Abnormal detection method, device, computing equipment and storage medium for subway community

Abstract

The present invention discloses a method, apparatus, computing device, and storage medium for detecting anomalies in a subway cell. The method comprises: generating a bidirectional reference table based on sweep frequency data of two running directions of a subway line; the bidirectional reference table records the cell identifiers of coverage cells detected in the two running directions corresponding to each position data block, wherein each position data block is obtained by dividing the cell identifiers by starting from a base station of the subway line and using a preset distance as a granularity; for any coverage cell recorded in the bidirectional reference table, if the number of coverage position data blocks corresponding to the coverage cell in both running directions exceeds a preliminary judgment threshold, the cell is determined to be a preliminarily judged abnormal cell; for any preliminarily judged abnormal cell, determining the coverage status of the preliminarily judged abnormal cell based on the bidirectional reference table, and determining the abnormality of the preliminarily judged abnormal cell based on the coverage status. This method can improve the efficiency and accuracy of determining anomaly in subway cells.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a method, device, computing equipment and storage medium for detecting anomalies in a subway cell. Background Art

[0002] The existing subway line coverage system consists of a signal source and a distribution system, with multiple coverage scenarios including tunnels, station halls, platforms, and entrances and exits. Tunnel coverage is a key difficulty in the optimization and maintenance of subway trunk networks.

[0003] Subway tunnels are divided into two lines, uplink and downlink, typically single-hole, single-track tunnels. Due to space constraints and government policies, subway operators are generally not permitted to build separate distribution systems. Instead, combiner equipment is employed, allowing all operators to share a common distribution system. Tunnels are typically covered by leaky cables, where multiple operators and multiple systems coexist, often combining multiple systems. For example, combiner (Point of Interest) equipment is deployed with a 4G Remote Radio Unit (RRU) and a DCS1800 RRU every 400 meters, and a GSM900 RRU every 800 meters. This demonstrates the integration of multiple components within the subway coverage system.

[0004] In principle, tunnel networking should be negotiated and agreed upon with other operators. The preferred approach is to use RRUs, Point of Interest (POIs), and dual-channel leaky cables, supporting LTE MIMO. 2G / 3G networks can flexibly utilize split or combined cables. Subway tunnels feature numerous signal sources and complex networking. Problems in any of the RRU hardware, combiners, or leaky cables can lead to congestion and disruption of the entire tunnel network. Furthermore, wireless signal coverage in subways can present hidden issues that are difficult to verify, such as cell mismatching. This occurs when multiple RRUs combine signals to a BBU, but one RRU misconfigured to its assigned BBU can cause signal disruption. Existing subway networks are high-load coverage scenarios, requiring multi-layer networks for overlapping coverage to ensure capacity. Furthermore, the attenuation of leaky cables used for end-to-end coverage limits the reach of a single cable. To avoid unnecessary handovers, multiple RRUs are combined to ensure a single single-frequency cell exists between two subway stations. Consequently, cell mismatching is a common problem during construction and data configuration. The existing detection method is to test the abnormal cell occupancy of the terminal, and analysts use drive test playback software to make manual judgments and arrange on-site reviews to locate the problems found.

[0005] However, in the process of realizing the present invention, the inventors found that the existing technology has at least the following deficiencies: First, the existing detection method is time-consuming and labor-intensive. If the test frequency and the amount of test data are insufficient, the accuracy of problem diagnosis will be reduced; second, in the subway scenario, higher requirements are placed on the accuracy of the test equipment (including sample positioning and cell resolution accuracy) and the acquisition efficiency. The current use of ordinary test terminals is not sufficient to meet the test frequency depth and acquisition speed requirements, thereby further reducing the accuracy of problem diagnosis; in addition, during the road test playback software and manual verification process, the judgment results obtained by different network optimization engineers based on their personal experience are often very different. In the subsequent actual investigation process, the success rate of discovering cell mismatches is still insufficient. Summary of the Invention

[0006] In view of the above problems, the present invention is proposed to provide a method, apparatus, computing device and storage medium for detecting anomalies in a subway cell that overcome the above problems or at least partially solve the above problems.

[0007] According to one aspect of the present invention, a method for detecting anomalies in a subway cell is provided, comprising:

[0008] Generate a bidirectional reference table for the subway line based on the frequency sweep data of the two operating directions of the subway line;

[0009] The bidirectional reference table records the cell identifiers of the coverage cells detected in both directions of travel for each location data block. Each location data block is obtained by dividing the data into preset distances starting from the reference station of the subway line.

[0010] For any coverage cell recorded in the bidirectional reference table of the line, if the number of coverage position data blocks corresponding to the coverage cell in both running directions exceeds the preliminary judgment threshold, the coverage cell is determined to be a preliminary judgment abnormal cell;

[0011] For any initially judged abnormal cell, the coverage condition of the initially judged abnormal cell is determined according to the line bidirectional reference table, and the abnormality of the initially judged abnormal cell is determined based on the coverage condition.

[0012] Optionally, determining the abnormality of the initially determined abnormal cell based on the coverage situation further includes:

[0013] Determine whether the initially judged abnormal cell meets the first abnormal judgment condition; if so, determine that the initially judged abnormal cell is a platform cell;

[0014] The first abnormal judgment condition includes: the initially judged abnormal cell is located within a preset distance range on both sides of the platform, the coverage position data blocks corresponding to the initially judged abnormal cell in the two running directions are distributed on both sides of the platform, and the number of coverage position data blocks corresponding to the initially judged abnormal cell in the two running directions is less than the first preset threshold.

