Distribution box remote diagnosis and maintenance system

Abstract

The invention relates to the technical field of equipment maintenance, in particular to a distribution box remote diagnosis and maintenance system which comprises a voltage deviation detection module, a node hot stacking identification module, a channel stability classification module, a contact aging trend evaluation module and a period adjustment trigger module. According to the method, peak value change of effective voltage in each channel period in the distribution box is collected and compared with a preset criterion so as to accurately identify an abnormal discharge unit and accurately position a potential risk channel, and the change rate of equivalent series capacitance, contact conductance and contact resistance of a node is continuously sampled in a non-power-on state so as to accurately identify the potential risk channel. According to the method, multi-parameter same-trend change characteristics are determined, the contact aging process is accurately evaluated by integrating the parameter trend, the node trend and the maintenance plan period remaining time are subjected to cross comparison, the maintenance task advance opportunity is automatically judged, the maintenance plan is actively adjusted, the node fault missing detection risk is effectively reduced, and the maintenance timeliness and accuracy are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment maintenance, and particularly to a remote diagnosis and maintenance system for distribution boxes. Background Art

[0002] In the technical field of equipment maintenance, the core objects of concern are the operation status monitoring, fault diagnosis, function evaluation, and implementation of maintenance decisions for various industrial equipment, electrical equipment, mechanical devices, etc. This field covers multiple aspects such as regular inspections, status monitoring, fault early warning and positioning, remote diagnosis, and optimization of maintenance plans. It often combines automatic control, communication technology, and information means to achieve high-reliability operation of equipment, reduce operation and maintenance costs, and extend the service life of equipment. In practical applications, equipment maintenance technology is widely used in multiple industries such as industrial production, energy transmission and distribution, power systems, and transportation, and is gradually evolving towards the direction of intelligence and networking.

[0003] Among them, the remote diagnosis and maintenance system for distribution boxes is a remote monitoring and maintenance solution designed for low-voltage distribution equipment such as distribution boxes, aiming to achieve real-time control and intelligent management of the operation status of distribution boxes. The system collects key electrical parameters inside the distribution box by installing sensing components, and through analyzing abnormal states, finally provides fault alarms, maintenance suggestions, and operation guidelines, thereby improving the stability, safety, and maintenance efficiency of the power distribution system, and is widely used in scenarios such as building electrical, industrial electricity, and energy management.

[0004] The traditional maintenance system obtains abnormal states through real-time monitoring of electrical parameters. Although it realizes operation status monitoring and basic fault early warning, the judgment of abnormal phenomena mostly depends on fixed thresholds rather than comprehensive dynamic characteristics to determine the causes of abnormalities. It is difficult to accurately identify the phenomenon of node heat accumulation or the trend of hidden contact aging, resulting in potential risks of nodes being ignored or identified lagging, seriously affecting the safe operation of distribution equipment; the judgment of channel stability in the traditional system is mostly limited to instantaneous current abnormality monitoring, lacking effective tracking and quantification of stability changes within continuous cycles, and unable to objectively evaluate the differences and dynamic change trends of the actual operation status of each channel, resulting in relatively rigid maintenance strategies and lagging adjustment of maintenance tasks, easily causing unnecessary increase in maintenance costs or accumulation of potential fault hazards, and further reducing the timeliness and economy of maintenance decisions. Summary of the Invention

[0005] The purpose of the present invention is to solve the deficiencies existing in the prior art, and to propose a remote diagnosis and maintenance system for distribution boxes.

[0006] To achieve the above purpose, the present invention adopts the following technical solution: A remote diagnosis and maintenance system for distribution boxes, the system includes: The voltage offset detection module obtains the effective voltage sequence of each channel in the distribution box during the operation cycle, extracts the lowest peak voltage based on the current cycle set, records the operating units with abnormal discharge phenomena, and generates a list of abnormal voltage offset channels; The node thermal accumulation identification module, based on the list of abnormal voltage offset channels, extracts the change rate of the residuals within consecutive cycles based on the fitting residuals between the fitting trend line and the actual temperature curve for each cycle, determines whether there is a continuously rising trend, and obtains a set of nodes with thermal accumulation anomalies; The channel stability classification module, based on the set of nodes with thermal accumulation anomalies, identifies the time segments that fall within the current fluctuation threshold range, calculates the proportion of the entire sampling cycle, compares the proportion differences between multiple channels, constructs stability labels, and obtains channel operation stability classification labels; The connection point aging trend evaluation module, based on the channel operation stability classification labels, collects the equivalent series capacitance, contact conductance value, and contact resistance parameters, extracts the change rate between daily values after continuous multi-day sampling, determines whether the parameters show the same-direction change or discontinuous jump, and obtains a list of connection point aging trend markers.

[0007] As a further solution of the present invention, the list of abnormal voltage offset channels specifically includes channel number, offset voltage range, voltage drop reference state, and number of voltage offset continuous cycles; the set of nodes with thermal accumulation anomalies specifically includes node identification code, temperature residual growth trend type, node installation location, and thermal component number; the channel operation stability classification labels include channel stability level label, stable proportion range, classification flag bit, and label generation timestamp; the list of connection point aging trend markers specifically includes node unique identification code, parameter change rate trend classification, risk evolution level, and node contact material type.

[0008] As a further solution of the present invention, the voltage offset detection module includes: The voltage sequence extraction sub-module obtains the effective voltage sequence of each channel in the distribution box during the operation cycle, records the voltage time sequence data by channel, extracts the set of maximum peak voltages within two adjacent cycles respectively, and calculates the root mean square value of the previous cycle set to obtain the channel cycle peak mean group; The voltage offset difference calculation sub-module, based on the channel cycle peak mean group, calls the minimum peak voltage within the current cycle according to the peak mean of the previous cycle of each channel, performs difference calculation on the two sets of data, and makes an interval judgment on the difference result and the voltage drop criterion. If the difference is greater than the lower limit value of the criterion, the channel is marked as a channel with an offset trend to obtain the channel offset difference status table; The abnormal channel recognition sub-module, based on the channel offset difference status table, filters the set of channels marked as offset status according to the offset judgment results of each channel, summarizes the channel numbers, voltage offset differences, and offset occurrence period numbers, and obtains a list of abnormal voltage offset channels.

