Base station fault detection method and device, electronic equipment and storage medium
By determining the scene type of the base station in the base station and processing the corresponding latitude and longitude data in the base station fault detection, the problem of regional limitations of base station fault group fault detection in the prior art is solved, and a more flexible and efficient detection effect is achieved.
Patent Information
- Application Number
- CN202310967624.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-08-02
- Publication Date
- 2025-02-14
AI Technical Summary
In the prior art, the detection of base station fault group faults needs to be carried out in fixed areas, resulting in greater regional limitations in the detection and poor results.
By determining the scene type and latitude and longitude data of the scene where the base station to be detected, the target processing information corresponding to the scene type is determined, the target processing results are obtained based on the target processing information, and whether a group obstacle occurs is determined based on the results. event.
The flexibility and effect of group failure event detection is improved, so that detection does not have to be limited to fixed areas, and the base station failure event can be detected more accurately.
Smart Images
Figure CN119450533A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the field of communication technology, and in particular to a base station fault detection method, device, electronic device and storage medium. Background Art
[0002] A group failure event of a base station refers to a large-scale loss of base stations or degradation of base station indicators in a certain area or region, which may cause communication failure in the area or region. Therefore, it is necessary to detect the group failure event of the base station.
[0003] In the related art, when detecting a group failure event of a base station, a fixed area (eg, a province, a city, a district, etc.) is usually used as a detection unit to determine whether a group failure event of a base station occurs in the fixed area.
[0004] In this way, the detection effect of group fault events of the base station is not good. Summary of the invention
[0005] The present disclosure proposes a base station fault detection method, device, electronic device, storage medium and computer program product, aiming to solve the technical problems in the related technologies at least to a certain extent.
[0006] The first aspect of the present disclosure proposes a base station fault detection method, including: determining the scene type of the scene in which the base station to be detected is located, and the longitude and latitude data of the base station to be detected; determining target processing information corresponding to the scene type, wherein the target processing information is reference information when processing the longitude and latitude data; processing the longitude and latitude data of the base station to be detected of the corresponding scene type according to the target processing information to obtain a target processing result; and determining whether a group fault event occurs according to the target processing result.
[0007] The second aspect embodiment of the present disclosure proposes a base station fault detection device, including: a first determination module, used to determine the scene type of the scene in which the base station to be detected is located, and the longitude and latitude data of the base station to be detected; a second determination module, used to determine the target processing information corresponding to the scene type, wherein the target processing information is the reference information when processing the longitude and latitude data; a processing module, used to process the longitude and latitude data of the base station to be detected of the corresponding scene type according to the target processing information to obtain a target processing result; and a third determination module, used to determine whether a group fault event occurs according to the target processing result.
[0008] The third aspect of the present disclosure provides an electronic device, comprising: a processor; a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement a base station fault detection method.
[0009] The fourth aspect of the present disclosure provides a computer-readable storage medium. When instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform a base station fault detection method.
[0010] The fifth aspect embodiment of the present disclosure proposes a computer program product, including a computer program, characterized in that the computer program is executed by a processor to perform a base station fault detection method.
[0011] The base station fault detection method, device, electronic device, storage medium and computer program product proposed in this embodiment have at least the following beneficial effects: by determining the scene type of the scene where the base station to be detected is located, and the longitude and latitude data of the base station to be detected, and determining the target processing information corresponding to the scene type, wherein the target processing information is the reference information when processing the longitude and latitude data, and then processing the longitude and latitude data of the base station to be detected of the corresponding scene type according to the target processing information to obtain the target processing result, and determining whether a group fault event occurs according to the target processing result, so that the detection of group fault events does not have to be limited to a fixed area, thereby improving the flexibility of group fault event detection and effectively improving the detection effect of group fault events. Furthermore, it solves the technical problem that the detection of base station fault group faults in the prior art needs to be carried out in a fixed area, resulting in a large geographical limitation of the detection of group fault events.
[0012] Additional aspects and advantages of the present disclosure will be given in part in the following description and in part will be obvious from the following description or learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS
[0013] The above and / or additional aspects and advantages of the present disclosure will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:
[0014] Figure 1 is a flow chart of a base station fault detection method according to the first embodiment of the present disclosure;
[0015] Figure 2 is a flow chart of a base station fault detection method according to the second embodiment of the present disclosure;
[0016] Figure 3 is a flow chart of a base station fault detection method according to the third embodiment of the present disclosure;
[0017] Figure 4 is a block diagram of a base station fault detection device according to the present disclosure;
[0018] Figure 5 A block diagram of an exemplary electronic device suitable for implementing embodiments of the present disclosure is shown. DETAILED DESCRIPTION
[0019] Embodiments of the present disclosure are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present disclosure, and are not to be construed as limitations of the present disclosure. On the contrary, the embodiments of the present disclosure include all changes, modifications, and equivalents that fall within the spirit and connotation of the appended claims.