[0015] Optionally, determining the abnormality of the initially determined abnormal cell based on the coverage situation further includes:

[0016] Determine whether the initially judged abnormal cell meets the second abnormal judgment condition; if so, determine that the abnormal situation of the initially judged abnormal cell is that the platform area signal has leaked to the outside;

[0017] The second abnormal judgment conditions include: the initially judged abnormal cell is located within a preset distance range on both sides of the platform, the difference in signal strength measured in the two running directions of the initially judged abnormal cell is greater than the signal strength threshold, the corresponding coverage position data blocks in the two running directions are distributed on both sides of the platform, and the number of coverage position data blocks corresponding to the running direction with a larger number of coverage position data blocks is greater than the second preset threshold.

[0018] Optionally, determining the abnormality of the initially determined abnormal cell based on the coverage situation further includes:

[0019] Determine whether the initially judged abnormal cell meets the third abnormal judgment condition; if so, determine that the abnormal situation of the initially judged abnormal cell is bidirectional shared cell coverage;

[0020] The third abnormality judgment condition includes: the coverage blocks of the initially judged abnormal cell in the two running directions are consistent, and the number of corresponding coverage position data blocks of the initially judged abnormal cell in the two running directions exceeds a third preset threshold.

[0021] Optionally, determining the abnormality of the initially determined abnormal cell based on the coverage situation further includes:

[0022] Determine whether the initially judged abnormal cell meets the fourth abnormality judgment condition; if so, determine that the abnormal condition of the initially judged abnormal cell is RRU alternating coverage;

[0023] The fourth abnormal judgment condition includes: there is no overlap between the coverage position data blocks corresponding to the two running directions of the initial judgment abnormal cell, and the number of coverage position data blocks corresponding to the running direction with fewer coverage position data blocks exceeds a fourth preset threshold.

[0024] Optionally, determining the abnormality of the initially determined abnormal cell based on the coverage situation further includes:

[0025] Determine whether the initially judged abnormal cell meets the fifth abnormality judgment condition; if so, determine that the abnormal condition of the initially judged abnormal cell is RRU staggered coverage;

[0026] The fifth abnormal judgment condition includes: initially judging that the coverage position data block corresponding to the abnormal cell in one running direction belongs to the coverage position data block corresponding to another running direction, and the number of coverage position data blocks corresponding to the running direction with fewer coverage position data blocks exceeds the fifth preset threshold.

[0027] Optionally, determining the abnormality of the initially determined abnormal cell based on the coverage situation further includes:

[0028] Determine whether the initially judged abnormal cell meets the sixth abnormality judgment condition; if so, determine that the abnormality of the initially judged abnormal cell is an RRU radio frequency abnormality;

[0029] The sixth abnormal judgment condition includes: the initial judgment that the abnormal cell is discontinuous between the two corresponding coverage location data blocks in one direction, any coverage location data block contains multiple continuous coverage location data blocks, and the number of location data blocks between the two coverage location data blocks exceeds the sixth preset threshold.

[0030] According to another aspect of the present invention, there is provided a device for detecting anomalies in a subway cell, comprising:

[0031] A reference table generation module is adapted to generate a bidirectional reference table for a subway line based on the frequency sweep data of the two running directions of the subway line;

[0032] The bidirectional reference table records the cell identifiers of the coverage cells detected in both directions of travel for each location data block. Each location data block is obtained by dividing the data into preset distances starting from the reference station of the subway line.

[0033] The preliminary judgment module is adapted to determine, for any coverage cell recorded in the bidirectional reference table of the line, that the coverage cell is a preliminarily judged abnormal cell if the number of coverage position data blocks corresponding to the coverage cell in both running directions exceeds the preliminary judgment threshold;

[0034] The abnormality determination module is adapted to determine the coverage of any initially determined abnormal cell according to the line bidirectional reference table, and determine the abnormality of the initially determined abnormal cell based on the coverage.

[0035] Optionally, the abnormality determination module is further adapted to:

[0036] Determine whether the initially judged abnormal cell meets the first abnormal judgment condition; if so, determine that the initially judged abnormal cell is a platform cell;

[0037] The first abnormal judgment condition includes: the initially judged abnormal cell is located within a preset distance range on both sides of the platform, the coverage position data blocks corresponding to the initially judged abnormal cell in the two running directions are distributed on both sides of the platform, and the number of coverage position data blocks corresponding to the initially judged abnormal cell in the two running directions is less than the first preset threshold.

[0038] Optionally, the abnormality determination module is further adapted to:

[0039] Determine whether the initially judged abnormal cell meets the second abnormal judgment condition; if so, determine that the abnormal situation of the initially judged abnormal cell is that the platform area signal has leaked to the outside;

[0040] The second abnormal judgment conditions include: the initially judged abnormal cell is located within a preset distance range on both sides of the platform, the difference in signal strength measured in the two running directions of the initially judged abnormal cell is greater than the signal strength threshold, the corresponding coverage position data blocks in the two running directions are distributed on both sides of the platform, and the number of coverage position data blocks corresponding to the running direction with a larger number of coverage position data blocks is greater than the second preset threshold.

[0041] Optionally, the abnormality determination module is further adapted to:

[0042] Determine whether the initially judged abnormal cell meets the third abnormal judgment condition; if so, determine that the abnormal situation of the initially judged abnormal cell is bidirectional shared cell coverage;

[0043] The third abnormality judgment condition includes: the coverage blocks of the initially judged abnormal cell in the two running directions are consistent, and the number of corresponding coverage position data blocks of the initially judged abnormal cell in the two running directions exceeds a third preset threshold.

[0044] Optionally, the abnormality determination module is further adapted to:

[0045] Determine whether the initially judged abnormal cell meets the fourth abnormality judgment condition; if so, determine that the abnormal condition of the initially judged abnormal cell is RRU alternating coverage;

[0046] The fourth abnormal judgment condition includes: there is no overlap between the coverage position data blocks corresponding to the two running directions of the initial judgment abnormal cell, and the number of coverage position data blocks corresponding to the running direction with fewer coverage position data blocks exceeds a fourth preset threshold.

