Real-time monitoring and intelligent diagnosis method and system for electric energy metering box

Abstract

This invention provides a method and system for real-time monitoring and intelligent diagnosis of electricity metering boxes, relating to the field of data processing technology. The method includes: extracting data from the meter front end, metering end, and outgoing line end of the metering unit from endpoint operation data and constructing a projection table; identifying the electricity consumption changes between the meter front end and metering end that are not recorded in the meter, obtaining a pre-meter stripping value; eliminating metering units where there is a unidirectional change in the metering end or outgoing line end; extracting the connection segment between the meter front end and metering end of the metering unit; binding the generation time of the pre-meter stripping value to the connection segment between the meter front end and metering end nodes; identifying the stability of the anomaly within the monitoring period after the box door is closed, obtaining a post-door solidification value; and determining the candidate pre-meter segment as the pre-meter diversion landing point when the pre-meter stripping value meets a preset stripping positioning interval and the post-door solidification value meets a preset solidification positioning interval. This invention enables accurate positioning of pre-meter diversion anomalies in multi-meter-position electricity metering boxes.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method and system for real-time monitoring and intelligent diagnosis of electricity metering boxes. Background Technology

[0002] In existing technologies, electricity metering boxes, as the electricity distribution and metering nodes at the end of low-voltage power distribution, typically house incoming circuit breakers, current transformers, metering units, outgoing switches, terminal blocks, and communication modules. The system collects data such as voltage, current, power, electricity consumption, door opening status, seal status, and temperature in real time through electricity meters and internal sensors. This data is then uploaded to the main station via carrier wave, RS485, or wireless network. The main station diagnoses power outages, overloads, phase loss, and metering anomalies based on threshold comparisons, event logs, and total electricity consumption verification.

[0003] However, existing technologies may lack criteria for identifying abnormalities in multi-meter meter boxes where the pre-meter branch is connected and diverted. For example, in a centralized meter box in a residential building, multiple users' meters share the same incoming line and terminal area. If a load is privately connected at the terminal block after the main switch and before a certain energy meter, the load current does not pass through the corresponding energy meter. The main station may only show an increase in the load on the incoming line side, but cannot determine the specific meter branch corresponding to the abnormality. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for real-time monitoring and intelligent diagnosis of electricity metering boxes, aiming to solve the problems mentioned in the background art.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows:

[0006] Firstly, a method for real-time monitoring and intelligent diagnosis of electricity metering boxes, the method comprising:

[0007] Acquire enclosure topology data, endpoint operation data, and enclosure door timing data within the same monitoring period;

[0008] Using each meter position in the box topology data as the index object, extract the front end, metering end and outgoing end data of each meter position from the endpoint operation data and construct a projection table to obtain the meter position projection table data;

[0009] Based on the meter projection data, identify the electricity consumption changes that are not recorded between the meter front end and the metering end of the meter position, and obtain the meter front stripping value.

[0010] When multiple meter positions generate pre-meter stripping values ​​within the same time period, meter positions with unidirectional changes at the metering end or outgoing end are removed to obtain meter position stripping data.

[0011] Based on the stripped data of the metering station, the connection segment between the front end and the metering end of the metering station is extracted. The time period in which the stripped value of the front end is generated is bound to the connection segment between the front end and the metering end nodes to obtain candidate front end segment data.

[0012] Based on the candidate table front section data and the door time sequence data, the stability of the anomaly during the monitoring period after the door is closed is identified, and the door-back solidification value is obtained.

[0013] When the stripping value before the table meets the preset stripping positioning range and the curing value after the door meets the preset curing positioning range, the candidate stripping segment before the table is determined as the stripping point before the table, and the stripping positioning record before the table is obtained.

[0014] Furthermore, using each meter position in the box topology data as the index object, the front end, metering end, and outgoing end data of each meter position are extracted from the endpoint operation data, and a projection table is constructed to obtain the meter position projection table data, including:

[0015] Based on the box topology data, using the meter positions as the index object, the meter position identifier, meter front end identifier, meter end identifier and outgoing line end identifier of each meter position are read and written into the same index item to obtain the meter position end point data;

[0016] Based on the endpoint data, using the front-end identifier, metering identifier, and outgoing identifier in the same index item as the column selection criteria, the front-end data column, metering data column, and outgoing data column within the monitoring period are extracted from the endpoint operation data to obtain the endpoint column selection data.

[0017] Based on the data taken from the endpoints of the table, and using the sampling time within the same monitoring period as the sorting basis, the data from the front-end data column, the metering end data column, and the outgoing end data column of the table are written into the same row to obtain the table position time sequence aligned data.

[0018] Based on the time-series alignment data of the meter positions, and using the meter position as the page identifier, the front-end data column, metering end data column, outgoing line data column, and sampling time identifier of the same meter position are written into the same projection table. The front column, metering column, and outgoing line column are set in the projection table to obtain the meter position projection table data.

[0019] Furthermore, based on the meter projection data, the electricity consumption changes not recorded in the meter between the meter front and the metering end are identified, and the pre-meter stripping value is obtained, including:

[0020] Based on the change in current at the meter front end, identify the degree of change in non-metered electricity consumption between the meter front end and the metering end, and obtain the stripped difference item; based on the stripped difference item, identify the actual degree of occupation of the monitoring cycle by the change in non-metered electricity consumption, and obtain the time period occupation amount.

[0021] Based on the change in current at the meter front end, the correlation between changes in electricity consumption not connected to the meter and changes in load on the common side is identified, and the common mapping quantity is obtained; based on the time period occupancy and the common mapping quantity, the abnormal contribution of changes in electricity consumption not connected to the meter at each sampling time is identified, and the stripping contribution quantity is obtained.

[0022] The stripping contribution at each sampling time is accumulated to identify the overall scale of the change in electricity consumption not connected to the meter, and the cumulative stripping amount is obtained; based on the current component not connected to the meter and the total number of sampling points in the change segment before the meter, the degree of stability of the abnormal change within the monitoring period is identified, and the stripping retention amount is obtained.

[0023] The cumulative stripping amount and the stripping retention amount are combined for calculation to identify the electricity consumption change characteristics that do not enter the metering path between the meter front end and the metering end, and the stripping value before the meter is obtained.

[0024] Furthermore, when multiple metering units generate pre-meter stripping values ​​within the same time period, metering units with unidirectional changes at the metering end or outgoing end are removed to obtain metering unit stripping data, including:

[0025] By merging the time periods of each meter position according to the time periods in which the values ​​before the table are stripped, meter positions with overlapping time periods are written into the same stripping time period group to obtain the stripping time period data.

[0026] Based on the stripping period data, read the direction of data change in the metering column and outgoing line column within the stripping period group, and write the data change that is consistent with the direction of change in the previous table into the acceptance verification column to obtain the acceptance verification data;

[0027] Based on the acceptance and verification data, the meter positions with data changes in the acceptance and verification column are written into the acceptance and exclusion column; otherwise, the meter positions are written into the stripping and retention column to obtain the stripping and column data.

[0028] Based on the stripped column data, the meter position identifier, the stripped value before the meter, the change segment before the meter, the generation time period, and the meter position projection table identifier in the stripped and retained column are bound to obtain the meter position stripped data.

[0029] Furthermore, based on the meter position stripping data, the connection segment between the front end and the metering end of the meter position is extracted. The time period in which the front-end stripping value is generated is bound to the connection segment between the front-end and metering end nodes to obtain candidate front-end segment data, including:

[0030] Based on the meter position stripping data, read the meter position identifier, the stripping value before the meter, the change segment before the meter, and the time period generated in the stripping retention column, and use the meter position identifier as the segment retrieval entry point to obtain the segment entry data.

[0031] Based on the segment entry data, retrieve the front-end node and metering end node of the metering position identifier, and read the connection sequence between the front-end node and the metering end node to obtain the front-end connection data.

[0032] Based on the data connected to the front of the table, the connection segments that do not enter the metering end node are extracted along the connection sequence from the front node to the metering end node, and the connection segments after the metering end node are excluded to obtain the metering connection segment data.

[0033] Based on the segment entry data, the pre-table stripping value, pre-table change segment, and generation time period are written into the metering connection segment data, and the metering position identifier is bound to the metering connection segment data to obtain candidate pre-table segment data.

[0034] Furthermore, based on the candidate table front section data and the door time series data, the stability of the anomaly within the monitoring period after the door is closed is identified, and the post-door solidification value is obtained, including:

[0035] Based on the duration of continuous existence of the candidate pre-table segment after the door is closed, the degree of continuity of the anomaly occupying the observation period after the door is closed is identified, and the door-back persistence item is obtained; based on the number of times the candidate pre-table segment recurs within the door-back observation period, the degree of anomaly recurrence is identified, and the door-back repetition item is obtained.

[0036] Based on the persistent and repeated items behind the door, the continuous existence and segmented recurrence characteristics of the anomaly after the door is closed are identified, and the existence item behind the door is calculated; based on the cumulative value of the peeling value before the table during the observation time behind the door, the degree of peeling retention is identified, and the peeling retention item is obtained.

[0037] Based on the number of times the candidate table front segment remains between the same table front node and metering end node, the segment node retention degree is identified, and the segment locking item is obtained; based on the average value of each table front stripping value within the observation period after the gate, the gate benchmark stripping degree is identified, and the gate benchmark item is obtained.

