CN117135027A - Fault discovery method, apparatus, device, storage medium, and computer program product - Google Patents

Fault discovery method, apparatus, device, storage medium, and computer program product Download PDF

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Publication number
CN117135027A
CN117135027A CN202310969225.7A CN202310969225A CN117135027A CN 117135027 A CN117135027 A CN 117135027A CN 202310969225 A CN202310969225 A CN 202310969225A CN 117135027 A CN117135027 A CN 117135027A
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CN
China
Prior art keywords
alarm information
fault
user
information
target
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CN202310969225.7A
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Chinese (zh)
Inventor
汪燕妮
杨旭平
方铭翔
卢忠渭
周荣
毛燕春
周雯
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China Telecom Corp Ltd
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China Telecom Corp Ltd
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Priority to CN202310969225.7A priority Critical patent/CN117135027A/en
Publication of CN117135027A publication Critical patent/CN117135027A/en
Pending legal-status Critical Current

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/06—Management of faults, events, alarms or notifications
    • H04L41/0604—Management of faults, events, alarms or notifications using filtering, e.g. reduction of information by using priority, element types, position or time
    • H04L41/0622—Management of faults, events, alarms or notifications using filtering, e.g. reduction of information by using priority, element types, position or time based on time
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/06—Management of faults, events, alarms or notifications
    • H04L41/0604—Management of faults, events, alarms or notifications using filtering, e.g. reduction of information by using priority, element types, position or time
    • H04L41/0618—Management of faults, events, alarms or notifications using filtering, e.g. reduction of information by using priority, element types, position or time based on the physical or logical position
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/06—Management of faults, events, alarms or notifications
    • H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/06—Management of faults, events, alarms or notifications
    • H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
    • H04L41/064—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis involving time analysis
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/06—Management of faults, events, alarms or notifications
    • H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
    • H04L41/065—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis involving logical or physical relationship, e.g. grouping and hierarchies
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/06—Management of faults, events, alarms or notifications
    • H04L41/0677—Localisation of faults

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)

Abstract

The present application relates to a fault finding method, apparatus, device, storage medium and computer program product. The method comprises the following steps: determining target alarm information of which the information occurrence time is within a preset time from a plurality of alarm information; grouping the target alarm information according to the geographic information of the target alarm information to obtain alarm information groups of different geographic information; acquiring a user reporting amount of each piece of alarm information in the alarm information group, and screening the alarm information with the user reporting amount being larger than a preset reporting amount to form a suspicious fault group; determining the number of affected user assets for the suspected fault group; and taking the suspicious fault group with the number of the influenced user assets being larger than the preset number of assets as a target fault group. The method can accurately and efficiently determine large-area homologous faults through the information occurrence time, the geographic information, the user reporting amount and the number of affected user assets corresponding to the alarm information.

Description

Fault discovery method, apparatus, device, storage medium, and computer program product
Technical Field
The present application relates to the field of communications internet technology, and in particular, to a fault discovery method, apparatus, device, storage medium, and computer program product.
Background
With the rapid development of communication internet technology, the quality requirement of users on network broadband is increasingly improved, and operators have a development trend of quality improvement and efficiency improvement, so that in order to improve the satisfaction degree of users on network quality, operators must shorten the duration of network faults of metropolitan area networks.
At present, in a metropolitan area network management system, a plurality of fault worksheets may be generated by homologous faults of the same fault cause, and the influence surface of the homologous faults is difficult to accurately calculate, so that large-area homologous faults are difficult to quickly identify, which is not beneficial to the targeted maintenance of operators on the metropolitan area network quality.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a fault finding method, apparatus, device, computer-readable storage medium, and computer program product that can accurately and efficiently find large-area homologous faults.
In a first aspect, the present application provides a fault finding method. The method comprises the following steps:
determining target alarm information of which the information occurrence time is within a preset time from a plurality of alarm information;
grouping the target alarm information according to the geographic information of the target alarm information to obtain alarm information groups of different geographic information;
Acquiring a user reporting amount of each piece of alarm information in the alarm information group, and screening the alarm information with the user reporting amount being larger than a preset reporting amount to form a suspicious fault group;
determining the number of affected user assets for the suspected fault group;
and taking the suspicious fault group with the number of the influenced user assets being larger than the preset number of assets as a target fault group.
