Access network maintenance method, access network maintenance device and electronic equipment

Abstract

The present disclosure relates to the technical field of network maintenance, and provides a maintenance method for an access network, a maintenance device for an access network, and an electronic device. The method includes: obtaining work order data and network management data, as well as obtaining maintenance action execution data, to obtain network operation data; using an electronic map to grid the access network resource data, and obtaining target resource data associated with the network operation data; combining the above network operation data and the above target resource data to obtain a data wide table; performing group fault analysis and severe fault analysis based on the above data wide table to maintain the above access network. The present technical solution can play the role of actively maintaining the access network, which is beneficial to improving customer service perception and improving maintenance efficiency.

Description

Technical Field

[0001] The present disclosure relates to the technical field of network maintenance, and in particular, to a maintenance method for an access network, a maintenance device for an access network, and a computer-readable storage and electronic device for implementing the method. Background Art

[0002] The access network refers to all the equipment between the backbone network and the user terminal. Its length is generally several hundred meters to several kilometers, so it is vividly called the "last mile". Since the backbone network generally adopts optical fiber structure and has a fast transmission speed, the access network has become the bottleneck of the entire network system. At the same time, the maintenance of the access network is also an important guarantee to ensure the user experience.

[0003] The traditional maintenance method is on-site maintenance of the access network, and in the traditional maintenance method, emergency repairs are generally carried out after an accident occurs. In other words, the traditional maintenance method has the problem of replacing maintenance with emergency repairs, and the proactive maintenance capability is poor.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure. Summary of the invention

[0005] The purpose of the present disclosure is to provide an access network maintenance method, an access network maintenance device, and a computer-readable storage and electronic device for implementing the above method, thereby at least to a certain extent playing the role of actively maintaining the access network, which is beneficial to improving customer service perception and improving maintenance efficiency.

[0006] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by the practice of the present disclosure.

[0007] According to one aspect of the present disclosure, there is provided a maintenance method for an access network, comprising: obtaining work order data and network management data, as well as maintenance action execution data, to obtain network operation data; gridding the access network resource data using an electronic map, and obtaining target resource data associated with the network operation data; combining the above network operation data and the above target resource data to obtain a data wide table; performing group fault analysis and severe fault analysis based on the above data wide table to maintain the above access network.

[0008] In some embodiments of the present disclosure, based on the above-mentioned solution, the above-mentioned obtaining of work order data includes: obtaining fault work orders, pre-work orders, complaint work orders and hidden danger work orders to obtain the above-mentioned work order data;

[0009] The above-mentioned acquisition of network management data includes: acquiring one or more of the following equipment information: network management alarm information and performance data of access equipment, network management alarm information and performance data of wireless networks, and network management alarm information of power environment professionals, to obtain the above-mentioned network management data; the above-mentioned acquisition of maintenance action execution data includes: acquiring positioning information, on-site photos and resource audit results of the following scenarios to realize the collection of on-site maintenance action information, and obtain the above-mentioned maintenance action execution data, wherein the above-mentioned scenarios include: one or more of fault handling scenarios, daily inspection scenarios, service activation scenarios, network cutover scenarios, new equipment network access scenarios and network delisting work order scenarios; the above-mentioned maintenance action execution data includes one or more of the following information: positioning information, photo information and artificial intelligence recognition data.

[0010] In some embodiments of the present disclosure, based on the aforementioned scheme, after the above-mentioned network operation data and the above-mentioned target resource data are combined to obtain a wide data table, the above-mentioned method also includes: sending the information of the above-mentioned wide data table to different maintenance teams; collecting the original information of the maintenance work corresponding to each maintenance team, and establishing a data model based on the above-mentioned original information, so as to perform group fault analysis and serious fault analysis through the output of the above-mentioned data model.

[0011] In some embodiments of the present disclosure, based on the aforementioned scheme, the above-mentioned group fault analysis and severe fault analysis based on the above-mentioned data wide table may be performed on one or more of the following information: group fault analysis and severe fault analysis on optical cables based on the above-mentioned data wide table; group fault analysis and severe fault analysis based on the above-mentioned data wide table and customer perception; group fault analysis and severe fault analysis on battery performance based on the above-mentioned data wide table; group fault analysis and severe fault analysis on access devices and wireless devices based on the above-mentioned data wide table.

[0012] In some embodiments of the present disclosure, based on the aforementioned scheme, in the case of group fault analysis and severe fault analysis of optical cables based on the above-mentioned data wide table, the above-mentioned group fault analysis and severe fault analysis based on the above-mentioned data wide table include: obtaining fault work orders related to optical cables in the above-mentioned work order type data; determining the first optical cable fault according to the above-mentioned fault work orders related to the optical cables and the network management alarm information in the above-mentioned network management type data; matching the above-mentioned first optical cable fault with the resource data related to the optical cable to determine the faulty optical cable section; collecting on-site emergency repair photos of the above-mentioned target management section, performing AI recognition based on the above-mentioned on-site emergency repair photos, locating the longitude and latitude of the fault point, and collecting material consumption to perform repeated fault analysis on the optical cable.

[0013] In some embodiments of the present disclosure, based on the aforementioned scheme, in the case of group fault analysis and serious fault analysis based on the aforementioned data broadband table and customer perception, the above-mentioned group fault analysis and serious fault analysis based on the above-mentioned data broadband table include: obtaining the user's complaint work order in the above-mentioned work order type data; determining the second optical cable fault according to the above-mentioned complaint work order and the network management alarm information in the above-mentioned network management type data; analyzing the above-mentioned second network management alarm information, and combining the above-mentioned second optical cable fault and resource data related to the optical cable to determine the business scope affected by the above-mentioned second optical cable failure, the above-mentioned business scope includes one or more of the following obligations: broadband business, iTV business, voice and government business; predicting the average household service unavailability duration of the target team according to the above-mentioned business scope and the interruption time in the above-mentioned complaint work order.

[0014] In some embodiments of the present disclosure, based on the aforementioned scheme, in the case of group fault analysis and serious fault analysis of battery performance based on the aforementioned data wide table, the above-mentioned group fault analysis and serious fault analysis based on the above-mentioned data wide table include: obtaining fault work orders related to the battery in the above-mentioned work order type data; determining the battery fault according to the above-mentioned fault work orders related to the battery and the network management alarm information in the above-mentioned network management type data; making an intelligent judgment on the power outage cause of related equipment according to the above-mentioned network management alarm information and power generation information, and giving corresponding processing procedures according to battery failure, untimely power generation failure, power supply equipment failure, and power supply air conditioning failure; determining the battery dischargeable time based on the battery discharge time, fault duration, and power off time of each professional network equipment.