[0047] Optionally, the abnormality determination module is further adapted to:

[0048] Determine whether the initially judged abnormal cell meets the fifth abnormality judgment condition; if so, determine that the abnormal condition of the initially judged abnormal cell is RRU staggered coverage;

[0049] The fifth abnormal judgment condition includes: initially judging that the coverage position data block corresponding to the abnormal cell in one running direction belongs to the coverage position data block corresponding to another running direction, and the number of coverage position data blocks corresponding to the running direction with fewer coverage position data blocks exceeds the fifth preset threshold.

[0050] Optionally, the abnormality determination module is further adapted to:

[0051] Determine whether the initially judged abnormal cell meets the sixth abnormality judgment condition; if so, determine that the abnormality of the initially judged abnormal cell is an RRU radio frequency abnormality;

[0052] The sixth abnormal judgment condition includes: the initial judgment that the abnormal cell is discontinuous between the two corresponding coverage location data blocks in one direction, any coverage location data block contains multiple continuous coverage location data blocks, and the number of location data blocks between the two coverage location data blocks exceeds the sixth preset threshold.

[0053] According to another aspect of the present invention, there is provided a computing device, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus;

[0054] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute operations corresponding to the above-mentioned subway cell anomaly detection method.

[0055] According to another aspect of the present invention, a computer storage medium is provided, wherein the storage medium stores at least one executable instruction, and the executable instruction enables a processor to perform operations corresponding to the above-mentioned method for detecting anomalies in a subway cell.

[0056] According to the method, device, computing equipment and storage medium for detecting abnormalities in a subway cell of the present invention, the method includes: generating a bidirectional reference table of the line based on the sweep frequency data of the two running directions of the subway line; the bidirectional reference table of the line records the cell identifiers of the coverage cells detected in the two running directions corresponding to each position data block, and each position data block is obtained by dividing the coverage cells by starting from the base station of the subway line and using a preset distance as the granularity; for any coverage cell recorded in the bidirectional reference table of the line, if the number of coverage position data blocks corresponding to the coverage cell in the two running directions exceeds the initial judgment threshold, the cell is determined to be a pre-judgment abnormal cell; for any pre-judgment abnormal cell, the coverage situation of the pre-judgment abnormal cell is determined according to the bidirectional reference table of the line, and the abnormal situation of the pre-judgment abnormal cell is determined based on the coverage situation. Through the above method, the efficiency and accuracy of the determination of abnormalities in subway cells can be improved.

[0057] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0059] Figure 1 A flowchart of a method for detecting anomalies in a subway cell provided by an embodiment of the present invention is shown;

[0060] Figure 2 A schematic diagram of a bidirectional reference table for a line according to an embodiment of the present invention is shown;

[0061] Figure 3 A schematic diagram showing the coverage of an abnormal cell in another embodiment of the present invention is shown;

[0062] Figure 4 A schematic diagram showing the coverage of an abnormal cell in another embodiment of the present invention is shown;

[0063] Figure 5 A schematic diagram showing the coverage of an abnormal cell in another embodiment of the present invention is shown;

[0064] Figure 6 A schematic diagram showing the coverage of an abnormal cell in another embodiment of the present invention is shown;

[0065] Figure 7 A schematic diagram showing the coverage of an abnormal cell in another embodiment of the present invention is shown;

[0066] Figure 8 A schematic diagram showing the coverage of an abnormal cell in another embodiment of the present invention is shown;

[0067] Figure 9 A schematic flow chart of a method for detecting anomalies in a subway area according to another embodiment of the present invention is shown;

[0068] Figure 10 A schematic structural diagram of an anomaly detection method for a subway cell in another embodiment of the present invention is shown;

[0069] Figure 11 A schematic structural diagram of a computing device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0070] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0071] Figure 1 FIG. 1 shows a flow chart of a method for detecting anomalies in a subway cell according to an embodiment of the present invention. Figure 1 As shown, the method includes the following steps:

[0072] Step S110 : generating a bidirectional reference table of the subway line according to the corresponding frequency sweep data of the two running directions of the subway line.

[0073] The bidirectional reference table of the line records the cell identifiers of the coverage cells detected in the two running directions corresponding to each location data block. Each location data block is obtained by starting from the reference station of the subway line and dividing it with a preset distance as the granularity.

[0074] The subway line's base station is one of the two end stations. Starting from the base station, the location data blocks are divided at a preset distance granularity, for example, at a 50-meter granularity, with each block generating a location data block. In this approach, the average of the indicators for the same cell within each data block is calculated.

[0075] Subway tunnels are divided into two lines, up and down. Testing generates frequency sweep data corresponding to both directions of travel. This data is then analyzed to determine cell coverage information for both directions. Based on this analysis, a bidirectional reference table is generated. This table contains cell coverage information for each location data block in both the forward and reverse directions of the subway line. For example, the forward and reverse test data are input into the trunk line test and analysis platform, which then outputs the forward and reverse data reference tables, which are then aggregated into a bidirectional reference table.

[0076] For example, for the first location data block, which corresponds to the range of 0 to 50 meters from the reference station on the subway line, based on the frequency scanning data in the positive direction of the line and the frequency scanning data in the reverse direction of the line within this range, the coverage cells corresponding to the location data block in the two running directions are analyzed, and the identifications of the coverage cells corresponding to the location data block in the two running directions are recorded in the bidirectional reference table.

[0077] In an optional manner, after analyzing and obtaining the cell coverage information in the two operating directions, screening is performed based on set conditions, for example, the default detection level is above -90dBm, and cells meeting the set conditions are written into the line bidirectional reference table.