In one embodiment, if the fault type corresponding to the target fault packet is a large-area fault caused by the cut-over legacy, the preset time is a first time interval and a second time interval;
the time length of the first time interval is smaller than that of the second time interval;
the second time interval is in a range from the first time endpoint to the second time endpoint, wherein the first time endpoint is a time point when the cutting starts, and the second time endpoint is a time point after the cutting is completed.
In one embodiment, the second time point is one of n preset time points, and the n preset time points are distributed in an arithmetic progression;
the method further comprises the following steps: and sequentially acquiring the geographic information of the target alarm information according to n preset time points.
In one embodiment, the method further comprises:
generating an alarm work order for the target fault group, wherein the alarm work order comprises the occurrence time, the alarm level, the geographic information corresponding to the target fault group, the sub-geographic information corresponding to the geographic information, the reporting quantity of the user, the number of assets affecting the user and the alarm quantity;
And sending the warning worksheet to a customer service scheduling system so that the customer service scheduling system performs maintenance scheduling aiming at the network condition corresponding to the target fault group.
In one embodiment, the determining the number of affected user assets for the suspected fault group includes:
acquiring the number of associated user numbers of each piece of alarm information in the suspicious fault group;
and summing the number of the associated user numbers of each piece of alarm information to obtain the number of the affected user assets corresponding to the suspicious fault group.
In one embodiment, the obtaining the number of the associated user numbers of each piece of alarm information in the suspicious fault packet includes:
acquiring the number of associated user numbers and the user liveness of each piece of alarm information;
the step of summing the number of the associated user numbers of each piece of alarm information to obtain the number of the affected user assets corresponding to the suspicious fault group comprises the following steps:
summing the number of the associated user of each piece of alarm information to obtain the sum of the associated numbers; and obtaining the number of the affected user assets corresponding to the suspicious fault group according to the sum of the associated numbers in the geographical area and the user liveness.
In a second aspect, the application further provides a fault finding device. The device comprises:
The target alarm information determining module is used for determining target alarm information with information occurrence time within preset time in the plurality of alarm information;
the alarm information grouping determining module is used for grouping the target alarm information according to the geographic information of the target alarm information to obtain alarm information groupings of different geographic information;
the suspicious fault grouping determining module is used for acquiring the user reporting amount of each piece of alarm information in the alarm information grouping and screening the alarm information with the user reporting amount being larger than the preset reporting amount to form suspicious fault grouping;
an affected user asset count determination module for determining an affected user asset count for the suspected fault group;
and the target fault grouping determination module is used for taking suspicious fault groupings with the number of the influenced user assets being greater than the preset number of assets as target fault groupings.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor which when executing the computer program performs the steps of:
determining target alarm information of which the information occurrence time is within a preset time from a plurality of alarm information;
Grouping the target alarm information according to the geographic information of the target alarm information to obtain alarm information groups of different geographic information;
acquiring a user reporting amount of each piece of alarm information in the alarm information group, and screening the alarm information with the user reporting amount being larger than a preset reporting amount to form a suspicious fault group;
determining the number of affected user assets for the suspected fault group;
and taking the suspicious fault group with the number of the influenced user assets being larger than the preset number of assets as a target fault group.
In a fourth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
determining target alarm information of which the information occurrence time is within a preset time from a plurality of alarm information;
grouping the target alarm information according to the geographic information of the target alarm information to obtain alarm information groups of different geographic information;
acquiring a user reporting amount of each piece of alarm information in the alarm information group, and screening the alarm information with the user reporting amount being larger than a preset reporting amount to form a suspicious fault group;
determining the number of affected user assets for the suspected fault group;
And taking the suspicious fault group with the number of the influenced user assets being larger than the preset number of assets as a target fault group. In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the steps of:
determining target alarm information of which the information occurrence time is within a preset time from a plurality of alarm information;
grouping the target alarm information according to the geographic information of the target alarm information to obtain alarm information groups of different geographic information;
acquiring a user reporting amount of each piece of alarm information in the alarm information group, and screening the alarm information with the user reporting amount being larger than a preset reporting amount to form a suspicious fault group;
determining the number of affected user assets for the suspected fault group;
and taking the suspicious fault group with the number of the influenced user assets being larger than the preset number of assets as a target fault group.