[0020] It should be noted that the executor of the base station fault detection method of this embodiment may be a base station fault detection device, which may be implemented by software and / or hardware, and which may be configured in an electronic device, which may include but is not limited to a terminal, a server, etc.
[0021] It should be noted that the process of obtaining, storing, using, and processing information in the disclosed technical solution complies with the relevant provisions of national laws and regulations and does not violate public order and good morals.
[0022] The base station fault detection method described in the embodiments of the present disclosure can be used to detect a group of base station fault events. A group of base station fault events refers to events such as large-scale loss of base stations or degradation of base station indicators in a certain area or region.
[0023] Figure 1 is a flow chart of a base station fault detection method according to the first embodiment of the present disclosure, such as Figure 1 As shown, the method includes:
[0024] S101: Determine the scene type of the scene where the base station to be detected is located, and the longitude and latitude data of the base station to be detected.
[0025] The base station to be detected may be a lost base station for which a group failure event detection is to be performed.
[0026] Optionally, in some embodiments, the base station to be detected is determined based on the following method: obtaining first registration information of the initial base station in the network at a first time, and obtaining second registration information of the initial base station in the network at a second time. If the first registration information and the second registration information are different, the initial base station is determined as the base station to be detected.
[0027] In the disclosed embodiment, the registration information of the initial base station may be collected periodically, that is, the registration information of the 4G base station may be collected by logging in (Mobility Management Entity, MME), or the registration information of the 5G base station may be collected by logging in (Access and Mobility Management Function, AMF).
[0028] The registration information of the initial base station collected at the first time is the first registration information, and the registration information of the initial base station collected at the second time is the second registration information. The first time may be the previous cycle collection time of the second time.
[0029] That is to say, in the embodiment of the present disclosure, the first registration information and the second registration information of the initial base station can be periodically collected twice, and it can be determined whether the first registration information and the second registration information are the same. If the first registration information and the second registration information are not the same (that is, the base station identifier of the initial base station is in the first registration information but not in the second registration information), the initial base station is determined as the base station to be detected.
[0030] In the disclosed embodiment, the scene where the base station to be detected is located can be divided into multiple scene types, and the scene type can be specifically, for example, an urban scene type, a suburban scene type, etc., without limitation.
[0031] In the disclosed embodiment, the longitude and latitude coordinates corresponding to the base station to be detected may be referred to as longitude and latitude data.
[0032] In some embodiments, the scene type of the scene in which the base station to be detected is located is determined based on the longitude and latitude data of the base station to be detected, combined with the longitude and latitude data of areas with different scene types. For example, when it is determined that the longitude and latitude data of the base station to be detected belong to the longitude and latitude data range corresponding to the urban scene type, it is determined that the scene type of the scene in which the base station to be detected is an urban scene type. There is no limitation on this.
[0033] S102: Determine target processing information corresponding to the scene type, wherein the target processing information is information referenced when processing longitude and latitude data.
[0034] In the embodiment of the present disclosure, after determining the scene type of the scene in which the base station to be detected is located, target processing information corresponding to the scene type is determined.
[0035] Among them, the target processing information is the information referenced when processing longitude and latitude data, that is, the target processing information can be used to process the longitude and latitude data of the base station to be detected in the scene of the corresponding scene type. The target processing information can be, for example, preset condition information (for example, thresholds) for the longitude and latitude data, rule information, processing means information, etc., and there is no restriction on this.
[0036] That is to say, in the embodiments of the present disclosure, different processing methods and / or target processing information such as processing procedures may be pre-configured for different scene types, and then, the longitude and latitude data of the base station to be detected of the corresponding scene type may be processed based on the target processing information corresponding to the corresponding scene type. For the specific method, please refer to the subsequent embodiments and will not be repeated here.
[0037] In some embodiments, during the historical fault detection process of the base station, the optimal processing means and / or processing rules suitable for each scenario type can be determined, and the aforementioned processing means and / or processing rules suitable for different scenario types can be used as target processing information, without limitation.
[0038] S103: Processing the latitude and longitude data of the base station to be detected of the corresponding scene type according to the target processing information to obtain a target processing result.
