic hazard index by weighted summing of the static risk weight and the dynamic stress weight, and classify the real-time hazard level according to the dynamic hazard index.

[0071] Furthermore, the circuit protection system triggered by the meter wiring error is also used for: the real-time danger level includes at least a first level, a second level, and a third level, wherein the third level is lower than the second level, and the second level is lower than the first level; when the real-time danger level is at the first level, an immediate trip command is generated; when the real-time danger level is at the second level, a current-limiting operation and delayed trip command is generated; when the real-time danger level is at the third level, an alarm signal is generated and the current power supply state is maintained.

[0072] Furthermore, the circuit protection system triggered by the meter wiring error is also used to: enter a safety lockout state after the protection action is completed; in the safety lockout state, the safety lockout state is released only when the abnormal index is determined to have returned to the normal range based on the real-time status feature set re-acquired after on-site correction, and an external authorized reset command is received.

[0073] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The circuit protection method and specific example triggered by meter wiring error in the aforementioned embodiment one are also applicable to the circuit protection system triggered by meter wiring error in this embodiment. Through the foregoing detailed description of the circuit protection method triggered by meter wiring error, those skilled in the art can clearly understand the circuit protection system triggered by meter wiring error in this embodiment. Therefore, for the sake of brevity, it will not be described in detail here.

[0074] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0075] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application also intends to include such modifications and variations.

Claims

1. A circuit protection method triggered by an incorrect wiring error in an electricity meter, characterized in that, include: The real-time status feature set of the meter is obtained and the anomaly index is calculated. If the anomaly index exceeds the preset anomaly trigger threshold, an anomaly trigger signal is generated, and the real-time status feature set is mapped as erroneous evidence. In the hierarchical state space of wiring errors, iterative probabilistic fusion reasoning is performed layer by layer based on the error evidence until the target error state node is locked and the corresponding target wiring error type is output. Static risk weights are determined based on the target wiring error type, dynamic stress weights are determined based on the real-time status feature set, and the real-time hazard level is evaluated to generate corresponding target protection strategies. Perform protection actions according to the target protection strategy, and associate the target wiring error type with the real-time status feature set.

2. The circuit protection method for meter wiring error triggering as described in claim 1, characterized in that, Calculate the anomaly index, including: Extract the baseline state feature vector based on the baseline state feature set, and extract the real-time state feature vector based on the real-time state feature set. The Mahalanobis distance between the baseline state feature vector and the real-time state feature vector is calculated and used as the anomaly index.

3. The circuit protection method for meter wiring error triggering as described in claim 1, characterized in that, In the hierarchical state space of wiring errors, iterative probabilistic fusion reasoning is performed layer by layer based on the error evidence until the target error state node is locked, and the corresponding target wiring error type is output, including: The wiring error hierarchical state space includes an error state tree; If the target erroneous state node that meets the convergence condition cannot be identified at the first level based on the aforementioned erroneous evidence, then highly suspicious nodes are selected based on the first-level error confidence of the first-level state nodes. The error confidence of the high-suspicion node and its sub-nodes is aggregated using the erroneous evidence until the target erroneous state node that meets the convergence condition is locked.

4. The circuit protection method for meter wiring error triggering as described in claim 3, characterized in that, The error state tree includes a first level up to the Nth level. The first level contains a first-level state node, which corresponds to a single wiring error state. The Nth level contains an Nth-level state node formed by coupling at least two single wiring error states. The Nth-level state node is a multi-coupled error state.

5. The circuit protection method for meter wiring error triggering as described in claim 3, characterized in that, The convergence conditions include: A breadth-first traversal fusion evaluation is performed at the first level to obtain the first-level error confidence, and the first-level error confidence sequence is obtained by sorting. If there is no node in the first-level error confidence sequence whose error confidence is greater than the first error confidence threshold and whose difference with the adjacent error confidence is greater than the second error confidence threshold, then it is determined that the erroneous evidence cannot lock the target error state node that meets the convergence condition at the first level.

6. The circuit protection method for meter wiring error triggering as described in claim 3, characterized in that, Using the aforementioned erroneous evidence, error confidence aggregation is performed on the high-suspicion nodes and their child nodes until the target erroneous state node that meets the convergence condition is identified, including: For the high-suspicion node, a high-suspicion child node of the high-suspicion node at the Nth level is generated in the error state tree. The high-suspicion child node represents the coupling between a single wiring error state corresponding to the high-suspicion node and at least another single wiring error state. The high-suspicion node and the high-suspicion child node constitute a local space. The error confidence of the high-suspicion node and the high-suspicion child node is re-aggregated using the erroneous evidence to obtain an updated error confidence, until the target erroneous state node that meets the convergence condition is locked.

7. The circuit protection method for meter wiring error triggering as described in claim 1, characterized in that, Static risk weights are determined based on the target wiring error type, dynamic stress weights are determined based on the real-time state feature set, and the real-time hazard level is assessed, including: The static risk weight is determined by the physical damage attribute of the target wiring error type; The dynamic stress weight is determined by the current amplitude and abnormal duration in the real-time load characteristics of the real-time state feature set. A dynamic hazard index is generated by weighting and summing the static risk weight and the dynamic stress weight, and the real-time hazard level is determined based on the dynamic hazard index.

8. The circuit protection method for meter wiring error triggering as described in claim 1, characterized in that, The mapping generates the corresponding target protection strategy, including: The real-time hazard level includes at least a first level, a second level, and a third level, wherein the third level is lower than the second level, and the second level is lower than the first level; When the real-time danger level is at the first level, an immediate trip command is generated; When the real-time danger level is at the second level, a current-limiting operation and delayed trip command is generated. When the real-time danger level is at the third level, an alarm signal is generated and the current power supply status is maintained.

9. A circuit protection method for meter wiring errors as described in claim 1, characterized in that, Also includes: After the protection action is completed, the system enters a safety lockout state. In the aforementioned safety lockout state, the safety lockout state is released only when the abnormal index is determined to have returned to the normal range based on the real-time status feature set re-acquired after on-site correction, and an external authorized reset command is received.

10. A circuit protection system triggered by an incorrect wiring error in an electricity meter, characterized in that, The steps for implementing a circuit protection method for a meter wiring error triggered according to any one of claims 1 to 9 include: An abnormal trigger signal generation module is used to acquire the real-time status feature set of the meter in real time and calculate the abnormal index. If the abnormal index exceeds the preset abnormal trigger threshold, an abnormal trigger signal is generated to map the real-time status feature set as erroneous evidence. The target wiring error type output module is used to perform iterative probabilistic fusion reasoning layer by layer in the wiring error hierarchical state space based on the error evidence until the target error state node is locked and the corresponding target wiring error type is output. The target protection strategy generation module is used to determine the static risk weight based on the target wiring error type, determine the dynamic stress weight based on the real-time status feature set, evaluate the real-time hazard level, and map and generate the corresponding target protection strategy. The protection action execution module is used to execute protection actions according to the target protection strategy and associate the target wiring error type with the real-time status feature set.

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