[0015] In some embodiments of the present disclosure, based on the aforementioned scheme, in the case of group fault analysis and serious fault analysis of access devices and wireless devices based on the above-mentioned data wide table, the above-mentioned group fault analysis and serious fault analysis based on the above-mentioned data wide table include: obtaining network management alarm information related to the access devices and wireless devices, and determining the fault work orders related to the access devices and wireless devices based on the above-mentioned network management alarm information and resource data related to the access devices and wireless devices; locating the cause of the fault and taking repair measures based on the fault work orders related to the access devices and wireless devices, and verifying the above-mentioned cause of the obstacle.

[0016] According to one aspect of the present disclosure, a maintenance device for an access network is provided, including: an acquisition module, a grid processing module, a combination module, and an analysis module.

[0017] Among them, the above-mentioned acquisition module is configured to: acquire work order type data and network management type data, as well as acquire maintenance action execution data, to obtain network operation data; the grid processing module is configured to: use electronic maps to perform grid processing on access network resource data, and acquire target resource data associated with the network operation data; the above-mentioned combination module is configured to: combine the above-mentioned network operation data and the above-mentioned target resource data to obtain a data wide table; and the above-mentioned analysis module is configured to: perform group fault analysis and severe fault analysis based on the above-mentioned data wide table to maintain the above-mentioned access network.

[0018] According to one aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the access network maintenance method described in the first aspect is implemented.

[0019] According to one aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the access network maintenance method described in the first aspect above by executing the executable instructions.

[0020] According to one aspect of the present disclosure, a computer program product or a computer program is provided, the computer program product or the computer program including computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the access network maintenance method provided in each of the above embodiments.

[0021] It can be seen from the above technical solutions that the access network maintenance method, access network maintenance device, computer-readable storage medium and electronic device in the exemplary embodiments of the present disclosure have at least the following advantages and positive effects:

[0022] In the technical solutions provided by some embodiments of the present disclosure, on the one hand, the standard actions of access network field maintenance personnel are solidified based on Internet technology means to realize the collection of network operation data, which is conducive to the implementation of key standard actions of access network maintenance personnel, and the real-time verification of maintenance materials one by one with the inventory system is realized, which is also conducive to the precise management of workload and material consumption. On the other hand, the access network resource data is gridded using electronic maps to enhance the management of the access network maintenance responsibility system. Then the target resource data associated with the above network operation data is obtained. Further, work order data, network management data, comprehensive maintenance action execution status and operation data based on AI (Artificial Intelligence, artificial intelligence) recognition are gathered, and a wide table is formed in combination with the above target resource data. At the same time, maintenance guidance and solutions are provided to field maintenance personnel through closed-loop processes and data analysis, which can accurately locate the work of actively maintaining the access network and actively promote key work, thereby promoting active maintenance of the access network and improving the maintenance efficiency and effectiveness of the access network.

[0023] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0025] In the attached picture:

[0026] Figure 1 A schematic diagram showing an exemplary system architecture to which the technical solution of the embodiments of the present disclosure can be applied.

[0027] Figure 2 A schematic flow chart of a method for maintaining an access network in an exemplary embodiment of the present disclosure is shown.

[0028] Figure 3 A schematic diagram showing a terminal interface for acquiring on-site photos in an exemplary embodiment of the present disclosure.

[0029] Figure 4 A schematic diagram of a terminal interface for intelligently identifying on-site photos in an exemplary embodiment of the present disclosure is shown.

[0030] Figure 5 A schematic flow chart showing a method for maintaining an access network in another exemplary embodiment of the present disclosure is shown.

[0031] Figure 6 A schematic diagram showing group fault analysis and severe fault analysis of an optical cable based on a data wide table in an exemplary embodiment of the present disclosure is shown.

[0032] Figure 7 A schematic diagram of group fault analysis and severe fault analysis based on a wide data table and customer perception in an exemplary embodiment of the present disclosure is shown.

[0033] Figure 8 A schematic diagram showing group fault analysis and severe fault analysis of battery performance based on a wide data table in another exemplary embodiment of the present disclosure is shown.

[0034] Fig. 9 A schematic diagram of group fault analysis and severe fault analysis of access devices and wireless devices based on a data wide table in an exemplary embodiment of the present disclosure is shown.

[0035] Fig.10 A schematic flow chart showing a method for maintaining an access network in yet another exemplary embodiment of the present disclosure is shown.

[0036] Fig.11 A schematic diagram of the structure of a maintenance device for an access network in an exemplary embodiment of the present disclosure is shown.

[0037] Fig.12 A schematic structural diagram of an electronic device in an exemplary embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0038] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be more comprehensive and complete and will fully convey the concept of the example embodiments to those skilled in the art.

[0039] In addition, the described features, structures or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known methods, devices, implementations or operations are not shown or described in detail to avoid blurring the various aspects of the present disclosure.

[0040] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0041] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0042] With the adjustment of access network maintenance mode, remote maintenance concentration and access layer network on-site integrated maintenance are gradually realized. Regarding the traditional access network on-site integrated maintenance issues:

[0043] The integrated access network on-site maintenance can significantly reduce the number of maintenance personnel and improve labor productivity. However, the traditional maintenance management method is still extensive management. The number and quality of maintenance personnel working outside the site cannot be known on-site. Maintenance work is carried out spontaneously by the grassroots, resulting in maintenance work focusing only on emergency repairs of obstacles. It is impossible to obtain accurate data on network quality and customer perception. Even if it is known through obstacles and customer complaints that the network quality in a certain district or county is poor, it is impossible to grasp the hidden danger area and the specific situation of the hidden danger. Therefore, the current traditional maintenance management methods are no longer suitable for on-site integrated maintenance, which is mainly reflected in the following:

[0044] (1) The problem of replacing maintenance with emergency repair is prominent, and the proactive maintenance capability is insufficient;

[0045] (2) Network quality issues such as group or severe network failures seriously affect customer perception;

[0046] (3) High cost and low network operation efficiency;

[0047] (4) It is impossible to obtain the details of network operation status in a timely manner, making it difficult to carry out accurate special rectification.

[0048] This technical solution is proposed to solve the difficulties faced by on-site integrated maintenance, improve the practical operation capabilities of employees, grasp the real-time operation risks of the network, implement proactive network maintenance, enhance customer business perception, and improve maintenance efficiency.

[0049] The solution provided in the embodiments of the present application will be specifically described by the following embodiments:

[0050] Figure 1 A schematic diagram of a system architecture of an exemplary application environment of a maintenance solution for an access network to which the embodiments of the present disclosure can be applied is shown.