The fault discovery method, the fault discovery device, the fault discovery equipment, the fault discovery storage medium and the fault discovery computer program product are used for determining target alarm information with information occurrence time within preset time in a plurality of alarm information; grouping the target alarm information according to the geographic information of the target alarm information to obtain alarm information groups of different geographic information; acquiring a user reporting amount of each piece of alarm information in the alarm information group, and screening the alarm information with the user reporting amount being larger than a preset reporting amount to form a suspicious fault group; determining the number of affected user assets for the suspected fault group; and taking the suspicious fault group with the number of the influenced user assets being larger than the preset number of assets as a target fault group. According to the fault discovery method provided by the embodiment, the suspicious fault group with the homologous fault is determined according to the information occurrence time, the geographic information and the user reporting quantity corresponding to the plurality of alarm information, and then the large-area homologous fault is determined according to the number of the affected user assets of the suspicious fault group, so that the target fault group with the large-area homologous fault is determined from the plurality of alarm information, and the large-area homologous fault is accurately and efficiently discovered.
Drawings
FIG. 1 is an application environment diagram of a fault discovery method in one embodiment;
FIG. 2 is a flow diagram of a fault discovery method in one embodiment;
FIG. 3 is a flow chart of a fault finding method according to another embodiment;
FIG. 4 is a block diagram of a fault finding apparatus in one embodiment;
FIG. 5 is a block diagram of a fault finding apparatus in another embodiment;
FIG. 6 is an internal block diagram of a computer device in one embodiment;
fig. 7 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
It should be noted that in the following description, the terms "first, second and third" are used merely to distinguish similar objects and do not represent a specific order for the objects, it being understood that the "first, second and third" may be interchanged with a specific order or sequence, if allowed, to enable embodiments of the application described herein to be practiced otherwise than as illustrated or described herein.
The fault discovery method provided by the embodiment of the application can be applied to an application environment shown in figure 1. Wherein the terminal 102 communicates with the server 104 via a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104 or may be located on a cloud or other network server. In some embodiments, the fault discovery method is performed by the terminal 102, the terminal 102 determining target alert information having an information occurrence time within a preset time among a plurality of alert information; the terminal 102 groups the target alarm information according to the geographic information of the target alarm information to obtain alarm information groups of different geographic information; the terminal 102 obtains the user reporting amount of each alarm information in the alarm information group, and filters the alarm information with the user reporting amount larger than the preset reporting amount to form a suspicious fault group; the terminal 102 determines the number of affected user assets for the suspected fault group; the terminal 102 takes as the target fault group a suspicious fault group with an affected user asset number greater than a preset asset number.
The terminal 102 may be a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, an internet of things device, and a portable wearable device, and the internet of things device may be a smart speaker, a smart television, a smart air conditioner, and a smart vehicle device. The portable wearable device may be a smart watch, smart bracelet, headset, or the like.
The server 104 may be a separate physical server or may be a service node in a blockchain system, where a Peer-To-Peer (P2P) network is formed between service nodes, and the P2P protocol is an application layer protocol that runs on top of a transmission control protocol (TCP, transmission Control Protocol) protocol.
The server 104 may be a server cluster formed by a plurality of physical servers, and may be a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.
The terminal 102 and the server 104 may be connected by a communication connection manner such as bluetooth, USB (Universal Serial Bus ) or a network, which is not limited herein.
In one embodiment, as shown in fig. 2, there is provided a fault discovery method, which may be performed by the server or the terminal in fig. 1, or by the server and the terminal in cooperation, and which is illustrated by way of example by the terminal in fig. 1, including the steps of:
S202, determining target alarm information with information occurrence time within preset time in a plurality of alarm information.
The alarm information may be generated for a network failure in a metropolitan area network, that is, for a network failure in a computer communication network established in a metropolitan area network, and further, for a network failure in an access layer of the metropolitan area network.
The targeted alert information may be one or more. The target alarm information can comprise information such as occurrence time, geographical information representing a position, reporting quantity of a user, the number of associated numbers of the user, alarm work order numbers, fault clearing time, associated fault work order numbers, alarm identification and the like.
The target alarm information with the information occurrence time within the preset time is relative to the current time, namely, the information occurrence time is less than or equal to the current time (the current time is less than or equal to the preset time).
Specifically, the terminal acquires the occurrence time of a plurality of alarm messages, and determines target alarm messages with the occurrence time of the messages within a preset time from the plurality of alarm messages according to the occurrence time of each alarm message in the plurality of alarm messages.