[0039] After determining the target processing information corresponding to the scene type, the embodiment of the present disclosure can process the longitude and latitude data of the base station to be detected of the corresponding scene type according to the target processing information to obtain a corresponding processing result, which can be called a target processing result. The target processing result can be, for example, the number of longitude and latitude data contained in a certain area, and there is no limitation on this.
[0040] That is to say, in the embodiments of the present disclosure, the longitude and latitude data of the base station to be detected of the corresponding scene type can be processed based on the pre-configured processing method corresponding to the scene type, and / or processing rules to obtain the target processing result, thereby, the target processing information processing adapted to the corresponding scene type can be determined, so that when the longitude and latitude data of the base station to be detected of the corresponding scene type is processed based on the corresponding target processing information, the processing effect of the longitude and latitude data of the base station to be detected of the corresponding scene type can be effectively improved.
[0041] S104: Determine whether a group fault event occurs based on the target processing result.
[0042] After the embodiment of the present disclosure processes the latitude and longitude data of the base station to be detected of the corresponding scenario type according to the target processing information to obtain the target processing result, it can determine whether a group fault event occurs according to the target processing result.
[0043] In some embodiments, whether a group fault event occurs may be determined based on the target processing result, and corresponding detection conditions may be pre-set. Then, when the target processing result satisfies the pre-set detection conditions, it may be determined that a group fault event occurs.
[0044] For example, the target processing result is the number of longitude and latitude data contained in a certain area. Accordingly, the pre-set detection condition may be a threshold value for the number of longitude and latitude data contained in the area. Then, when the number is greater than or equal to the threshold value, it is determined that a group fault event has occurred, and when the number is less than the threshold value, it is determined that no group fault event has occurred. There is no restriction on this.
[0045] In the disclosed embodiment, by determining the scene type of the scene in which the base station to be detected is located, and the longitude and latitude data of the base station to be detected, and determining the target processing information corresponding to the scene type, wherein the target processing information is the reference information when processing the longitude and latitude data, and then processing the longitude and latitude data of the base station to be detected of the corresponding scene type according to the target processing information to obtain the target processing result, and determining whether a group obstacle event occurs according to the target processing result, so that the detection of group obstacle events does not have to be limited to a fixed area, thereby improving the flexibility of group obstacle event detection and effectively improving the group obstacle event detection effect.
[0046] Figure 2 is a flow chart of a base station fault detection method according to a second embodiment of the present disclosure, such as Figure 2 As shown, the method includes:
[0047] S201: Determine the scene type of the scene where the base station to be detected is located, and the longitude and latitude data of the base station to be detected.
[0048] In some embodiments, before executing the base station fault detection method described in the embodiments of the present disclosure, other group fault event detection methods may be used to determine whether a group fault event occurs, that is, to determine whether there are T lost base stations whose Internet Protocol version 4 / Internet Protocol version 6 addresses are in the same segment. If there are T lost base stations whose Internet Protocol version 4 / Internet Protocol version 6 addresses are in the same segment, it is determined that a base station group fault event occurs. For example, if there are T lost base stations whose Internet Protocol version 4 addresses are in a 24-bit segment or whose Internet Protocol version 6 addresses are in a 112-bit segment, it can be determined that a base station group fault event occurs in the Internet Protocol version 4 / Internet Protocol version 6 address segment.
[0049] S202: Determine the number of target clusters preset for the corresponding scene type, wherein the target cluster is a collection of longitude and latitude data in the scene of the corresponding scene type.
[0050] After determining the scene type of the scene in which the base station to be detected is located and the longitude and latitude data of the base station to be detected, the embodiment of the present disclosure can determine the number of target clusters preset for the corresponding scene type, wherein the target cluster is a collection of longitude and latitude data in the scene of the corresponding scene type.
[0051] That is to say, in the embodiments of the present disclosure, the corresponding target number of clusters may be pre-set for each scene type. For example, for urban scenes and types and mountainous scenes, the number of base stations in the urban scene types is higher than the number of base stations in the suburban scene types. Thus, when clustering the longitude and latitude data of the base stations corresponding to the urban scene types, the number of clusters of the longitude and latitude data obtained by clustering will be higher than the number of clusters of the longitude and latitude data obtained by clustering the longitude and latitude data of the base stations corresponding to the mountainous scene types.
[0052] Therefore, when determining the target number of clusters preset for the corresponding scenario type, the corresponding target number of clusters may be preset according to the number of base stations in different scenario types.
[0053] S203: Determine the target area size of the location area preset for the corresponding scene type.
