Method and device for dynamically evaluating health degree of power distribution terminal and computer device

Abstract

The application relates to a power distribution terminal health degree dynamic evaluation method, device and computer equipment. The method comprises the following steps: acquiring health evaluation basic data of a power distribution terminal in a current evaluation period; converting the health evaluation basic data into a discrete state mark set according to a preset state mapping rule, processing the state mark set, and obtaining a current health degree evaluation result; retrieving a historical health degree evaluation result sequence of the power distribution terminal in continuous historical periods from a historical database, calculating a jump amplitude sequence between adjacent historical periods and an oscillation count, and constructing a health degree change baseline based on an extreme value statistic quantity of the jump amplitude sequence and the oscillation count; when a maintenance completion event is detected, determining a basic influence intensity, performing scale constraint on the baseline, obtaining an effective adjustment amount to update the health degree evaluation result. Therefore, the maintenance influence can be constrained by the historical fluctuation characteristics, the health degree jump distortion can be avoided, and the evaluation stability and the maintenance strategy credibility are improved.

Description

Technical Field

[0001] This application relates to the field of power distribution automation technology, and in particular to a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for dynamic evaluation of the health of power distribution terminals. Background Technology

[0002] With the continuous expansion of distribution network scale and the ongoing construction of centralized self-healing distribution networks, the number of distribution automation terminals, as important carriers for "three-remote" (telemetry, remote signaling, and remote control) sensing, remote control execution, and fault isolation and recovery, has increased dramatically, covering various geographical environments including urban areas, rural areas, and remote mountainous regions. In engineering sites, distribution terminals of the same batch or model exhibit significant differences in operating environment (such as temperature and humidity, electromagnetic interference), communication quality (such as signal strength and packet loss rate), load fluctuation patterns, and maintenance history (such as inspection records and troubleshooting history) due to different installation locations.

[0003] In traditional technologies, maintenance personnel mainly rely on conducting unified inspections and troubleshooting work according to fixed cycles (such as monthly or quarterly). Health assessment results are mostly formed within a single inspection cycle and output as static levels to guide subsequent maintenance plans.

[0004] However, the above methods are highly subjective and lack historical baseline constraints, resulting in insufficient relevance and accuracy of the evaluation results. Summary of the Invention

[0005] Based on this, it is necessary to provide a dynamic assessment method, device, computer equipment, computer-readable storage medium, and computer program product for the health of power distribution terminals that can improve the stability and consistency of health assessment in large-scale power distribution terminal scenarios, in order to address the above-mentioned technical problems.

[0006] In a first aspect, this application provides a dynamic assessment method for the health of a power distribution terminal, the method comprising:

[0007] Obtain basic health assessment data for the power distribution terminal within the current assessment period;

[0008] According to the preset state mapping rules, the basic health assessment data is converted into a discrete set of state labels, and the set of state labels is processed based on the principle of the most unfavorable state to obtain the current health assessment result.

[0009] Retrieve the historical health assessment result sequence of the power distribution terminal in a continuous historical period from the historical database, calculate the jump amplitude sequence and oscillation count between adjacent historical periods, and construct a health change baseline based on the extreme value statistics of the jump amplitude sequence and the oscillation count;

[0010] When an operation and maintenance completion event for the power distribution terminal is detected, the basic impact intensity corresponding to the type of the operation and maintenance completion event is determined;

[0011] The effective health adjustment amount is obtained by applying a scale constraint on the basic influence intensity through the baseline of health change, and then applying the effective health adjustment amount to the current health assessment result to obtain the updated health assessment result.

[0012] In one embodiment, the basic health assessment data includes: online status information, defect and anomaly records, and function execution result records; the step of converting the basic health assessment data into a discrete set of status labels according to a preset status mapping rule includes:

[0013] For each data item in the basic health assessment data, it is converted into a corresponding status level label according to a preset mapping relationship between status and level; the status level label includes at least one of normal label, attention label, abnormal label and severe label, and the status level labels corresponding to each data item in the basic health assessment data form a discrete status label set.

[0014] In one embodiment, processing the set of state markers based on the worst-case scenario principle to obtain the current health assessment result includes:

[0015] The state marker with the highest severity is selected from the set of state markers, and the health score corresponding to the state marker with the highest severity is used as the current health assessment result.

[0016] When there are multiple status markers with the same highest severity level, the health score corresponding to any one of the status markers with the highest severity level is taken as the current health assessment result.

[0017] In one embodiment, the step of calculating the jump amplitude sequence and oscillation count between adjacent historical periods, and constructing a health change baseline based on the extreme value statistics of the jump amplitude sequence and the oscillation count, includes:

[0018] The absolute value of the difference between the health assessment results of two adjacent historical periods in the historical health assessment result sequence is calculated sequentially to obtain the jump amplitude sequence;

[0019] The number of times the direction of health change reversed between adjacent periods in the historical health assessment result sequence is counted to obtain the oscillation count;

[0020] Extract the maximum and minimum values ​​from the jump amplitude sequence, and determine the baseline constraint upper limit value based on the difference between the maximum and minimum values ​​and the preset fluctuation coefficient;

[0021] The baseline constraint lower limit value is determined based on the oscillation count;

[0022] The health status change baseline is formed by the upper limit of the baseline constraint and the lower limit of the baseline constraint.

[0023] In one embodiment, determining the basic impact intensity corresponding to the type of the maintenance completion event includes:

[0024] Obtain the type information of the maintenance completion event, wherein the type information includes at least one of defect elimination type, equipment replacement type, and parameter adjustment type;

[0025] Based on the preset mapping relationship between maintenance type and impact intensity, find the basic impact intensity value that matches the type information.