S204, grouping the target alarm information according to the geographic information of the target alarm information to obtain alarm information groups of different geographic information.
Wherein the geographic information may refer to a corresponding geographic area range. For example, the geographic information of the target alert information may indicate that the location of occurrence of the target alert information is located in a city, a region, or a street.
And obtaining alarm information groups of different geographic information, namely, each alarm information group corresponds to different geographic information in one or more obtained alarm information groups, and the different geographic information corresponds to each alarm information group one by one.
S206, obtaining the user reporting amount of each piece of alarm information in the alarm information group, and screening the alarm information with the user reporting amount larger than the preset reporting amount to form a suspicious fault group.
The user reporting amount of each piece of alarm information in the alarm information packet refers to the number of user complaints, received by each piece of alarm information in the alarm information packet, aiming at the network condition.
The preset reporting amount may be 0, so that as long as a certain alarm information is reported by a user, the alarm information is filtered to form a suspicious fault group.
S208, determining the number of affected user assets of the suspicious fault group.
Wherein the number of affected user assets can be determined by how many associated numbers of users are within the geographic area corresponding to the geographic information of the suspected fault group. Guan Lianhao code number may refer to the number of broadband accounts associated with the corresponding user.
Specifically, the terminal is in communication connection with the asset list of the broadband operator, so that the terminal determines the number of the affected user assets of the suspicious fault group according to the asset conditions of the users in the asset list in the geographical area range corresponding to the geographical information of the suspicious fault group.
S210, taking suspicious fault groups with the number of the influenced user assets being larger than the preset number of assets as target fault groups.
Specifically, after the suspicious fault group with the number of the affected user assets being greater than the preset number of assets is used as the target fault group, an alarm work order can be generated for the target fault group, and the alarm work order is sent to the customer service dispatching system, so that the customer service dispatching system alarms the fault management and control post dispatch order to related maintenance personnel for maintenance and dispatching according to the network condition corresponding to the target fault group. Further, the warning worksheet can comprise warning levels of target fault groups, the warning levels are in positive correlation with the number of the affected user assets, and the warning levels are used for reminding a client service scheduling system that the corresponding high-low-level scheduling levels should be adopted to conduct targeted network repair on large-area homologous faults corresponding to the target fault groups, so that differentiated management and control on network faults are achieved.
After the suspicious fault group with the number of the affected user assets being larger than the preset asset number is used as the target fault group, the sampling period timer can be started to start a new time counting, after the timing time of the sampling period timer reaches the preset sampling time, the new target alarm information with the information occurrence time within the preset time is determined in the new alarm information, namely, the steps S202-S210 are executed again for the new alarm information, so that the continuous timely discovery processing of the large-area homologous faults is realized.
The fault discovery method provided by the embodiment of the application can be independently applied to the terminal, and can also be integrated in a network management system in the terminal for application, wherein the network management system can be a management system aiming at a metropolitan area network.
In the fault discovery method, suspicious fault groups which have the same geographic information and have larger reporting quantity than the preset reporting quantity are determined in the information occurrence time within the preset time in the plurality of alarm information, and at the moment, because the alarm occurrence time points of the suspicious fault groups are relatively concentrated, the alarm occurrence regions are relatively concentrated and the reporting users can perceive faults, the suspicious fault groups can be indicated to correspond to homologous faults; further, the more the number of the affected user assets is, the larger the influence area is, therefore, suspicious fault groups with the number of the affected user assets being larger than the preset number of the assets are taken as target fault groups, and further determination of large-area homologous faults in the homologous faults is achieved.
In the fault discovery method, target alarm information with information occurrence time within preset time is determined in a plurality of alarm information; grouping the target alarm information according to the geographic information of the target alarm information to obtain alarm information groups of different geographic information; acquiring a user reporting amount of each piece of alarm information in the alarm information group, and screening the alarm information with the user reporting amount being larger than a preset reporting amount to form a suspicious fault group; determining the number of affected user assets for the suspected fault group; and taking the suspicious fault group with the number of the influenced user assets being larger than the preset number of assets as a target fault group. According to the fault discovery method provided by the embodiment, the suspicious fault group with the homologous fault is determined according to the information occurrence time, the geographic information and the user reporting quantity corresponding to the plurality of alarm information, and then the large-area homologous fault is determined according to the number of the affected user assets of the suspicious fault group, so that the target fault group with the large-area homologous fault is determined from the plurality of alarm information, and the large-area homologous fault is accurately and efficiently discovered.