[0038] By fusing the back-door baseline, back-door presence, stripping retention, and section locking items, the stability of the anomaly during the monitoring period after the door is closed is identified, and the back-door solidification value is obtained.

[0039] Furthermore, when the pre-table stripping value meets the preset stripping positioning range and the post-door curing value meets the preset curing positioning range, the candidate pre-table segment is determined as the pre-table diversion landing point, and a pre-table diversion positioning record is obtained, including:

[0040] By writing the front stripping value, back solidification value, generation time period and front change segment of the same candidate front segment into the same segment overprint table in multiple monitoring cycles, segment overprint data is obtained.

[0041] Based on the segment overprint data, the monitoring period for the stripping value before the table that meets the preset stripping positioning interval is written into the stripping hit column, and the monitoring period for the solidification value after the door that meets the preset solidification positioning interval is written into the solidification hit column. The monitoring period for the simultaneous existence of the stripping hit column and the solidification hit column is identified to obtain steady-state hit data.

[0042] Based on the steady-state hit data, read other candidate table front sections in the same generation period. When the meter position of other candidate table front sections is different from that of the candidate table front section, and its table front change section has been taken by the metering column or the outgoing line column, write the other candidate table front section into the rejection column. When the candidate table front section is not written into the rejection column, write it into the landing point pending column to obtain the landing point pending data.

[0043] Based on the data of undetermined landing points, the connection segment located after the front-end node and before the metering end node is determined as the front-end diversion landing point. The front-end diversion landing point is then bound to the metering position identifier, monitoring cycle, and generation time period to obtain the front-end diversion location record.

[0044] Secondly, a real-time monitoring and intelligent diagnostic system for electricity metering boxes, the system comprising:

[0045] The data module is used to acquire the enclosure topology data, endpoint operation data, and enclosure door time sequence data within the same monitoring period;

[0046] The projection table module is used to extract the front end, metering end and outgoing end data of each metering position from the endpoint running data, and construct the projection table to obtain the metering position projection table data, using each metering position in the box topology data as the index object.

[0047] The stripping value module is used to identify the electricity consumption changes that are not recorded between the front end and the metering end of the metering unit based on the meter projection meter data, and to obtain the stripping value before the meter.

[0048] The meter position stripping module is used to remove meter positions with the same direction of change at the metering end or the outgoing end when multiple meter positions generate pre-meter stripping values ​​in the same time period, and obtain meter position stripping data.

[0049] The candidate segment module is used to extract the connection segment between the front end and the metering end of the metering station based on the metering station stripping data, and bind the generation time of the front end stripping value with the connection segment between the front end and the metering end nodes to obtain candidate front end segment data.

[0050] The solidified value module is used to identify the stability of the anomaly within the monitoring period after the door is closed, based on the candidate table front section data and the door time sequence data, and to obtain the door back solidified value;

[0051] The diversion and positioning module is used to determine the candidate front section as the front diversion landing point when the front stripping value meets the preset stripping positioning range and the back solidification value meets the preset solidification positioning range, and to obtain the front diversion and positioning record.

[0052] The above-described solution of the present invention has at least the following beneficial effects:

[0053] This invention uses each metering station in the box topology data as an index object to extract data from the front end, metering end, and outgoing end of the metering station and construct a projection table. This solves the problem that the collected data in multi-metering energy metering boxes cannot reflect the correspondence between the front end, metering end, and outgoing end within a single metering station. It merges the operating data of multiple endpoints belonging to the same metering station into the same projection table, making each metering station an independent data processing unit. This projection table is not merely a data display page, but a data carrier for subsequent difference identification, exclusion, and section location. Each metering station has a structured data set containing operating quantities from the front end, metering end, and outgoing end, facilitating data calculation for each branch power supply path.

[0054] This invention identifies the electricity consumption changes that are not recorded in the meter between the meter front and the metering end of the metering unit to obtain the pre-meter stripping value. It differentiates the pre-meter changes and recorded changes in the branch operation data. The pre-meter stripping value separates these data changes that do not enter the metering end from the meter projection table and represents them in a numerical form that can be called by subsequent processing. This makes abnormal electricity consumption changes no longer just a discrepancy between the total load and the sub-meter metering, but is converted into a data difference for a specific metering unit and a specific path from the meter front to the metering end. This value provides input for subsequent metering unit screening and section binding.

[0055] This invention achieves grouping and filtering of concurrent load changes by eliminating metering units that show unidirectional load changes at the metering end or outgoing line end when multiple metering units generate pre-meter stripping values ​​within the same time period. Multiple user branches within a centralized metering box may experience synchronous load increases or decreases within the same monitoring cycle. If stripping values ​​are generated solely based on changes at the meter front end, power consumption changes normally received through the electricity meter and outgoing line switch may also enter the candidate set. By checking whether there are load changes at the metering end or outgoing line end consistent with the pre-meter change direction, metering units that have already formed corresponding responses in the metering path or outgoing line path are excluded from the abnormal candidates. Data objects where the pre-meter change occurs but the metering end or outgoing line end does not form unidirectional load changes are retained. This data set can distinguish between load changes in normal power supply branches and changes not recorded at the meter front end.

[0056] This invention obtains a post-door fixed value by identifying the stability of an anomaly within a monitoring period after the box door is closed, and time-couples power supply branch anomaly data with box operation status data. Candidate pre-meter section data reflects the sections and time periods where there are unmetered power consumption changes between the meter front and the metering end. Box door time-series data reflects the opening, closing, and observation time after the box door is closed. The system can determine from the timeline whether candidate anomalies still exist after the box door is closed, and their persistence within the monitoring period after closure. The post-door fixed value is a stability characterization data formed by the existence of candidate section anomaly data after the box door is closed. This value can distinguish changes related only to the opening process, such as door opening maintenance, temporary contact, and instantaneous disturbances, from pre-meter shunt changes that still exist after the box door is closed.

[0057] This invention determines candidate pre-meter sections as pre-meter diversion points when both the pre-meter stripping value and the post-door fixing value meet a preset fixing positioning range, forming a positioning output constrained by numerical thresholds, temporal stability, and topological sections. The pre-meter stripping value limits the data scale of changes in electricity consumption not connected to the meter, the post-door fixing value limits the existence of this change within the monitoring period after the box door is closed, and the candidate pre-meter sections limit the electrical connection range corresponding to this change. Only when all the above data conditions are met simultaneously will the system write the candidate section into the pre-meter diversion positioning record. This positioning record contains data results with associated fields such as the pre-meter diversion point, corresponding meter position, monitoring period, and generation time, enabling the main station or local monitoring unit to store pre-meter diversion events in a structured record format. Attached Figure Description

[0058] Figure 1 This is a flowchart of a method for real-time monitoring and intelligent diagnosis of an energy metering box provided in an embodiment of the present invention. Detailed Implementation

[0059] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0060] like Figure 1 As shown, embodiments of the present invention propose a method for real-time monitoring and intelligent diagnosis of electricity metering boxes, the method comprising:

[0061] Acquire enclosure topology data, endpoint operation data, and enclosure door timing data within the same monitoring period;

[0062] Using each meter position in the box topology data as the index object, extract the front end, metering end and outgoing end data of each meter position from the endpoint operation data and construct a projection table to obtain the meter position projection table data;

[0063] Based on the meter projection data, identify the electricity consumption changes that are not recorded between the meter front end and the metering end of the meter position, and obtain the meter front stripping value.

[0064] When multiple meter positions generate pre-meter stripping values ​​within the same time period, meter positions with unidirectional changes at the metering end or outgoing end are removed to obtain meter position stripping data.

[0065] Based on the stripped data of the metering station, the connection segment between the front end and the metering end of the metering station is extracted. The time period in which the stripped value of the front end is generated is bound to the connection segment between the front end and the metering end nodes to obtain candidate front end segment data.

[0066] Based on the candidate table front section data and the door time sequence data, the stability of the anomaly during the monitoring period after the door is closed is identified, and the door-back solidification value is obtained.

[0067] When the stripping value before the table meets the preset stripping positioning range and the curing value after the door meets the preset curing positioning range, the candidate stripping segment before the table is determined as the stripping point before the table, and the stripping positioning record before the table is obtained.

[0068] In this embodiment of the invention, the topology data of the distribution box, the endpoint operation data, and the timing data of the box door within the same monitoring period are acquired to provide data for identifying changes in unmetered electricity consumption between the meter front-end and the metering end. Using each meter position in the distribution box topology data as an index object, the front-end, metering end, and outgoing line data of each meter position are extracted from the endpoint operation data and a projection table is constructed to obtain meter position projection table data. This process splits the mixed endpoint data across the entire distribution box into multiple meter position projection tables, clearly expressing the data boundaries of each user branch in the distribution metering box, and providing data for subsequent meter front-end stripping values. Meter-level data carrier; based on meter projection data, identify the unmetered electricity consumption changes between the meter front end and the metering end of the meter position, and obtain the meter front stripping value. It can express the abnormal situation of increased total load but corresponding meter not being metered as the unmetered electricity consumption change of a certain meter position. When multiple meter positions generate meter front stripping values ​​in the same period, meter positions with changes in the same direction at the metering end or outgoing end are removed to obtain meter position stripping data, which reflects the branches where changes occur at the meter front end but are not synchronously received by the metering end or outgoing end, providing meter position-level data for subsequent section positioning.