[0054] The target area size may be a clustering area radius preset when clustering the longitude and latitude data of the base stations to be processed in the scene of the corresponding scene type, and there is no restriction on this.
[0055] That is to say, in the embodiments of the present disclosure, the corresponding clustering neighborhood radius can be pre-set according to the density of base stations in different scenario types, and the aforementioned pre-determined clustering neighborhood radius can be used as the target area size. Then, the subsequent base station fault detection method can be triggered based on the target number of cluster clusters and the target area size. For details, please refer to the subsequent embodiments and will not be repeated here.
[0056] S204: The number of target clusters and the size of the target region are taken together as target processing information.
[0057] After determining the number of target clustering clusters preset for the corresponding scene type and determining the target area size of the location area preset for the corresponding scene type, the embodiment of the present disclosure can use the number of target clustering clusters and the target area size together as target processing information, thereby effectively improving the comprehensiveness and referenceability of the target processing information, and thus when processing the longitude and latitude data of the base station in the scene of the corresponding scene type based on the target processing information, it is possible to effectively improve the processing effect of the longitude and latitude data.
[0058] S205: Clustering the longitude and latitude data according to the number of target clusters and the size of the target area to obtain at least one cluster, and taking the at least one cluster as the target processing result.
[0059] Among them, clusters refer to the collections formed by grouping adjacent longitude and latitude data. That is, in cluster analysis, the algorithm divides longitude and latitude data into different clusters based on the similarity measure between data points. The longitude and latitude data within each cluster are more similar to each other, while the data points between different clusters are quite different.
[0060] After determining the number of target clusters preset for the corresponding scene type and determining the target area size of the location area preset for the corresponding scene type, the embodiment of the present disclosure can cluster the longitude and latitude data according to the number of target clusters and the target area size, that is, the density clustering algorithm (Density-Based Spatial Clustering of Applications with Noise, DBSCAN) can be used to cluster the longitude and latitude data in combination with the number of target clusters and the target area size to obtain at least one cluster, and use the at least one cluster as the target processing result.
[0061] When clustering the longitude and latitude data according to the target number of clusters and the target area size, the embodiment of the present disclosure can cluster the longitude and latitude data according to the target number of clusters and the target area size based on different clustering algorithms, and then use the clustering algorithm evaluation indicators Calinski-Harabaz index (CH), Davies-Bouldin index (DBI), and Silhouette Coefficient (SC) for comprehensive scoring, select the clustering algorithm with the best clustering effect, and realize clustering the longitude and latitude data according to the target number of clusters and the target area size to obtain at least one cluster, and use at least one cluster as the target processing result, thereby ensuring the best clustering effect.
[0062] S206: Determine whether a group fault event occurs based on the target processing result.
[0063] The specific description of S206 can be found in the above embodiment, which will not be repeated here.
[0064] In the embodiment of the present disclosure, by determining the scene type of the scene in which the base station to be detected is located, and the longitude and latitude data of the base station to be detected, and determining the number of target clusters preset for the corresponding scene type, and then determining the target area size of the location area preset for the corresponding scene type, the number of target clusters and the target area size are used together as target processing information, thereby effectively improving the comprehensiveness and referenceability of the target processing information, so that when the longitude and latitude data of the base station in the scene of the corresponding scene type is processed based on the target processing information, the processing effect of the longitude and latitude data can be effectively improved, and according to the number of target clusters and the target area The latitude and longitude data are clustered according to the size of the target clusters to obtain at least one cluster, and at least one cluster is used as the target processing result. Since the latitude and longitude data are clustered according to the number of target clusters and the size of the target area, the adjacent longitude and latitude data can be divided into a cluster, so that the area range where the group fault event occurs can be determined, and whether the group fault event occurs can be determined according to the target processing result. The cluster can detect the group fault event more quickly. Compared with the traditional one-by-one detection method, which requires checking the status of base stations one by one, the cluster can process the longitude and latitude data corresponding to multiple adjacent or similar base stations together. Once the cluster shows an abnormality, the possible group fault event can be discovered and identified more quickly, thereby effectively improving the detection efficiency of the group fault event.
[0065] Figure 3 is a flow chart of a base station fault detection method according to the third embodiment of the present disclosure, such as Figure 3 As shown, the method includes:
[0066] S301: Determine the scene type of the scene in which the base station to be detected is located.