[0009] As a further aspect of the present invention, the node thermal accumulation recognition module includes: The temperature curve acquisition sub-module, based on the list of abnormal voltage offset channels, collects the output values of the thermistors of the corresponding connected nodes according to the marked channels, records the node temperature data every second during consecutive operation periods, constructs a node temperature change curve by period division, and obtains a node period temperature sequence group; The thermal residual extraction sub-module, based on the node period temperature sequence group, extracts the temperature sequence composed of corresponding time points within each period according to each period temperature curve, constructs a temperature trend line within the period and performs a difference calculation with the actual temperature data, summarizes the residual curves within each period, calculates and obtains a group of period residual change amplitudes, constructs a node thermal residual change trend quantity according to the numerical change interval and increment direction, and establishes a node residual trend quantity table; The accumulation trend judgment sub-module calls the node residual trend quantity table, judges whether there is a one-way increase in three consecutive periods according to the trend change value sequence, and extracts the corresponding node identifier, starting growth period number, and total residual change amplitude to obtain a set of thermally accumulated abnormal nodes.

[0010] As a further aspect of the present invention, the formula for calculating and obtaining the group of period residual change amplitudes is specifically: ; Wherein, represents the node thermal residual change amplitude within the th operation period, represents the measured node temperature value at the th sampling time point in the th operation period, represents the fitting value of the temperature trend line at the th sampling time point in the th operation period, represents the total number of sampling time points, represents the number of consecutive periods in which the voltage offset status is maintained within the th operation period, represents the normalized value of the channel current fluctuation interval ratio in the th operation period, represents the thermal fluctuation amplification factor.

[0011] As a further aspect of the present invention, the channel stability classification module includes: The current sequence acquisition sub-module identifies the corresponding connected channels based on the thermal accumulation abnormal node set, acquires the load current value sequence per unit time on each channel, sets the sampling period and records the sampled point current values according to the time stamp, and generates a channel current sampling sequence group; The fluctuation ratio calculation sub-module sets a fluctuation amplitude threshold range based on the sampled point values of the channels in the channel current sampling sequence group, determines whether the current value falls within the range, accumulates the length of the time segment of the sampled points falling within the range and calculates the ratio with the total sampling duration to obtain the fluctuation stability ratio value of each channel, and obtains a channel stability ratio set; The stable label generation sub-module calls the channel stability ratio set, performs a comparison of the ratio differences between channels according to the ratio values of each channel, sets a ratio difference limit, groups the channels according to the ratio differences and marks classification labels, and establishes a channel operation stability classification label.

[0012] As a further solution of the present invention, the contact aging trend evaluation module includes: The electrical parameter acquisition sub-module identifies the connected wiring nodes based on the channel operation stability classification label, acquires the equivalent series capacitance, contact conductance value and contact resistance value in the first non-powered state every day, constructs a daily electrical parameter data record according to the node number, and obtains a node multi-day parameter sequence set; The change rate extraction sub-module calculates the difference between two adjacent days and divides it by the time interval based on the daily electrical parameter values in the node multi-day parameter sequence set, extracts the capacitance change rate sequence, conductance change rate sequence and resistance change rate sequence of each node respectively, and combines the three types of results to obtain a node parameter change rate combined value; The trend state judgment sub-module calls the node parameter change rate combined value, sets the same-direction change and jump threshold criteria according to the three change rate sequences corresponding to the nodes, determines whether the node satisfies two of the three conditions of capacitance decrease, conductance increase and resistance increase in a continuous period, screens the node numbers, index types and change trend identifiers that meet the conditions, and obtains a wiring node aging trend mark list.

[0013] As a further solution of the present invention, the system further includes: The cycle adjustment trigger module calls the wiring node aging trend mark list, cross-compares with the remaining maintenance cycle corresponding to the node in the maintenance plan according to the corresponding node data, constructs a matching index between the trend level and the cycle duration, and if the node trend level exceeds the preset tolerance range and falls into the risk interval of the remaining cycle, moves the corresponding maintenance task forward and enters it into the inspection operation plan to generate a node-level maintenance advance task list; The node-level maintenance advance task list includes a task number, an advance day index, an inspection priority identifier, and a corresponding maintenance cycle reference number.

[0014] As a further aspect of the present invention, the cycle adjustment trigger module includes: The node data call sub-module calls the wiring node aging trend marking list, matches the remaining maintenance cycles recorded in the maintenance plan according to the corresponding node data, extracts the node number, trend level identifier, and corresponding remaining cycle value, and establishes a node maintenance cycle association table; The matching degree calculation sub-module, based on the node maintenance cycle association table, performs a matching degree evaluation between the trend level and the cycle duration according to the trend level and the maintenance cycle value of each node, sets a trend level influence factor and a cycle compression adjustment factor, calculates the matching degree value of each node, and filters the node numbers that need to perform cycle advance according to whether the matching degree value is greater than the set matching tolerance threshold, and obtains a node adjustment matching index group; The maintenance plan generation sub-module calls the node adjustment matching index group, correspondingly adjusts the advanced maintenance days according to the identified set of node numbers, updates the inspection priority field in the maintenance plan and supplements the maintenance task number and insertion order, and establishes a node-level maintenance advance task list.

[0015] As a further aspect of the present invention, the formula for calculating the matching degree value of each node is specifically: ; Wherein, represents the cycle trend matching degree value of the th node, represents the trend level value of the th node, and respectively represent the mean and standard deviation of the trend levels of all nodes, is a matching adjustment factor, represents the th node's current remaining maintenance cycle length.