[0069] Based on the meter stripping data, the connection segment between the meter front end and the metering end of the meter position is extracted. The time period of the stripping value is bound to the connection segment between the meter front end and the metering end node to obtain candidate meter front section data. The abnormal change quantity is correlated with the specific electrical connection range, so that the subsequent diagnostic object is transformed from the meter position to the candidate meter front section. Based on the candidate meter front section data and the box door time sequence data, the stability of the anomaly during the monitoring period after the box door is closed is identified to obtain the door-back solidified value. The operation performance of the candidate meter front section after the box door is closed is included in the positioning condition to provide the door-back status basis for the subsequent determination of the candidate section as the meter front diversion landing point. When the stripping value of the meter front meets the preset stripping positioning interval and the door-back solidified value meets the preset solidified positioning interval, the candidate meter front section is determined as the meter front diversion landing point, and the meter front diversion positioning record is obtained. The meter front diversion positioning record with meter position, section, time period and numerical basis is output for the monitoring of power distribution nodes and the diagnosis of abnormal power supply paths.

[0070] Specifically, acquiring the enclosure topology data, endpoint operation data, and enclosure door time-series data within the same monitoring period includes:

[0071] After the electricity metering box enters real-time monitoring mode, the current monitoring cycle used for diagnosis is first determined, and a cycle identifier is generated for this monitoring cycle. The monitoring cycle can be divided according to a fixed time length, or it can be triggered by data acquisition tasks issued by the main station, box door status change events, or endpoint operation data change events. The start time, end time, cycle number, and sampling interval of the cycle are written into the cycle buffer, so that the box topology data, endpoint operation data, and box door timing data belong to the same cycle identifier.

[0072] When acquiring the enclosure topology data, the system reads the enclosure structure configuration file pre-stored in the metering box's local memory or the master station configuration library. The enclosure topology data includes at least the correspondence between the incoming terminal, main switch, common connection terminal, each meter position, the meter front end, metering terminal, outgoing terminal, terminal block, connection nodes, and connection sections. Based on the topology number, endpoint identifier, meter position identifier, and connection sequence of each node, electrical connection relationship data from the incoming side to each user's outgoing side within the enclosure is formed, and this electrical connection relationship data is written into the topology data area of ​​the current monitoring cycle. If no topology configuration change is detected in the current monitoring cycle, the enclosure topology data from the previous valid cycle is used, and a reference relationship is established in the current cycle; if a meter position change, endpoint replacement, terminal wiring change, metering module replacement, or the master station reissues the topology configuration is detected, the updated topology configuration is read, and the updated topology data is used as the valid topology data for the current monitoring cycle.

[0073] When acquiring endpoint operation data, the system reads the operation data uploaded by each acquisition endpoint in the box according to the sampling time set within the current monitoring cycle. The endpoint operation data may include data such as meter front-end current, metering end current, outgoing line current, endpoint voltage, active power, reactive power, power factor, power increment, switch status, terminal temperature, or communication status. Each endpoint operation data item carries an endpoint identifier, sampling time, data type, and data value. The monitoring unit writes it into the endpoint operation data area of ​​the current monitoring cycle based on the endpoint identifier, preserving the original sampling order. The system performs time normalization processing on the endpoint data. For cases where different acquisition channels have different sampling times within the same monitoring cycle, the monitoring unit uses the preset sampling time within the cycle as the time reference, merging endpoint data falling within the same sampling time window to the same sampling time. Missing sampled values ​​can be marked as null, invalid, or pending supplementation. For duplicate uploaded data, valid records can be determined based on timestamps, data versions, or communication sequence numbers.

[0074] When acquiring door timing data, the system reads door status data generated by the door status detection device, magnetic door switch, limit switch, electronic seal, camera linkage module, or access control module. The door timing data includes at least the door opening time, door closing time, door status duration, and door status change sequence. If one or more opening or closing events occur within the current monitoring period, each door status event is written into the door timing data area according to the event occurrence time. If no door status change occurs within the current monitoring period, the system records the continuous state of the door remaining open or closed during that period. The system aligns the door status events with the period time axis, mapping door opening events, closing events, and their duration intervals to the sampling time sequence of the current monitoring period, so that each sampling time corresponds to one of the following states: door open, closed, or unknown. For door events occurring between two sampling times, the monitoring unit determines its assigned interval according to the event timestamp and retains the precise occurrence time of the event.

[0075] The system binds the enclosure topology data, endpoint operation data, and door timing data according to the same monitoring cycle identifier to form a periodic monitoring data packet. The periodic monitoring data packet includes a topology data area, an endpoint operation data area, a door timing data area, and a cycle index area. The cycle index area records the cycle number, start and end times, sampling interval, topology version, data integrity identifier, and communication status identifier. The data packet is then subjected to integrity verification. Verification includes checking whether each table position in the topology data has a corresponding table front-end, metering end, and outgoing line end; whether the endpoint operation data contains data columns corresponding to the topology endpoints; whether the door timing data has a clear start and end status relationship; and whether all three types of data are within the same monitoring cycle. If the verification passes, the periodic monitoring data packet is used as the data input for subsequently constructing the table position projection table. If there are missing, conflicting, or inconsistent times, an anomaly identifier is added to the corresponding data, and this anomaly identifier is stored along with the periodic monitoring data packet.

[0076] In a preferred embodiment of the present invention, each metering station in the box topology data is used as an index object. Data from the front end, metering end, and outgoing end of each metering station are extracted from the endpoint operation data and a projection table is constructed to obtain metering station projection table data, including:

[0077] Based on the box topology data, using the meter positions as the index object, the meter position identifier, meter front end identifier, meter end identifier and outgoing line end identifier of each meter position are read and written into the same index item to obtain the meter position end point data;

[0078] Based on the endpoint data, using the front-end identifier, metering identifier, and outgoing identifier in the same index item as the column selection criteria, the front-end data column, metering data column, and outgoing data column within the monitoring period are extracted from the endpoint operation data to obtain the endpoint column selection data.

[0079] Based on the data taken from the endpoints of the table, and using the sampling time within the same monitoring period as the sorting basis, the data from the front-end data column, the metering end data column, and the outgoing end data column of the table are written into the same row to obtain the table position time sequence aligned data.

[0080] Based on the time-series alignment data of the meter positions, and using the meter position as the page identifier, the front-end data column, metering end data column, outgoing line data column, and sampling time identifier of the same meter position are written into the same projection table. The front column, metering column, and outgoing line column are set in the projection table to obtain the meter position projection table data.

[0081] In this embodiment of the invention, based on the enclosure topology data, using the meter positions as index objects, the meter position identifier, meter front-end identifier, metering end identifier, and outgoing line end identifier of each meter position are read and written into the same index entry to obtain the meter position endpoint data. This clarifies which endpoint data should be extracted from the endpoint operation data for each meter position, avoiding matching all endpoints in the enclosure one by one in subsequent processing. Based on the meter position endpoint data, using the meter front-end identifier, metering end identifier, and outgoing line end identifier in the same index entry as the column retrieval criteria, the meter front-end data column, metering end data column, and outgoing line end data column within the monitoring period are extracted from the endpoint operation data to obtain the meter position endpoint column data. This preserves the time series characteristics of the operation volume and simultaneously establishes a connection with the meter position index. The system establishes a hierarchy; based on the endpoint data of the meter position, and using the sampling time within the same monitoring period as the arrangement basis, it writes the data from the front-end data column, metering end data column, and outgoing end data column at the same sampling time into the same row, obtaining meter position time-series aligned data. This ensures that each row of data reflects the synchronous operation status of the front-end, metering end, and outgoing end of the meter position at a given sampling time. Based on the meter position time-series aligned data, using the metering meter position as the page identifier, it writes the front-end data column, metering end data column, outgoing end data column, and sampling time identifier of the same metering meter position into the same projection table. It then sets the front column, metering column, and outgoing column in the projection table to obtain meter position projection table data, making each metering meter position an independent data processing object.

[0082] Specifically, based on the data taken from the endpoints of the table, and using the sampling time within the same monitoring period as the arrangement basis, data from the front-end data column, metering end data column, and outgoing end data column at the same sampling time are written into the same row to obtain the table position time sequence aligned data, which specifically includes:

[0083] The system reads the front-end data column, metering data column, and outgoing data column corresponding to a given meter position and establishes a sampling time sequence for the current monitoring period. This sampling time sequence can be derived from a preset sampling interval of the monitoring period or generated based on the actual timestamps present in the endpoint's operational data. Using this sampling time sequence as a row index, the system writes the front-end data, metering data, and outgoing data at the same sampling time into the same row, ensuring that the same row simultaneously contains the operating status of the meter position at the same time across the front-end, metering, and outgoing sides. During time sequence alignment, if the sampling times of the front-end, metering, and outgoing ends are completely identical, the system directly writes them into the same row according to the same timestamp; if there is a sampling delay or upload time difference between different endpoints, the system can merge data falling within the same time window into the same sampling time according to a preset time window. If a certain endpoint does not have valid data at a specific sampling time, the system writes a null value, invalid value, or missing identifier in the corresponding column of that row; if the same endpoint has multiple data at the same sampling time, the system can determine the written value based on the data timestamp, collection sequence number, or data validity identifier, and mark other records as duplicate records.