[0067] Optionally, in some embodiments, determining the scene type of the scene in which the base station to be detected is located may be to determine the base station density in the scene in which the base station to be detected is located, and when the base station density is less than or equal to a first density threshold, determining that the scene type is the first scene type; when the base station density is greater than the first density threshold and less than or equal to a second density threshold, determining that the scene type is the second scene type; and when the base station density is greater than the second density threshold, determining that the scene type is the third scene type, wherein the first scene type, the second scene type, and the third scene type are different from each other.
[0068] The second density threshold is greater than the first density threshold.
[0069] The density of base stations in the scene where the base station to be detected is located is the base station density.
[0070] Among them, the first scene type, the second scene type, and the third scene type are different from each other. The first scene type can be, for example, a mountain scene type, the second scene type can be, for example, a suburban scene type, and the third scene type can be, for example, an urban scene type. There is no limitation on this.
[0071] That is to say, in the embodiments of the present disclosure, the first density threshold and the second density threshold may be set in advance, and then, the number of base stations per unit area in the scene where the base station to be detected is located may be determined as the base station density, and then, the density may be compared with the first density threshold and the second density threshold, and when the base station density is less than or equal to the first density threshold, the scene type is determined to be the first scene type, when the base station density is greater than the first density threshold and less than or equal to the second density threshold, the scene type is determined to be the second scene type, and when the base station density is greater than the second density threshold, the scene type is determined to be the third scene type. Thus, the base station density, the first density threshold and the second density threshold may be combined to accurately determine the scene type of the scene where the base station is located.
[0072] S302: Determine the longitude and latitude data of the base station to be detected.
[0073] The specific description of S302 can be found in the above embodiment, which will not be repeated here.
[0074] S303: Determine the number of target clusters preset for the corresponding scene type, wherein the target cluster is a collection of longitude and latitude data in the scene of the corresponding scene type.
[0075] Optionally, in some embodiments, the target number of clustering clusters preset for the corresponding scene type is determined by, when the scene type is a first scene type, using the first number of clustering clusters as the target number of clustering clusters, when the scene type is a second scene type, using the second number of clustering clusters as the target number of clustering clusters, wherein the second number of clustering clusters is greater than the first number of clustering clusters, and when the scene type is a third scene type, using the third number of clustering clusters as the target number of clustering clusters, wherein the third number of clustering clusters is greater than the second number of clustering clusters. Thus, the corresponding target number of clustering clusters can be matched for different scene types.
[0076] It can be understood that for the third scenario type, since the density of base stations in the scenario type is higher, for the first scenario type, the density of base stations in the scenario type is lower.
[0077] Thus, in an embodiment of the present disclosure, when the scene type is a first scene type, the first number of clusters is used as the target number of clusters, and when the scene type is a second scene type, the second number of clusters is used as the target number of clusters, wherein the second number of clusters is greater than the first number of clusters, and when the scene type is a third scene type, the third number of clusters is used as the target number of clusters.
[0078] S304: Determine the target area size of the location area preset for the corresponding scene type.
[0079] Optionally, in some embodiments, the target area size of the preset position area for the corresponding scene type is determined by, when the scene type is a first scene type, determining the target area size to be a first area size, and when the scene type is a second scene type, determining the target area size to be a second area size, wherein the second area size is smaller than the first area size, and when the scene type is a third scene type, determining the target area size to be a third area size, wherein the third area size is smaller than the second area size. Thus, appropriate target area sizes can be matched for different scene types.
[0080] That is to say, in the embodiments of the present disclosure, when the scene type is the first scene type, the target area size is determined to be the first area size, and when the scene type is the second scene type, the target area size is determined to be the second area size, wherein the second area size is smaller than the first area size, and when the scene type is the third scene type, the target area size is determined to be the third area size, wherein the third area size is smaller than the second area size.
[0081] S305: The number of target clusters and the size of the target region are taken as target processing information.
[0082] S306: Clustering the longitude and latitude data according to the number of target clusters and the size of the target area to obtain at least one cluster, and taking the at least one cluster as the target processing result.
[0083] The specific description of S305 - S306 can be found in the above embodiment, which will not be repeated here.
[0084] S307: Determine the number of longitude and latitude data in the cluster.
[0085] After clustering the longitude and latitude data according to the target cluster number and the target area size to obtain at least one cluster, the embodiment of the present disclosure may count the number of longitude and latitude data in the cluster to obtain the number of longitude and latitude data in the cluster.
[0086] S308: Obtain a threshold value for the number of longitude and latitude data in a cluster of the scene type.
[0087] In the implementation of the present disclosure, a corresponding quantity threshold may be pre-set for the longitude and latitude data in the cluster of each scene type.