[0051] like Figure 1 As shown, the system architecture 100 may include a terminal 110 , a network 120 , and a server 130 . The terminal 110 and the server 130 are connected via the network 120 .

[0052] Specifically, the terminal 110 can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, etc., but is not limited to this. In the embodiment provided by the present technical solution, the network operation data can be obtained through the terminal 110, and then sent to the server 130 through the network 120. The access network resource data is also gridded using an electronic map through the service network 130, and the target resource data associated with the network operation data is obtained. Then, based on the server 130, the network operation data and the above-mentioned target resource data are combined to obtain a data wide table; and, based on the data wide table, group fault analysis and heavy fault analysis are performed to maintain the access network. Those skilled in the art can know that the number of the above-mentioned terminals 110 can be more or less. For example, the above-mentioned terminal can be only one, or the above-mentioned terminal can be dozens or hundreds, or more. The embodiment of the present application does not limit the number of terminals and device types.

[0053] The network 120 may be a communication medium of various connection types that can provide a communication link between the terminal 110 and the server 130, such as a wired communication link, a wireless communication link, or an optical fiber cable, etc., which is not limited in this application. The server 130 is used to execute the maintenance solution of the access network provided in the present disclosure. It may be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, and big data and artificial intelligence platforms. It can be known to those skilled in the art that the number of the above-mentioned servers 130 may be more or less. The embodiment of the present application does not limit the number and device type of the server.

[0054] Based on the system architecture of the above application environment, an embodiment of a maintenance method of an access network is introduced below:

[0055] In an exemplary embodiment, the application scenarios of the present technical solution can be: for scenarios such as fault handling, daily inspections, service activation, network cutover, new equipment joining / de-joining the network, etc. during the on-site integrated maintenance of the access network, by collecting information such as positioning, on-site photos, and resource audit results, the implementation of key standard actions of on-site integrated maintenance personnel can be managed and controlled.

[0056] In an exemplary embodiment, the application scenario of this technical solution can also be: for proactive maintenance of access networks, this solution uses multi-professional and multi-dimensional group fault analysis and serious fault analysis, and the result output can be applied to proactive maintenance and special remediation project guidance.

[0057] In an exemplary embodiment, Figure 2A schematic diagram showing a flow chart of a maintenance method for an access network in an exemplary embodiment of the present disclosure is shown. Figure 2 The access network maintenance method provided by the embodiment shown in the figure includes:

[0058] Step S210, obtaining work order data and network management data, as well as maintenance action execution data, to obtain network operation data; Step S220, gridding the access network resource data using an electronic map, and obtaining target resource data associated with the network operation data; Step S230, combining the network operation data and the target resource data to obtain a data wide table; and, Step S240, performing group fault analysis and severe fault analysis based on the data wide table to maintain the access network.

[0059] Among them, group failure refers to telecommunication network failures discovered by various units during the maintenance process that affect the normal communication of multiple users at the same time, and serious failure refers to repeated and high-incidence failures.

[0060] For example, the characteristics of integrated access network on-site maintenance are as follows: (1) The maintenance objects mainly involve four professions: optical cable, access equipment, wireless, and power environment, as well as other auxiliary professions. Integrated maintenance can integrate multi-professional skills, and a single maintenance personnel can undertake multiple professional maintenance. However, due to the wide range of required skills, there are generally shortcomings in maintenance capabilities. (2) The maintenance objects are numerous and widespread, covering streets, towns, and the wild. Most of the workload is outdoors, so the maintenance process and maintenance quality cannot be known without visiting the site, cost consumption is uncontrollable, and management is difficult.

[0061] This application Figure 2 In the technical solution provided by the illustrated embodiment, on the one hand, the standard actions of the access network on-site maintenance personnel are solidified based on Internet technology means to realize the collection of network operation data, which is conducive to the implementation of key standard actions of the access network maintenance personnel, and the real-time verification of maintenance materials one by one with the inventory system is realized, which is also conducive to the precise management of workload and material consumption. On the other hand, the access network resource data is gridded using electronic maps to enhance the management of the access network maintenance responsibility system. Then the target resource data associated with the above network operation data is obtained. Further, work order data, network management data, comprehensive maintenance action execution status and operation data based on artificial intelligence recognition are gathered, and a wide table is formed in combination with the above target resource data. At the same time, maintenance guidance and solutions are provided to on-site maintenance personnel through closed-loop processes and data analysis, which can accurately locate the work of actively maintaining the access network and actively promote key tasks, thereby realizing active maintenance of the access network and improving the maintenance efficiency and effectiveness of the access network.

[0062] The following Figure 2 The specific implementation methods of each step in the embodiment shown are described in detail:

[0063] In step S210, work order data, network management data, and maintenance action execution data are acquired to obtain network operation data.

[0064] In an exemplary embodiment, the maintenance action execution data is obtained, and the specific implementation methods include: for fault handling scenarios, daily inspection scenarios, service activation scenarios, network cutover scenarios, new equipment network entry scenarios, and network decommissioning work order scenarios, etc., the positioning information, on-site photos, and resource audit results of the above scenarios are obtained to realize the collection of on-site maintenance action information and obtain the maintenance action execution data.

[0065] In an exemplary embodiment, the positioning information of the above scene can be determined by a Global Positioning System (GPS).

[0066] In an exemplary embodiment, the terminal interface for obtaining the above-mentioned on-site photos is as follows: Figure 3 Reference Figure 3 , a live photo taking interface 300 for the above scenario. The interface includes the following multiple areas, each area is used to take photos of different types of equipment, and the photos of the type of equipment are stored in the area to facilitate the classification of photos of different types of equipment, thereby facilitating search and analysis.

[0067] Exemplarily, the above-mentioned areas include: an area 31 for taking photos of optical cables and storing photos of optical cables. Specifically, the user can start the photo taking function of the terminal by touching the "optical cable photo taking" control, and then take photos of the cable. In addition, the on-site photo taking interface 300 also includes: an area 32 for taking photos of joint boxes and storing photos of optical cables, an area 33 for taking photos of electric poles and storing photos of optical cables, and an area 34 for taking photos of fault points and storing photos of optical cables. Through the above-mentioned partitions, photos of optical cables, joint boxes, electric poles and fault points can be classified, which is conducive to further viewing, management and analysis.