[0016] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by collecting the peak value changes of the effective voltage within each channel period of the distribution box and comparing them with the preset criteria, abnormal discharge units are accurately identified, potential risk channels are precisely located, and the temperature residual change trend of the corresponding connection nodes is obtained in real time. Taking the residual change rate within consecutive periods as an index, hidden nodes with thermal accumulation are automatically determined, realizing the refined and dynamic identification of hidden nodes. Based on the results of abnormal node temperatures, the load current data of associated channels are collected, the operation stability of channels is quantified using the current fluctuation characteristics per unit time, the stability ratio differences of each channel are compared, and objective stable classification labels are formed to improve the accuracy of channel stability evaluation. For channels marked as unstable categories, by continuously sampling the equivalent series capacitance, contact conductance, and contact resistance change rate of nodes in the non-powered state, the multi-parameter same-trend change characteristics are confirmed, the aging process of the contact points is accurately evaluated based on the comprehensive parameter trend, and the node trend is cross-compared with the remaining time of the maintenance plan period to automatically determine the early timing of maintenance tasks and actively adjust the maintenance plan, effectively reducing the risk of undetected node failures and significantly improving the timeliness and accuracy of maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0018] Figure 1 is the system flow chart of the present invention; Figure 2 is the schematic diagram of the system framework of the present invention; Figure 3 is the flow chart of the voltage offset detection module of the present invention; Figure 4 is the flow chart of the node thermal accumulation identification module of the present invention; Figure 5 is the flow chart of the channel stability classification module of the present invention; Figure 6 is the flow chart of the contact point aging trend evaluation module of the present invention; Figure 7 is the flow chart of the cycle adjustment trigger module of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] The following describes the technical solutions in the present invention in conjunction with the drawings.

[0020] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as an "example" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of the word "example" is intended to present concepts in a specific manner. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two can be selected.

[0021] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, the meanings they express are the same. "(of)", "corresponding", and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, the meanings they express are the same.

[0022] In the embodiments of the present invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meanings they express are the same.

[0023] To make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0024] Please refer to Figure 1 , a remote diagnosis and maintenance system for a distribution box, the system includes: The voltage offset detection module obtains the effective voltage sequence of each channel in the distribution box during the operation cycle, constructs the maximum peak voltage set of adjacent two cycles for each channel respectively, calculates the root mean square voltage mean based on the set of the previous cycle, extracts the lowest peak voltage based on the set of the current cycle, performs difference calculation, and compares it with the preset voltage sag criterion. If the difference exceeds the lower limit defined by the criterion, record the channel as an operating unit with abnormal discharge phenomenon, and generate a list of abnormal voltage offset channels; The node thermal accumulation identification module, based on the list of abnormal voltage offset channels, samples the node temperature change curve of the thermistor on the connection node for consecutive operation cycles according to the identified channels, extracts the change rate of the residual error within consecutive cycles based on the fitting residual error between the fitted trend line and the actual temperature curve of each cycle, and determines whether it shows a continuous upward trend. If the trend holds, mark the node as a potential thermal accumulation point and obtain the set of abnormal nodes with thermal accumulation; Based on the set of nodes with abnormal thermal accumulation, the channel stability classification module collects the load current data sequence within a unit time according to the connection channels, sets the current fluctuation threshold range, identifies the time segments falling within the range and accumulates their lengths, calculates the proportion of the entire sampling period, compares the proportion differences between multiple channels, constructs stability labels based on the differences, and obtains the channel operation stability classification labels; The current fluctuation threshold is often set in the form of rated current ±ΔI, where ΔI is the allowable fluctuation limit defined by engineering experience or the manufacturer; Based on the channel operation stability classification labels, the joint aging trend evaluation module collects the equivalent series capacitance, contact conductance value, and contact resistance parameters of the connected wiring nodes in the non-powered state according to the channels marked as unstable categories. After continuous multi-day sampling, the change rate between each day is extracted to determine whether the parameters show the same-direction change or discontinuous jump. If multiple parameters simultaneously meet the trend conditions, it is marked as the aging trend appearance state, and the wiring node aging trend mark list is obtained; The change in contact resistance is usually obtained through the four-wire measurement method; conductance is its reciprocal and is often used as one of the criteria for judging the integrity of the joint connection; The cycle adjustment trigger module calls the wiring node aging trend mark list, cross-compares it with the remaining maintenance cycles corresponding to the nodes in the maintenance plan according to the corresponding node data, constructs the matching index between the trend level and the cycle duration. If the node trend level exceeds the preset tolerance range and falls into the risk interval of the remaining cycle, the corresponding maintenance task is advanced and entered into the inspection operation plan, generating the node-level maintenance advance task list; The remaining maintenance cycle is often in units of the calendar cycle. The matching index can be defined as the comprehensive index obtained by multiplying the parameter change rate by the remaining cycle amount, which is used for decision-making support in cycle adjustment; The list of channels with abnormal voltage offset specifically includes the channel number, offset voltage range, voltage drop reference state, and number of voltage offset duration cycles. The set of nodes with abnormal thermal accumulation specifically includes the node identification code, temperature residual growth trend type, node installation location, and thermal component number. The channel operation stability classification labels include the channel stability level label, stable proportion range, classification flag bit, and label generation timestamp. The wiring node aging trend mark list specifically includes the node unique identification code, parameter change rate trend classification, risk evolution level, and node contact material type. The node-level maintenance advance task list includes the task number, advance days index, inspection priority identifier, and corresponding maintenance cycle reference number.