[0088] For example, for the third scene type, since the density of base stations in the scene of this scene type is relatively high, a higher quantity threshold can be pre-set for the longitude and latitude data in the clustering cluster of this scene type. For the first scene type, since the density of base stations in the scene of this scene type is relatively low, a lower quantity threshold can be pre-set for the longitude and latitude data in the clustering cluster of this scene type. There is no restriction on this.
[0089] S309: Determine whether a group fault event occurs based on the quantity and the quantity threshold.
[0090] After obtaining the quantity threshold of the longitude and latitude data in the cluster of the scene type, the embodiment of the present disclosure can compare the quantity with the preset quantity threshold to obtain a corresponding comparison result, and then, can determine whether a group fault event occurs in combination with the comparison result.
[0091] Optionally, in some embodiments, whether a group failure event occurs is determined based on the quantity and the quantity threshold. When the quantity is greater than or equal to the quantity threshold, it is determined that a group failure event occurs, and when the quantity is less than the quantity threshold, it is determined that no group failure event occurs. Thus, the quantity threshold can be combined to accurately determine whether a group failure event occurs, thereby effectively improving the detection effect of group failure events.
[0092] After determining that a group fault event has occurred, the disclosed embodiment can randomly select M base stations from the group fault base stations for tracking, and determine the faulty node based on the results returned by each node on the target base station path. If the return results of more than or equal to X% of the base stations show that node P is abnormal, it is determined that node P is in a faulty state, that is, you can log in to the MME / AMF, use the IP address of the base station as the destination address, initiate a trace command, and determine the base station faulty node based on the returned result analysis.
[0093] In the embodiment of the present disclosure, by determining the scene type of the scene in which the base station to be detected is located, the scene type of the scene in which the base station is located can be accurately determined by combining the base station density and the first density threshold and the second density threshold, and the longitude and latitude data of the base station to be detected can be determined, and then the number of target clustering clusters preset for the corresponding scene type can be determined, wherein the target clustering cluster is a collection of longitude and latitude data in the scene of the corresponding scene type, and the target area size of the location area preset for the corresponding scene type is determined, and then the number of target clustering clusters and the target area size are used together as target processing information, and the longitude and latitude data are clustered according to the number of target clustering clusters and the target area size to obtain at least one clustering cluster, and at least one clustering cluster is used as the target processing result, and then the number of longitude and latitude data in the clustering cluster is determined, and then the number threshold of the longitude and latitude data in the clustering cluster of the scene type is obtained, and according to the number and the number threshold, it is determined whether a group obstacle event occurs, thereby, it is possible to accurately determine whether a group obstacle event occurs in combination with the number threshold, thereby effectively improving the detection effect of the group obstacle event.
[0094] Figure 4 is a block diagram of a base station fault detection device according to the present disclosure, such as Figure 4 As shown, the base station fault detection device 40 includes:
[0095] The first determination module 401 is used to determine the scene type of the scene where the base station to be detected is located, and the longitude and latitude data of the base station to be detected;
[0096] A second determination module 402 is used to determine target processing information corresponding to the scene type, wherein the target processing information is reference information when processing longitude and latitude data;
[0097] The processing module 403 is used to process the latitude and longitude data of the base station to be detected of the corresponding scene type according to the target processing information to obtain a target processing result; and
[0098] The third determination module 404 is used to determine whether a group fault event occurs according to the target processing result.
[0099] In some embodiments of the present disclosure, the second determining module 402 is further configured to:
[0100] Determine the number of target clusters preset for the corresponding scene type, wherein the target cluster is a collection of longitude and latitude data in the scene of the corresponding scene type;
[0101] Determine the target area size of the preset location area for the corresponding scene type;
[0102] The number of target clusters and the size of the target region are taken together as target processing information.
[0103] In some embodiments of the present disclosure, the processing module 403 is further configured to:
[0104] The longitude and latitude data are clustered according to the number of target clusters and the size of the target area to obtain at least one cluster, and the at least one cluster is used as the target processing result.
[0105] In some embodiments of the present disclosure, the first determining module 401 is further configured to:
[0106] Determine the base station density in the scene where the base station to be detected is located;
[0107] If the base station density is less than or equal to the first density threshold, determining that the scene type is the first scene type;
[0108] If the base station density is greater than a first density threshold and less than or equal to a second density threshold, determining that the scenario type is a second scenario type, wherein the second density threshold is greater than the first density threshold;
[0109] If the base station density is greater than the second density threshold, it is determined that the scene type is a third scene type, wherein the first scene type, the second scene type, and the third scene type are different from each other.
