CN117479201A - Base station operation and maintenance management method and system - Google Patents
Base station operation and maintenance management method and system Download PDFInfo
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- CN117479201A CN117479201A CN202311797491.2A CN202311797491A CN117479201A CN 117479201 A CN117479201 A CN 117479201A CN 202311797491 A CN202311797491 A CN 202311797491A CN 117479201 A CN117479201 A CN 117479201A
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- 238000007726 management method Methods 0.000 title claims abstract description 57
- 238000012423 maintenance Methods 0.000 title claims abstract description 56
- 230000002159 abnormal effect Effects 0.000 claims abstract description 137
- 238000011156 evaluation Methods 0.000 claims abstract description 131
- 238000012545 processing Methods 0.000 claims abstract description 75
- 238000004458 analytical method Methods 0.000 claims description 45
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- 238000012216 screening Methods 0.000 claims description 14
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/04—Arrangements for maintaining operational condition
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W88/00—Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices
- H04W88/08—Access point devices
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Abstract
The invention provides a base station operation and maintenance management method and system, which belong to the technical field of base station management and specifically comprise the following steps: according to the number of abnormal restarting frequencies of different service data intervals, the problem evaluation quantity and the occurrence time of the abnormal restarting frequencies, the interval problem evaluation quantity of the base station in different service data intervals is determined, the comprehensive problem evaluation quantity of the base station is determined by combining the running time of the base station in different service data intervals, whether operation and maintenance management is needed or not is determined by the data processing busyness and the comprehensive problem evaluation quantity of the base station, the timeliness of operation and maintenance processing is improved, and the influence of faults of the base station on the communication reliability of users is reduced.
Description
Technical Field
The invention belongs to the technical field of base station management, and particularly relates to a base station operation and maintenance management method and system.
Background
The communication base station is used as a key facility for users to acquire communication services, the operation safety and reliability of the communication base station are critical to the operation stability of the whole communication network, but with the rapid speed of the 5G technology, the number of the communication base stations in the communication network is further increased, so that the operation and maintenance management of the base station becomes a technical problem to be solved urgently.
In order to solve the above technical problems, in the prior art, the method for locating the network service based on fiber breaking of the analog base station is usually implemented by identifying the faulty base station and performing operation and maintenance management in a targeted manner, specifically in the invention patent CN202110436164.9, "a locating method, device, equipment and readable storage medium for the faulty base station", by reversely searching the faulty base station through the actual faulty network service, but the following technical problems exist:
once a base station fails, the user communication is interrupted due to the failure of the base station when the targeted operation and maintenance management is performed, so that if the identification of the base station with potential failure risk cannot be realized, the operation reliability of the base station cannot be ensured.
Under different communication pressure conditions, the running power of the communication equipment in the base station is also different, and at the moment, the probability of abnormal automatic restarting of the communication equipment due to the difference of the running power is also different, so that if the potential fault risk of the base station cannot be evaluated by combining the abnormal automatic restarting data of the communication equipment under different communication pressures, the base station with the potential fault risk cannot be accurately identified.
Aiming at the technical problems, the invention provides a base station operation and maintenance management method and system.
Disclosure of Invention
In order to achieve the purpose of the invention, the invention adopts the following technical scheme:
according to one aspect of the present invention, a base station operation and maintenance management method is provided.
The base station operation and maintenance management method is characterized by comprising the following steps:
s1, acquiring the number of times of automatic restarting of a base station in different dates in recording time, determining the basic operation reliability of the base station by combining the environmental temperatures of different dates, and entering the next step when the basic operation reliability does not meet the requirement;
s2, acquiring occurrence time of different automatic restarting times, and carrying out problem evaluation of different automatic restarting times and determination of abnormal restarting frequency according to the processing business data volume of the base station and the environmental temperature in the latest preset time period of the occurrence time of the different automatic restarting times;
s3, based on the processed service data volume at the occurrence time of the abnormal restarting frequency, determining a service data volume interval matched with the abnormal restarting frequency, determining interval problem evaluation volume of the base station in different service data volume intervals according to the number of the abnormal restarting frequency, the problem evaluation volume and the occurrence time of different service data volume intervals, and determining comprehensive problem evaluation volume of the base station by combining the operation time of the base station in different service data volume intervals;
s4, determining the busyness of the data processing of the base station according to the operation time length of the base station in a preset service data volume interval and the processing service data volume in the operation time length, and determining whether operation and maintenance management is needed or not according to the comprehensive problem evaluation quantity.