[0025] Please refer to Figure 2 and Figure 3 As shown in, the voltage offset detection module includes a voltage sequence extraction sub-module, a voltage offset difference calculation sub-module, and an abnormal channel identification sub-module; The voltage sequence extraction sub-module obtains the effective value voltage sequence of each channel in the distribution box during the operation cycle, records the voltage time series data according to the channels, extracts the maximum peak voltage sets in two adjacent cycles respectively, and calculates the root mean square value of the previous cycle set to obtain the channel cycle peak mean group; To obtain the effective value voltage sequence of each channel in the distribution box during the operation cycle, it is necessary to continuously record the voltage in the operating state based on the sampling module at a fixed sampling frequency. For example, in the way of sampling once per second, 1800 voltage effective value points can be obtained in a complete operation cycle (set as 30 minutes). Classify according to the channel numbers, and form two-dimensional sequences for the two channels numbered CH01 and CH02 respectively. Then, identify the local peak points in the sequence according to the channels. By detecting the local maximum points in the voltage value change trend every 10 seconds. For example, there are peak voltages at the 200th second, 530th second, and 1100th second in the CH01 channel, and record their values as 231V, 229V, and 228V respectively. Extract the maximum peak sets in two adjacent operation cycles (set as 08:00–08:30 and 08:30–09:00 on the same day) to form sets P1 = {231, 229, 228} and P2 = {230, 227, 225}. Calculate the root mean square of all the peaks in set P1 according to the formula , where is the single peak voltage in the set, is the number of peaks. Applying the above formula to P1, we get: ; Take this result as the mean value of the CH01 channel in cycle P1 and store it in the result set, and repeat the above process for other channels in turn. Finally, obtain the channel cycle peak mean group; Based on the channel cycle peak mean group, the voltage offset difference calculation sub-module calls the minimum peak voltage in the current cycle according to the peak mean of the previous cycle of each channel, performs difference calculation on the two sets of data, and makes an interval judgment on the difference result and the voltage drop criterion. If the difference is greater than the lower limit value of the criterion, mark the channel as a channel with an offset trend to obtain the channel offset difference status table; Based on the channel cycle peak mean group, it is necessary to call the root mean square value of each channel in the previous cycle and the minimum peak value in the current cycle to determine whether the voltage change trend is abnormal. Continuing with the CH01 channel as an example, the minimum peak voltage identified in the current cycle P2 is 225V. A difference operation is performed on the root mean square value of 229.3V obtained in the previous cycle P1 and the current cycle minimum value of 225V, resulting in an offset value of ΔV = 229.3 - 225 = 4.3V. The voltage drop criterion is set at 3V, that is, when the offset value ΔV ≥ 3V, it is considered an abnormal offset situation. Combining the actual engineering scenario, this 3V comes from a 10% amplitude warning limit of the power supply tolerance setting value in the distribution box, which is derived from the set allowable voltage fluctuation range. After repeating the above calculation operations for all channels, the following record structure is formed for each channel: channel number CH01, previous cycle mean 229.3V, current cycle minimum peak 225V, difference 4.3V, and the judgment result is "offset". Finally, a channel offset difference status table is summarized and formed; The abnormal channel identification sub-module, based on the channel offset difference status table, screens the set of channels marked as the offset status according to the offset judgment results of each channel, summarizes the channel number, voltage offset difference, and the offset occurrence cycle number, and obtains a list of abnormal voltage offset channels; Based on the offset judgment records of all channels in the channel offset difference status table, it is necessary to screen each channel marked as the "offset" status item by item, extract the channels with the judgment result of "offset", and organize their channel numbers, offset differences, and offset judgment cycle numbers. Further, in combination with the on-site identification number, the channels are mapped to a unique identification item in the system. For example, if the CH01 channel has an offset in the 08:30–09:00 cycle, the number is CH01, the offset difference is 4.3V, and the cycle number is P2, then this record is stored in the abnormal set. Then, the situation where the CH03 channel detects an offset difference of 3.5V in the P4 cycle is also entered. After traversing all channels, a structured set containing multiple abnormal channel data items is formed, and finally, a list of abnormal voltage offset channels is obtained.

[0026] Please refer to Figure 2 and Figure 4 , the node thermal accumulation identification module includes a temperature curve acquisition sub-module, a thermal residue extraction sub-module, and a stacking trend judgment sub-module; The temperature curve acquisition sub-module, based on the list of abnormal voltage offset channels, collects the output values of the thermistors of the corresponding connected nodes according to the marked channels, records the node temperature data every second during continuous operation cycles, constructs a node temperature change curve according to the cycle division, and obtains a node cycle temperature sequence group; Based on the abnormal voltage offset channel list, according to the channels such as CH01 and CH03 identified therein, through the line configuration diagram of the corresponding distribution box, determine the physical wiring node numbers connected to each channel, retrieve the thermistor numbers installed on this node, obtain the corresponding analog output terminal numbers of this component as the source of the sampling channel, set the sampling period to 60 minutes, and collect voltage-to-temperature values at a frequency of 1 time per second within this period. Then, convert the analog value into a digital temperature value through the internal AD conversion module. For example, the node number connected under the CH01 channel is ND01, and its thermistor number is TR101. A total of 3,600 temperature values are collected during the operation period from 08:00 to 09:00, forming a temperature sequence group. , Subsequently, take this sequence as the temperature change curve of the ND01 node in this operation period according to the period. If there are multiple channels connected to ND01, it is necessary to collect and merge each channel corresponding period separately, perform interpolation and smoothing processing according to the multiple channel sequences within the same period, and uniformly generate the periodic temperature curve of this node. Finally, index the results collected from all nodes according to the node numbers, establish a node temperature sequence dictionary with ND01, ND02, etc. as the key values, and combine the timestamp and data points to form a structured data table for subsequent fitting and trend judgment to obtain the node periodic temperature sequence group; The thermal residual extraction sub-module is based on the node periodic temperature sequence group. According to each periodic temperature curve, extract the temperature sequence composed of the corresponding time points within the period, construct the temperature trend line within the period and perform difference calculation with the actual temperature data, summarize to obtain the residual curve within each period, calculate and obtain the group of periodic residual change amplitudes, construct the node thermal residual change trend quantity according to the numerical change interval and increment direction, and establish a node residual trend measurement table; The formula for calculating and obtaining the group of periodic residual change amplitudes is specifically: ; Among them, represents the node thermal residual change amplitude within the th operation period, represents the measured node temperature value at the th sampling time point in the th operation period, represents the fitting value of the temperature trend line at the th sampling time point in the th operation period, represents the total number of sampling time points, represents the number of consecutive periods during which the voltage offset state is maintained within the th operation period, represents the normalized value of the channel current fluctuation interval ratio in the th operation period, represents the thermal fluctuation amplification factor; The change amplitude of the node thermal residual is a normalized comprehensive index used to measure the residual strength of the node temperature curve fitting based on the characteristics of the abnormal temperature change trend of the distribution box node during the continuous operation cycle. Its essential purpose is to capture the aggregation degree of the temperature deviating from the normal trend under abnormal voltage offset conditions, and combine the voltage anomaly persistence and current fluctuation effects to obtain a sensitive parameter that comprehensively characterizes the potential thermal accumulation risk of the node; Measure the cumulative deviation strength between the actual temperature curve of the node and the fitting trend line in the current cycle. This item takes the square root after absolute value integration to ensure that it reflects the fluctuation strength without over-amplifying extreme values and improves the sensitivity to long-term trend perturbations; Indicates the number of voltage offset cycles maintained in the current cycle, reflecting the possible cumulative effect of abnormal voltage on thermal anomaly accumulation; Introduce the normalized ratio of the channel current fluctuation in the current cycle to increase the weighted effect of the fluctuation on the thermal residual, is the empirical adjustment factor; Based on the complete temperature curve of each node in the node cycle temperature sequence group within a single cycle, first extract the temperature value pairs at each time point to construct a time series set such as , and use linear interpolation combined with least squares fitting to establish a trend line for this sequence , and then calculate the error for each time point, using the absolute error form: , accumulate the sum of squares of errors per second, extract the cycle residual value, and according to the extended definition, introduce the number of voltage offset maintenance cycles obtained in the previous stage and the normalized value of the channel current fluctuation ratio , select the thermal fluctuation amplification factor and then perform comprehensive weighted processing, using the formula: ; Taking the CH01 channel in the 4th cycle as an example, let , , , substitute into the calculation: ; Record the result as the residual change amplitude value of the ND01 node in the 4th cycle, perform the same operation for all cycles, establish a multi-cycle residual sequence for each node such as , for the next step of trend judgment, and finally establish a node residual trend scale; The accumulation trend judgment submodule calls the node residual trend scale, and judges whether there is unidirectional growth for three consecutive cycles according to the trend change value sequence, and extracts the corresponding node identification, the starting growth cycle number, and the total residual change amplitude to obtain the heat accumulation abnormal node set; Call the multi-period residual value sequence corresponding to each node in the node residual trend table, and perform monotonic growth trend judgment on each sequence according to the time series. The judgment rule is set as follows: if the residual values ​​of three or more consecutive periods show a unidirectional upward trend, it satisfies If the relationship is established more than twice, the node is marked as trending upward. For example, the sequence of the ND01 node is , the corresponding difference values ​​are 2.8, 7.6, and 5.8, respectively, satisfying three consecutive increases. The node is determined to be a heat accumulation trend node. The node number ND01, the starting period is the second period, and the total residual increase is 16.2 are recorded. The structured field is constructed as {node_id:ND01,trend_start:2,rise_value:16.2}. All nodes that meet the conditions are collected in a form format to obtain a set of heat accumulation anomaly nodes.