[0084] Specifically, based on the time-series alignment of the meter positions, and using the meter position as the page identifier, the front-end data column, metering end data column, outgoing line data column, and sampling time identifier of the same meter position are written into the same projection table. A front column, metering column, and outgoing line column are then set in the projection table to obtain the meter position projection table data, which specifically includes:

[0085] The system uses the meter position identifier as the page identifier for the projection table, creating an independent logical page or data table for each meter position. The system writes the meter position time-series aligned data into this projection table and sets up a sampling time column, a table front column, a metering column, and an outgoing line column on the page. The sampling time column records the sampling time corresponding to each row, the table front column records the front-end operating data, the metering column records the metering end operating data, and the outgoing line column records the outgoing line operating data. During the projection table generation process, the system writes the meter position identifier, table front-end identifier, metering end identifier, outgoing line identifier, monitoring cycle identifier, and topology version identifier into the projection table's page header or metadata area. If there are missing endpoints, invalid data, communication anomalies, or time alignment anomalies in the aforementioned steps, the system can write the corresponding identifiers into the projection table's status column, enabling subsequent processing to obtain both data values ​​and data status when reading the projection table. Each meter position projection table corresponds to one meter position, and the data within the projection table is arranged continuously according to the sampling time, allowing the system to directly call the front-end, metering, and outgoing line operating status of that meter position throughout the entire monitoring cycle based on the page identifier.

[0086] In a preferred embodiment of the present invention, based on the meter projection data, the amount of electricity consumption change not recorded in the meter between the front end and the metering end of the meter position is identified to obtain the front-end stripping value, including:

[0087] Based on the change in current at the meter front end, identify the degree of change in non-metered electricity consumption between the meter front end and the metering end, and obtain the stripped difference item; based on the stripped difference item, identify the actual degree of occupation of the monitoring cycle by the change in non-metered electricity consumption, and obtain the time period occupation amount.

[0088] Based on the change in current at the meter front end, the correlation between changes in electricity consumption not connected to the meter and changes in load on the common side is identified, and the common mapping quantity is obtained; based on the time period occupancy and the common mapping quantity, the abnormal contribution of changes in electricity consumption not connected to the meter at each sampling time is identified, and the stripping contribution quantity is obtained.

[0089] The stripping contribution at each sampling time is accumulated to identify the overall scale of the change in electricity consumption not connected to the meter, and the cumulative stripping amount is obtained; based on the current component not connected to the meter and the total number of sampling points in the change segment before the meter, the degree of stability of the abnormal change within the monitoring period is identified, and the stripping retention amount is obtained.

[0090] The cumulative stripping amount and the stripping retention amount are combined for calculation to identify the electricity consumption change characteristics that do not enter the metering path between the meter front end and the metering end, and the stripping value before the meter is obtained.

[0091] In this embodiment of the invention, based on the change in current at the meter front end, the degree of change in non-metered electricity consumption between the meter front end and the metering end is identified, resulting in a stripping difference item that reflects the data inconsistency between the power supply path and the metering path. Based on the stripping difference item, the actual occupancy of non-metered electricity consumption changes on the monitoring period is identified, resulting in a time period occupancy, which can distinguish between instantaneous sampling errors, short-term fluctuations, and non-metered electricity consumption changes that actually persist within the monitoring period. Based on the change in current at the meter front end, the correlation between non-metered electricity consumption changes and common-side load changes is identified, resulting in a common mapping quantity, which identifies abnormal loads between the common power supply node and the branch metering node. Based on the time period occupancy and the common mapping quantity, the abnormal contribution of non-metered electricity consumption changes at each sampling moment is identified, resulting in a stripping contribution quantity, which can be marked in the time series. Which sampling points contribute effectively to the pre-meter stripping value, and which sampling points are merely invalid fluctuations or unmapped differences? The stripping contribution at each sampling time is accumulated to identify the overall scale of electricity consumption changes not entering the meter, yielding a cumulative stripping amount that comprehensively expresses the scale of electricity consumption changes not entering the metering path between the meter front and the metering end. Based on the non-meter current component and the total number of sampling points in the pre-meter change segment, the stability of this abnormal change within the monitoring period is identified, yielding a stripping retention amount that expresses the retention status of the abnormal change within the monitoring period. The cumulative stripping amount and the stripping retention amount are fused and calculated to identify the characteristics of electricity consumption changes not entering the metering path between the meter front and the metering end, yielding a pre-meter stripping value. This value can serve as a data criterion for branch pre-meter current shunting identification and is used for subsequent meter location screening, topology segment binding, and location record generation.

[0092] The formula for calculating the pre-table stripping value is as follows:

[0093] ,

[0094] in, This is the value stripped from the table. This represents the starting sampling time for the data change segment in the first column of the table. This represents the final sampling time for the data change segment in the front column of the table. For the first The change in current at the meter front end at each sampling time is obtained by taking the absolute value of the difference between the current sampled current value and the previous sampled current value. For the first The input current at each sampling moment is determined by the portion of the change in current at the metering end and the change in current at the output end that is in the same direction as the change in current at the meter front end. For the unlisted current component, when When the difference is greater than zero, the difference is taken. Take zero when less than or equal to zero. The sampling interval between two adjacent sampling times. For the first The change in current at the common connection terminal at each sampling time is obtained by taking the absolute value of the difference between the current sampled current value and the previous sampled current value at the common connection terminal. To prevent corrections where the denominator is zero, It is 0.001. This represents the number of sampling points containing current components that are not included in the table within the data change segment in the front column of the table. This represents the total number of sampling points within the data change segment in the front column of the table.

[0095] Specifically, based on the meter projection data, the electricity consumption changes between the meter front and the metering end that are not recorded in the meter are identified, and the pre-meter stripping value is obtained, which includes:

[0096] The system in the The change in current at the front end of the meter is obtained at each sampling time. This quantity is essentially derived from the current difference between adjacent sampling points and is used to characterize the instantaneous changes in the load at the meter's upstream end. The system synchronously acquires the change responses at the metering end and the outgoing line end at the same moment and summarizes them to form the in-meter load quantity. This capacity reflects the portion of energy change at the meter front end that actually enters the electricity metering path. When the change at the meter front end exceeds the metering end's capacity, the difference between the two is... Current components deemed not to have entered the metering link are constrained through positive conversion operations to retain only the positive anomalous portion. The system compares the current components not included in the meter with adjacent sampling time intervals. By performing multiplication, the current difference at a single point is transformed into a cumulative contribution over time, expanding the instantaneous change into a continuous change with temporal significance. Based on this, the system introduces the current change at the common connection terminal. This, together with the total changes in the table front end and the common side, constitutes the normalized proportional term. This ratio is used to characterize whether changes at the current meter reading can be reflected in the common power supply node. The system monitors the period from the start time... until the end time All sampling points are accumulated, and the contribution value composed of the non-metered current component, time weight, and common-side mapping weight at each sampling time is summed to form the cumulative stripping amount. This process unifies the local differences originally scattered across multiple sampling points into a total anomaly scale over the entire variation range, reflecting the overall intensity of the non-metered electricity consumption change of this meter location during the entire monitoring period. After accumulation, the system calculates the stripping retention amount, which is expressed as follows: ,in This indicates the number of sampling points where valid non-metered current components were detected within the range of changes before the meter reading. This represents the total number of sampling points within the range of variation. This ratio characterizes the persistence of the anomaly throughout the entire time period. A value closer to 1 indicates that the anomaly persists for the vast majority of sampling times; a smaller value indicates that the anomaly exhibits more intermittent or short-term fluctuations. The system combines the cumulative stripping amount with the stripping retention amount to obtain the stripping value before the table. ,Should The value not only reflects the scale of the current difference between the front end of the meter and the metering end, but also combines the duration ratio and the common side load consistency constraint to express the characteristics of electricity consumption changes that do not enter the metering path between the front end of the meter and the metering end.

[0097] In a preferred embodiment of the present invention, when multiple metering units generate pre-meter stripping values ​​within the same time period, metering units with unidirectional changes at the metering end or output end are removed to obtain metering unit stripping data, including:

[0098] By merging the time periods of each meter position according to the time periods in which the values ​​before the table are stripped, meter positions with overlapping time periods are written into the same stripping time period group to obtain the stripping time period data.

[0099] Based on the stripping period data, read the direction of data change in the metering column and outgoing line column within the stripping period group, and write the data change that is consistent with the direction of change in the previous table into the acceptance verification column to obtain the acceptance verification data;

[0100] Based on the acceptance and verification data, the meter positions with data changes in the acceptance and verification column are written into the acceptance and exclusion column; otherwise, the meter positions are written into the stripping and retention column to obtain the stripping and column data.

[0101] Based on the stripped column data, the meter position identifier, the stripped value before the meter, the change segment before the meter, the generation time period, and the meter position projection table identifier in the stripped and retained column are bound to obtain the meter position stripped data.

[0102] In this embodiment of the invention, by merging the time periods of each metering station according to the generation time of the pre-meter stripping value, metering stations with overlapping generation time periods are written into the same stripping time period group to obtain stripping time period data. This allows identification of which metering stations simultaneously exhibit pre-meter stripping characteristics within the same time range and which metering stations belong to independent time period anomalies. Based on the stripping time period data, the direction of data change in the metering column and the outgoing line column within the stripping time period group is read, and data changes consistent with the direction of the pre-meter change segment are written into the acceptance verification column to obtain acceptance verification data. This allows identification of whether the changes at the front end of the meter have been transmitted to the metering end or the outgoing line end along the normal metering path. Based on the acceptance verification data, the acceptance verification... Metering stations with data changes are written to the "Acceptance and Exclusion" column; conversely, they are written to the "Stripping and Retention" column, resulting in stripped column data. This allows the system to exclude stations with normal load changes from multiple stations that simultaneously generate pre-meter stripping values, retaining data objects that better match the characteristics of changes not yet recorded in the meter. Based on the stripped column data, the metering station identifier, pre-meter stripping value, pre-meter change segment, generation time period, and station projection table identifier in the "Stripping and Retention" column are bound to obtain station stripping data. This enables the system to retrieve the connection segment between the meter front end and the metering end from the box topology data based on the metering station identifier, and bind abnormal data to the connection segment based on the generation time period.