In one embodiment, if the fault type corresponding to the target fault packet is a large-area fault caused by the cutover legacy, the preset time is a first time interval and a second time interval;
The time length of the first time interval is smaller than that of the second time interval;
the second time interval is in a range from the first time endpoint to the second time endpoint, wherein the first time endpoint is a time point when the cutting starts, and the second time endpoint is a time point after the cutting is completed.
The cutting refers to operating the network line and the network equipment in use, and directly affects the service carried on the operating network line and the network equipment.
In this embodiment, since the preset time is a first time interval and a second time interval, and the time length of the first time interval is smaller than the time length of the second time interval, the first time endpoint of the second time interval is the time point when the cutting starts and the second time endpoint is the time point after the cutting is completed, so that the embodiment can find a fault that the alarm information is relatively close to the current time, and can also find a fault caused by cutting legacy.
In one embodiment, the second time point is one of n preset time points, and the n preset time points are distributed in an arithmetic progression;
the method further comprises the following steps: and sequentially acquiring the geographic information of the target alarm information according to n preset time points.
The n preset time points are distributed in an arithmetic progression, and the preset time intervals are used as tolerances. Illustratively, since the conventional cutover start time is 0:00, end time 6:00, therefore, the first time endpoint is 00:00; the second time point comprises 9 preset time points, and the earliest preset time point is 6:05, the preset time interval is 15 minutes, and the second time endpoint may include: 06: 05. 06: 20. 06:35 … …:05 total 9 preset time points.
And sequentially acquiring the geographic information of the target alarm information according to n preset time points, so as to determine whether large-area homologous faults caused by cutting and leaving exist or not after each preset time interval.
In this embodiment, the fault caused by the cutover legacy can be timely found by acquiring the geographical information of the target alarm information at the time points after the completion of the n cutovers to perform the subsequent fault finding step.
Specifically, if the fault type corresponding to the target fault group is a conventional large-area fault, the preset time is a fixed time value, and the preset time may be, for example, 30 minutes or other time, so that the conventional large-area fault is regularly found within 24 hours a day; if the fault type corresponding to the target fault packet is a large-area fault caused by the cutting-over legacy, the preset time is a first time interval and a second time interval, so that the large-area fault caused by the cutting-over legacy is found in a specific time after the cutting-over. By setting two preset times, comprehensive and timely discovery of large-area faults of different types can be realized.
In one embodiment, the method further comprises:
generating an alarm work order for the target fault group, wherein the alarm work order comprises the occurrence time, the alarm level, the geographic information corresponding to the target fault group, the sub-geographic information corresponding to the geographic information, the reporting quantity of the user, the number of assets affecting the user and the alarm quantity;
and sending the warning worksheet to a customer service scheduling system so that the customer service scheduling system performs maintenance scheduling aiming at the network condition corresponding to the target fault group.
The warning level refers to the fault severity degree corresponding to the target fault packet. Further, the warning level can be determined according to the number of the affected user assets corresponding to the target fault group, and the larger the number of the affected user assets is, the larger the influence area is, namely, the more serious the network fault condition is, so that the height of the warning level is in positive correlation with the number of the affected user assets.
The customer service scheduling system performs maintenance scheduling for the network condition corresponding to the target fault packet, and may include: and the client service dispatching system carries out maintenance dispatching of the corresponding dispatching level aiming at the network condition corresponding to the target fault group according to the warning level included in the warning work order, and the warning level and the dispatching level are in positive correlation. Further, the higher the scheduling level, the more scheduling resources allocated by the customer service scheduling system for repairing the network failure corresponding to the target failure packet.
Geographic information, which may be a municipal administration area; when the geographic information is a municipal administrative area, the sub-geographic information corresponding to the geographic information is a district administrative area. For example, if the geographic information is Hangzhou city, the sub-geographic information corresponding to the geographic information may be a district-level administrative district such as a western lake district, a coastal river district, a Shaoshan district, etc. in Hangzhou city.