The invention has the beneficial effects that:
1. the basic operation reliability of the base station is determined according to the number of automatic restarting times of the base station on different dates and the environmental temperature on different dates in the recording time, so that the operation reliability of the base station is estimated from the angle of automatic restarting, the base station with insufficient operation reliability is screened during the fault germination period, and meanwhile, the screening of the number of automatic restarting times caused by overhigh environmental temperature is realized by comprehensively combining the influence of the environmental temperature, and the reliability of the estimation is improved.
2. By performing the problem evaluation of the number of different automatic restarts and the determination of the abnormal restart frequency according to the processing traffic data volume and the ambient temperature of the base station in the latest preset time period of the occurrence time of the number of different automatic restarts, the influence of the external conditions caused by the ambient temperature of the number of different automatic restarts on the operation reliability is considered, and the influence of the processing traffic data volume in a certain time on the operation reliability is also considered, so that the screening and the identification of the abnormal restart from a plurality of angles are realized.
3. The method and the system realize the evaluation of the real running state of the base station from the problem conditions of different business data volume intervals by determining the comprehensive problem evaluation quantity of the base station according to the interval problem evaluation quantity of the different business data volume intervals and the running time of the base station of the different business data volume intervals, fully consider the difference of the correlation degree between the problem severity of the different business data volume intervals and the real running state of the base station, and lay a foundation for the screening of the base station which needs operation and maintenance management in a differentiated mode.
The further technical scheme is that the number of times of automatic restarting of the base station on different dates in the recording time is determined through the reading result of the operation log of the base station.
The further technical scheme is that when the basic operation reliability meets the requirement, the operation state of the base station is determined to be reliable, and the operation and maintenance management of the base station is determined to be unnecessary.
The further technical scheme is that the abnormal restart frequency is determined according to the problem evaluation value of the base station, wherein when the problem evaluation value of the base station is within a preset interval, the analysis frequency corresponding to the problem evaluation value is determined to be the abnormal restart frequency.
The further technical scheme is that the method for determining the comprehensive problem evaluation amount of the base station comprises the following steps:
and determining the weight value of the interval problem evaluation quantity of different service data intervals according to the operation time length of the base station in the different service data intervals and the deviation quantity of the different service data intervals and the rated processing service data of the base station, and determining the comprehensive problem evaluation quantity of the base station by combining the interval problem evaluation quantity of the different service data intervals.
The further technical scheme is that the method for determining whether operation and maintenance management is needed or not by combining the comprehensive problem evaluation quantity specifically comprises the following steps:
and determining the busyness threshold value of the base station according to the comprehensive problem evaluation value, and determining whether operation and maintenance management is needed according to the data processing busyness of the base station.
On the other hand, the invention provides a base station operation and maintenance management system, which adopts the above base station operation and maintenance management method, and is characterized by comprising the following steps:
the system comprises a reliability evaluation module, a restarting frequency division module, a base station evaluation module and an operation and maintenance management module;
the reliability evaluation module is responsible for acquiring the number of times of automatic restarting of the base station in different dates within the recorded time, and determining the basic operation reliability of the base station by combining the environmental temperatures of different dates;
the restarting frequency dividing module is responsible for acquiring occurrence time of different automatic restarting times, and carrying out problem evaluation of different automatic restarting times and determination of abnormal restarting frequency according to the processing business data volume of the base station in the latest preset time period of the occurrence time of the different automatic restarting times and the ambient temperature;
the base station evaluation module is responsible for determining a service data volume interval matched with the abnormal restart frequency based on the processed service data volume at the occurrence time of the abnormal restart frequency, determining interval problem evaluation amounts of the base station in different service data volume intervals according to the number of the abnormal restart frequency, the problem evaluation amounts and the occurrence time of the abnormal restart frequency in different service data volume intervals, and determining comprehensive problem evaluation amounts of the base station by combining the operation time of the base station in the different service data volume intervals;
the operation and maintenance management module is responsible for determining the busyness of the data processing of the base station according to the operation time length of the base station in a preset service data volume interval and the processing service data volume in the operation time length, and determining whether operation and maintenance management is needed or not according to the comprehensive problem evaluation quantity.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the invention as set forth hereinafter.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings;
FIG. 1 is a flow chart of a method of base station operation and maintenance management;
FIG. 2 is a flow chart of a method of determining a base station's base operational reliability;
FIG. 3 is a flow chart of a method of determining a problem assessment amount for different numbers of automatic restarts;
FIG. 4 is a flow chart of a method of determining an inter-zone problem assessment by a base station at different traffic data volume intervals;
fig. 5 is a block diagram of a base station operation and maintenance management system.