[0068] In an exemplary embodiment, the intelligent recognition function can also be realized by a machine learning model based on pre-training. For example, after starting the function of photographing the cable, if the photographed object does not belong to the optical cable, the photographing will fail. This effectively regulates the management of the photographing behavior, which is conducive to improving the quality of the collected pictures, providing more reliable reference materials for the maintenance of the access network, and improving the maintenance efficiency and effectiveness of the access network. At the same time, it is conducive to the implementation of key standard actions of access network maintenance personnel, and realizes the real-time verification of maintenance materials one by one with the inventory system, which is conducive to the precise management of workload and material consumption.

[0069] In an exemplary embodiment, in order to further improve the degree of automated processing and the degree of standardization of photo processing results, the on-site photos taken in the above-mentioned scenes can be identified by artificial intelligence. Figure 4 The terminal interface 400 shown includes an area 420 for displaying on-site photos, an area 410 for displaying recognition results of the on-site photos, and an area 430 for user notes.

[0070] Exemplarily, the area 410 may be any on-site photo. The identification items displayed in the area 420 may be different according to the type of the on-site photo. For example, when the on-site photo is of an optical cable type, it corresponds to the first group of identification items, and when the on-site photo is of a joint box type, it corresponds to the second group of identification items. Thus, different identification items are obtained according to the different adaptability of the on-site photos, which is conducive to reflecting the personalized characteristics of different types of on-site photos and is conducive to the accuracy of the identification results.

[0071] Exemplarily, for the on-site photos displayed in area 410 of the terminal interface 400, the identification items displayed in area 420 include: whether the barcode is included, whether it is a copy, whether only the label is photographed, and whether the barcode matches. For each identification item, the corresponding "identification result" determined based on artificial intelligence is included. In order to improve the accuracy of the identification results, this solution also sets "manual review results". Exemplarily, the user can trigger the "manual review" control to realize the function of manually confirming each identification item, so that the user can manually determine the results of each identification item.

[0072] Exemplarily, the "final result" is determined based on the above-mentioned "manual review results" and "recognition results". The above-mentioned "final result" can be qualified or unqualified. In the case of qualified, it means that the current on-site photos can meet the preset requirements and there is no need to take photos again; in the case of unqualified, it means that the current on-site photos cannot meet the preset requirements, and the photos need to be discarded and re-provided. It should be noted that in the process of determining the "final result", the priority of the "manual review results" is higher than the priority of the "recognition results".

[0073] For example, when the user disagrees with the "barcode information" determined based on artificial intelligence, re-identification can be achieved by touching the "barcode re-identification" control.

[0074] In an exemplary embodiment, the network operation data also includes work order data, wherein a work order defines a simple maintenance or manufacturing plan consisting of one or more operations, and is the basis for the superior department to issue tasks and the subordinate department to accept tasks.

[0075] Exemplarily, obtaining network management data in step S210 includes: obtaining one or more of the following device information: network management alarm information and performance data of access equipment, network management alarm information and performance data of wireless networks, and network management alarm information of power environment professionals, to obtain the above-mentioned network management data.

[0076] This technical solution collects resource data and daily maintenance information through the Internet technology (IT) system to obtain the above-mentioned network operation data, which specifically includes: work order data, network management data and maintenance action execution data. Among them, the above-mentioned maintenance action execution data includes: positioning information, photo information and artificial intelligence recognition data. In an exemplary embodiment, the above-mentioned network operation data will be used to realize the analysis of network operation status.

[0077] In this technical solution, on the one hand, the above network operation data is obtained, and on the other hand, the access network resource data is gridded using an electronic map, and the target resource data associated with the above network operation data is obtained. For example, there is a cable device of SS model at a certain place (longitude: aaa, latitude: bbb), etc. At the same time, this solution manages the relevant resources throughout their life cycle, and through the full life cycle data management of key points in each link of network maintenance, it can ensure that the data is dynamically updated, accurate and effective.

[0078] Exemplary, reference Figure 5 In this embodiment, the following cyclic process 51 is implemented based on the business middle platform / data middle platform: on-site data acquisition stage, data aggregation stage, model building stage, optimization process stage, iterative calculation stage, and on-site data acquisition stage again. Through continuous cyclic output analysis, the work of actively maintaining the access network can be accurately located and key tasks can be actively promoted, thereby helping the digital transformation of cloud network operations.

[0079] Among them, the data middle platform refers to a sustainable mechanism for "making the enterprise's data useful", a strategic choice and organizational form, which is based on the enterprise's unique business model and organizational structure, supported by tangible products and implementation methodologies, to build a mechanism that continuously turns data into assets and serves the business. The data middle platform needs to have the core capabilities of data aggregation and integration, data purification and processing, data service visualization, and data value realization, so that enterprise employees, customers, and partners can easily use data.

[0080] Exemplarily, based on the above embodiment, in the above field data acquisition stage, network operation data can be obtained. Figure 5 In the loop process 51, in the data aggregation stage, the above network operation data and the target resource data associated with the above network operation data are associated and combined to obtain a data wide table.

[0081] Exemplary, reference Figure 5 In the loop process 51, during the model building phase, the information of the above-mentioned data wide table is sent to different maintenance teams, and the original information of the maintenance work corresponding to each maintenance team is collected, and then a data model is built based on the above-mentioned original information to perform group fault analysis and serious fault analysis through the output of the data model.

[0082] Specifically, work order data (network fault work order, user fault work order, optical network pre-work order, wireless pre-work order, complaint work order, hidden danger work order), network management data (access equipment, wireless, power environment professional network management alarm and performance data), comprehensive maintenance standard action execution (APP positioning photography, AI intelligent recognition and other data) and other operational data are gathered, associated with the target resource data to form a data wide table, all of which fall into the comprehensive maintenance team, collect the original information of the maintenance work of the comprehensive maintenance team, establish a data model, and the model is used for the next step of analysis and output. In this embodiment, by gathering operational data, associating it with the target resource data to form a data wide table and falling into the comprehensive maintenance team, the abnormal data analysis and dispatching will be closed-loop processed.

[0083] For example, based on the above cycle process 51, digital services 52 can be realized, including: digital customer service, digital cloud network operation, and digital resource assets. Specifically, the whole resource process, customer control, precise operation, resource value, cloud network operation, investment benefits, energy cost reduction, etc.

[0084] In an exemplary embodiment, the following describes data modeling based on the above data wide table and output of multi-dimensional group fault analysis and repeated fault analysis. Specifically, repeated fault high-incidence areas and corresponding repeated fault causes can be obtained through repeated fault analysis, and the fault causes that affect the normal communication of multiple users at the same time found during the maintenance process can be obtained through group fault analysis. And it can also further effectively evaluate the work performed by different teams.