[0026] In one embodiment, the step of applying a scale constraint to the baseline influence intensity based on the health status change baseline to obtain the effective health status adjustment amount includes:

[0027] Compare the intensity of the basic impact with the constraint range of the baseline of health status change;

[0028] When the basic influence intensity is within the constraint range of the health change baseline, the basic influence intensity is used as the effective health adjustment amount;

[0029] When the intensity of the basic influence exceeds the upper limit of the constraint range of the baseline of health change, the upper limit is used as the effective health adjustment amount;

[0030] When the intensity of the basic influence is lower than the lower limit of the constraint range of the baseline of health change, the lower limit is used as the effective health adjustment amount.

[0031] In one embodiment, after obtaining the updated health assessment results, the method further includes:

[0032] The updated health assessment results are compared with the preset health grading thresholds to determine the target maintenance level, and maintenance execution instructions containing the inspection interval and defect elimination time limit are generated based on the target maintenance level.

[0033] In one embodiment, comparing the updated health assessment result with a preset health grading threshold to determine the target maintenance level, and generating maintenance execution instructions including the inspection interval and defect elimination time limit based on the target maintenance level, includes:

[0034] The updated health assessment results are compared with the first grading threshold and the second grading threshold, respectively, wherein the first grading threshold is greater than the second grading threshold;

[0035] When the updated health assessment result is greater than or equal to the first classification threshold, the target maintenance level is determined to be the first level, and maintenance execution instructions with the corresponding first inspection interval and first defect elimination time limit are generated.

[0036] When the updated health assessment result is less than the first grading threshold and greater than or equal to the second grading threshold, the target maintenance level is determined to be the second level, and maintenance execution instructions corresponding to the second inspection interval and the second defect elimination time limit are generated.

[0037] When the updated health assessment result is less than the second classification threshold, the target maintenance level is determined to be the third level, and maintenance execution instructions with corresponding third inspection interval and third defect elimination time limit are generated.

[0038] Wherein, the first video cycle interval is greater than the second video cycle interval, the second video cycle interval is greater than the third video cycle interval; the first defect elimination time limit is greater than the second defect elimination time limit, and the second defect elimination time limit is greater than the third defect elimination time limit.

[0039] Secondly, this application also provides a dynamic assessment device for the health of a power distribution terminal, the device comprising:

[0040] The data acquisition module is used to acquire basic health assessment data of the power distribution terminal within the current assessment period;

[0041] The basic assessment module is used to convert the basic health assessment data into a discrete set of state labels according to a preset state mapping rule, and process the set of state labels based on the worst-case state dominance principle to obtain the current health assessment result.

[0042] The baseline construction module is used to retrieve the historical health assessment result sequence of the power distribution terminal in a continuous historical period from the historical database, calculate the jump amplitude sequence and oscillation count between adjacent historical periods, and construct a health change baseline based on the extreme value statistics of the jump amplitude sequence and the oscillation count.

[0043] The impact determination module is used to determine the basic impact intensity corresponding to the type of the operation and maintenance completion event when an operation and maintenance completion event for the power distribution terminal is detected.

[0044] The dynamic correction module is used to apply scale constraints to the basic influence intensity through the health change baseline to obtain an effective health adjustment amount, and then apply the effective health adjustment amount to the current health assessment result to obtain an updated health assessment result.

[0045] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0046] Obtain basic health assessment data for the power distribution terminal within the current assessment period;

[0047] According to the preset state mapping rules, the basic health assessment data is converted into a discrete set of state labels, and the set of state labels is processed based on the principle of the most unfavorable state to obtain the current health assessment result.

[0048] Retrieve the historical health assessment result sequence of the power distribution terminal in a continuous historical period from the historical database, calculate the jump amplitude sequence and oscillation count between adjacent historical periods, and construct a health change baseline based on the extreme value statistics of the jump amplitude sequence and the oscillation count;

[0049] When an operation and maintenance completion event for the power distribution terminal is detected, the basic impact intensity corresponding to the type of the operation and maintenance completion event is determined;

[0050] The effective health adjustment amount is obtained by applying a scale constraint on the basic influence intensity through the baseline of health change, and then applying the effective health adjustment amount to the current health assessment result to obtain the updated health assessment result.

[0051] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0052] Obtain basic health assessment data for the power distribution terminal within the current assessment period;

[0053] According to the preset state mapping rules, the basic health assessment data is converted into a discrete set of state labels, and the set of state labels is processed based on the principle of the most unfavorable state to obtain the current health assessment result.

[0054] Retrieve the historical health assessment result sequence of the power distribution terminal in a continuous historical period from the historical database, calculate the jump amplitude sequence and oscillation count between adjacent historical periods, and construct a health change baseline based on the extreme value statistics of the jump amplitude sequence and the oscillation count;

[0055] When an operation and maintenance completion event for the power distribution terminal is detected, the basic impact intensity corresponding to the type of the operation and maintenance completion event is determined;

[0056] The effective health adjustment amount is obtained by applying a scale constraint on the basic influence intensity through the baseline of health change, and then applying the effective health adjustment amount to the current health assessment result to obtain the updated health assessment result.

[0057] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0058] Obtain basic health assessment data for the power distribution terminal within the current assessment period;

[0059] According to the preset state mapping rules, the basic health assessment data is converted into a discrete set of state labels, and the set of state labels is processed based on the principle of the most unfavorable state to obtain the current health assessment result.

[0060] Retrieve the historical health assessment result sequence of the power distribution terminal in a continuous historical period from the historical database, calculate the jump amplitude sequence and oscillation count between adjacent historical periods, and construct a health change baseline based on the extreme value statistics of the jump amplitude sequence and the oscillation count;

[0061] When an operation and maintenance completion event for the power distribution terminal is detected, the basic impact intensity corresponding to the type of the operation and maintenance completion event is determined;

[0062] The effective health adjustment amount is obtained by applying a scale constraint on the basic influence intensity through the baseline of health change, and then applying the effective health adjustment amount to the current health assessment result to obtain the updated health assessment result.