Detailed Description
In order to make the technical solutions in the present specification better understood by those skilled in the art, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present specification, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present disclosure.
When a base station needing operation and maintenance management is carried out, the determination of a fault base station is often realized through screening fault characteristics, but once the base station fails, the base station can have influence on communication users of a base station coverage area, so that if the base station with low operation reliability cannot be screened in a fault germination stage, the communication reliability of the base station can be caused to have a certain degree of difference.
In order to solve the technical scheme, the following technical scheme is mainly adopted:
firstly, determining the basic operation reliability of a base station according to the number of automatic restarting times of the base station on different dates and the environmental temperatures of the different dates in the recording time, specifically, screening the dates with low environmental temperature by the environmental temperatures of the different dates, then determining the weight value of the dates with low environmental temperature according to the ratio of the number of automatic restarting times of the dates with low environmental temperature to the preset automatic restarting times, and further determining the basic operation reliability according to the number of the weight values of the dates with high environmental temperature and the basic operation reliability, and entering the next step when the basic operation reliability is not high;
then, determining analysis time periods of different automatic restarting times according to occurrence time of the different automatic restarting times and a preset time period, performing problem evaluation of the different automatic restarting times and determination of abnormal restarting frequency according to processing service data volume and ambient temperature of the analysis time period, specifically, determining problem evaluation of different automatic restarting times according to the product of the ratio of the processing service data volume to the rated processing service data volume of a base station and the ratio of the ambient temperature to the highest value of the rated operating temperature, and taking the frequency of the automatic restarting with larger problem evaluation as the abnormal restarting frequency;
the method comprises the steps of determining a service data volume interval matched with an abnormal restarting frequency based on a processing service data volume at the occurrence time of the abnormal restarting frequency, determining a section problem evaluation volume of a base station in different service data volume intervals according to the number of the abnormal restarting frequency, a problem evaluation volume and the occurrence time of the different service data volume intervals, specifically determining weights of different abnormal restarting frequencies through differences between the occurrence time and the current time and the problem evaluation volume, determining a section problem evaluation volume of the different service data volume intervals according to the number of the weights of the abnormal restarting frequency of the different service data volume intervals and the deviation between the operation time of a base station in the different service data volume intervals and the rated processing data volume, determining weights of the different service data volume intervals, and finally determining a comprehensive problem evaluation volume of the base station through the weights of the different section problem evaluation volumes;
and finally, determining the data processing busyness of the base station through the operation time length of a high-intensity business data volume interval, in which the deviation between the base station and the rated processing data volume is smaller than the preset deviation, in the latest certain time and the processing business data volume in the operation time length, determining the busyness threshold of the base station according to the comprehensive problem evaluation, and determining whether operation and maintenance management is needed according to the data processing busyness of the base station.
Further description will be made from two embodiments.
In order to solve the above-mentioned problems, according to one aspect of the present invention, as shown in fig. 1, there is provided a base station operation and maintenance management method, which is characterized by specifically comprising:
s1, acquiring the number of times of automatic restarting of a base station in different dates in recording time, determining the basic operation reliability of the base station by combining the environmental temperatures of different dates, and entering the next step when the basic operation reliability does not meet the requirement;
the number of automatic restarts of the base station on different dates within the recording time is determined by the reading result of the operation log of the base station.
In a possible embodiment, as shown in fig. 2, the method for determining the basic operational reliability of the base station in the step S1 is:
s11, determining the total number of automatic restarting times of the base station in the recording time based on the number of the automatic restarting times of the base station in different dates in the recording time, judging whether the total number of the automatic restarting times is smaller than a preset number of times, if so, determining that the basic operation reliability of the base station meets the requirement, and if not, entering the next step;
s12, determining the reliable temperature date of the base station through the environmental temperatures of different dates, determining the screening total times of automatic restarting of the base station based on the reliable temperature date, judging whether the screening total times meet the requirement, if so, entering the next step, and if not, determining that the basic operation reliability of the base station does not meet the requirement;
s13, determining the environment temperature abnormality degree values of different reliable temperature dates through the environment temperatures of different dates, determining the reliability evaluation amounts of the different reliable temperature dates by combining the automatic restarting times of the different reliable temperature dates, determining the abnormality dates through the reliability evaluation amounts of the different reliable temperature dates, judging whether the number of the abnormality dates meets the requirement, if so, entering the next step, and if not, determining that the basic operation reliability of the base station does not meet the requirement;
s14, determining the basic operation reliability of the base station through the reliability evaluation quantity and the quantity of the reliable temperature dates, the screening total number of automatic restarting of the base station and the quantity of abnormal dates.