In this embodiment, by generating, for the target fault packet, an alert work order and an alert number including an occurrence time, an alert level, a geographic information, sub-geographic information corresponding to the geographic information, a user reporting amount, and an number of alert work orders affecting the number of user assets corresponding to the target fault packet, the client service scheduling system can know the specific network condition of the target fault packet in detail, can distinguish network faults with a greater degree of influence on the user according to the alert work order, and can further invoke different resources to perform maintenance scheduling for the network condition corresponding to the target fault packet, thereby implementing differentiated management and control of the network faults.
In one embodiment, the determining the number of affected user assets for the suspected fault group includes:
acquiring the number of associated user numbers of each piece of alarm information in the suspicious fault group;
and summing the number of the associated user numbers of each piece of alarm information to obtain the number of the affected user assets corresponding to the suspicious fault group.
The number of associated user numbers can refer to the number of broadband account numbers under the user name, and also can refer to the number of mobile phone numbers under the user name.
The obtaining of the number of associated user numbers of each alarm message in the suspicious fault group may be obtaining an asset list of the broadband operator, and then retrieving asset conditions of the users within the geographic area in the asset list to obtain the number of associated user numbers.
In this embodiment, the number of associated user numbers of each alarm information in the suspicious fault group is obtained, so that the number of associated user numbers of each alarm information is summed to obtain the number of affected user assets corresponding to the suspicious fault group, and a target fault group with a large influence on the user is accurately determined. .
In one embodiment, the obtaining the number of the associated user numbers of each piece of alarm information in the suspicious fault group includes:
acquiring the number of associated user numbers and the user liveness of each piece of alarm information;
the step of summing the number of the associated user numbers of each piece of alarm information to obtain the number of the affected user assets corresponding to the suspicious fault group comprises the following steps:
summing the number of the associated user of each piece of alarm information to obtain the sum of the associated numbers; and obtaining the number of the affected user assets corresponding to the suspicious fault group according to the sum of the associated numbers in the geographical area and the user liveness.
The user activity level can be determined by at least one of information such as daily average online time length, monthly average online time length, annual average online time length, expenditure condition of network broadband and the like of the user.
Obtaining the number of the affected user assets corresponding to the suspicious fault group according to the association number sum and the user activity, namely respectively distributing a corresponding first weight and a corresponding second weight for the association number sum and the user activity, and then determining the number of the affected user assets according to the weighted summation results of the first weight, the association number sum, the second weight and the user activity; further, the size between the first weight and the second weight may be adjusted according to the actual network management requirement, for example, if the network operator wishes to determine through the number of associated user numbers when determining the area of influence of the network failure, the first weight corresponding to the sum of the associated numbers may be set to be greater than the second weight corresponding to the average of the liveness.
In this embodiment, user liveness is also obtained based on summing the number of associated user numbers of each piece of alarm information, and then the number of affected user assets corresponding to the suspicious fault group is obtained according to the sum of the associated numbers and the user liveness, so that accuracy of determining the target fault group with a large influence on the user is further improved. .
The following describes the application process of the fault discovery method in combination with a detailed embodiment, specifically as follows: as shown in fig. 3, the fault discovery method provided by the application is applied to a terminal and integrated in a network management system in the terminal, wherein the network management system presets a reporting amount of 0 and a preset asset number of K before a preset time is an S time of a current time for a metropolitan area network, and the network management system receives a plurality of alarm information, and determines target alarm information with an information occurrence time within the S time of the current time, namely (current time-S) is less than or equal to the current time, from the plurality of alarm information in order to determine whether the network fault is a large area; next, grouping target alarm information according to geographic information of the target alarm information to obtain m alarm information groups of different geographic information, wherein m is more than or equal to 0 and less than or equal to the number of the geographic information, and the geographic information corresponds to the alarm information groups one by one; then, screening out alarm information with the reporting quantity of the user more than 0 from each alarm information group to form suspicious fault groups, wherein the number of the suspicious fault groups is expressed as n, n is less than or equal to m, and n suspicious fault groups are homologous fault alarm groups;
The homologous fault alarm group has been determined, and in order to further determine the affected user area of the homologous fault alarm group to determine a large-area homologous fault, the number of associated numbers of users in the geographical area range corresponding to the geographical information of each suspicious fault group in the n suspicious fault groups is obtained and summed to obtain the number of affected user assets C corresponding to the n suspicious fault groups 1 、C 2 ……C N The method comprises the steps of carrying out a first treatment on the surface of the Judging the number of the affected user assets C one by one 1 、C 2 ……C N Whether or not it is greater than K; if the suspicious fault group has a target fault group with the number of the affected user assets being greater than K, determining that a large-area homologous fault occurs, generating a warning work order of the large-area homologous fault for the target fault group and sending the warning work order to a customer service dispatching system so as to remind the customer service dispatching system of the occurrence of the large-area homologous fault at the moment, and simultaneously, starting a timer to count time; if the target fault group with the number of the affected user assets being larger than K does not exist in the suspicious fault group, determining that the large-area homologous fault does not occur, starting a timer to count, when the timer counts to reach the sampling period time T, And determining target alarm information with the information occurrence time within the S time of the current time in the plurality of alarm information again, and executing subsequent steps to continuously find out large-area homologous faults.