[0063] The aforementioned dynamic assessment method, device, computer equipment, computer-readable storage medium, and computer program product for the health of distribution terminals acquire basic health assessment data of the distribution terminals within the current assessment period and convert it into a discrete set of state labels. Simultaneously, processing based on the worst-case scenario principle allows multi-dimensional and heterogeneous basic health assessment data to be uniformly quantified into health assessment results. Furthermore, the safety-oriented logic based on the worst-case scenario principle ensures that any anomaly in any key dimension is fully reflected, avoiding the dilution and masking of serious defects by weighted averaging methods, and improving the accuracy and security of the assessment results in representing the actual risks of the terminals. By retrieving historical health sequences of the same terminal and calculating jump amplitudes and oscillation counts to construct individualized health change baselines, the health assessment has a change reference matching the terminal's own historical fluctuation characteristics. This provides an objective and personalized benchmark for controlling the update amplitude after subsequent maintenance events, overcoming the deficiency that a uniform threshold cannot reflect individual differences among terminals. By determining the basic impact intensity when an operation and maintenance (O&M) completion event is triggered and using the health change baseline for scale constraints, the impact of O&M actions (such as defect elimination and replacement) on health status retains a reasonable adjustment direction in engineering semantics while being limited to an acceptable range of historical fluctuations for the terminal. This effectively avoids the problem of excessively large or small health status update magnitudes after O&M, ensuring the stability and reliability of continuous health status updates. By applying scale constraints to the basic impact intensity using the health change baseline, an effective health status adjustment amount is obtained. This effective health status adjustment amount is then applied to the current health status assessment result to obtain an updated health status assessment result. Therefore, the final updated health status assessment result is more accurate, more stable, and more consistent with the individual characteristics of the terminal compared to existing technologies, effectively supporting lean O&M management of the distribution network. Attached Figure Description

[0064] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0065] Figure 1 This is an application environment diagram of a dynamic assessment method for the health of power distribution terminals in one embodiment;

[0066] Figure 2 This is a flowchart illustrating a dynamic assessment method for the health of a power distribution terminal in one embodiment.

[0067] Figure 3 This is a flowchart illustrating a dynamic assessment method for the health of a power distribution terminal in another embodiment.

[0068] Figure 4 This is a structural block diagram of a dynamic assessment device for the health of a power distribution terminal in one embodiment;

[0069] Figure 5 This is a structural block diagram of a dynamic assessment device for the health of a power distribution terminal in another embodiment;

[0070] Figure 6 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0071] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0072] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0073] With the continuous expansion of distribution network scale and the ongoing construction of centralized self-healing distribution networks, distribution automation terminals, as crucial carriers for "three-remote" (telemetry, remote signaling, and remote control) sensing, remote control execution, and fault isolation and recovery, are experiencing a dramatic increase in deployment, covering various geographical environments including urban areas, rural areas, and remote mountainous regions. In engineering sites, distribution terminals of the same batch or model exhibit significant differences in operating environment (e.g., temperature and humidity, electromagnetic interference), communication quality (e.g., signal strength, packet loss rate), load fluctuation patterns, and maintenance history (e.g., inspection records, troubleshooting history) due to varying installation locations. Currently, health status management for these large-scale terminal groups primarily relies on maintenance personnel conducting unified inspections and troubleshooting work according to fixed cycles (e.g., monthly, quarterly). Health assessment results are mostly generated within a single inspection cycle and output as static levels to guide subsequent maintenance plans.

[0074] It is evident that the most significant problems with current technology are as follows:

[0075] 1) Health assessments are usually based on a single inspection cycle to form a static level, which lacks constraints on the evolution of the historical level of the same terminal. This makes it difficult to determine whether the jump in health between adjacent cycles is consistent with the historical fluctuation characteristics of the terminal itself, and thus makes it difficult to adjust the frequency of maintenance without a stable reference benchmark.

[0076] 2) Operation and maintenance activities have strong intervention attributes on site. After the completion of actions such as fault handling, defect elimination and closed loop, and equipment replacement, the terminal status often changes significantly. However, existing methods usually only retain operation and maintenance records as supplementary information. There is a lack of an update mechanism to quantify the impact of operation and maintenance and combine it with historical change benchmarks. This can easily lead to the health update being too large or too small after operation and maintenance, which affects the credibility of subsequent operation and maintenance strategies.

[0077] 3) The health assessment results and operation and maintenance execution strategies (such as the number of inspections and the time limit for defect elimination) rely heavily on manual experience or discrete thresholds for coarse-grained mapping. There is a lack of an engineering closed loop to stably implement the updated health status into specific operation and maintenance instructions, which makes it difficult to maintain consistency and traceability of differentiated operation and maintenance in large-scale terminal scenarios.

[0078] This application aims to provide a dynamic assessment method, device, and computer equipment for the health of distribution terminals. It constructs an individualized health change baseline based on the terminal's own historical health sequence, imposes scale constraints on the health update magnitude after the operation and maintenance event is triggered, and stably maps the updated health into specific operation and maintenance instructions that include the number of inspections and the time limit for troubleshooting. This overcomes the shortcomings of existing technologies, such as the lack of historical baseline constraints leading to distorted health jumps, the lack of reliable references for post-operation and maintenance updates, and the difficulty in engineering the assessment results. It improves the stability, consistency, and executability of health assessment in large-scale distribution terminal scenarios.

[0079] For example, Figure 1 This is an application environment diagram of a dynamic assessment method for the health of distribution terminals in one embodiment, such as... Figure 1As shown, the system includes a power distribution terminal 101 and a server 102, which are connected via a communication network. The power distribution terminal 101 collects local health assessment data and uploads it to the server 102 via the communication network. After receiving the data, the server 102 executes the dynamic health assessment method for power distribution terminals provided in this embodiment of the invention to obtain updated health assessment results for each power distribution terminal 101. It can further generate corresponding maintenance execution instructions and send them to maintenance personnel terminals or the maintenance management system to guide the scheduling of on-site inspections and defect elimination deadlines. Optionally, the power distribution terminal 101 includes, but is not limited to, feeder terminal units (FTUs), distribution terminal units (DTUs), and transformer terminal units (TTUs).