[0110] In some embodiments of the present disclosure, it is characterized in that,
[0111] The first scene type, the second scene type, and the third scene type correspond to different numbers of target clusters;
[0112] The first scene type, the second scene type, and the third scene type correspond to different target area sizes respectively.
[0113] In some embodiments of the present disclosure, the second determining module 402 is further configured to:
[0114] If the scene type is the first scene type, the first cluster number is used as the target cluster number;
[0115] If the scene type is the second scene type, the second number of clusters is used as the target number of clusters, wherein the second number of clusters is greater than the first number of clusters;
[0116] If the scene type is the third scene type, the third number of clusters is used as the target number of clusters, wherein the third number of clusters is greater than the second number of clusters.
[0117] In some embodiments of the present disclosure, the second determining module 402 is further configured to:
[0118] If the scene type is the first scene type, determining the target region size is the first region size;
[0119] If the scene type is a second scene type, determining that the target region size is a second region size, wherein the second region size is smaller than the first region size;
[0120] If the scene type is the third scene type, the target region size is determined to be a third region size, wherein the third region size is smaller than the second region size.
[0121] In some embodiments of the present disclosure, the target processing result includes: a plurality of clusters;
[0122] The third determining module 404 is further configured to:
[0123] Determine the number of longitude and latitude data in the cluster;
[0124] Get the threshold of the number of longitude and latitude data in the clusters corresponding to the scene type;
[0125] Determine whether a group failure event occurs based on the quantity and quantity threshold.
[0126] In some embodiments of the present disclosure, the third determining module 404 is further configured to:
[0127] If the number is greater than or equal to the number threshold, it is determined that a group failure event occurs;
[0128] If the number is less than the number threshold, it is determined that no group failure event occurs.
[0129] In some embodiments of the present disclosure, it is characterized in that the base station to be detected is determined based on the following method:
[0130] Acquire first registration information of the initial base station in the network at a first time, and acquire second registration information of the initial base station in the network at a second time;
[0131] If the first registration information and the second registration information are not the same, the initial base station is determined as the base station to be detected.
[0132] In this embodiment, by determining the scene type of the scene in which the base station to be detected is located, and the longitude and latitude data of the base station to be detected, and determining the target processing information corresponding to the scene type, wherein the target processing information is the reference information when processing the longitude and latitude data, and then processing the longitude and latitude data of the base station to be detected of the corresponding scene type according to the target processing information to obtain the target processing result, and determining whether a group obstacle event occurs according to the target processing result, so that the detection of group obstacle events does not have to be limited to a fixed area, thereby improving the flexibility of group obstacle event detection and effectively improving the group obstacle event detection effect.
[0133] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a computer-readable storage medium, and a computer program product.
[0134] Figure 5 A block diagram of an exemplary electronic device suitable for implementing embodiments of the present disclosure is shown.
[0135] Figure 5 The electronic device 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.
[0136] like Figure 5 As shown, the electronic device 12 is in the form of a general purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a memory 28, and a bus 18 that connects various system components (including the memory 28 and the processing unit 16).
[0137] The bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor or a local bus using any of a variety of bus structures. For example, these architectures include but are not limited to Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus and Peripheral Component Interconnection (PCI) bus.
[0138] The electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 12, including volatile and non-volatile media, removable and non-removable media.
[0139] The memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 5 Not shown, often called a "hard drive").
[0140] although Figure 5 Not shown in the figure, a disk drive for reading and writing a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing a removable non-volatile optical disk (e.g., a compact disc read only memory (hereinafter referred to as: CD-ROM), a digital versatile disc read only memory (hereinafter referred to as: DVD-ROM) or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present disclosure.
[0141] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in the memory 28, such program modules 42 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 42 generally perform the functions and / or methods of the embodiments described in the present disclosure.
[0142] The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), may also communicate with one or more devices that enable the human body to interact with the electronic device 12, and / or communicate with any device that enables the electronic device 12 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed through an input / output (I / O) interface 22. In addition, the electronic device 12 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 through a bus 18. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.
[0143] The processing unit 16 executes various functional applications and parameter information determination by running the program stored in the memory 28, such as implementing the business data storage method mentioned in the above embodiment, or implementing the business data acquisition method mentioned in the above embodiment.
[0144] It should be noted that, in the description of the present disclosure, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present disclosure, unless otherwise specified, the meaning of "plurality" is two or more.
[0145] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present disclosure includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present disclosure belong.
[0146] It should be understood that the various parts of the present disclosure can be implemented in hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.