The scheme of the application determines the homologous fault alarm group in the plurality of alarm information according to the information occurrence time, the geographic information and the user reporting amount of the alarm information, determines the number of the affected user assets according to the number of the association numbers of the users in the geographic area range corresponding to the geographic information of the homologous fault alarm group, and further determines whether the homologous fault alarm group is a large-area homologous fault or not, thereby realizing accurate and efficient determination of the large-area homologous fault.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a fault finding device for realizing the fault finding method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in one or more embodiments of the fault finding device provided below may refer to the limitation of the fault finding method hereinabove, and will not be repeated herein.
In one embodiment, as shown in fig. 4, there is provided a fault finding apparatus including: a target alert information determination module 1002, an alert information grouping determination module 1004, a suspicious fault grouping determination module 1006, an affected user asset count determination module 1008, and a target fault grouping determination module 1010, wherein:
a target alarm information determining module 1002, configured to determine target alarm information with an information occurrence time within a preset time from among a plurality of alarm information;
an alarm information grouping determination module 1004, configured to group the target alarm information according to the geographic information of the target alarm information, so as to obtain alarm information groupings of different geographic information;
the suspicious fault grouping determination module 1006 is configured to obtain a user reporting amount of each piece of alarm information in the alarm information grouping, and screen alarm information with a user reporting amount greater than a preset reporting amount to form a suspicious fault grouping;
An affected user asset count determination module 1008 for determining an affected user asset count for the suspected fault group;
the target fault group determination module 1010 is configured to take as a target fault group a suspicious fault group with an affected user asset number greater than a preset asset number.
In one embodiment, if the fault type corresponding to the target fault packet is a large-area fault caused by the cutover legacy, the preset time is a first time interval and a second time interval;
the time length of the first time interval is smaller than that of the second time interval;
the second time interval is in a range from the first time endpoint to the second time endpoint, wherein the first time endpoint is a time point when the cutting starts, and the second time endpoint is a time point after the cutting is completed.
In one embodiment, the second time point is one of n preset time points, and the n preset time points are distributed in an arithmetic progression;
as shown in fig. 5, the apparatus further includes a geographic information sequential acquisition module 1012, where the geographic information sequential acquisition module 1012 is configured to: and sequentially acquiring the geographic information of the target alarm information according to n preset time points.
In one embodiment, as shown in fig. 5, the apparatus further includes an alert work order generation module 1014, where the alert work order generation module 1014 is configured to:
Generating an alarm work order for the target fault group, wherein the alarm work order comprises the occurrence time, the alarm level, the geographic information corresponding to the target fault group, the sub-geographic information corresponding to the geographic information, the reporting quantity of the user, the number of assets affecting the user and the alarm quantity;
and sending the warning worksheet to a customer service scheduling system so that the customer service scheduling system performs maintenance scheduling aiming at the network condition corresponding to the target fault group.
In one embodiment, the affected user asset count determination module 1008 is further configured to:
acquiring the number of associated user numbers of each piece of alarm information in the suspicious fault grouping alarm information group;
and summing the number of the associated user numbers of each piece of alarm information to obtain the number of the affected user assets corresponding to the suspicious fault group.
In one embodiment, the affected user asset count determination module 1008 is further configured to:
acquiring the number of associated user numbers and the user liveness of each piece of alarm information;
the determining module 1008 is further configured to, in terms of summing the number of associated user numbers of each alert message to obtain the number of affected user assets corresponding to the suspicious fault group:
Summing the number of the associated user of each piece of alarm information to obtain the sum of the associated numbers; and obtaining the number of the affected user assets corresponding to the suspicious fault group according to the sum of the associated numbers in the geographical area and the user liveness.