[0080] In one exemplary embodiment, such as Figure 2 As shown, a dynamic assessment method for the health of a power distribution terminal is provided, which can be applied to... Figure 1 Taking the server in the example, the explanation includes the following steps S201 to S205. Wherein:

[0081] Step S201: Obtain the basic health assessment data of the power distribution terminal within the current assessment period.

[0082] In this embodiment, the server 102 receives basic health assessment data uploaded by each distribution terminal 101 (including but not limited to feeder terminal FTU, substation terminal DTU, and distribution transformer terminal TTU) via a communication network. Optionally, the basic health assessment data includes: online status information, defect and anomaly records, and function execution result records.

[0083] Among them, online status information refers to the communication connectivity status between the power distribution terminal and the master station, the heartbeat signal response status, and the power-on operation status of the terminal itself, which is used to reflect whether the terminal is online and whether there are abnormalities such as communication interruption or frequent disconnection; defect and anomaly records refer to various alarm information, fault messages, limit overrun records, and equipment defect descriptions entered by maintenance personnel during inspection or maintenance, which are used to reflect the known problems and severity of the terminal; function execution result records refer to the success or failure records of the power distribution terminal when performing remote control operations (such as switch opening and closing commands), setting value issuance, remote parameter adjustment, etc., which are used to reflect the availability of the terminal's core functions.

[0084] In one possible example, the basic health assessment data may further include environmental monitoring data (such as temperature and humidity inside the chassis where the terminal is located), communication quality data (such as signal strength, bit error rate, and packet loss rate), and load statistics (such as the number of times current and voltage exceedances). This application does not limit the specific data types and sources of the basic health assessment data, and can be extended and configured according to actual engineering needs.

[0085] It should be understood that the server 102 can proactively query and obtain the aforementioned data from each power distribution terminal 101 according to a preset evaluation cycle (such as once a month, once a quarter, or a cycle dynamically set according to the operation and maintenance strategy), or the power distribution terminal 101 can proactively report the data at predetermined time intervals. This embodiment does not limit the method of data acquisition, as long as complete basic health assessment data within the current evaluation cycle can be obtained.

[0086] Step S202: According to the preset state mapping rules, the basic health assessment data is converted into a discrete set of state labels, and the set of state labels is processed based on the principle of the most unfavorable state to obtain the current health assessment result.

[0087] In this embodiment, after obtaining the basic health assessment data, the server 102 converts each data item in the basic health assessment data into a corresponding status level label according to the preset mapping relationship between status and level. The status level label includes at least one of normal label, attention label, abnormal label and serious label. The status level labels corresponding to each data item in the basic health assessment data form a discrete set of status labels.

[0088] For example, server 102 is pre-configured with a status mapping table, which defines the status level labels corresponding to different values ​​or status intervals of various health assessment basic data. For example, for online status information, if the terminal communication is normal and the heartbeat signal is stable, it is mapped to a "normal label"; if the terminal communication is intermittently interrupted, it is mapped to a "pay attention label"; if the terminal communication is completely interrupted and the duration exceeds a preset threshold, it is mapped to an "abnormal label". Similarly, for defect and abnormal records, if the terminal has no defect records, it is mapped to a "normal label"; if there are general defects (such as indicator light failure or minor parameter offset) that do not affect core functions, it is mapped to a "pay attention label"; if there are serious defects (such as communication module failure or power supply abnormality) but the terminal can still partially operate, it is mapped to an "abnormal label"; if there are fatal defects (such as CPU failure or motherboard burnout) that render the terminal completely unusable, it is mapped to a "serious label". For example, regarding the recording of function execution results, if all remote control operations within the terminal's most recent preset number of attempts are successful, it is mapped to a "normal mark"; if there is a single execution failure but a success after retry, it is mapped to a "note mark"; if there are consecutive execution failures and it is confirmed that they are not due to communication reasons, it is mapped to an "abnormal mark".

[0089] It should be noted that after the mapping is completed, each health assessment basic data corresponds to a status level label, and these labels together constitute the status label set of the current assessment cycle of the power distribution terminal.

[0090] For example, after obtaining the set of status markers, server 102 processes them based on the worst-case scenario principle to obtain the current health assessment result. Optionally, the worst-case scenario principle means: selecting the status marker with the highest severity from the set of status markers, and using the health score corresponding to the status marker with the highest severity as the current health assessment result; when there are multiple status markers with the same highest severity, taking the health score corresponding to any one of the status markers with the highest severity as the current health assessment result.

[0091] Step S203: Retrieve the historical health assessment result sequence of the power distribution terminal in a continuous historical period from the historical database, calculate the jump amplitude sequence and oscillation count between adjacent historical periods, and construct the health change baseline based on the extreme value statistics of the jump amplitude sequence and the oscillation count.

[0092] In this embodiment, after obtaining the current health assessment result, the server 102 retrieves the historical health assessment result sequence of the power distribution terminal within a continuous historical period from the historical database, using the unique identifier of the power distribution terminal (such as equipment number or asset number) as an index. The historical database stores the historical health assessment results generated by the terminal in each past assessment period through steps S201~S202 (or the corresponding historical version of the assessment method).

[0093] For example, the absolute value of the difference between the health assessment results of two adjacent historical periods in the historical health assessment result sequence is calculated sequentially to obtain the jump amplitude sequence; the number of times the direction of health change in adjacent periods in the historical health assessment result sequence is reversed is counted to obtain the oscillation count.

[0094] For example, the maximum and minimum values ​​in the jump amplitude sequence are extracted, and the upper limit of the baseline constraint is determined based on the difference between the maximum and minimum values ​​and the preset fluctuation coefficient; the lower limit of the baseline constraint is determined based on the oscillation count; the upper limit of the baseline constraint and the lower limit of the baseline constraint together constitute the health change baseline.