[0085] In an exemplary embodiment, group fault analysis and severe fault analysis of optical cables are performed based on the above data wide table. Figure 6 For a detailed introduction:

[0086] Obtain the fault work order related to the optical cable from the above work order data, determine the first optical cable obstacle based on multiple fault work orders related to the optical cable and the network management alarm information in the above network management data; match the first optical cable obstacle with the target resource data related to the optical cable to determine the faulty optical cable section. Collect on-site repair photos of the above faulty optical cable section, perform AI recognition based on the on-site repair photos, locate the longitude and latitude of the fault point, and collect material consumption to perform repeated obstacle analysis on the optical cable.

[0087] Furthermore, the list of remediation items can be output by merging them according to the location element, time element, and reason element. Figure 6 The "query conditions" shown include: organizational level, local network, and start / end month. After determining the above query conditions and clicking the "query" control, data that meets the above query conditions can be obtained. In this way, the maintenance team that meets the above query conditions can be obtained, and the number of optical cable failures can be counted and viewed, so that the subsequent failures of the optical cable section can be automatically tracked after the rectification is completed, and the work performed by the relevant team can be effectively evaluated.

[0088] In an exemplary embodiment, based on the above data wide table and customer perceived group fault analysis and severe fault analysis. Figure 7 For a detailed introduction:

[0089] Obtain the user's complaint work order from the above work order data, and determine the second optical cable failure based on the complaint work order and the network management alarm information in the above network management data. Analyze the above second network management alarm information, combine the above second optical cable failure and the target resource data related to the optical cable, and determine the business scope affected by the above second optical cable failure, which includes one or more of the following obligations: broadband business, iTV business, voice and government business; predict the average service unavailable time of the target team based on the above business scope and the interruption time in the above complaint work order.

[0090] Further, refer to Figure 7 The "query conditions" shown include: local network, three-level organization, driver organization, statistical month (including start month and end month), optical cable name, number of faults, etc. After determining the above query conditions and clicking the "query" control, data that meets the above query conditions can be obtained. In this way, information that meets the above query conditions can be obtained, and the maintenance quality and customer perception of the comprehensive maintenance team can be further evaluated, and applied to the performance of the subdivided contracting unit.

[0091] In an exemplary embodiment, the group fault analysis and the serious fault analysis of the battery performance are performed based on the above data wide table. Figure 8 For a detailed introduction:

[0092] Obtain the fault work order 81 related to the battery from the work order data, and determine the battery fault according to the fault work order 81 related to the battery and the network management alarm information in the network management data. Exemplarily, based on the screening conditions, determine that the responsible department for the battery fault is the comprehensive maintenance group, and the primary cause of the battery fault is the dynamic environment fault. Exemplarily, obtain the number of users affected by the battery fault and the number of users complaining according to the attributes determined by the power environment major.

[0093] Based on the above network management alarm information and power generation information, make intelligent judgments on the reasons for power outages of related equipment. Figure 8 The work order categories are divided into: battery failure, untimely power generation failure, power supply equipment failure, and power supply air conditioning failure. Furthermore, the corresponding processing procedures are given according to battery failure, untimely power generation failure, power supply equipment failure, and power supply air conditioning failure. The battery discharge time is determined based on the battery discharge time, fault duration, and power outage time of each professional network device.

[0094] For example, a battery rectification list can be output, and a rectification item list can be output according to the location element, time element, and reason element. The rectification effect can be evaluated based on the automatic battery performance after battery replacement and the occurrence of equipment power failure.

[0095] In an exemplary embodiment, group fault analysis and severe fault analysis of access devices and wireless devices are performed based on the above data wide table. Fig. 9 For a detailed introduction:

[0096] Obtain network management alarm information related to the access device and the wireless device, and determine the fault work order related to the access device and the wireless device according to the network management alarm information and the target resource data related to the access device and the wireless device. Fig. 9 User trouble tickets and network trouble tickets are shown.

[0097] According to the fault work orders related to access devices and wireless devices, the fault cause is located and repaired, and the cause of the fault is verified. Fig. 9 , based on the screening conditions, it is determined that the responsible department for the above user fault work order is the comprehensive maintenance group, and the diagnosis conclusion is that the uplink status is abnormal. It is then assigned to the access network major, and the attributes including the attributes of the user fault work order are further determined to include: the number of intercepted users, the number of affected TV users, the number of affected voice users, the number of affected broadband users, and the number of invisible government and enterprise users. Exemplarily, based on the screening conditions, it is determined that the responsible department for the above network fault work order is the comprehensive maintenance group, the first-level cause is equipment failure, and the third-level cause is access network failure. It is then assigned to the access network major, and the attributes including the attributes of the user fault work order are further determined to include: the number of intercepted users, the number of affected TV users, the number of affected voice users, the number of affected broadband users, and the number of invisible government and enterprise users.

[0098] For example, continue to refer to Fig. 9, mark the user fault list and network fault list as serious faults, and classify the work orders according to the serious fault marks as follows: Optical Line Terminal (OLT) equipment hidden danger work order, OLT card board hidden danger work order, and OLT PON PON (Passive Optical Network) hidden danger work order. Further, output the rectification list of various hidden dangers of the above equipment, and output the rectification project list according to location, time, cause, etc.

[0099] In an exemplary embodiment, reference Fig.10 In an access network maintenance solution provided, network fault work orders, production data (including intelligent network management, resource GIS (Geographic Information System or Geo-Information system, location information), CRM data, etc.) are stored in HIVE clusters through Sqoop, text or OGG. Among them, OGG is an audio compression format, similar to music formats such as MP3. Hive is a data warehouse tool based on Hadoop, which can map structured data files to a database table and provide SQL-like query functions. Sqoop is a tool for transferring data between Hadoop and relational databases. It can import data from a relational database (such as MySQL, Oracle, Postgres, etc.) into Hadoop's HDFS (Hadoop Distributed File System), and can also import HDFS data into a relational database. HIVE cluster is a data warehouse tool based on Hadoop, which is used for data extraction, transformation, and loading. This is a mechanism for storing, querying and analyzing large-scale data stored in Hadoop.

[0100] Furthermore, the data center subscribes to the data in the HIVE cluster and classifies the above data into ftpdata / system data and App / data data.

[0101] For the above ftpdata / system data, it will enter the data table in the MID library of cloud network resources in the form of datax, and further determine ITSP (information technology strategic plan, enterprise informationization strategic planning) 3.0 in the Potral library (fully integrated automation programming software) according to the data table in the MID library. The above App / data data will enter the optical cable information in the Potral library of cloud network resources in the form of Python.