[0078] Figure 2 FIG. 1 shows a schematic diagram of a bidirectional reference table for a line according to an embodiment of the present invention. Figure 2 As shown, the location data block can be determined by the distance tag, and the value of the distance tag represents the distance from the site. For example, for the cell identifier "460-00-647478-73" in the second row and third column of the line bidirectional reference table, it means the location data block within the range of 0 to 50 meters from site 1, and the cell identifier of the coverage cell detected from the uplink direction is "460-00-647478-73"; for the cell identifier "460-00-733662-128" in the second row and fourth column of the line bidirectional reference table, it means the location data block within the range of 0 to 50 meters from site 1, and the cell identifier of the coverage cell detected from the downlink direction is "460-00-733662-128". The same applies to other cases and are not described in detail here. For the cell ID "460-00-647472-72" in the bidirectional reference table, the corresponding location data blocks in the uplink direction include all locations within a range of 0-350 meters from Site 2. The location data blocks covered in the reverse direction include all locations within a range of 100-400 meters from Site 2. Furthermore, for data integrity, detailed information such as the city and line name can also be written into the bidirectional reference table.

[0079] Step S120: For any coverage cell recorded in the bidirectional reference table, if the number of coverage position data blocks corresponding to the coverage cell in both running directions exceeds the preliminary judgment threshold, the coverage cell is determined to be a preliminary judgment abnormal cell.

[0080] For any coverage cell included in the bidirectional reference table, based on the data recorded in the bidirectional reference table for that line, if the coverage cell detects coverage signals in both directions of travel, and the number of coverage location data blocks detected in both directions exceeds the initial judgment threshold, then the coverage cell is preliminarily determined to be abnormal. A coverage location data block is a location data block where a coverage signal is detected. Typically, a cell covers multiple consecutive location data blocks. In other cases, such as when a coverage cell detects coverage signals in only one direction of travel, or when the number of coverage location data blocks detected in both directions of travel does not exceed the initial judgment threshold, no abnormality is determined.

[0081] Step S130: For any initially determined abnormal cell, the coverage of the initially determined abnormal cell is determined according to the bidirectional reference table, and the abnormality of the initially determined abnormal cell is determined based on the coverage.

[0082] For any initially judged abnormal cell, the number and distribution of corresponding coverage position data blocks in the two running directions of the line are queried in the line bidirectional reference table according to the identification of the initially judged abnormal cell, and the abnormality of the initially judged abnormal cell is determined based on the statistical analysis results.

[0083] In one optional approach, after initially determining each abnormal cell, a preliminary abnormal cell list is formed based on the identifiers of each abnormal cell. Optionally, the preliminary abnormal cell list may also include the number of coverage location data blocks corresponding to each abnormal cell in both directions. In this step, a cell ID (cell[i]) is extracted from the preliminary abnormal cell list, where i ranges from 1 to N, and N is the number of cell identifiers in the preliminary abnormal cell list. The bidirectional reference table of the line is queried based on the cell ID (cell[i]) to obtain the location data blocks covered by the cell in both directions.

[0084] The judgment rules are different for different abnormal situations. The judgment rules for each abnormal situation are introduced below.

[0085] First, determine whether the initially judged abnormal cell meets the first abnormal judgment condition; if so, determine that the initially judged abnormal cell is a platform cell; the first abnormal judgment condition includes: the initially judged abnormal cell is located within a preset distance range on both sides of the platform, the coverage position data blocks corresponding to the initially judged abnormal cell in the two running directions are distributed on both sides of the platform, and the number of coverage position data blocks corresponding to the initially judged abnormal cell in the two running directions is less than the first preset threshold.

[0086] Figure 3 FIG. 1 is a schematic diagram showing the coverage of an abnormal cell according to another embodiment of the present invention. Figure 3 As shown, the area filled with solid lines corresponds to the coverage of the initially judged abnormal cell detected in the upward direction of line A, and the area filled with dotted lines corresponds to the coverage of the initially judged abnormal cell detected in the upward direction of line B. Specifically, the coverage of the initially judged abnormal cell can be determined by querying the bidirectional reference table of the line based on the cell identifier of the initially judged abnormal cell. If the initially judged abnormal cell is near the platform, has coverage on both sides of the platform, and the number of corresponding coverage position data blocks in both operating directions is not large (for example, both are less than 12), then the initially judged abnormal cell is determined to be a platform cell.

[0087] Second, determine whether the initially judged abnormal cell meets the second abnormal judgment condition; if so, determine that the abnormal situation of the initially judged abnormal cell is that the signal in the platform area has leaked to the outside; the second abnormal judgment condition includes: the initially judged abnormal cell is located within a preset distance range on both sides of the platform, the difference in signal strength measured in the two running directions of the initially judged abnormal cell is greater than the signal strength threshold, the coverage position data blocks corresponding to the initially judged abnormal cell in the two running directions are distributed on both sides of the platform, and the number of coverage position data blocks corresponding to the direction with a larger number of coverage position data blocks is greater than the second preset threshold.

[0088] Figure 4 FIG. 1 is a schematic diagram showing the coverage of an abnormal cell according to another embodiment of the present invention. Figure 4 As shown, the area filled with solid lines corresponds to the coverage of the initially judged abnormal cell detected in the upward direction of line A, and the area filled with dotted lines corresponds to the coverage of the initially judged abnormal cell detected in the upward direction of line B. If the initially judged abnormal cell covers location data blocks on both sides of the site and is within 300 meters from the site, the number of corresponding covered location data blocks in the signal direction (the running direction with a larger number of covered location data blocks) is greater than a second preset threshold (assuming it is 14), and the difference in signal strength measured in the two running directions is greater than a threshold (assuming it is 5DB), then the abnormality of the initially judged abnormal cell is determined to be signal leakage to the outside of the platform area.