[0095] In a specific embodiment, the baseline constraint lower limit L can be determined based on the oscillation count. When the oscillation count is less than a preset first threshold (indicating that the terminal's historical changes are stable), L takes the preset first lower limit (e.g., 2 points); when the oscillation count is greater than or equal to a preset second threshold (indicating that the terminal's historical changes are drastic), L takes the preset second lower limit (e.g., 8 points), and the second lower limit is greater than the first lower limit; when the oscillation count is between the two, L is determined by interpolation. This lower limit ensures that even if the maintenance event has a significant positive impact on the terminal's status, the single improvement in health will not be less than this lower limit, avoiding insufficient adjustment that results in no substantial change in health after the update.

[0096] It should be noted that the constraint range [L, U] of the health status change baseline is jointly constituted by the upper limit value U and the lower limit value L of the baseline constraint. This baseline is constructed entirely based on the terminal's own historical data, and therefore has individual characteristics. That is, different terminals will have different health status change baselines due to differences in their historical fluctuation characteristics.

[0097] Step S204: When an operation and maintenance completion event for a power distribution terminal is detected, determine the basic impact intensity corresponding to the type of operation and maintenance completion event.

[0098] In this embodiment, after the maintenance personnel complete the maintenance operations (such as defect elimination, equipment replacement, parameter adjustment, etc.) for the power distribution terminal, they will close the loop on the work order in the maintenance management system. The server 102 detects the maintenance completion event for the power distribution terminal by listening to the work order status changes in the maintenance management system or receiving the work order completion notification pushed by the maintenance management system.

[0099] For example, after detecting an operation and maintenance completion event, server 102 obtains the type information of the operation and maintenance completion event. The type information includes at least one of defect elimination type, equipment replacement type, and parameter adjustment type. Based on the preset mapping relationship between operation and maintenance type and impact intensity, it finds the basic impact intensity value that matches the type information.

[0100] In this embodiment, the type of maintenance completion event determines the expected direction and extent of its impact on terminal health: defect elimination type usually eliminates existing defects or anomalies in the terminal, which has a positive impact on health; equipment replacement type (such as replacing the entire terminal or replacing key components) may restore the terminal status to a near-new level, which has a significant positive impact on health; parameter adjustment type (such as adjusting protection settings or correcting measurement coefficients) has a relatively small impact on health.

[0101] Optionally, server 102 may be pre-configured with a mapping relationship between operation and maintenance types and their impact intensity. This mapping relationship defines the basic impact intensity value corresponding to different operation and maintenance types. For example, the defect elimination type corresponds to a basic impact intensity value of +10 points (indicating that the health level should be improved by 10 points); the equipment replacement type corresponds to a basic impact intensity value of +25 points (indicating that the health level should be improved by 25 points); and the parameter tuning type corresponds to a basic impact intensity value of +5 points (indicating that the health level should be improved by 5 points). Server 102 searches for a matching basic impact intensity value in the above mapping relationship based on the obtained operation and maintenance completion event type information.

[0102] It should be noted that the basic impact strength values ​​in the above mapping relationship are all positive, indicating that the maintenance completion event has a positive impact on the health of the terminal. The trigger condition for the maintenance completion event is usually that the maintenance personnel have completed the closed-loop work order, which means that the terminal has been repaired or adjusted, and its status should be better than before maintenance. In other embodiments, negative basic impact strength values ​​can be configured for specific types of maintenance events (such as detecting equipment aging or performance degradation events) according to the actual engineering scenario, and this application does not limit this. The specific magnitude of the basic impact strength value can be predetermined based on historical maintenance data statistics, expert experience, or machine learning methods, and continuously optimized and adjusted in actual operation.

[0103] Step S205: Apply scale constraints to the baseline influence intensity through the health change baseline to obtain the effective health adjustment amount, and apply the effective health adjustment amount to the current health assessment result to obtain the updated health assessment result.

[0104] In this embodiment, the server 102 compares the basic influence intensity determined in step S204 with the constraint range [L, U] of the health change baseline constructed in step S203, where L represents the lower limit of the baseline constraint and U represents the upper limit of the baseline constraint.

[0105] For example, the basic impact intensity is compared with the constraint range of the health change baseline; when the basic impact intensity is within the constraint range of the health change baseline, the basic impact intensity is used as the effective health adjustment amount; when the basic impact intensity exceeds the upper limit of the constraint range of the health change baseline, the upper limit is used as the effective health adjustment amount; when the basic impact intensity is lower than the lower limit of the constraint range of the health change baseline, the lower limit is used as the effective health adjustment amount.

[0106] For example, suppose the historical health status change baseline constraint range for a certain terminal is [5, 15], meaning the normal range of health status change between adjacent periods in the history of this terminal is between 5 and 15 points. If the basic impact intensity corresponding to a defect elimination completion event is +12 points, which is within the range of [5, 15], then server 102 will directly apply +12 points as an effective health status adjustment amount to the current health status assessment result. If the basic impact intensity is +20 points, exceeding the upper limit of 15 points, then server 102 will use 15 points as an effective health status adjustment amount to avoid excessive health status improvement due to a single maintenance event, which would be seriously inconsistent with historical patterns. If the basic impact intensity is +3 points, lower than the lower limit of 5 points, then server 102 will use 5 points as an effective health status adjustment amount to ensure that there is a substantial positive change in health status after maintenance, avoiding the updated result being no significant difference from the pre-maintenance result due to an insufficient adjustment amount.

[0107] For example, server 102 applies the effective health adjustment amount obtained after scale constraints to the current health assessment result obtained in step S202, that is: updated health assessment result = current health assessment result + effective health adjustment amount. Continuing the example above, if the current health assessment result is 60 points and the effective health adjustment amount is +12 points, then the updated health assessment result is 72 points.

[0108] It should be noted that the health assessment results are usually set between 0 and 100 points. When calculating the updated health assessment results, if the result exceeds 100 points, it will be truncated to 100 points; if the result is below 0 points, it will be truncated to 0 points.