[0103] Specifically, by merging the time periods of each meter position according to the time period of the pre-table stripping value, meter positions with overlapping time periods are written into the same stripping time period group to obtain stripping time period data, which specifically includes:

[0104] The system reads the pre-table stripping values ​​of each meter position and simultaneously reads the generation time period corresponding to each pre-table stripping value. The generation time period can be determined by the start and end sampling times of the pre-table change segment, or by the time interval from the first formation of the pre-table stripping value to the end of the stripping state. Based on the time axis, the system compares the generation time periods of all meter positions. When the generation time periods of two or more meter positions overlap, contain each other, are adjacent and continuous, or are within the same preset time window, the system groups these meter positions into the same stripping time period group. If the generation time period of the pre-table stripping value of a certain meter position does not overlap with other meter positions, then that meter position can form a separate stripping time period group, or be entered into subsequent processing as an independent stripping record.

[0105] Specifically, based on the stripping period data, the direction of data change in the metering and outgoing line columns within the stripping period group is read, and data changes consistent with the direction of change in the preceding table segment are written into the acceptance verification column to obtain the acceptance verification data, which specifically includes:

[0106] For each stripping time period group, the system reviews the meter projection data corresponding to each meter position within that group and reads the meter front column, metering column, and outgoing line column data for that meter position during the generated time period. The system determines the direction of change in the meter front section, such as an increase in meter front current, a decrease in meter front current, or an increase or decrease in power. The system reads the direction of change in the metering column and outgoing line column within the same time period and determines whether there is a change at the metering end or outgoing line end consistent with the direction of change in the meter front section. If the meter front increases, and the metering column or outgoing line column also increases, the change is considered to have a unidirectional continuity; if the meter front decreases, and the metering column or outgoing line column also decreases, this is also written into the continuity verification column. The system writes the column type, change direction, change time period, and corresponding meter position identifier of the unidirectional continuity changes into the continuity verification column, forming continuity verification data.

[0107] Specifically, based on the acceptance and verification data, meter positions with data changes in the acceptance and verification column are written into the acceptance and exclusion column; conversely, meter positions with no changes are written into the stripping and retention column, resulting in stripped column data, which specifically includes:

[0108] The system reads the acceptance verification column corresponding to each metering unit within the stripping period group one by one. If the acceptance verification column of a metering unit records a change in the same direction at the metering end and the outgoing end, or if one of them shows a change in the same direction as the change segment before the meter, the system writes the metering unit into the acceptance exclusion column. This processing indicates that although the unit generated a stripping value before the meter in the preliminary calculation, its change has a corresponding response at the metering end or the outgoing end, and it will not be prioritized for subsequent pre-meter diversion positioning. Conversely, if the acceptance verification column of a metering unit is empty, or if neither the metering end nor the outgoing end shows a change in the same direction as the change before the meter, the system writes the metering unit into the stripping retention column.

[0109] In a preferred embodiment of the present invention, based on the meter position stripping data, the connection segment between the front end and the metering end of the meter position is extracted, and the generation time of the front-end stripping value is bound to the connection segment between the front-end and metering end nodes to obtain candidate front-end segment data, including:

[0110] Based on the meter position stripping data, read the meter position identifier, the stripping value before the meter, the change segment before the meter, and the time period generated in the stripping retention column, and use the meter position identifier as the segment retrieval entry point to obtain the segment entry data.

[0111] Based on the segment entry data, retrieve the front-end node and metering end node of the metering position identifier, and read the connection sequence between the front-end node and the metering end node to obtain the front-end connection data.

[0112] Based on the data connected to the front of the table, the connection segments that do not enter the metering end node are extracted along the connection sequence from the front node to the metering end node, and the connection segments after the metering end node are excluded to obtain the metering connection segment data.

[0113] Based on the segment entry data, the pre-table stripping value, pre-table change segment, and generation time period are written into the metering connection segment data, and the metering position identifier is bound to the metering connection segment data to obtain candidate pre-table segment data.

[0114] In this embodiment of the invention, based on the meter position stripping data, the meter position identifier, the stripping value before the meter, the change segment before the meter, and the time period generated are read from the stripping retention column. The meter position identifier is used as the segment retrieval entry point to obtain segment entry data, enabling subsequent segment extraction to target the already filtered meter positions, rather than traversing all meter positions or all connection segments. Based on the segment entry data, the front-end node and the metering end node of the meter position identifier are retrieved, and the connection order between the front-end node and the metering end node is read to obtain the front-end connection data, which can determine the possible existence of anomalies. The system determines the logical or physical connection range. Based on the connection data before the meter, it extracts the connection segments that do not enter the metering terminal node along the connection sequence from the front-end node to the metering terminal node, and excludes the connection segments after the metering terminal node to obtain the metering connection segment data. This limits the candidate range of anomalies to the connection segments before the electricity meter's metering path. Based on the segment entry data, it writes the front-end stripping value, the front-end change segment, and the occurrence time period into the metering connection segment data, and binds the meter position identifier to the metering connection segment data to obtain the candidate front-end segment data. It then merges the non-metered change amount, the anomaly occurrence time period, and the front-end connection range.

[0115] Specifically, based on the segment entry data, the front-end node and metering end node of the metering station are retrieved, and the connection sequence between the front-end node and the metering end node is read to obtain the front-end connection data, which includes:

[0116] The system uses the meter position identifier in the section entry data as a search condition to enter the enclosure topology data corresponding to the current monitoring cycle and search for the endpoint relationship of that meter position. The system determines the front-end node corresponding to the meter position, then determines the metering end node. Following the connection relationships recorded in the enclosure topology, the system reads the terminals, connecting wires, terminal blocks, transition nodes, or other intermediate connection nodes traversed from the front-end node to the metering end node, and forms a connection sequence according to the electrical connection direction. This connection sequence can be represented as a node sequence or a connection segment sequence, used to describe the actual power supply path of the meter position from the front-end to the metering end.

[0117] Specifically, based on the data connected before the table, the connection segments that do not enter the metering end node are extracted along the connection order from the front-end node to the metering end node, and the connection segments after the metering end node are excluded, to obtain the metering connection segment data, which specifically includes:

[0118] The system reads the connection data before the meter and identifies the connection segments between the two nodes sequentially, starting from the front-end node and ending at the metering end node. For connection segments located after the front-end node but before reaching the metering end node, the system identifies them as potential front-end shunting connections. Connection segments on the outgoing side after the metering end node, user-side load connections, or connections that have entered the metering path are excluded. The system obtains only the connection segments between the front-end node and the metering end that have not yet entered the metering end node.

[0119] In a preferred embodiment of the present invention, based on the candidate pre-table segment data and the door timing data, the stability of the anomaly within the monitoring period after the door is closed is identified to obtain the post-door solidification value, including:

[0120] Based on the duration of continuous existence of the candidate pre-table segment after the door is closed, the degree of continuity of the anomaly occupying the observation period after the door is closed is identified, and the door-back persistence item is obtained; based on the number of times the candidate pre-table segment recurs within the door-back observation period, the degree of anomaly recurrence is identified, and the door-back repetition item is obtained.

[0121] Based on the persistent and repeated items behind the door, the continuous existence and segmented recurrence characteristics of the anomaly after the door is closed are identified, and the existence item behind the door is calculated; based on the cumulative value of the peeling value before the table during the observation time behind the door, the degree of peeling retention is identified, and the peeling retention item is obtained.

[0122] Based on the number of times the candidate table front segment remains between the same table front node and metering end node, the segment node retention degree is identified, and the segment locking item is obtained; based on the average value of each table front stripping value within the observation period after the gate, the gate benchmark stripping degree is identified, and the gate benchmark item is obtained.

[0123] By fusing the back-door baseline, back-door presence, stripping retention, and section locking items, the stability of the anomaly during the monitoring period after the door is closed is identified, and the back-door solidification value is obtained.

[0124] In this embodiment of the invention, based on the continuous existence duration of the candidate pre-table segment after the door is closed, the degree of continuity of the anomaly occupying the observation period after the door is closed is identified, resulting in a post-door persistence term. This term records whether the anomaly continues after the door is closed and the continuous time range it occupies within the post-door observation period. Based on the number of times the candidate pre-table segment recurs within the post-door observation duration, the degree of anomaly repetition is identified, resulting in a post-door repetition term, which describes whether the anomaly recurs in different sampling segments. Based on the post-door persistence term and the post-door repetition term, the continuous existence characteristic and segmented reproduction characteristic of the anomaly after the door is closed are identified, and the post-door existence term is calculated, which can express whether the candidate anomaly still exists after the box is closed using an intermediate quantity. Based on the cumulative value of each pre-table stripping value within the post-door observation duration, the degree of stripping retention is identified, resulting in a stripping retention term. This reflects whether the anomaly continuously generates pre-meter stripping during its existence; based on the number of times the candidate pre-meter segment remains between the same front-end node and metering end node, the segment node retention degree is identified, resulting in a segment locking item, which can record whether the candidate anomaly is stably maintained on the connection segment between the same front-end node and metering end; based on the average value of each pre-meter stripping value within the observation period behind the door, the back-door baseline stripping degree is identified, resulting in a back-door baseline item, reflecting the average stripping level under unit occurrence or unit observation conditions; by fusing the back-door baseline item, back-door existence item, stripping retention item, and segment locking item, the stability of the anomaly's existence within the monitoring period after the box door is closed is identified, resulting in a back-door solidification value, which can convert the operational performance of the candidate pre-meter segment after the box door is closed into numerical results, providing a back-door status basis for determining the pre-meter diversion landing point.