[0089] Third, determine whether the initially judged abnormal cell meets the third abnormal judgment condition; if so, determine that the abnormal situation of the initially judged abnormal cell is bidirectional co-cell coverage; the third abnormal judgment condition includes: the coverage situation blocks of the initially judged abnormal cell in the two running directions are consistent, and the number of corresponding coverage position data blocks of the initially judged abnormal cell in the two running directions exceeds the third preset threshold.

[0090] Figure 5 FIG. 1 is a schematic diagram showing the coverage of an abnormal cell according to another embodiment of the present invention. Figure 5 As shown, the area filled with solid lines corresponds to the coverage of the initially judged abnormal cell detected in the upward direction of line A, and the area filled with dotted lines corresponds to the coverage of the initially judged abnormal cell detected in the upward direction of line B. If the location data blocks covered by the initially judged abnormal cell in both directions of the line exceed the third preset threshold and cover the same section, it is bidirectional co-cell coverage. This situation may be caused by the actual design of the existing network when the network coverage capacity demand is small, or it may be caused by the mismatch of the cell RRU equipment. In an optional method, the coverage situation is output for relevant personnel to conduct further analysis.

[0091] Fourth, determine whether the initially determined abnormal cell meets a fourth abnormality determination condition; if so, determine that the abnormal condition of the initially determined abnormal cell is RRU alternating coverage. The fourth abnormality determination condition includes: there is no overlap between the coverage position data blocks corresponding to the two operating directions of the initially determined abnormal cell, and the number of coverage position data blocks corresponding to the operating direction with fewer coverage position data blocks exceeds a fourth preset threshold.

[0092] Figure 6 FIG. 1 is a schematic diagram showing the coverage of an abnormal cell according to another embodiment of the present invention. Figure 6 As shown, the area filled with solid lines corresponds to the coverage of the initially determined abnormal cell detected in the upward direction of line A, and the area filled with dotted lines corresponds to the coverage of the initially determined abnormal cell detected in the upward direction of line B. If the initially determined abnormal cell is detected to be covered in both directions of the line and covers different sections, and the number of position data blocks covered in the direction with fewer covered position data blocks (i.e., direction A in Examples 1 and 2) exceeds a fourth preset threshold (assuming it is 5), then the abnormal condition of the abnormal cell is determined to be RRU alternating coverage.

[0093] Fifth, determine whether the initially judged abnormal cell meets the fifth abnormal judgment condition; if so, determine that the abnormal situation of the initially judged abnormal cell is RRU staggered coverage; the fifth abnormal judgment condition includes: the coverage position data block corresponding to the initially judged abnormal cell in one running direction belongs to the coverage position data block corresponding to the other running direction, and the number of coverage position data blocks corresponding to the running direction with fewer coverage position data blocks exceeds the fifth preset threshold.

[0094] Figure 7 FIG. 1 is a schematic diagram showing the coverage of an abnormal cell according to another embodiment of the present invention. Figure 7 As shown, the area filled with solid lines corresponds to the coverage of the initially judged abnormal cell detected in the upward direction of line A, and the area filled with dotted lines corresponds to the coverage of the initially judged abnormal cell detected in the upward direction of line B. If the initially judged abnormal cell has coverage in the one-way tunnel and the coverage signal appears in the other direction of the road section, and the number of problematic location data blocks (coverage location data blocks corresponding to the direction with fewer coverage location data blocks) exceeds the fifth preset threshold, the abnormality of the initially judged abnormal cell is determined to be RRU staggered coverage.

[0095] Sixth, determine whether the initially judged abnormal cell meets the sixth abnormal judgment condition; if so, determine that the abnormal situation of the initially judged abnormal cell is an RRU radio frequency abnormality; the sixth abnormal judgment condition includes: the initially judged abnormal cell is discontinuous between the two corresponding coverage position data blocks in a unidirectional direction, any coverage position data block contains multiple continuous coverage position data blocks, and the number of position data blocks between the two coverage position data blocks exceeds the sixth preset threshold.

[0096] Figure 8 FIG. 1 is a schematic diagram showing the coverage of an abnormal cell according to another embodiment of the present invention. Figure 8 As shown in the figure, the dotted line fill area corresponds to the coverage of the initially judged abnormal cell detected in the upward direction of line B. The initially judged abnormal cell has coverage gaps in the middle of the continuous coverage area of ​​the unidirectional tunnel, and the number of problematic location data blocks (i.e., the number of discontinuous location data blocks) exceeds the threshold. In this case, it is judged as an RRU RF abnormality.

[0097] In addition, if the coverage of the initially judged abnormal cell does not meet the above six abnormal judgment conditions, the abnormal cause of the initially judged abnormal cell is determined to be other reasons, and relevant prompt information is output.

[0098] According to the subway cell anomaly detection method provided in this embodiment, an algorithm for determining cell mismatch in subway scenarios is involved based on a bidirectional reference table of lines. This algorithm can automatically analyze and determine abnormal problems in subway cells, avoid the process of manually defining abnormal problems in subway cells, and improve the efficiency and accuracy of determining abnormalities in subway cells.

[0099] Figure 9 FIG. 1 is a flow chart showing a method for detecting anomalies in a subway area according to another embodiment of the present invention. Figure 9 As shown, the method is implemented based on a cyclic algorithm, and the method includes the following steps:

[0100] S0: Collect sweep frequency data.

[0101] S1: Generate line bidirectional reference table JZ_A.

[0102] Based on the collected sweep frequency data, the line reference table is output on the trunk test analysis platform. It is necessary to input the forward and reverse test data separately, output the forward and reverse data reference tables, and summarize them into the line bidirectional reference table JZ_A.