[0109] The aforementioned dynamic assessment method for the health of distribution terminals obtains basic health assessment data of the distribution terminals within the current assessment period, providing a complete data source foundation for subsequent assessments. Through preset state mapping rules, heterogeneous multidimensional basic data is uniformly converted into a discrete set of state labels, and processed based on the principle of worst-case scenario dominance. This ensures that any serious anomaly in any key dimension can be fully captured, avoiding the dilution or masking of serious defects by weighted averaging or comprehensive scoring methods. This improves the sensitivity and security of the assessment results to the actual operational risks of the terminals. Simultaneously, it quantifies multi-source heterogeneous data into calculable and comparable health scores, laying the data foundation for subsequent historical sequence analysis and dynamic updates. Furthermore, it retrieves historical health sequences of the same terminal and calculates the jump amplitude. By using degree and oscillation counts to construct an individualized health change baseline, the health assessment has an objective reference that matches the historical fluctuation characteristics of the terminal itself. This provides a personalized scale for controlling the update amplitude after subsequent maintenance events, overcoming the shortcomings of fixed thresholds or uniform weights that cannot reflect the individual differences of different terminals. Based on this, the basic impact intensity is determined when a maintenance completion event is triggered and scaled by the health change baseline. This ensures that the impact of maintenance actions (such as defect elimination, equipment replacement, parameter adjustment, etc.) on health retains a reasonable adjustment direction in engineering semantics while being limited to the acceptable range of the terminal's historical fluctuations. This effectively avoids the problem of inaccurate strategies due to excessively large or small health update amplitudes after maintenance, ensuring the stability and reliability of continuous health updates. Therefore, the final updated health assessment results are more accurate, more stable, and more consistent with the individual characteristics of the terminal compared to existing technologies, providing a reliable data foundation for lean maintenance management of distribution networks.

[0110] In another exemplary embodiment, such as Figure 3 As shown, a dynamic assessment method for the health of a power distribution terminal is provided, which can be applied to... Figure 1 Taking the server in the example, the explanation includes the following steps S301 to S306. Wherein:

[0111] Step S301: Obtain the basic health assessment data of the power distribution terminal within the current assessment period.

[0112] Step S302: According to the preset state mapping rules, the basic health assessment data is converted into a discrete set of state labels, and the set of state labels is processed based on the principle of the most unfavorable state to obtain the current health assessment result.

[0113] Step S303: Retrieve the historical health assessment result sequence of the power distribution terminal in a continuous historical period from the historical database, calculate the jump amplitude sequence and oscillation count between adjacent historical periods, and construct the health change baseline based on the extreme value statistics of the jump amplitude sequence and the oscillation count.

[0114] Step S304: When an operation and maintenance completion event for a power distribution terminal is detected, determine the basic impact intensity corresponding to the type of operation and maintenance completion event.

[0115] Step S305: Apply scale constraints to the baseline influence intensity through the health change baseline to obtain the effective health adjustment amount, and apply the effective health adjustment amount to the current health assessment result to obtain the updated health assessment result.

[0116] For the specific implementation process and technical effects of steps S301 to S305 in this embodiment, please refer to [link to documentation]. Figure 2 The relevant descriptions of steps S201 to S205 in the method embodiment shown will not be repeated here.

[0117] Step S306: Compare the updated health assessment results with the preset health grading thresholds to determine the target maintenance level, and generate maintenance execution instructions that include the patrol interval and defect elimination time limit based on the target maintenance level.

[0118] In this embodiment, the updated health assessment result obtained in server step S305 is compared with the first grading threshold and the second grading threshold, wherein the first grading threshold is greater than the second grading threshold. When the updated health assessment result is greater than or equal to the first grading threshold, the target maintenance level is determined to be the first level (e.g., "Excellent"), and maintenance execution instructions with a corresponding first inspection interval (e.g., once per quarter) and a first defect elimination deadline (e.g., 30 days) are generated. When the updated health assessment result is less than the first grading threshold but greater than or equal to the second grading threshold, the target maintenance level is determined to be the second level (e.g., "Attention"), and maintenance execution instructions with a corresponding second inspection interval (e.g., once per month) and a second defect elimination deadline (e.g., 15 days) are generated. When the updated health assessment result is less than the second grading threshold, the target maintenance level is determined to be the third level (e.g., "Severe"), and maintenance execution instructions with a corresponding third inspection interval (e.g., once per week) and a third defect elimination deadline (e.g., 3 days) are generated.

[0119] Among them, the interval between the first video inspection is greater than the interval between the second video inspection, and the interval between the second video inspection is greater than the interval between the third video inspection; the first defect elimination time limit is greater than the second defect elimination time limit, and the second defect elimination time limit is greater than the third defect elimination time limit, so that terminals with lower health assessment results receive more frequent inspections and more urgent defect elimination arrangements, thereby achieving differentiated and precise operation and maintenance.

[0120] Optionally, after generating the operation and maintenance execution instruction, the server sends the instruction to the mobile terminal of the operation and maintenance personnel or the operation and maintenance management system. The operation and maintenance personnel then conduct inspections on the corresponding terminals according to the inspection interval specified in the instruction and complete the defect handling within the defect elimination time limit, thereby realizing an engineering closed loop from dynamic health assessment to specific operation and maintenance actions.

[0121] In this embodiment, Figure 2 Building upon all the beneficial effects of the illustrated embodiments, step S306 automatically determines the target maintenance level by comparing the updated health assessment results with preset health grading thresholds. Based on this, it generates maintenance execution instructions containing specific patrol intervals and defect elimination deadlines. This allows the health assessment results to be directly and stably translated into executable and traceable maintenance tasks, solving the problem of insufficient consistency and traceability in existing technologies where health status and maintenance execution rely on coarse-grained mapping using manual experience or discrete thresholds. Through a dual-threshold, three-tier mechanism, terminals with different health statuses are automatically matched with differentiated patrol densities and defect elimination urgency, achieving precise deployment and scientific allocation of maintenance resources in large-scale terminal scenarios. This ensures the feasibility and sustainable operation of differentiated maintenance strategies in large-scale terminal scenarios.