[0027] See also Figure 2 and Figure 5 ,The channel stability classification module includes a current sequence acquisition submodule, a fluctuation ratio calculation submodule, and a stable label generation submodule; The current sequence acquisition submodule identifies the corresponding connected channels based on the thermal accumulation abnormal node set, collects the load current value sequence per unit time on each channel, sets the sampling period and records the current value of the sampling point according to the timestamp, and generates a channel current sampling sequence group; Based on the abnormal heat accumulation node set, first extract the unique identification number of each node from the set, such as ND01, ND03, etc., and consult the channel connection mapping table in the system to confirm that the ND01 node connection channels are CH01 and CH05, and the ND03 node connection channel is CH04. Then, according to the connected channel number, start the current sampling process for each channel, set the sampling period to 60 seconds, and the sampling frequency to 10Hz, that is, collect 10 current data points per second, and collect a total of 600 current values ​​in the entire period. Construct a sequence data structure for each channel, and record it in the form of a list of current values ​​corresponding to the timestamp. For example, the CH01 channel sampling sequence can be expressed as , the sampling data unit is ampere (A), and the data is saved in a structured CSV format, and the channel number and sampling cycle number are added as index fields. After the sampling of multiple channels is completed, they are sorted by channel number to form a sampling set under the channel dimension, and finally summarized to generate a channel current sampling sequence group; The fluctuation ratio calculation sub-module sets a threshold range for the fluctuation amplitude based on the channel current sampling sequence group and the sampling point values of the channels, determines whether the current value falls within the range, accumulates the length of the time segments of the sampling points that fall within the range, calculates the ratio with the total sampling duration, obtains the fluctuation stability ratio value for each channel, and acquires the channel stability ratio set. Based on the current value data corresponding to each channel in the channel current sampling sequence group, the threshold range for the current fluctuation amplitude is set to ±0.2A. This value is determined with reference to the current offset tolerance under the stable operating state of the device. For example, when the rated current is 8.2A, the stable interval is set to [8.0A, 8.4A]. Each sampling point value under the CH01 channel is judged. If the current value falls within this range, it is marked as "stable", otherwise it is marked as "unstable". The number of sampling points marked as stable is accumulated. For example, there are 470 sampling points within the range in CH01. The calculated fluctuation stability ratio is , that is, the fluctuation stability ratio value of CH01 is 0.783. This value is included in the channel stability result set. After performing the same processing on all channels, a record dictionary with the structure {CH01:0.783, CH04:0.652, CH05:0.817} is formed, and finally the channel stability ratio set is obtained. The stable label generation sub-module calls the channel stability ratio set, performs a comparison of the ratio differences between channels according to the ratio value of each channel, sets the ratio difference limit, groups the channels according to the ratio difference for stability and marks classification labels, and establishes the channel operation stability classification labels. Call the ratio values of each channel in the channel stability ratio set, set the ratio difference limit to 0.15, which is used as the judgment benchmark for whether the stability difference between different channels constitutes the boundary of the stable grouping. First, sort in ascending order according to the ratio value to construct a sorted sequence such as CH04:0.652, CH01:0.783, CH05:0.817. Calculate the ratio differences between adjacent channels. For example, the difference between CH01 and CH04 is 0.131, and the difference between CH05 and CH01 is 0.034. Only the difference between CH01 and CH04 does not exceed 0.15 and is grouped into the same stable group, while CH05 forms another group alone because the difference is less than the limit. Finally, mark CH04 and CH01 as "medium stable" of one category, and mark CH05 as "highly stable", and attach a label structure to each channel such as {channel number: CH05, stable label: highly stable}, generate a structured form according to the standard fields, and establish the channel operation stability classification labels.