[0103] S2: Preliminary screening of abnormal cells and generation of a preliminary abnormal cell table QL.

[0104] Based on the JZ_A statistics, the cell IDs involved in the forward and reverse directions of the line are counted and the number of data blocks is counted to generate a cell coverage statistics table. A list of cells occupied in both directions is retained, abnormal cells are screened according to relevant threshold settings, and a preliminary abnormal cell table QL is generated.

[0105] S3: Extract the data cell cell[i] in row i from QL, and perform abnormality determination on the initially determined abnormal cell cell[i]. In the method of this embodiment, abnormality determination is performed according to a step-by-step elimination method.

[0106] S4: According to the cell ID (cell[i]), the forward and reverse positions of the line are found in the JZ_A reference table.

[0107] S5: Determine whether the initially judged abnormal cell is a platform cell.

[0108] For example, the judgment conditions are: 1: the distance threshold on both sides of the platform is exceeded (the default is 300 meters), 2: data blocks exist in both the forward and reverse directions and the total number in each direction is less than the threshold (the default is 12). If the judgment result is "No", the process proceeds to S6. If the result is "Yes", the process jumps to S11.

[0109] S6: Determine whether the initially judged abnormal cell is a platform area with external signal leakage.

[0110] For example, the judgment conditions are: 1: The distance threshold on both sides of the platform is met (default is 300 meters); 2: The opposite signal exists and the difference is greater than the threshold (default is 5dB); 3: The number of consecutive data blocks in the signal direction is greater than the threshold (default is 14), and the signal direction is the direction of operation with the most covered position data blocks. If the judgment result is "No", the process proceeds to S7. If the judgment result is "Yes", the process jumps to S11.

[0111] S7: Determine whether the initially judged abnormal cell has bidirectional shared cell coverage.

[0112] If the cell has coverage in both the forward and reverse directions of the tunnel and covers the same section, and the number of consecutive data blocks of bidirectional shared cell coverage exceeds the threshold (default is 20), this situation is bidirectional shared cell coverage. If the judgment result is "No", the process proceeds to S8. If the result is "Yes", the process jumps to S11.

[0113] S8: Determine whether the initially determined abnormal cell is an RRU mismatch.

[0114] Among them, there are two types of RRU mismatch:

[0115] (1) RRU alternating coverage.

[0116] For example, the judgment condition is: the number of problematic data blocks caused by the mismatch exceeds a threshold (the default is 5), and the problematic data blocks caused by the mismatch are relatively small. If the cell has coverage in both the forward and reverse directions of the tunnel and covers different sections, and the number of problematic data blocks exceeds the threshold, this situation is judged as an RRU mismatch with alternating coverage.

[0117] (2) RRU staggered coverage.

[0118] For example, the judgment condition is: the number of problematic data blocks caused by the mismatch exceeds a threshold (the default is 5), and the problematic data blocks caused by the mismatch are relatively small location data blocks. If the cell has coverage on a one-way tunnel and the coverage signal appears on the other side of the road, and the number of problematic data blocks exceeds the threshold, this situation is judged as an RRU mismatch with staggered coverage.

[0119] In the above two cases, if the judgment result is no, the process goes to S9 in sequence; if the result is yes, the process jumps to S11.

[0120] S9: Determine whether the initially judged abnormal cell has an RRU radio frequency abnormality.

[0121] If a cell has coverage loss in the middle of the continuous coverage area of ​​a one-way tunnel, and the number of problematic data blocks exceeds a threshold, the problematic data blocks are those in the middle of the coverage loss. This is considered an RRU RF anomaly. If the judgment result is "no," the process proceeds to step S10. If the result is "yes," the process jumps to step S11.

[0122] S10: If the abnormal cell cannot be classified into any of the situations in steps S5 to S9 above, it is judged as other abnormal situations.

[0123] S11: Determine whether all the contents of the QL list have been judged. If not, start the judgment of the next preliminary abnormal cell. If yes, output all the judgment results.

[0124] Figure 10 FIG. 1 shows a schematic diagram of a method for detecting anomalies in a subway area according to another embodiment of the present invention. Figure 10 As shown, the device includes:

[0125] The reference table generating module 101 is adapted to generate a bidirectional reference table for a subway line based on the sweep frequency data of the two running directions of the subway line;

[0126] The bidirectional reference table records the cell identifiers of the coverage cells detected in both directions of travel for each location data block. Each location data block is obtained by dividing the data into preset distances starting from the reference station of the subway line.

[0127] The preliminary judgment module 102 is adapted to determine, for any coverage cell recorded in the bidirectional reference table of the line, that the coverage cell is a preliminarily judged abnormal cell if the number of coverage position data blocks corresponding to the coverage cell in both running directions exceeds a preliminarily judged threshold;

[0128] The abnormality determination module 103 is adapted to determine the coverage of any initially determined abnormal cell according to the bidirectional reference table, and determine the abnormality of the initially determined abnormal cell based on the coverage.

[0129] In an optional manner, the abnormality determination module 103 is further adapted to:

[0130] Determine whether the initially judged abnormal cell meets the first abnormal judgment condition; if so, determine that the initially judged abnormal cell is a platform cell;

[0131] The first abnormal judgment condition includes: the initially judged abnormal cell is located within a preset distance range on both sides of the platform, the coverage position data blocks corresponding to the initially judged abnormal cell in the two running directions are distributed on both sides of the platform, and the number of coverage position data blocks corresponding to the initially judged abnormal cell in the two running directions is less than the first preset threshold.