[0122] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0123] Based on the same inventive concept, this application also provides a dynamic assessment device for the health of distribution terminals, used to implement the dynamic assessment method for the health of distribution terminals described above. The solution provided by this device is similar to the implementation described in the above method. Therefore, the specific limitations of one or more embodiments of the dynamic assessment device for the health of distribution terminals provided below can be found in the limitations of the dynamic assessment method for the health of distribution terminals described above, and will not be repeated here.

[0124] In one exemplary embodiment, such as Figure 4As shown, a dynamic assessment device for the health of a power distribution terminal is provided, comprising: a data acquisition module 401, a basic assessment module 402, a baseline construction module 403, an impact determination module 404, and a dynamic correction module 405, wherein:

[0125] Data acquisition module 401 is used to acquire basic health assessment data of the power distribution terminal within the current assessment period;

[0126] The basic assessment module 402 is used to convert the basic health assessment data into a discrete set of state labels according to the preset state mapping rules, and process the set of state labels based on the principle of the most unfavorable state to obtain the current health assessment result.

[0127] The baseline construction module 403 is used to retrieve the historical health assessment result sequence of the power distribution terminal in a continuous historical period from the historical database, calculate the jump amplitude sequence and oscillation count between adjacent historical periods, and construct the health change baseline based on the extreme value statistics of the jump amplitude sequence and the oscillation count.

[0128] The impact determination module 404 is used to determine the basic impact intensity corresponding to the type of operation and maintenance completion event when an operation and maintenance completion event for a power distribution terminal is detected.

[0129] The dynamic correction module 405 is used to apply scale constraints to the basic influence intensity through the health change baseline, obtain the effective health adjustment amount, and apply the effective health adjustment amount to the current health assessment result to obtain the updated health assessment result.

[0130] In some embodiments, the basic data for health assessment includes: online status information, defect and anomaly records, and function execution result records.

[0131] In some embodiments, the basic assessment module 402 is specifically used to: convert each data item in the basic health assessment data into a corresponding status level label according to a preset mapping relationship between status and level; the status level label includes at least one of normal label, attention label, abnormal label and severe label, and the status level labels corresponding to each data item in the basic health assessment data form a discrete set of status labels.

[0132] In some embodiments, the basic assessment module 402 is specifically used to: filter out the status marker with the highest severity from the status marker set, and take the health score corresponding to the status marker with the highest severity as the current health assessment result; when there are multiple status markers with the same highest severity, take the health score corresponding to any one of the status markers with the highest severity as the current health assessment result.

[0133] In some embodiments, the baseline construction module 403 is specifically used to: sequentially calculate the absolute value of the difference between the health assessment results of two adjacent historical periods in the historical health assessment result sequence to obtain the jump amplitude sequence; count the number of times the direction of health change in adjacent periods reverses in the historical health assessment result sequence to obtain the oscillation count; extract the maximum and minimum values ​​in the jump amplitude sequence, and determine the upper limit of the baseline constraint based on the difference between the maximum and minimum values ​​and the preset fluctuation coefficient; determine the lower limit of the baseline constraint based on the oscillation count; and construct the health change baseline together with the upper limit of the baseline constraint and the lower limit of the baseline constraint.

[0134] In some embodiments, the impact determination module 404 is specifically used to: obtain type information of the maintenance completion event, the type information including at least one of defect elimination type, equipment replacement type and parameter adjustment type; and find the basic impact intensity value that matches the type information according to the preset mapping relationship between maintenance type and impact intensity.

[0135] In some embodiments, the dynamic correction module 405 is specifically used to: compare the basic influence intensity with the constraint range of the health change baseline; when the basic influence intensity is within the constraint range of the health change baseline, use the basic influence intensity as the effective health adjustment amount; when the basic influence intensity exceeds the upper limit of the constraint range of the health change baseline, use the upper limit as the effective health adjustment amount; when the basic influence intensity is lower than the lower limit of the constraint range of the health change baseline, use the lower limit as the effective health adjustment amount.

[0136] In another exemplary embodiment, such as Figure 5 As shown, a dynamic assessment device for the health of a power distribution terminal is provided. Figure 4 Based on the device shown, it may also include:

[0137] The execution instruction generation module 406 is used to compare the updated health assessment results with the preset health classification threshold, determine the target maintenance level, and generate maintenance execution instructions including the inspection interval and the defect elimination time limit based on the target maintenance level.

[0138] In some embodiments, the execution instruction generation module 406 is specifically configured to: compare the updated health assessment result with a first grading threshold and a second grading threshold, wherein the first grading threshold is greater than the second grading threshold; when the updated health assessment result is greater than or equal to the first grading threshold, determine the target maintenance level as the first level, and generate maintenance execution instructions corresponding to the first inspection interval and the first defect elimination time limit; when the updated health assessment result is less than the first grading threshold but greater than or equal to the second grading threshold, determine the target maintenance level as the second level, and generate maintenance execution instructions corresponding to the second inspection interval and the second defect elimination time limit; when the updated health assessment result is less than the second grading threshold, determine the target maintenance level as the third level, and generate maintenance execution instructions corresponding to the third inspection interval and the third defect elimination time limit; wherein the first inspection interval is greater than the second inspection interval, the second inspection interval is greater than the third inspection interval; the first defect elimination time limit is greater than the second defect elimination time limit, and the second defect elimination time limit is greater than the third defect elimination time limit.

[0139] Each module in the aforementioned dynamic assessment device for the health of power distribution terminals can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0140] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 6As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When executed by the processor, the computer program implements a dynamic assessment method for the health of a power distribution terminal. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0141] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0142] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method steps of the various embodiments described above.

[0143] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method steps of the various embodiments described above.

[0144] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the method steps of the various embodiments described above.