The respective modules in the above-described fault finding apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 6. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing alarm information data. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a fault finding method.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure of which may be as shown in fig. 7. The computer device includes a processor, a memory, an input/output interface, a communication interface, a display unit, and an input means. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a fault finding method. The display unit of the computer equipment is used for forming a visual picture, and can be a display screen, a projection device or a virtual reality imaging device, wherein the display screen can be a liquid crystal display screen or an electronic ink display screen, the input device of the computer equipment can be a touch layer covered on the display screen, can also be a key, a track ball or a touch pad arranged on a shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in FIG. 7 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In an embodiment, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, carries out the steps of the method embodiments described above.
In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.
It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data need to comply with the related laws and regulations and standards of the related country and region.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.

Claims (10)

1. A method of fault discovery, the method comprising:
determining target alarm information of which the information occurrence time is within a preset time from a plurality of alarm information;
grouping the target alarm information according to the geographic information of the target alarm information to obtain alarm information groups of different geographic information;
acquiring a user reporting amount of each piece of alarm information in the alarm information group, and screening the alarm information with the user reporting amount being larger than a preset reporting amount to form a suspicious fault group;
Determining the number of affected user assets for the suspected fault group;
and taking the suspicious fault group with the number of the influenced user assets being larger than the preset number of assets as a target fault group.
2. The method of claim 1, wherein if the fault type corresponding to the target fault packet is a large-area fault caused by a cutover legacy, the preset time is a first time interval and a second time interval;
the time length of the first time interval is smaller than that of the second time interval;
the second time interval is in a range from a first time endpoint to a second time endpoint, the first time endpoint is a time point when the cutting starts, and the second time endpoint is a time point after the cutting is completed.
3. The method of claim 2, wherein the second time point is one of n preset time points, and the n preset time points are distributed in an arithmetic progression;
the method further comprises the steps of: and sequentially acquiring the geographic information of the target alarm information according to the n preset time points.
4. The method according to claim 1, wherein the method further comprises:
Generating an alarm work order for the target fault group, wherein the alarm work order comprises the occurrence time, the alarm level and the geographic information corresponding to the target fault group, the sub-geographic information corresponding to the geographic information, the user reporting amount, the influence user asset number and the alarm number;
and sending the warning worksheet to a customer service scheduling system so that the customer service scheduling system performs maintenance scheduling aiming at the network condition corresponding to the target fault group.
5. The method of claim 1, wherein the determining the number of affected user assets for the suspected fault group comprises:
acquiring the number of associated user numbers of each piece of alarm information in the suspicious fault group;
and summing the number of the associated user numbers of each piece of alarm information to obtain the number of the affected user assets corresponding to the suspicious fault group.
6. The method of claim 5, wherein the obtaining the number of associated user numbers for each piece of alarm information in the suspicious fault packet comprises:
acquiring the number of the associated user number and the user activity of each piece of alarm information;
the step of summing the number of the associated user numbers of each piece of alarm information to obtain the number of the affected user assets corresponding to the suspicious fault group comprises the following steps:
Summing the number of the associated user number of each piece of alarm information to obtain an associated number sum; and obtaining the number of the affected user assets corresponding to the suspicious fault group according to the sum of the associated numbers in the geographical area and the user liveness.
7. A fault finding apparatus, the apparatus comprising:
the target alarm information determining module is used for determining target alarm information with information occurrence time within preset time in the plurality of alarm information;
the alarm information grouping determination module is used for grouping the target alarm information according to the geographic information of the target alarm information to obtain alarm information groupings of different geographic information;
the suspicious fault grouping determining module is used for acquiring the user reporting amount of each piece of alarm information in the alarm information grouping, and screening the alarm information with the user reporting amount being larger than a preset reporting amount to form suspicious fault grouping;
an affected user asset count determination module for determining an affected user asset count of the suspicious fault group;
and the target fault grouping determination module is used for taking the suspicious fault grouping with the number of the influenced user assets being larger than the preset number of assets as a target fault grouping.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
CN202310969225.7A 2023-08-02 2023-08-02 Fault discovery method, apparatus, device, storage medium, and computer program product Pending CN117135027A (en)

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