[0028] Please refer to Figure 2 and Figure 6 , the contact aging trend evaluation module includes an electrical parameter acquisition sub-module, a change rate extraction sub-module, and a trend state judgment sub-module. The electrical parameter acquisition sub-module classifies tags based on the stable operation of channels. According to the channels marked as unstable, it identifies the connected wiring nodes, collects the equivalent series capacitance, contact conductance value, and contact resistance value in the first non-powered state every day, constructs a daily electrical parameter data record according to the node number, and obtains a multi-day parameter sequence set of nodes; Based on the channel operation stability classification tags, filter out the channel numbers marked as "low stability" or "unstable", such as CH02, CH06, CH09, etc. Combine the channel-node mapping relationship to extract the wiring node numbers connected to these channels. For the CH02 channel, identify its connected node as ND07, for the CH06 channel, identify the node as ND12, and so on to determine the monitoring object node range. Perform electrical parameter acquisition operations on the above nodes in the first non-powered state every day. The specific operation is to apply a low-amplitude detection signal through the detection circuit embedded in the node before powering on every morning, and record its equivalent series capacitance value (unit: μF), contact conductance value (unit: S), and contact resistance value (unit: Ω). For example, the three parameter acquisition values of the ND07 node on the first day and the second day are: capacitance values of 1.02 μF and 0.97 μF, conductance values of 5.1 S and 5.4 S, and resistance values of 0.19 Ω and 0.23 Ω. All data is constructed into a structured record table with time tags, node numbers, and electrical parameter type fields. The daily data of multiple nodes is accumulated in a row record manner, and a multi-day electrical parameter sequence group in the cycle dimension is constructed according to the node number to obtain a multi-day parameter sequence set of nodes; The change rate extraction sub-module, based on the multi-day parameter sequence set of nodes, calculates the difference between two adjacent days and divides it by the time interval according to the daily electrical parameter values, extracts the capacitance change rate sequence, conductance change rate sequence, and resistance change rate sequence of each node respectively, and combines the three types of results to obtain the combined value of the node parameter change rate; Based on the multi-day parameter sequence set of nodes, extract the differences of the three types of parameters during consecutive days for each node and calculate the change rate. Use the formula: change rate = (value on the current day - value on the previous day) / time interval, where the time interval is counted as 1 day. For the ND07 node, the capacitance change is (0.97 - 1.02) / 1 = -0.05 μF / d, the conductance change is (5.4 - 5.1) / 1 = 0.3 S / d, and the resistance change is (0.23 - 0.19) / 1 = 0.04 Ω / d, which are respectively marked as capacitance decrease, conductance increase, and resistance increase, and construct three change rate sequences corresponding to the capacitance change rate sequence ,conductance change rate sequence ,resistance change rate sequence ,combine the three sequences into a parameter change structure body of node ND07, and the structure form is {ND07: {C’, G’, R’}}. After processing all nodes, summarize them in dictionary form to obtain the combined value of the node parameter change rate; The trend status judgment sub-module calls the combined value of the node parameter change rate, sets the co-directional change and jump threshold criteria according to the three change rate sequences corresponding to the node, judges whether the node satisfies two of the three conditions of capacitance decrease, conductance increase, and resistance increase within a continuous period, screens the node numbers, index types, and change trend identifiers that meet the conditions, and obtains the wiring node aging trend mark list; Call the combined value of the node parameter change rate to perform a directional judgment on the three change rate sequences constructed for each node. Set the "co-directional change" criterion as: if any two of the continuous decrease of capacitance, continuous increase of conductance, and continuous increase of resistance are established simultaneously, it is considered that there is an aging trend. At the same time, define the "jump threshold" as: the difference between the maximum and minimum values of any change rate value within three days exceeds the set threshold, and the thresholds are: capacitance 0.03 μF / d, conductance 0.2 S / d, and resistance 0.02 Ω / d. Taking node ND07 as an example, the capacitance change rate is continuously decreasing, the conductance and resistance are both continuously increasing, and the maximum and minimum differences are 0.02, 0.1, and 0.02 respectively, all of which do not exceed the jump threshold, but the direction meets the two conditions. Therefore, ND07 is recorded as an aging trend node, marked with trend_type = "direction consistent", trend_code = "decrease + increase", and written into the structure field such as {node_id: ND07, trend_code: 1, direction_type: "two-way positive judgment"}. After completing the screening process, obtain the wiring node aging trend mark list.