[0145] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0146] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0147] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A dynamic assessment method for the health of a power distribution terminal, characterized in that, The method includes: Obtain basic health assessment data for the power distribution terminal within the current assessment period; According to the preset state mapping rules, the basic health assessment data is converted into a discrete set of state labels, and the set of state labels is processed based on the principle of the most unfavorable state to obtain the current health assessment result. The historical health assessment result sequence of the power distribution terminal in a continuous historical period is retrieved from the historical database. The jump amplitude sequence and oscillation count between adjacent historical periods are calculated. A health change baseline is constructed based on the extreme value statistics of the jump amplitude sequence and the oscillation count. When an operation and maintenance completion event for the power distribution terminal is detected, the basic impact intensity corresponding to the type of the operation and maintenance completion event is determined; The effective health adjustment amount is obtained by applying a scale constraint on the basic influence intensity through the baseline of health change, and then applying the effective health adjustment amount to the current health assessment result to obtain the updated health assessment result.

2. The method according to claim 1, characterized in that, The basic health assessment data includes: online status information, defect and anomaly records, and function execution result records; the process of converting the basic health assessment data into a discrete set of status labels according to a preset status mapping rule includes: For each data item in the basic health assessment data, it is converted into a corresponding status level label according to a preset mapping relationship between status and level; the status level label includes at least one of normal label, attention label, abnormal label and severe label, and the status level labels corresponding to each data item in the basic health assessment data form a discrete status label set.

3. The method according to claim 1, characterized in that, The process of processing the set of state markers based on the worst-case scenario principle to obtain the current health assessment result includes: The state marker with the highest severity is selected from the set of state markers, and the health score corresponding to the state marker with the highest severity is used as the current health assessment result. When there are multiple status markers with the same highest severity level, the health score corresponding to any one of the status markers with the highest severity level is taken as the current health assessment result.

4. The method according to claim 1, characterized in that, The calculation of the jump amplitude sequence and oscillation count between adjacent historical periods, and the construction of a health status change baseline based on the extreme value statistics of the jump amplitude sequence and the oscillation count, includes: The absolute value of the difference between the health assessment results of two adjacent historical periods in the historical health assessment result sequence is calculated sequentially to obtain the jump amplitude sequence; The number of times the direction of health change reversed between adjacent periods in the historical health assessment result sequence is counted to obtain the oscillation count; Extract the maximum and minimum values ​​from the jump amplitude sequence, and determine the baseline constraint upper limit value based on the difference between the maximum and minimum values ​​and the preset fluctuation coefficient; The baseline constraint lower limit value is determined based on the oscillation count; The health status change baseline is formed by the upper limit of the baseline constraint and the lower limit of the baseline constraint.

5. The method according to claim 1, characterized in that, The determination of the basic impact intensity corresponding to the type of the operation and maintenance completion event includes: Obtain the type information of the maintenance completion event, wherein the type information includes at least one of defect elimination type, equipment replacement type, and parameter adjustment type; Based on the preset mapping relationship between maintenance type and impact intensity, find the basic impact intensity value that matches the type information.

6. The method according to claim 1, characterized in that, The step of applying a scale constraint to the baseline influence intensity based on the health status change baseline to obtain the effective health status adjustment amount includes: Compare the intensity of the basic impact with the constraint range of the baseline of health status change; When the basic influence intensity is within the constraint range of the health change baseline, the basic influence intensity is used as the effective health adjustment amount; When the intensity of the basic influence exceeds the upper limit of the constraint range of the baseline of health change, the upper limit is used as the effective health adjustment amount; When the intensity of the basic influence is lower than the lower limit of the constraint range of the baseline of health change, the lower limit is used as the effective health adjustment amount.

7. The method according to any one of claims 1 to 6, characterized in that, After obtaining the updated health assessment results, the method further includes: The updated health assessment results are compared with the preset health grading thresholds to determine the target maintenance level, and maintenance execution instructions containing the inspection interval and defect elimination time limit are generated based on the target maintenance level.

8. The method according to claim 7, characterized in that, The step involves comparing the updated health assessment result with a preset health grading threshold to determine the target maintenance level, and generating maintenance execution instructions that include the inspection interval and defect elimination time limit based on the target maintenance level, including: The updated health assessment results are compared with the first grading threshold and the second grading threshold, respectively, wherein the first grading threshold is greater than the second grading threshold; When the updated health assessment result is greater than or equal to the first classification threshold, the target maintenance level is determined to be the first level, and maintenance execution instructions with the corresponding first inspection interval and first defect elimination time limit are generated. When the updated health assessment result is less than the first grading threshold and greater than or equal to the second grading threshold, the target maintenance level is determined to be the second level, and maintenance execution instructions corresponding to the second inspection interval and the second defect elimination time limit are generated. When the updated health assessment result is less than the second classification threshold, the target maintenance level is determined to be the third level, and maintenance execution instructions with corresponding third inspection interval and third defect elimination time limit are generated. Wherein, the first video cycle interval is greater than the second video cycle interval, the second video cycle interval is greater than the third video cycle interval; the first defect elimination time limit is greater than the second defect elimination time limit, and the second defect elimination time limit is greater than the third defect elimination time limit.

9. A dynamic assessment device for the health status of a power distribution terminal, characterized in that, The device includes: The data acquisition module is used to acquire basic health assessment data of the power distribution terminal within the current assessment period; The basic assessment module is used to convert the basic health assessment data into a discrete set of state labels according to a preset state mapping rule, and process the set of state labels based on the worst-case state dominance principle to obtain the current health assessment result. The baseline construction module is used to retrieve the historical health assessment result sequence of the power distribution terminal in a continuous historical period from the historical database, calculate the jump amplitude sequence and oscillation count between adjacent historical periods, and construct a health change baseline based on the extreme value statistics of the jump amplitude sequence and the oscillation count. The impact determination module is used to determine the basic impact intensity corresponding to the type of the operation and maintenance completion event when an operation and maintenance completion event for the power distribution terminal is detected. The dynamic correction module is used to apply scale constraints to the basic influence intensity through the health change baseline to obtain an effective health adjustment amount, and then apply the effective health adjustment amount to the current health assessment result to obtain an updated health assessment result.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 8.

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