[0125] The formula for calculating the post-door curing value is as follows:

[0126] ,

[0127] in, This is the value after the door is cured. This represents the average value of the pre-examination peeling values ​​during the observation period behind the door. The duration of continuous existence of the candidate table segment after the box door is closed. The duration of observation behind the door. This represents the number of times the candidate segment before the gate appears repeatedly during the observation period after the gate. This represents the total number of sampling segments during the observation period behind the door. This is the cumulative value of the pre-screening stripping values ​​during the observation period behind the gate. This represents the cumulative change between two consecutive pre-screening values ​​within the observation period after the door is opened. This is the pre-table stripping value when the candidate pre-table segment first appears. The number of times the candidate table front segment remains between the same table front node and metering end node. The total number of times candidate records are generated for the first segment of the candidate table.

[0128] Specifically, based on the candidate table front section data and the door time series data, the stability of the anomaly within the monitoring period after the door is closed is identified, and the door-back solidification value is obtained, including:

[0129] The system determines the closing time of the cabinet door and uses a preset time after the closing time as the observation duration behind the door. During this observation period, the system continuously reads the pre-table stripping values ​​corresponding to each candidate pre-table segment and calculates the average of these pre-table stripping values. ,Should This is used to represent the baseline stripping level of the candidate meter pre-meter section after the enclosure door is closed, which is the average intensity of the change in electricity consumption before the meter is connected in the downstream phase. The system counts the continuous existence duration of the candidate meter pre-meter section after the enclosure door is closed. And compare it with the observation time behind the door. Perform ratio calculations to obtain This ratio represents the proportion of anomalies that continuously occupy the observation period after the door is closed. A higher ratio indicates a longer duration of occurrence in the candidate table front section after the door is closed; a lower ratio indicates a shorter duration of occurrence. The system counts the number of times the candidate table front section recurs within the observation period after the door is closed. And compare it with the total number of sampling segments during the observation period behind the door. Perform ratio calculations to obtain This ratio indicates the degree of recurrence of anomalies within the post-gate observation period. The system can include both continuously occurring anomalies and segmented recurring anomalies in the post-gate solidification judgment. The system reads the cumulative value of each pre-table stripping value within the post-gate observation period. And read the cumulative change between two consecutive pre-table stripping values. Combined with the pre-table stripping value when the candidate pre-table segment first appears ,calculate ,in Reflects the overall scale of stripping values ​​during the post-gate period. Reflecting the degree of fluctuation between stripping values, This is used to provide the baseline peel amount at the first occurrence. This ratio indicates the degree to which the peel value remains stable during continuous observation. When the cumulative peel amount is large and the cumulative fluctuation amount is small, this item can reflect a relatively stable peel retention state. The system counts the number of times the candidate table front segment remains between the same table front node and metering end node. And read the total number of times the candidate table's preceding segment is used to form candidate records. ,calculate This ratio indicates the degree to which abnormal segment points are preserved. If multiple candidate records point to the same connection segment between the table front end and the metering end, the ratio is larger; if the candidate segment varies between different nodes or different connection segments, the ratio is smaller. The system multiplies and fuses the above factors to obtain the post-gate fixed value. ,Should The value includes the average peel level behind the door, the proportion of continuous existence, the proportion of repeated occurrence, the proportion of peel value retention, and the proportion of segment locking. The solidification value behind the door is not simply a record of the door closing event, nor is it a single peel value. Instead, it is a comprehensive calculation result used to characterize whether the candidate segment before the table is continuous, repeated, stable, and remains on the same segment after the door is closed.

[0130] In a preferred embodiment of the present invention, when the pre-table stripping value meets a preset stripping positioning interval and the post-door curing value meets a preset curing positioning interval, the candidate pre-table segment is determined as the pre-table diversion landing point, and a pre-table diversion positioning record is obtained, including:

[0131] By writing the front stripping value, back solidification value, generation time period and front change segment of the same candidate front segment into the same segment overprint table in multiple monitoring cycles, segment overprint data is obtained.

[0132] Based on the segment overprint data, the monitoring period for the stripping value before the table that meets the preset stripping positioning interval is written into the stripping hit column, and the monitoring period for the solidification value after the door that meets the preset solidification positioning interval is written into the solidification hit column. The monitoring period for the simultaneous existence of the stripping hit column and the solidification hit column is identified to obtain steady-state hit data.

[0133] Based on the steady-state hit data, read other candidate table front sections in the same generation period. When the meter position of other candidate table front sections is different from that of the candidate table front section, and its table front change section has been taken by the metering column or the outgoing line column, write the other candidate table front section into the rejection column. When the candidate table front section is not written into the rejection column, write it into the landing point pending column to obtain the landing point pending data.

[0134] Based on the data of undetermined landing points, the connection segment located after the front-end node and before the metering end node is determined as the front-end diversion landing point. The front-end diversion landing point is then bound to the metering position identifier, monitoring cycle, and generation time period to obtain the front-end diversion location record.

[0135] In this embodiment of the invention, by writing the front-side stripping value, back-side solidification value, generation time period, and front-side change segment of the same candidate front-side segment into the same segment overprint table in multiple monitoring cycles, segment overprint data is obtained. This allows observation of whether the same front-side connection segment repeatedly exhibits front-side stripping characteristics and whether its back-side solidification state maintains a corresponding relationship in multiple cycles. Based on the segment overprint data, monitoring cycles in which the front-side stripping value meets the preset stripping positioning interval are written into the stripping hit column, and monitoring cycles in which the back-side solidification value meets the preset solidification positioning interval are written into the solidification hit column. Monitoring cycles in which both the stripping hit column and the solidification hit column exist simultaneously are identified to obtain steady-state hit data. This provides subsequent positioning objects with dual data basis of numerical scale and back-side state, avoiding direct judgment of the landing point based solely on the existence of the stripping value or solely on the existence of the back-side state. Based on the steady-state hit data, data is read from the same production... For other candidate pre-meter sections during the generation period, if the metering position of the other candidate pre-meter section is different from that of the candidate pre-meter section, and its pre-meter change section has been accepted by the metering column or the outgoing line column, the other candidate pre-meter section is written into the exclusion column. If the candidate pre-meter section is not written into the exclusion column, it is written into the pending landing point column to obtain the pending landing point data. This can retain candidate sections that have not been accepted for change interpretation in the same time background and use them as the final landing point determination objects. Based on the pending landing point data, the connection section located after the front-end node and before the metering end node is determined as the pre-meter diversion landing point. The pre-meter diversion landing point is bound with the metering position identifier, monitoring cycle and generation period to obtain the pre-meter diversion positioning record. This completes the boundary distinction between the abnormal connection section and the normal metering connection section, so that the positioning result can directly correspond to the connection area where pre-meter diversion may occur inside the energy metering box.

[0136] The preset stripping positioning interval can be calculated by collecting the stripping values ​​before the door is exposed under normal conditions in five or more historical monitoring cycles, calculating their statistical distribution, and using the mean + 3 times the standard deviation as the lower limit of the preset stripping positioning interval, and the mean + 10 times the standard deviation or the maximum historical value as the upper limit. The preset solidification positioning interval can be calculated by collecting the distribution of the solidification values ​​after five or more known normal operation of the door, and using the 95th percentile of this distribution as the lower limit of the preset solidification positioning interval. The preset stripping positioning interval is [0.8, 10.0], and the preset solidification positioning interval is [0.3, 1.0].

[0137] Specifically, based on the segment overprint data, the monitoring period for which the pre-table stripping value meets the preset stripping positioning interval is written into the stripping hit column, and the monitoring period for which the post-table solidification value meets the preset solidification positioning interval is written into the solidification hit column. Furthermore, monitoring periods where both the stripping hit column and the solidification hit column exist simultaneously are identified to obtain steady-state hit data, specifically including:

[0138] The system reads the segment overprint data corresponding to the same candidate front-end segment. This data records the front-end stripping value, back-end solidification value, generation time period, front-end change segment, and corresponding monitoring cycle identifier for the candidate front-end segment across multiple monitoring cycles. The system extracts the front-end stripping value for each monitoring cycle sequentially, using the monitoring cycle identifier as the reading order, and compares this value with a preset stripping positioning interval. The preset stripping positioning interval defines the range of stripping amounts that can be used as the basis for front-end diversion positioning. When the front-end stripping value within a monitoring cycle falls within this preset stripping positioning interval, the system writes the monitoring cycle identifier, the front-end stripping value, the corresponding candidate front-end segment identifier, the front-end change segment, and the generation time period into the stripping hit column. When the front-end stripping value does not fall within the preset stripping positioning interval, the system does not write the monitoring cycle into the stripping hit column and retains a miss identifier in the segment overprint data.