[0102] Furthermore, group fault analysis and severe fault analysis are performed based on ITSP 3.0, work orders and the above-mentioned optical cable information in the Potral library. Group fault analysis and severe fault analysis will analyze the following aspects, including optical cable network, access network, power environment and wireless.

[0103] Through the application of this technical solution, active maintenance of the access network can be achieved, and at the same time, customer perception during access network maintenance can be greatly improved. Through data modeling, multi-dimensional group fault, serious fault analysis and TOP areas can be output. First, it can promote maintenance personnel to carry out proactive maintenance work, greatly reduce the occurrence of faults, improve customer perception, and save manpower and material resources for emergency repairs; second, it can accurately guide limited remediation costs to key areas to ensure that the remediation projects achieve the greatest benefits. At the same time, it can conduct pre- and post-remediation effect evaluations on proactive remediation projects to ensure the effectiveness of remediation projects.

[0104] Based on the output results of group fault analysis and severe fault analysis, a special remediation project library and a closed-loop project evaluation system can be established in the target area (e.g., within the province) to evaluate the value and benefits of each project. The first is project evaluation: clarify the priority of remediation projects based on the fault analysis, and digitally evaluate the expected value of the project; the second is post-project evaluation: continue to track subsequent changes in obstacles after the remediation is completed, and digitally evaluate the actual benefits of the project. Examples of scenarios where optical cable professional group fault analysis and severe fault analysis are applied to active maintenance are shown in Table 1:

[0105] Table 1

[0106]

[0107]

[0108] The present application provides a maintenance solution for an access network, which, on the one hand, uses Internet technology to solidify the standard actions of on-site maintenance personnel of the access network, realizes the collection of network operation data, and is conducive to the implementation of key standard actions of access network maintenance personnel, and realizes the real-time verification of maintenance materials one by one with the inventory system, which is also conducive to the precise management of workload and material consumption. On the other hand, the use of electronic maps to grid the access network resource data can enhance the management of the access network maintenance responsibility system. Then obtain the target resource data associated with the above network operation data. Further gather operational data such as work order data, network management data, comprehensive maintenance action execution status and AI intelligent identification, and combine the above target resource data to form a wide table. At the same time, through closed-loop processes and data analysis, maintenance guidance and solutions are provided to on-site maintenance personnel, which can accurately locate the work of actively maintaining the access network and actively promote key tasks, thereby promoting active maintenance of the access network and improving the maintenance efficiency and effectiveness of the access network.

[0109] At the same time, this technical solution also manages the entire life cycle of resource data. By managing the entire life cycle data of key points in each link of network maintenance, it can ensure that the data is dynamically updated, accurate and effective. In addition, the operation data is gathered and associated with the target resource data to form a wide data table that falls into the relevant team, and the abnormal data is analyzed and dispatched for closed-loop processing. Therefore, through the above means, based on resource data accuracy, serious faults, group faults, complaints, maintenance costs, energy consumption, rental fees, etc., new evaluation indicators and subdivision mechanisms are established to guide the operation system based on fault repair and obstacle single processing to the operation system oriented to resource operation efficiency and customer perception. Compared with the existing technology, the advantage of this technical solution is that through process + data drive + closed loop, it is conducive to realizing active maintenance of the access network, improving the maintenance efficiency and effectiveness of the access network, and helping to promote the digital transformation of cloud network operations.

[0110] Those skilled in the art will appreciate that all or part of the steps to implement the above embodiments are implemented as a computer program executed by a processor (including a GPU / CPU). When the computer program is executed by the GPU / CPU, the above functions defined by the above method provided in the present disclosure are performed. The program may be stored in a computer-readable storage medium, which may be a read-only memory, a disk or an optical disk, etc.

[0111] In addition, it should be noted that the above figures are only schematic illustrations of the processes included in the method according to the exemplary embodiment of the present disclosure, and are not intended to be limiting. It is easy to understand that the processes shown in the above figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0112] The following Fig.11 An embodiment of a maintenance device for an access network disclosed in the present invention is introduced, which can be used to execute the maintenance method for the access network disclosed above.

[0113] Fig.11 A schematic diagram of the structure of a maintenance device for an access network in an exemplary embodiment of the present disclosure is shown.

[0114] like Fig.11 As shown, the access network maintenance device 1100 includes: an acquisition module 1101 , a grid processing module 1102 , a combination module 1103 and an analysis module 1104 .

[0115] Among them, the above-mentioned acquisition module 1101 is configured to: acquire work order type data and network management type data, and acquire maintenance action execution data to obtain network operation data; the above-mentioned grid processing module 1102 is configured to: use an electronic map to grid the access network resource data, and acquire target resource data associated with the network operation data; the above-mentioned combination module 1103 is configured to: combine the network operation data and the above-mentioned target resource data to obtain a data wide table; and the above-mentioned analysis module 1104 is configured to: perform group fault analysis and severe fault analysis based on the data wide table to maintain the access network.

[0116] In some embodiments of the present disclosure, based on the aforementioned scheme, the above-mentioned acquisition module 1101 is specifically configured to: acquire fault work orders, pre-work orders, complaint work orders and hidden danger work orders, and obtain the above-mentioned work order type data; the above-mentioned acquisition module 1101 is also specifically configured to: acquire one or more of the following equipment information: network management alarm information and performance data of access equipment, network management alarm information and performance data of wireless networks, and network management alarm information of power environment professionals, and obtain the above-mentioned network management type data; the above-mentioned acquisition module 1101 is also specifically configured to: acquire positioning information, on-site photos and resource audit results of the following scenarios to realize the collection of on-site maintenance action information and obtain the above-mentioned maintenance action execution data, wherein the above-mentioned scenarios include: one or more of fault handling scenarios, daily inspection scenarios, service activation scenarios, network cutover scenarios, new equipment network access scenarios and network decommissioning work order scenarios; the above-mentioned maintenance action execution data includes one or more of the following information: positioning information, photo information and artificial intelligence recognition data.

[0117] In some embodiments of the present disclosure, based on the aforementioned solution, the access network maintenance device 1100 further includes: a sending module 1105 and a collecting module 1106 .

[0118] Among them, the above-mentioned sending module 1105 is configured to: after combining the above-mentioned network operation data and the above-mentioned target resource data to obtain the data wide table, send the information of the above-mentioned data wide table to different maintenance teams; the above-mentioned collecting module 1106 is configured to: collect the original information of the maintenance work corresponding to each maintenance team, and establish a data model based on the above-mentioned original information, so as to perform group fault analysis and serious fault analysis through the output of the above-mentioned data model.