[0132] In an optional manner, the abnormality determination module 103 is further adapted to:

[0133] Determine whether the initially judged abnormal cell meets the second abnormal judgment condition; if so, determine that the abnormal situation of the initially judged abnormal cell is that the platform area signal has leaked to the outside;

[0134] The second abnormal judgment conditions include: the initially judged abnormal cell is located within a preset distance range on both sides of the platform, the difference in signal strength measured in the two running directions of the initially judged abnormal cell is greater than the signal strength threshold, the corresponding coverage position data blocks in the two running directions are distributed on both sides of the platform, and the number of coverage position data blocks corresponding to the running direction with a larger number of coverage position data blocks is greater than the second preset threshold.

[0135] In an optional manner, the abnormality determination module 103 is further adapted to:

[0136] Determine whether the initially judged abnormal cell meets the third abnormal judgment condition; if so, determine that the abnormal situation of the initially judged abnormal cell is bidirectional shared cell coverage;

[0137] The third abnormality judgment condition includes: the coverage blocks of the initially judged abnormal cell in the two running directions are consistent, and the number of corresponding coverage position data blocks of the initially judged abnormal cell in the two running directions exceeds a third preset threshold.

[0138] In an optional manner, the abnormality determination module 103 is further adapted to:

[0139] Determine whether the initially judged abnormal cell meets the fourth abnormality judgment condition; if so, determine that the abnormal condition of the initially judged abnormal cell is RRU alternating coverage;

[0140] The fourth abnormal judgment condition includes: there is no overlap between the coverage position data blocks corresponding to the two running directions of the initial judgment abnormal cell, and the number of coverage position data blocks corresponding to the running direction with fewer coverage position data blocks exceeds a fourth preset threshold.

[0141] In an optional manner, the abnormality determination module 103 is further adapted to:

[0142] Determine whether the initially judged abnormal cell meets the fifth abnormality judgment condition; if so, determine that the abnormal condition of the initially judged abnormal cell is RRU staggered coverage;

[0143] The fifth abnormal judgment condition includes: initially judging that the coverage position data block corresponding to the abnormal cell in one running direction belongs to the coverage position data block corresponding to another running direction, and the number of coverage position data blocks corresponding to the running direction with fewer coverage position data blocks exceeds the fifth preset threshold.

[0144] In an optional manner, the abnormality determination module 103 is further adapted to:

[0145] Determine whether the initially judged abnormal cell meets the sixth abnormality judgment condition; if so, determine that the abnormality of the initially judged abnormal cell is an RRU radio frequency abnormality;

[0146] The sixth abnormal judgment condition includes: the initial judgment that the abnormal cell is discontinuous between the two corresponding coverage location data blocks in one direction, any coverage location data block contains multiple continuous coverage location data blocks, and the number of location data blocks between the two coverage location data blocks exceeds the sixth preset threshold.

[0147] An embodiment of the present invention provides a non-volatile computer storage medium, wherein the computer storage medium stores at least one executable instruction, and the computer executable instruction can execute the subway cell anomaly detection method in any of the above method embodiments.

[0148] Figure 11 The schematic diagram of the structure of the computing device embodiment of the present invention is shown. The specific embodiment of the present invention does not limit the specific implementation of the computing device.

[0149] like Figure 11 As shown, the computing device may include: a processor, a communication interface, a memory, and a communication bus.

[0150] The processor, communication interface, and memory communicate with each other via a communication bus. The communication interface is used to communicate with other devices, such as clients or other server network elements. The processor is used to execute programs, specifically, to perform the steps described in the aforementioned embodiment of the method for detecting anomalies in a subway cell for a computing device.

[0151] Specifically, the program may include program codes including computer operation instructions.

[0152] The processor may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention. The one or more processors included in the computing device may be processors of the same type, such as one or more CPUs, or processors of different types, such as one or more CPUs and one or more ASICs.

[0153] Memory is used to store programs. The memory may include high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk storage.

[0154] The algorithm or demonstration provided herein are not inherently relevant to any particular computer, virtual system or other equipment. Various general-purpose systems may also be used together with the teachings based on this. According to the above description, it is apparent that the structure required for constructing this type of system. In addition, the embodiment of the present invention is not directed to any specific programming language yet. It should be understood that various programming languages ​​can be utilized to realize the content of the present invention described herein, and the above description of specific languages ​​is for the purpose of disclosing the best mode of the present invention.

[0155] In the description provided herein, numerous specific details are described. However, it is understood that embodiments of the present invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques are not shown in detail so as not to obscure the understanding of this description.

[0156] Similarly, it should be understood that in order to streamline the present invention and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the invention, various features of the embodiments of the invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this disclosed method should not be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the claims below, inventive aspects lie in less than all the features of the individual embodiments disclosed above. Accordingly, the claims that follow the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of the invention.

[0157] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and in addition may be divided into multiple submodules or subunits or subcomponents. All features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed herein may be combined in any combination, except that at least some of such features and / or processes or units are mutually exclusive. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0158] Furthermore, those skilled in the art will appreciate that although some embodiments herein include certain features included in other embodiments but not other features, combinations of features from different embodiments are intended to be within the scope of the present invention and to form different embodiments. For example, in the claims below, any of the claimed embodiments may be used in any combination.

[0159] The various component embodiments of the present invention can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It will be appreciated by those skilled in the art that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all of the functions of some or all of the components according to an embodiment of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., a computer program and a computer program product) for executing a part or all of the methods described herein. Such a program implementing the present invention can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0160] It should be noted that the above embodiments illustrate rather than limit the invention, and that alternative embodiments may be devised by a person skilled in the art without departing from the scope of the appended claims. In the claims, any reference signs placed between brackets should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising several different elements and by means of appropriately programmed computers. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments should not be understood as limiting the order of execution unless otherwise specified.