[0029] Please refer to Figure 2 and Figure 7 , the period adjustment trigger module includes a node data call sub-module, a matching degree calculation sub-module, and a maintenance plan generation sub-module; The node data call sub-module calls the wiring node aging trend mark list, matches the remaining maintenance periods recorded in the maintenance plan according to the corresponding node data, extracts the node numbers, trend level identifiers, and corresponding remaining period values, and establishes a node maintenance period association table; Call the aging trend marker list of wiring nodes, extract the node numbers and trend level identifiers of each record therein. For example, if the list contains ND01: Level 3, ND05: Level 4, ND08: Level 2, etc., based on this, search for the current maintenance plan items of the corresponding nodes in the system maintenance plan database, read the remaining maintenance cycle values under each record, with the unit expressed in days. For example, ND01 is 12 days, ND05 is 8 days, ND08 is 18 days. Construct a data structure as {node_id: ND01, trend_level: 3, remain_day: 12}, form a mapping table for all effectively matched nodes, with the node number as the primary key field, the trend level as an integer identifier, and the remaining maintenance cycle as a continuous numerical parameter. At the same time, record the extraction timestamp as the maintenance reference date to ensure that each record is in the latest and valid state, and finally establish a node maintenance cycle association table; Based on the node maintenance cycle association table, the matching degree calculation sub-module performs a matching degree evaluation between the trend level and the cycle duration according to the trend level and the maintenance cycle value of each node. Set the trend level influence factor and the cycle compression adjustment factor, calculate the matching degree value of each node, and screen the node numbers that need to perform cycle forward movement according to whether the matching degree value is greater than the set matching tolerance threshold to obtain the node adjustment matching index group; The formula for calculating the matching degree value of each node is specifically: ; Among them, represents the cycle trend matching degree value of the th node, represents the trend level value of the th node, and respectively represent the mean and standard deviation of the trend levels of all nodes, is the matching adjustment factor, represents the th node's current remaining maintenance cycle length; The cycle trend matching degree value is a comprehensive index set for the matching degree of the wiring node aging trend and the urgency of the remaining maintenance cycle. It is used to quantify the deviation degree of the node aging trend level in the overall node distribution, and conduct a risk urgency assessment in combination with the current remaining maintenance cycle; is the standard deviation multiple of the node trend level relative to the overall trend level distribution, equivalent to the absolute value of the standardized Z-score, representing the relative severity of the node trend level in the group; is the reciprocal of the node's remaining maintenance cycle, reflecting that the shorter the remaining time, the higher the risk urgency; To verify the adjustment factor and control the influence weight of the cycle duration on the matching degree; Based on the node maintenance cycle association table, extract the trend level values of each node And the remaining cycle length And calculate the average value of the trend levels of all nodes And the standard deviation For each node, calculate the degree of deviation of the trend level. By calculating Obtain the standardized difference index, and at the same time set the matching adjustment factor Indicating the sensitivity to the compression judgment of the cycle dimension, and then calculate the cycle compression weight term Based on the logic that a high remaining number of days brings a low weight, combine the two results to form a matching degree calculation formula: ; Taking node ND05 as an example, assume its , , , , Substitute into the formula to get: ; Compare the matching degree value with the preset tolerance threshold of 1.5. If Then it is determined that the node needs to trigger a cycle forward shift. Screen the set of nodes that meet the conditions, record the corresponding node numbers, trend levels, remaining cycles and matching degree values, and obtain the node adjustment matching index group; The maintenance plan generation sub-module calls the node adjustment matching index group, corresponding to adjust the advanced maintenance days according to the identified set of node numbers, update the inspection priority field according to the maintenance plan and supplement the maintenance task number and insertion order, and establish a node-level maintenance advance task list; Call all the node records in the node adjustment matching index group that meet the matching degree limit. According to the matching degree value of each node and the cycle compression logic, perform a forward shift operation on the remaining maintenance cycle. Set the forward shift step size to the closest integer number of days within 5 days. Combine the original maintenance task schedule structure, modify the content of its maintenance time field and inspection priority field, and at the same time insert a new maintenance task number, named the task number in the format of "MT + node number + date stamp", for example, the task number of node ND05 is MTND050531, rearrange the insertion order field of the adjusted node maintenance plan, complete the maintenance queue update operation, and establish a node-level maintenance advance task list.

[0030] It should be understood that the term "and / or" in this text is merely a description of the relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. Additionally, the character " / " in this text generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be specifically understood by referring to the context before and after.

[0031] In the present invention, "at least one" means one or more, and "a plurality" means two or more. "At least one of the following" or its similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple.

[0032] It should be understood that in various embodiments of the present invention, the magnitudes of the sequence numbers of the above processes do not imply the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0033] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0034] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the devices, apparatuses, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0035] In several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be in an electrical, mechanical, or other form.

[0036] The unit described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0037] In addition, each functional unit in various embodiments of the present invention may be integrated into a processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.

[0038] If the above-mentioned function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0039] As described above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A remote diagnosis and maintenance system for a distribution box, characterized in that, The system includes: The voltage offset detection module obtains the effective voltage sequence of each channel in the distribution box during the operation cycle, extracts the lowest peak voltage based on the current cycle set, records the operation units with abnormal discharge phenomena, and generates a list of abnormal voltage offset channels. The node thermal accumulation identification module, based on the list of abnormal voltage offset channels, extracts the change rate of the residuals within consecutive cycles based on the fitting residuals between the fitted trend line and the actual temperature curve per cycle, determines whether there is a continuously rising trend, and obtains a set of nodes with thermal accumulation anomalies. The channel stability classification module, based on the set of nodes with thermal accumulation anomalies, identifies the time segments that fall within the current fluctuation threshold range, calculates the proportion of the entire sampling cycle, compares the proportion differences between multiple channels, constructs stability labels, and obtains the channel operation stability classification labels. The joint aging trend evaluation module, based on the channel operation stability classification labels, collects the equivalent series capacitance, contact conductance value, and contact resistance parameters, extracts the change rate between each day after continuous multi-day sampling, determines whether the parameters show the same direction of change or discontinuous jumps, and obtains a list of joint aging trend markers.

2. The remote diagnosis and maintenance system for the distribution box according to claim 1, characterized in that The list of abnormal voltage offset channels specifically includes the channel number, offset voltage range, voltage drop reference status, and number of voltage offset continuous cycles. The set of nodes with thermal accumulation anomalies specifically includes the node identification code, temperature residual growth trend type, node installation location, and thermal component number. The channel operation stability classification labels include the channel stability level label, stable proportion range, classification flag bit, and label generation timestamp. The list of joint aging trend markers specifically includes the node unique identification code, parameter change rate trend classification, risk evolution level, and node contact material type.

3. The remote diagnosis and maintenance system for the distribution box according to claim 2, characterized in that, The voltage offset detection module includes: The voltage sequence extraction sub-module obtains the effective voltage sequence of each channel in the distribution box during the operation cycle, records the voltage time series data by channel, extracts the maximum peak voltage sets within two adjacent cycles respectively, and calculates the root mean square value of the previous cycle set to obtain the channel cycle peak mean group. The voltage offset difference calculation sub-module, based on the channel cycle peak mean group, calls the minimum peak voltage within the current cycle according to the peak mean of the previous cycle of each channel, performs a difference calculation on the two sets of data, and makes an interval judgment on the difference result and the voltage drop criterion. If the difference is greater than the lower limit of the criterion, the channel is marked as a channel with an offset trend to obtain the channel offset difference status table. The abnormal channel identification sub-module, based on the channel offset difference status table, filters the set of channels marked as offset status according to the offset judgment result of each channel, summarizes the channel number, voltage offset difference, and offset occurrence cycle number to obtain a list of abnormal voltage offset channels.