[0119] In some embodiments of the present disclosure, based on the aforementioned scheme, the above-mentioned analysis module 1104 is configured to: perform group fault analysis and severe fault analysis based on the above-mentioned data wide table and one or more of the following information: group fault analysis and severe fault analysis on optical cables based on the above-mentioned data wide table; group fault analysis and severe fault analysis based on the above-mentioned data wide table and customer perception; group fault analysis and severe fault analysis on battery performance based on the above-mentioned data wide table; and group fault analysis and severe fault analysis on access devices and wireless devices based on the above-mentioned data wide table.

[0120] In some embodiments of the present disclosure, based on the aforementioned scheme, in the case of group fault analysis and severe fault analysis of optical cables based on the aforementioned data wide table, the above-mentioned analysis module 1104 is specifically configured as follows: obtaining fault work orders related to optical cables in the above-mentioned work order type data; determining the first optical cable fault based on the above-mentioned fault work orders related to the optical cables and the network management alarm information in the above-mentioned network management type data; matching the above-mentioned first optical cable fault with the resource data related to the optical cable to determine the faulty optical cable section; collecting on-site repair photos of the above-mentioned target management section, performing AI recognition based on the above-mentioned on-site repair photos, locating the longitude and latitude of the fault point, and collecting material consumption to perform repeated fault analysis on the optical cable.

[0121] In some embodiments of the present disclosure, based on the aforementioned scheme, in the case of group fault analysis and severe fault analysis based on the aforementioned data broadband table and customer perception, the aforementioned analysis module 1104 is specifically configured as follows: obtaining the user's complaint work order from the aforementioned work order type data; determining the second optical cable fault based on the aforementioned complaint work order and the network management alarm information in the aforementioned network management type data; analyzing the aforementioned second network management alarm information, and combining the aforementioned second optical cable fault and resource data related to the optical cable to determine the business scope affected by the aforementioned second optical cable fault, the aforementioned business scope including one or more of the following obligations: broadband business, iTV business, voice and government business; predicting the average household unavailability duration of the target team's business based on the aforementioned business scope and the interruption time in the aforementioned complaint work order.

[0122] In some embodiments of the present disclosure, based on the aforementioned scheme, in the case of group fault analysis and severe fault analysis of battery performance based on the aforementioned data wide table, the aforementioned analysis module 1104 is specifically configured as follows: obtaining a fault work order related to the battery in the aforementioned work order type data; determining the battery fault based on the aforementioned fault work order related to the battery and the network management alarm information in the aforementioned network management type data; making an intelligent judgment on the cause of power outage of related equipment based on the aforementioned network management alarm information and power generation information, and providing corresponding processing procedures according to battery failure, untimely power generation failure, power supply equipment failure, and power supply air conditioning failure; determining the dischargeable time of the battery based on the discharge time of the battery, the duration of the fault, and the power off time of each professional network equipment.

[0123] In some embodiments of the present disclosure, based on the aforementioned scheme, in the case of group fault analysis and severe fault analysis of access devices and wireless devices based on the aforementioned data wide table, the aforementioned analysis module 1104 is specifically configured to: obtain network management alarm information related to the access devices and wireless devices, and determine the fault work orders related to the access devices and wireless devices based on the aforementioned network management alarm information and resource data related to the access devices and wireless devices; locate the cause of the fault and take repair measures based on the fault work orders related to the access devices and wireless devices, and verify the above-mentioned cause of the obstacle.

[0124] In the access network maintenance solution implemented by the maintenance device of the above-mentioned access network, on the one hand, the standard actions of the access network on-site maintenance personnel are solidified based on Internet technology to realize the collection of network operation data. On the other hand, the access network resource data is gridded using an electronic map, and the target resource data associated with the above-mentioned network operation data is obtained. Then, work order data, network management data, comprehensive maintenance action execution status and operational data based on artificial intelligence recognition are gathered, and a wide table is formed in combination with the above-mentioned target resource data. At the same time, maintenance guidance and solutions are provided to on-site maintenance personnel through closed-loop processes and data analysis, which can accurately locate the work of actively maintaining the access network and actively promote key work, thereby promoting active maintenance of the access network and improving the maintenance efficiency and effectiveness of the access network.

[0125] The specific details of each unit in the maintenance device of the access network have been described in detail in the embodiment of the maintenance method of the access network, so they will not be repeated here.

[0126] Fig.12 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present disclosure is shown.

[0127] It should be noted that Fig.12 The computer system 1200 of the electronic device 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.

[0128] like Fig.12As shown, the computer system 1200 includes a processor 1201, wherein the processor 1201 may specifically include: a graphics processing unit (Graphics Processing Unit, referred to as: GPU) and a central processing unit (Central Processing Unit, referred to as: CPU), which can perform various appropriate actions and processes according to the program stored in the read-only memory (Read-Only Memory, referred to as: ROM) 1202 or the program loaded from the storage part 1208 to the random access memory (Random Access Memory, referred to as: RAM) 1203. In RAM 1203, various programs and data required for system operation are also stored. The processor 1201, ROM 1202 and RAM 1203 are connected to each other through a bus 1204. An input / output (Input / Output, referred to as: I / O) interface 1205 is also connected to the bus 1204.

[0129] The following components are connected to the I / O interface 1205: an input section 1206 including a keyboard, a mouse, etc.; an output section 1207 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage section 1208 including a hard disk, etc.; and a communication section 1209 including a network interface card such as a local area network (LAN) card, a modem, etc. The communication section 1209 performs communication processing via a network such as the Internet. A drive 1210 is also connected to the I / O interface 1205 as needed. A removable medium 1211, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1210 as needed so that a computer program read therefrom is installed into the storage section 1208 as needed.

[0130] In particular, according to an embodiment of the present disclosure, the process described below with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 1209, and / or installed from a removable medium 1211. When the computer program is executed by the processor 1201, various functions defined in the system of the present application are executed.

[0131] It should be noted that the computer-readable storage medium shown in the embodiment of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by an instruction execution system, device or device or used in combination with it. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable storage medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0132] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0133] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware, and the units described may also be arranged in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0134] Exemplarily, as another aspect, the present application also provides a computer-readable storage medium, including a program product for describing the method according to an embodiment of the present invention, which can be a portable compact disk read-only memory (CD-ROM) and includes program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited to this. In this document, a readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, an apparatus or a device.

[0135] The program product may adopt any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium.

[0136] Computer readable signal media may include a data signal propagated in baseband or as part of a carrier wave, wherein a readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, device, or device. The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above.

[0137] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0138] The computer-readable storage medium may be included in the electronic device described in the above embodiment; or it may exist independently without being assembled into the electronic device. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the method described in the above embodiment.