Claims

1. A method for detecting anomalies in a subway area, comprising: Generate a bidirectional reference table for the subway line based on the frequency sweep data of the two operating directions of the subway line; The bidirectional reference table records the cell identifiers of the coverage cells detected in the two running directions corresponding to each position data block, and each position data block is obtained by dividing the data blocks by a preset distance starting from the reference station of the subway line; For any coverage cell recorded in the bidirectional reference table of the line, if the number of coverage position data blocks corresponding to the coverage cell in the two running directions exceeds the preliminary judgment threshold, the coverage cell is determined to be a preliminarily judged abnormal cell; For any initially determined abnormal cell, determining the coverage of the initially determined abnormal cell according to the line bidirectional reference table, and determining the abnormality of the initially determined abnormal cell based on the coverage; The determining of the abnormality of the initially determined abnormal cell based on the coverage condition further includes: Determine whether the initially judged abnormal cell meets the first abnormal judgment condition; if so, determine that the initially judged abnormal cell is a platform cell; wherein, the first abnormal judgment condition includes: the initially judged abnormal cell is located within a preset distance range on both sides of the platform, the coverage position data blocks corresponding to the initially judged abnormal cell in the two running directions are distributed on both sides of the platform, and the number of coverage position data blocks corresponding to the initially judged abnormal cell in the two running directions is less than a first preset threshold.

2. The method according to claim 1, characterized in that The determining the abnormality of the initially judged abnormal cell based on the coverage condition further includes: Determining whether the initially determined abnormal cell meets a second abnormality determination condition; if so, determining that the abnormality of the initially determined abnormal cell is that a signal leakage occurs in the platform area; The second abnormal judgment condition includes: the initially judged abnormal cell is located within a preset distance range on both sides of the platform, the difference in signal strength measured by the initially judged abnormal cell in the two running directions is greater than the signal strength threshold, the corresponding coverage position data blocks in the two running directions are distributed on both sides of the platform, and the number of coverage position data blocks corresponding to the running direction with a larger number of coverage position data blocks is greater than the second preset threshold.

3. The method according to claim 1, characterized in that The determining the abnormality of the initially judged abnormal cell based on the coverage condition further includes: Determining whether the initially determined abnormal cell meets a third abnormality determination condition; if so, determining that the abnormal condition of the initially determined abnormal cell is bidirectional shared cell coverage; The third abnormality judgment condition includes: the coverage of the initially judged abnormal cell in two running directions is consistent, and the number of coverage position data blocks corresponding to the initially judged abnormal cell in two running directions exceeds a third preset threshold.

4. The method according to claim 1, wherein The determining the abnormality of the initially judged abnormal cell based on the coverage condition further includes: Determining whether the initially determined abnormal cell meets a fourth abnormality determination condition; if so, determining that the abnormality of the initially determined abnormal cell is RRU alternating coverage; The fourth abnormality judgment condition includes: initially judging that there is no overlap between the coverage position data blocks corresponding to the abnormal cell in the two running directions, and the number of coverage position data blocks corresponding to the running direction with fewer coverage position data blocks exceeds a fourth preset threshold.

5. The method according to claim 1, wherein The determining the abnormality of the initially judged abnormal cell based on the coverage condition further includes: Determining whether the initially determined abnormal cell meets a fifth abnormality determination condition; if so, determining that the abnormal condition of the initially determined abnormal cell is RRU staggered coverage; The fifth abnormal judgment condition includes: preliminarily judging that the coverage position data block corresponding to the abnormal cell in one running direction belongs to the coverage position data block corresponding in another running direction, and the number of coverage position data blocks corresponding to the running direction with fewer coverage position data blocks exceeds the fifth preset threshold.

6. The method according to claim 1, characterized in that The determining the abnormality of the initially judged abnormal cell based on the coverage condition further includes: Determining whether the initially determined abnormal cell meets a sixth abnormality determination condition; if so, determining that the abnormality of the initially determined abnormal cell is an RRU radio frequency abnormality; The sixth abnormal judgment condition includes: the initial judgment that the abnormal cell is discontinuous between two corresponding coverage position data blocks in one direction, any coverage position data block contains multiple continuous coverage position data blocks, and the number of position data blocks between the two coverage position data blocks exceeds the sixth preset threshold.

7. An abnormality detection device for a subway area, comprising: A reference table generation module is adapted to generate a bidirectional reference table for a subway line based on the frequency sweep data of the two running directions of the subway line; The bidirectional reference table records the cell identifiers of the coverage cells detected in the two running directions corresponding to each position data block, and each position data block is obtained by dividing the data blocks by a preset distance starting from the reference station of the subway line; a preliminary judgment module adapted to determine, for any coverage cell recorded in the bidirectional reference table of the line, that the coverage cell is a preliminarily judged abnormal cell if the number of coverage position data blocks corresponding to the coverage cell in the two running directions exceeds a preliminary judgment threshold; an abnormality determination module adapted to determine, for any initially determined abnormal cell, the coverage of the initially determined abnormal cell according to the line bidirectional reference table, and determine the abnormality of the initially determined abnormal cell based on the coverage; The abnormality determination module is further adapted to: Determine whether the initially judged abnormal cell meets the first abnormal judgment condition; if so, determine that the initially judged abnormal cell is a platform cell; wherein, the first abnormal judgment condition includes: the initially judged abnormal cell is located within a preset distance range on both sides of the platform, the coverage position data blocks corresponding to the initially judged abnormal cell in the two running directions are distributed on both sides of the platform, and the number of coverage position data blocks corresponding to the initially judged abnormal cell in the two running directions is less than a first preset threshold.

8. A computing device comprising: A processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform operations corresponding to the subway cell anomaly detection method according to any one of claims 1 to 6.

9. A computer storage medium, wherein at least one executable instruction is stored in the storage medium, and wherein the executable instruction enables a processor to execute an operation corresponding to the method for detecting anomalies in a subway cell according to any one of claims 1 to 6.

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