[0147] A person of ordinary skill in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.
[0148] In addition, each functional unit in each embodiment of the present disclosure may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.
[0149] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.
[0150] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.
[0151] Although the embodiments of the present disclosure have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present disclosure. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present disclosure.
Claims
1. A base station fault detection method, characterized in that: The method comprises: Determine the scene type of the scene in which the base station to be detected is located, and the latitude and longitude data of the base station to be detected; Determining target processing information corresponding to the scene type, wherein the target processing information is information referenced when processing the latitude and longitude data; Processing the latitude and longitude data of the base station to be detected corresponding to the scene type according to the target processing information to obtain a target processing result; and Determine whether a group fault event occurs based on the target processing result.
2. The method according to claim 1, characterized in that The determining of the target processing information corresponding to each of the scene types includes: Determine the number of target clusters preset for the corresponding scene type, wherein the target cluster is a set of the latitude and longitude data in the scene corresponding to the scene type; Determining a target area size for a preset location area corresponding to the scene type; The target cluster number and the target region size are used together as the target processing information.
3. The method according to claim 2, characterized in that The step of processing the latitude and longitude data of the base station to be detected corresponding to the scene type according to the target processing information to obtain a target processing result includes: The longitude and latitude data are clustered according to the number of target clusters and the size of the target area to obtain at least one cluster, and the at least one cluster is used as the target processing result.
4. The method according to claim 2, characterized in that The determining the scene type of the scene in which the base station to be detected is located includes: Determining the base station density in the scene where the base station to be detected is located; If the base station density is less than or equal to a first density threshold, determining that the scene type is a first scene type; If the base station density is greater than the first density threshold and less than or equal to a second density threshold, determining that the scenario type is a second scenario type, wherein the second density threshold is greater than the first density threshold; If the base station density is greater than the second density threshold, it is determined that the scene type is a third scene type, wherein the first scene type, the second scene type, and the third scene type are different from each other.
5. The method according to claim 4, characterized in that in, The first scene type, the second scene type, and the third scene type respectively correspond to different numbers of target clusters; The first scene type, the second scene type, and the third scene type correspond to different target area sizes respectively.
6. The method according to claim 5, characterized in that The determining of the number of target clusters preset for the corresponding scene type includes: If the scene type is the first scene type, taking the first number of clusters as the target number of clusters; If the scene type is the second scene type, taking a second number of clusters as the target number of clusters, wherein the second number of clusters is greater than the first number of clusters; If the scene type is the third scene type, a third number of clusters is used as the target number of clusters, wherein the third number of clusters is greater than the second number of clusters.
7. The method according to claim 5, characterized in that The determining of the target area size of the preset location area corresponding to the scene type includes: If the scene type is the first scene type, determining that the target area size is a first area size; If the scene type is the second scene type, determining that the target region size is a second region size, wherein the second region size is smaller than the first region size; If the scene type is the third scene type, determining that the target region size is a third region size, wherein the third region size is smaller than the second region size.
8. The method according to claim 3, characterized in that The target processing results include: multiple clusters; Wherein, determining whether a group fault event occurs according to the plurality of target processing results includes: Determine the number of the longitude and latitude data in the cluster; Obtaining a threshold value of the number of the longitude and latitude data in the cluster of the scene type; It is determined whether the group fault event occurs according to the quantity and the quantity threshold.
9. The method according to claim 8, characterized in that The determining whether the group fault event occurs according to the quantity and the quantity threshold includes: If the number is greater than or equal to the number threshold, determining that the group fault event occurs; If the number is less than the number threshold, it is determined that the group failure event has not occurred.
10. The method according to any one of claims 1 to 9, characterized in that: The base station to be detected is determined based on the following method: Acquire first registration information of an initial base station in a network at a first time, and acquire second registration information of the initial base station in the network at a second time; If the first registration information and the second registration information are different, the initial base station is determined as the base station to be detected.
11. A base station fault detection device, characterized in that: The device comprises: A first determination module, used to determine the scene type of the scene in which the base station to be detected is located, and the latitude and longitude data of the base station to be detected; A second determination module is used to determine target processing information corresponding to the scene type, wherein the target processing information is reference information when processing the latitude and longitude data; a processing module, configured to process the latitude and longitude data of the base station to be detected corresponding to the scene type according to the target processing information to obtain a target processing result; and The third determination module is used to determine whether a group fault event occurs according to the target processing result.
12. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the method according to any one of claims 1 to 10.
13. A computer-readable storage medium, when instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the method according to any one of claims 1 to 10.