[0139] The system continues to use the same monitoring cycle identifier as the reading object, extracting the corresponding door-back solidified value within each monitoring cycle, and comparing this door-back solidified value with a preset solidified positioning interval. The preset solidified positioning interval is used to limit the solidified range within which the candidate table front section can be considered to have a continuous existence after the box door is closed. When the door-back solidified value within a certain monitoring cycle falls into the preset solidified positioning interval, the system writes the monitoring cycle identifier, the door-back solidified value, the candidate table front section identifier, the door-back observation duration, the box door closing time, and the corresponding generation time period into the solidified hit column; when the door-back solidified value does not fall into the preset solidified positioning interval, the system does not write the monitoring cycle into the solidified hit column and can mark the cycle as a solidified miss cycle. The system performs same-cycle matching on the stripped hit column and the solidified hit column, reading the monitoring cycle identifier in the stripped hit column and searching for the existence of the same monitoring cycle identifier in the solidified hit column. If the same monitoring period exists in both the stripping hit column and the solidification hit column, it indicates that the candidate pre-meter segment simultaneously meets the pre-meter stripping amount condition and the post-door solidification condition within that monitoring period. The system then writes this monitoring period into the steady-state hit data. The steady-state hit data includes at least the candidate pre-meter segment identifier, meter position identifier, monitoring period identifier, generation time period, pre-meter change segment, pre-meter stripping value, post-door solidification value, stripping hit status, and solidification hit status. This filters the scattered periodic data in the segment overprint data into steady-state periodic data that simultaneously meets both positioning conditions.

[0140] Specifically, based on the steady-state hit data, other candidate table front segments within the same generation period are read. When the metering position of another candidate table front segment is different from that of the candidate table front segment, and its table front change segment has been taken over by the metering column or the outgoing line column, the other candidate table front segment is written into the rejection column. When the candidate table front segment is not written into the rejection column, it is written into the pending landing point column to obtain the pending landing point data, which specifically includes:

[0141] The system reads the candidate table front segment identifier, meter position identifier, monitoring cycle identifier, and generation time period from the steady-state hit data, and uses the generation time period as the time retrieval condition to search for other candidate table front segments within the same monitoring cycle or adjacent associated monitoring cycles. These other candidate table front segments refer to candidate data that also form candidate records within the same generation time period, but whose segment identifier, meter position identifier, or connection segment from the table front end to the metering end is not completely identical to the current candidate table front segment. The system compares the retrieved other candidate table front segments with the current candidate table front segment to determine if their meter position identifiers are different. If the meter position identifiers are the same, they are processed as candidate records within the same meter position; if the meter position identifiers are different, the system proceeds to the acceptance verification process.

[0142] During the acceptance verification process, the system reads the table position projection table data corresponding to other candidate table front sections and extracts the table front change segment, metering column data, and outgoing line column data of the other candidate table front sections within the same generation time period. The system determines the change direction and range of the table front change segment, and then reads the data change direction of the metering column or outgoing line column within the same time range. If the metering column or outgoing line column has a change in the same direction as the table front change segment, and this change can cover the table front change segment corresponding to the other candidate table front section, then the system determines that the table front change segment of the other candidate table front section has been accepted by the metering column or outgoing line column. At this time, the system writes the other candidate table front section identifier, corresponding metering column identifier, accepting column type, accepting change direction, accepting time period, and accepting status into the rejection column. The system performs a status check on the candidate pre-table segments that are currently in a steady state. If the current candidate pre-table segment also has a record that has been accepted by the metering column or the outgoing line column, or if it has been marked as an object to be excluded by other data rules within the same generation period, the system writes it into the exclusion column and it will not proceed to the pending landing point processing. If the current candidate pre-table segment is not written into the exclusion column, and all objects in other candidate pre-table segments within the same generation period that have been accepted by the normal metering column or the outgoing line column have completed the exclusion record, the system writes the current candidate pre-table segment into the pending landing point column. The pending landing point column records at least the candidate pre-table segment identifier, metering position identifier, monitoring cycle identifier, generation period, pre-table change segment, pre-table stripping value, post-gate solidification value, and non-exclusion status to obtain pending landing point data. The pending landing point data is used to represent candidate pre-table segments that, after comparison and acceptance exclusion by other candidate segments within the same generation period, are still not normally accepted and interpreted by the metering column or the outgoing line column.

[0143] Based on the data with undetermined landing points, the connection segment located after the front-end node and before the metering end node is identified as the pre-meter diversion landing point. This pre-meter diversion landing point is then bound to the metering location identifier, monitoring cycle, and generation time period to obtain the pre-meter diversion location record, which specifically includes:

[0144] The system reads each pending landing point record from the pending landing point data and retrieves the corresponding enclosure topology data based on the candidate pre-meter segment identifier in the record. The system determines the front-end node, metering end node, and connection sequence between the candidate pre-meter segment from the enclosure topology data. The system reads the connection segments segment by segment along the connection direction from the front-end node to the metering end node, determining the positional attributes of each connection segment in the topology path. For connection segments located after the front-end node but before reaching the metering end node, the system marks them as candidate pre-meter connection segments. For connection segments after the metering end node, after the outgoing line, or after entering the electricity meter metering path, the system does not consider them as pre-meter diversion landing points. The system combines the pre-meter stripping value, post-door fixed value, generation time period, and pre-meter change segment in the pending landing point record to confirm the location of the connection segment. If the candidate pre-meter segment to which the connection segment belongs already satisfies both the stripping positioning interval and the fixed positioning interval in the steady-state hit data, and was not written into the rejection column during the rejection process, the system determines the connection segment as a pre-meter diversion landing point. If a candidate pre-meter segment contains multiple connection segments located after the front-end node and before the metering end node, the system can record these multiple connection segments as the same pre-meter diversion landing point range, or write them separately into the landing point sub-segment field of the same location record according to the topology granularity. The system binds the determined pre-meter diversion landing point with the metering position identifier, monitoring cycle, and generation time period, and writes it into the location record data area. The pre-meter diversion location record includes at least the pre-meter diversion landing point identifier, front-end node identifier, metering end node identifier, connection segment identifier between the front-end and metering end, metering position identifier, monitoring cycle identifier, generation time period, pre-meter change segment, pre-meter stripping value, gate-after-fixed value, steady-state hit identifier, landing point pending identifier, and segment overprint table identifier. The system also writes the exclusion check result into this record to indicate that other candidate pre-meter segments within the same generation time period have been accepted and excluded by the metering column or outgoing line column. The system stores the pre-meter shunt location records in a local diagnostic record database or uploads them to the main monitoring platform. These records can be queried by meter location, monitoring cycle, time period, or pre-meter connection segment, and can serve as data for subsequent alarms, verifications, or maintenance dispatch. The technical effect of this step is that it transforms candidate pre-meter segments, after steady-state hit detection, rejection, and topology location confirmation, into location results with clear meter location, time, and connection segment attribution. By limiting the landing point to after the meter front-end node and before the metering end node, the system distinguishes the boundary between the pre-meter shunt location and the normal power consumption path after metering, ensuring that the output data is not a general anomaly alert but a pre-meter shunt location record that points to a specific meter branch and a specific pre-meter connection range.

[0145] Embodiments of the present invention also provide a real-time monitoring and intelligent diagnostic system for electricity metering boxes, the system comprising:

[0146] The data module is used to acquire the enclosure topology data, endpoint operation data, and enclosure door time sequence data within the same monitoring period;

[0147] The projection table module is used to extract the front end, metering end and outgoing end data of each metering position from the endpoint running data, and construct the projection table to obtain the metering position projection table data, using each metering position in the box topology data as the index object.

[0148] The stripping value module is used to identify the electricity consumption changes that are not recorded between the front end and the metering end of the metering unit based on the meter projection meter data, and to obtain the stripping value before the meter.

[0149] The meter position stripping module is used to remove meter positions with the same direction of change at the metering end or the outgoing end when multiple meter positions generate pre-meter stripping values ​​in the same time period, and obtain meter position stripping data.

[0150] The candidate segment module is used to extract the connection segment between the front end and the metering end of the metering station based on the metering station stripping data, and bind the generation time of the front end stripping value with the connection segment between the front end and the metering end nodes to obtain candidate front end segment data.

[0151] The solidified value module is used to identify the stability of the anomaly within the monitoring period after the door is closed, based on the candidate table front section data and the door time sequence data, and to obtain the door back solidified value;

[0152] The diversion and positioning module is used to determine the candidate front section as the front diversion landing point when the front stripping value meets the preset stripping positioning range and the back solidification value meets the preset solidification positioning range, and to obtain the front diversion and positioning record.

[0153] It should be noted that this system is a system corresponding to the above method. All implementation methods in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0154] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0155] Embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0156] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A real-time monitoring and intelligent diagnosis method for an electric energy metering box, characterized in that, The method includes: Acquire enclosure topology data, endpoint operation data, and enclosure door timing data within the same monitoring period; Using each meter position in the box topology data as the index object, extract the front end, metering end and outgoing end data of each meter position from the endpoint operation data and construct a projection table to obtain the meter position projection table data; Based on the meter projection data, identify the electricity consumption changes that are not recorded between the meter front end and the metering end of the meter position, and obtain the meter front stripping value. When multiple meter positions generate pre-meter stripping values ​​within the same time period, meter positions with unidirectional changes at the metering end or outgoing end are removed to obtain meter position stripping data. Based on the stripped data of the metering station, the connection segment between the front end and the metering end of the metering station is extracted. The time period in which the stripped value of the front end is generated is bound to the connection segment between the front end and the metering end nodes to obtain candidate front end segment data. Based on the candidate table front section data and the door time sequence data, the stability of the anomaly during the monitoring period after the door is closed is identified, and the door-back solidification value is obtained. When the stripping value before the table meets the preset stripping positioning range and the curing value after the door meets the preset curing positioning range, the candidate stripping segment before the table is determined as the stripping point before the table, and the stripping positioning record before the table is obtained.