[0139] For example, the electronic device can implement Figure 2 As shown in: Step S210, obtaining work order data and network management data, as well as maintenance action execution data, to obtain network operation data; Step S220, gridding the access network resource data using an electronic map, and obtaining target resource data associated with the network operation data; Step S230, combining the network operation data and the target resource data to obtain a data wide table; and Step S240, performing group fault analysis and severe fault analysis based on the data wide table to maintain the access network.

[0140] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0141] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0142] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0143] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for maintaining an access network, characterized in that: The method comprises: Obtain work order data, network management data, and maintenance action execution data to obtain network operation data; Using an electronic map to grid the access network resource data, and obtaining target resource data associated with the network operation data; Combining the network operation data and the target resource data to obtain a data wide table; Perform group fault analysis and severe fault analysis based on the data wide table to maintain the access network, wherein the group fault refers to a telecommunications network fault that affects normal communications of multiple users at the same time and is discovered by various units during the maintenance process, and the severe fault refers to a repeated and high-occurrence fault; Among them, the obtaining of maintenance action execution data includes: obtaining the positioning information, on-site photos and resource audit results of the following scenarios to realize the collection of on-site maintenance action information and obtain the maintenance action execution data; the scenarios include: one or more of fault handling scenarios, daily inspection scenarios, service activation scenarios, network cutover scenarios, new equipment access scenarios and network delisting work order scenarios; the maintenance action execution data includes one or more of the following information: positioning information, photo information and artificial intelligence recognition data.

2. The access network maintenance method according to claim 1, characterized in that: The obtaining of work order data includes: obtaining fault work orders, pre-work orders, complaint work orders and hidden danger work orders to obtain the work order data; The obtaining of network management data includes: obtaining one or more of the following equipment information: network management alarm information and performance data of access equipment, network management alarm information and performance data of wireless network, network management alarm information of power environment, to obtain the network management data.

3. The access network maintenance method according to claim 1, characterized in that: After combining the network operation data and the target resource data to obtain a data wide table, the method further includes: Sending the information of the data wide table to different maintenance teams; The original information of the maintenance work corresponding to each maintenance team is collected, and a data model is established based on the original information, so as to perform group fault analysis and serious fault analysis through the output of the data model.

4. The access network maintenance method according to any one of claims 1 to 3, characterized in that: The group fault analysis and the serious fault analysis based on the data wide table may include one or more of the following information: Group fault analysis and severe fault analysis of optical cables based on the data wide table; Group fault analysis and severe fault analysis based on the data table and customer perception; Group fault analysis and severe fault analysis of battery performance based on the data table; Based on the data table, group fault analysis and severe fault analysis of access devices and wireless devices are performed.

5. The access network maintenance method according to claim 4, characterized in that: In the case of performing group fault analysis and severe fault analysis on the optical cable based on the wide data table, performing group fault analysis and severe fault analysis based on the wide data table includes: Obtaining a fault work order related to the optical cable from the work order data; Determine a first optical cable fault according to the optical cable related fault work order and the network management alarm information in the network management data; matching the first optical cable obstacle with resource data associated with the optical cable to determine a faulty optical cable section; Collect on-site emergency repair photos of the faulty optical cable section, perform AI recognition based on the on-site emergency repair photos, locate the longitude and latitude of the fault point, and collect material consumption to perform repeated obstacle analysis on the optical cable.

6. The access network maintenance method according to claim 4, characterized in that: In the case of group fault analysis and severe fault analysis based on the wide data table and customer perception, the group fault analysis and severe fault analysis based on the wide data table includes: Obtaining the user's complaint work order from the work order data; Determine the second optical cable failure according to the complaint work order and the network management alarm information in the network management data; Analyze the network management alarm information, combine the second optical cable obstacle and resource data related to the optical cable, and determine the service scope affected by the second optical cable obstacle, wherein the service scope includes one or more of the following obligations: broadband service, iTV service, voice and government business; According to the business scope and the interruption time in the complaint work order, the average service unavailability duration per household in the target team is predicted.

7. The access network maintenance method according to claim 4, characterized in that: In the case of performing group fault analysis and severe fault analysis on battery performance based on the wide data table, performing group fault analysis and severe fault analysis based on the wide data table includes: Obtaining a fault work order related to the battery from the work order data; Determine the battery fault according to the fault work order related to the battery and the network management alarm information in the network management data; According to the network management alarm information and power generation information, an intelligent judgment is made on the power failure cause of the relevant equipment, and corresponding processing procedures are given according to battery failure, untimely power generation failure, power supply equipment failure, and power supply air conditioning failure; Determine the battery discharge time based on the battery discharge time, fault duration, and power outage time of each professional network equipment.

8. The access network maintenance method according to claim 4, characterized in that: In the case of performing group fault analysis and severe fault analysis on access devices and wireless devices based on the data wide table, performing group fault analysis and severe fault analysis based on the data wide table includes: Acquire network management alarm information related to the access device and the wireless device, and determine the fault work order related to the access device and the wireless device according to the network management alarm information and resource data related to the access device and the wireless device; Based on the fault work orders related to access devices and wireless devices, fault causes are located and repair measures are taken, and the causes of the failures are verified.

9. A maintenance device for an access network, characterized in that: The device comprises: The acquisition module is configured to: acquire work order data, acquire network management data, and acquire maintenance action execution data to obtain network operation data; The grid processing module is configured to: perform grid processing on the access network resource data using an electronic map, and obtain target resource data associated with the network operation data; A combining module is configured to: combine the network operation data and the target resource data to obtain a data wide table; The analysis module is configured to: perform group fault analysis and severe fault analysis based on the data wide table to maintain the access network, wherein the group fault refers to a telecommunications network fault that affects normal communications of multiple users at the same time and is discovered by various units during the maintenance process, and the severe fault refers to a repeated and high-occurring fault; Among them, the obtaining of maintenance action execution data includes: obtaining the positioning information, on-site photos and resource audit results of the following scenarios to realize the collection of on-site maintenance action information and obtain the maintenance action execution data; the scenarios include: one or more of fault handling scenarios, daily inspection scenarios, service activation scenarios, network cutover scenarios, new equipment access scenarios and network delisting work order scenarios; the maintenance action execution data includes one or more of the following information: positioning information, photo information and artificial intelligence recognition data.

10. An electronic device, characterized in that: The electronic device comprises: one or more processors; A storage device, used to store one or more programs, when the one or more programs are executed by the one or more processors, enables the one or more processors to implement the access network maintenance method as described in any one of 1 to 8.

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