4. The remote diagnosis and maintenance system for the distribution box according to claim 3, characterized in that, The node thermal accumulation identification module includes: The temperature curve acquisition sub-module, based on the list of abnormal voltage offset channels, collects the output value of the thermistor of the corresponding connection node according to the identified channels, records the node temperature data per second during consecutive operation cycles, constructs the node temperature change curve by cycle, and obtains the node cycle temperature sequence group. The thermal residual extraction sub-module, based on the node cycle temperature sequence group, extracts the temperature sequence formed by the corresponding time points within each cycle according to each cycle temperature curve, constructs the temperature trend line within the cycle and performs difference calculation with the actual temperature data, aggregates the residual curves within each cycle, calculates and obtains the group of cycle residual change amplitudes, constructs the node thermal residual change trend quantity according to the numerical change interval and the increment direction, and establishes the node residual trend measurement table. The stacking trend judgment sub-module calls the node residual trend measurement table, judges whether there is a one-way increase in three consecutive cycles according to the trend change value sequence, and extracts the corresponding node identifier, the starting growth cycle number, and the total amplitude of residual change, to obtain the set of heat accumulation abnormal nodes.

5. The remote diagnosis and maintenance system for distribution box according to claim 4, characterized in that, The formula for calculating and obtaining the group of cycle residual change amplitudes is specifically: ； Among them, represents the change range of the node thermal residual in the th operation cycle, represents the measured node temperature value at the th sampling time point in the th operation cycle, represents the fitting value of the temperature trend line at the th sampling time point in the th operation cycle, represents the total number of sampling time points, represents the number of consecutive cycles in which the voltage offset state is maintained within the th operation cycle, represents the normalized value of the channel current fluctuation interval ratio in the th operation cycle, represents the thermal fluctuation amplification factor.

6. The remote diagnosis and maintenance system for the distribution box according to claim 5, characterized in that, The channel stability classification module includes: The current sequence acquisition sub-module, based on the set of heat accumulation abnormal nodes, identifies the corresponding connected channels, collects the load current value sequence per unit time on each channel, sets the sampling period and records the sampling point current values according to the time stamp, and generates the channel current sampling sequence group. The fluctuation ratio calculation sub-module, based on the channel current sampling sequence group, sets the fluctuation amplitude threshold range according to the sampling point values of the channels, judges whether the current values fall within the range, accumulates the time segment length of the sampling points falling within the range and calculates the ratio with the total sampling duration, to obtain the fluctuation stability ratio value of each channel, and obtains the set of channel stability ratios. The stable label generation sub-module calls the set of channel stability ratios, performs the comparison of the ratio differences between channels according to the ratio values of each channel, sets the ratio difference limit, groups the channels according to the ratio differences and marks the classification labels, and establishes the channel operation stability classification label.

7. The remote diagnosis and maintenance system for distribution box according to claim 6, characterized in that, The joint aging trend evaluation module includes: The electrical parameter acquisition sub-module, based on the channel operation stability classification label, identifies the connected wiring nodes according to the channels marked as unstable, collects the equivalent series capacitance, contact conductance value and contact resistance value in the first non-powered state every day, constructs the daily electrical parameter data record according to the node number, and obtains the set of multi-day parameter sequences of the nodes. The change rate extraction sub-module, based on the set of multi-day parameter sequences of the nodes, calculates the difference between two adjacent days and divides it by the time interval according to the daily electrical parameter values, extracts the capacitance change rate sequence, conductance change rate sequence and resistance change rate sequence of each node respectively, and combines the three types of results to obtain the combined value of the node parameter change rate. The trend state judgment sub-module calls the combined value of the node parameter change rate, sets the co-directional change and jump threshold criteria according to the three change rate sequences corresponding to the nodes, judges whether the nodes meet two of the three conditions of capacitance decrease, conductance increase, and resistance increase in consecutive cycles, and screens the node numbers, index types and change trend identifiers that meet the conditions, to obtain the wiring node aging trend marking list.

8. The remote diagnosis and maintenance system for a distribution box according to claim 7, characterized in that The system further includes: The cycle adjustment trigger module calls the aging trend mark list of the wiring nodes, cross-compares with the remaining maintenance cycles corresponding to the nodes in the maintenance plan according to the corresponding node data, constructs a matching index between the trend level and the cycle duration. If the node trend level exceeds the preset tolerance range and falls into the risk interval of the remaining cycle, the corresponding maintenance task is advanced and entered into the inspection operation plan to generate a node-level maintenance advance task list; The node-level maintenance advance task list includes a task number, an advance days index, an inspection priority identifier, and a corresponding maintenance cycle reference number.

9. The remote diagnosis and maintenance system for distribution box according to claim 8, wherein The cycle adjustment trigger module includes: The node data call sub-module calls the aging trend mark list of the wiring nodes, matches the remaining maintenance cycles recorded in the maintenance plan according to the corresponding node data, extracts the node number, trend level identifier, and corresponding remaining cycle value, and establishes a node maintenance cycle association table; The matching degree calculation sub-module, based on the node maintenance cycle association table, performs a matching degree evaluation between the trend level and the cycle duration according to the trend level and the maintenance cycle value of each node, sets a trend level influence factor and a cycle compression adjustment factor, calculates the matching degree value of each node, and filters the node numbers that need to perform cycle advance according to whether the matching degree value is greater than the set matching tolerance threshold to obtain a node adjustment matching index group; The maintenance plan generation sub-module calls the node adjustment matching index group, correspondingly adjusts the advanced maintenance days according to the identified set of node numbers, updates the inspection priority field according to the maintenance plan, supplements the maintenance task number and the insertion order, and establishes a node-level maintenance advance task list.

10. The remote diagnosis and maintenance system for the distribution box according to claim 9, wherein, The formula for calculating the matching degree value of each node is specifically: ； Among them, represents the periodic trend matching degree value of the th node, represents the trend level value of the th node, and respectively represent the mean and standard deviation of the trend levels of all nodes, is the matching adjustment factor, represents the current remaining maintenance cycle length of the th node.

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