2. The method for real-time monitoring and intelligent diagnosis of the electric energy metering box according to claim 1, characterized in that, Using each meter position in the box topology data as the index object, the front end, metering end, and outgoing end data of each meter position are extracted from the endpoint operation data, and a projection table is constructed to obtain the meter position projection table data, including: Based on the box topology data, using the meter positions as the index object, the meter position identifier, meter front end identifier, meter end identifier and outgoing line end identifier of each meter position are read and written into the same index item to obtain the meter position end point data; Based on the endpoint data, using the front-end identifier, metering identifier, and outgoing identifier in the same index item as the column selection criteria, the front-end data column, metering data column, and outgoing data column within the monitoring period are extracted from the endpoint operation data to obtain the endpoint column selection data. Based on the data taken from the endpoints of the table, and using the sampling time within the same monitoring period as the sorting basis, the data from the front-end data column, the metering end data column, and the outgoing end data column of the table are written into the same row to obtain the table position time sequence aligned data. Based on the time-series alignment data of the meter positions, and using the meter position as the page identifier, the front-end data column, metering end data column, outgoing line data column, and sampling time identifier of the same meter position are written into the same projection table. The front column, metering column, and outgoing line column are set in the projection table to obtain the meter position projection table data.

3. The method for real-time monitoring and intelligent diagnosis of the electric energy metering box according to claim 2, characterized in that, Based on the meter projection data, identify the electricity consumption changes between the meter front and the metering end that are not recorded in the meter, and obtain the pre-meter stripping value, including: Based on the change in current at the meter front end, identify the degree of change in non-metered electricity consumption between the meter front end and the metering end, and obtain the stripped difference item; based on the stripped difference item, identify the actual degree of occupation of the monitoring cycle by the change in non-metered electricity consumption, and obtain the time period occupation amount. Based on the change in current at the meter front end, the correlation between changes in electricity consumption not connected to the meter and changes in load on the common side is identified, and the common mapping quantity is obtained; based on the time period occupancy and the common mapping quantity, the abnormal contribution of changes in electricity consumption not connected to the meter at each sampling time is identified, and the stripping contribution quantity is obtained. The stripping contribution at each sampling time is accumulated to identify the overall scale of the change in electricity consumption not connected to the meter, and the cumulative stripping amount is obtained; based on the current component not connected to the meter and the total number of sampling points in the change segment before the meter, the degree of stability of the abnormal change during the monitoring period is identified, and the stripping retention amount is obtained. The cumulative stripping amount and the stripping retention amount are combined for calculation to identify the electricity consumption change characteristics that do not enter the metering path between the meter front end and the metering end, and the stripping value before the meter is obtained.

4. The method for real-time monitoring and intelligent diagnosis of the electric energy metering box according to claim 3, characterized in that, When multiple metering units generate pre-meter stripping values ​​within the same time period, metering units with unidirectional changes at the metering end or outgoing end are removed to obtain metering unit stripping data, including: By merging the time periods of each meter position according to the time periods in which the values ​​before the table are stripped, meter positions with overlapping time periods are written into the same stripping time period group to obtain the stripping time period data. Based on the stripping period data, read the direction of data change in the metering column and outgoing line column within the stripping period group, and write the data change that is consistent with the direction of change in the previous table into the acceptance verification column to obtain the acceptance verification data; Based on the acceptance and verification data, the meter positions with data changes in the acceptance and verification column are written into the acceptance and exclusion column; otherwise, the meter positions are written into the stripping and retention column to obtain the stripping and column data. Based on the stripped column data, the meter position identifier, the stripped value before the meter, the change segment before the meter, the generation time period, and the meter position projection table identifier in the stripped and retained column are bound to obtain the meter position stripped data.

5. The method for real-time monitoring and intelligent diagnosis of electric energy metering box according to claim 4, characterized in that, Based on the metering station stripping data, the connection segment between the front end and the metering end of the metering station is extracted. The time period in which the front-end stripping value is generated is bound to the connection segment between the front-end and metering end nodes to obtain candidate front-end segment data, including: Based on the meter position stripping data, read the meter position identifier, the stripping value before the meter, the change segment before the meter, and the time period generated in the stripping retention column, and use the meter position identifier as the segment retrieval entry point to obtain the segment entry data. Based on the segment entry data, retrieve the front-end node and metering end node of the metering position identifier, and read the connection sequence between the front-end node and the metering end node to obtain the front-end connection data. Based on the data connected to the front of the table, the connection segments that do not enter the metering end node are extracted along the connection sequence from the front node to the metering end node, and the connection segments after the metering end node are excluded to obtain the metering connection segment data. Based on the segment entry data, the pre-table stripping value, pre-table change segment, and generation time period are written into the metering connection segment data, and the metering position identifier is bound to the metering connection segment data to obtain candidate pre-table segment data.

6. The method for real-time monitoring and intelligent diagnosis of the electric energy metering box according to claim 5, characterized in that, Based on the candidate table front section data and the door time series data, the stability of the anomaly during the monitoring period after the door is closed is identified, and the post-door solidification value is obtained, including: Based on the duration of continuous existence of the candidate pre-table segment after the door is closed, the degree of continuity of the anomaly occupying the observation period after the door is closed is identified, and the door-back persistence item is obtained; based on the number of times the candidate pre-table segment recurs within the door-back observation period, the degree of anomaly recurrence is identified, and the door-back repetition item is obtained. Based on the persistent and repeated items behind the door, the continuous existence and segmented recurrence characteristics of the anomaly after the door is closed are identified, and the existence item behind the door is calculated; based on the cumulative value of the peeling value before the table during the observation time behind the door, the degree of peeling retention is identified, and the peeling retention item is obtained. Based on the number of times the candidate table front segment remains between the same table front node and metering end node, the segment node retention degree is identified, and the segment locking item is obtained; based on the average value of each table front stripping value within the observation period after the gate, the gate benchmark stripping degree is identified, and the gate benchmark item is obtained. By fusing the back-door baseline, back-door presence, stripping retention, and section locking items, the stability of the anomaly during the monitoring period after the door is closed is identified, and the back-door solidification value is obtained.

7. The method for real-time monitoring and intelligent diagnosis of an electricity metering box according to claim 6, characterized in that, When the pre-table stripping value meets the preset stripping positioning range and the post-door curing value meets the preset curing positioning range, the candidate pre-table segment is determined as the pre-table diversion landing point, and the pre-table diversion positioning record is obtained, including: By writing the front stripping value, back solidification value, generation time period and front change segment of the same candidate front segment into the same segment overprint table in multiple monitoring cycles, segment overprint data is obtained. Based on the segment overprint data, the monitoring period for the stripping value before the table that meets the preset stripping positioning interval is written into the stripping hit column, and the monitoring period for the solidification value after the door that meets the preset solidification positioning interval is written into the solidification hit column. The monitoring period for the simultaneous existence of the stripping hit column and the solidification hit column is identified to obtain steady-state hit data. Based on the steady-state hit data, read other candidate table front sections in the same generation period. When the meter position of other candidate table front sections is different from that of the candidate table front section, and its table front change section has been taken by the metering column or the outgoing line column, write the other candidate table front section into the rejection column. When the candidate table front section is not written into the rejection column, write it into the landing point pending column to obtain the landing point pending data. Based on the data of undetermined landing points, the connection segment located after the front-end node and before the metering end node is determined as the front-end diversion landing point. The front-end diversion landing point is then bound to the metering position identifier, monitoring cycle, and generation time period to obtain the front-end diversion location record.

8. A real-time monitoring and intelligent diagnostic system for electricity metering boxes, characterized in that: The system is used to perform the method as described in any one of claims 1 to 7, the system comprising: The data module is used to acquire the enclosure topology data, endpoint operation data, and enclosure door time sequence data within the same monitoring period; The projection table module is used to extract the front end, metering end and outgoing end data of each metering position from the endpoint running data, and construct the projection table to obtain the metering position projection table data, using each metering position in the box topology data as the index object. The stripping value module is used to identify the electricity consumption changes that are not recorded between the front end and the metering end of the metering unit based on the meter projection meter data, and to obtain the stripping value before the meter. The meter position stripping module is used to remove meter positions with the same direction of change at the metering end or the outgoing end when multiple meter positions generate pre-meter stripping values ​​in the same time period, and obtain meter position stripping data. The candidate segment module is used to extract the connection segment between the front end and the metering end of the metering station based on the metering station stripping data, and bind the generation time of the front end stripping value with the connection segment between the front end and the metering end nodes to obtain candidate front end segment data. The solidified value module is used to identify the stability of the anomaly within the monitoring period after the door is closed, based on the candidate table front section data and the door time sequence data, and to obtain the door back solidified value; The diversion and positioning module is used to determine the candidate front section as the front diversion landing point when the front stripping value meets the preset stripping positioning range and the back solidification value meets the preset solidification positioning range, and to obtain the front diversion and positioning record.

9. A computing device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program that, when executed by a processor, implements the method as described in any one of claims 1 to 7.

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