When the basic operation reliability meets the requirement, the operation state of the base station is determined to be reliable, and the operation and maintenance management of the base station is determined to be unnecessary.
S2, acquiring occurrence time of different automatic restarting times, and carrying out problem evaluation of different automatic restarting times and determination of abnormal restarting frequency according to the processing business data volume of the base station and the environmental temperature in the latest preset time period of the occurrence time of the different automatic restarting times;
specifically, the preset time period in the step S1 is determined according to the average value of the traffic data amounts processed by the base station at different times, where the larger the average value of the traffic data amounts processed by the base station at different times is, the longer the preset time period is.
In a possible embodiment, as shown in fig. 3, the method for determining the problem assessment amount of the number of different automatic restarts in the step S1 is:
s21, taking the latest preset time period of the occurrence time of the automatic restarting analysis frequency as an analysis time period of the analysis frequency, determining whether the analysis frequency does not belong to an abnormal restarting frequency according to the ambient temperature of the analysis time period, if so, determining that the analysis frequency does not belong to the abnormal restarting frequency, and if not, entering the next step;
s22, determining the processing business data quantity of the base station at different moments based on the processing business data quantity of the base station in the analysis period, determining the quantity of business peak moments of the base station according to the processing business data quantity and the rated processing business data quantity of the base station, determining the basic business processing busyness of the base station in the analysis period according to the processing business data quantity of the base station in the business peak moments of the base station and the processing business data quantity of the base station in the analysis period, judging whether the basic business processing busyness meets the requirement, if not, entering the next step, and if yes, entering the step S24;
s23, determining continuous duration of different business peak times according to different business peak times, determining business processing busyness of the analysis period according to the maximum value of the continuous duration of the business peak times, the number of the continuous duration longer than a preset duration and the processed business data volume of the business peak times longer than the preset duration, and judging whether the business processing busyness of the analysis period meets the requirement, if yes, entering the next step, and if no, determining that the analysis frequency does not belong to an abnormal restarting frequency;
s24, acquiring the environment temperature of the analysis period, and determining the problem evaluation amount of the base station of the analysis period by combining the business processing busyness of the analysis period and the basic business processing busyness of the base station of the analysis period.
Specifically, the abnormal restart frequency is determined according to the problem evaluation value of the base station, wherein when the problem evaluation value of the base station is within a preset interval, the analysis frequency corresponding to the problem evaluation value is determined to be the abnormal restart frequency.
In another possible embodiment, the method for determining the problem assessment amount of the number of different automatic restarts in the step S1 is as follows:
taking the latest preset time period of the occurrence time of the automatic restarting analysis frequency as an analysis time period of the analysis frequency, and determining that the analysis frequency does not belong to an abnormal restarting frequency when the environmental temperature of the analysis time period is greater than the preset environmental temperature;
when the ambient temperature of the analysis period is not greater than a preset ambient temperature, determining the maximum value of the processing service data volume of the analysis period based on the ambient temperature of the analysis period, and when the processing service data volume of the base station of the analysis period is greater than the maximum value of the processing service data volume, determining that the analysis frequency does not belong to an abnormal restarting frequency;
when the processing traffic data volume of the base station of the analysis period is not greater than the maximum value of the processing traffic data volume and the deviation amount from the maximum value of the processing traffic data volume is smaller than a preset deviation:
determining the processing business data quantity of the base station at different moments based on the processing business data quantity of the base station in the analysis period, determining the quantity of business peak moments of the base station according to the processing business data quantity and the rated processing business data quantity of the base station, and determining the basic business processing busyness of the base station in the analysis period by combining the processing business data quantity of the business peak moments of the base station and the processing business data quantity of the base station in the analysis period;
determining continuous duration of different service peak time according to different service peak time, determining the busyness of the analysis period according to the maximum value of the continuous duration of the service peak time, the number of the continuous duration longer than the preset duration and the processed service data volume of the service peak time longer than the preset duration in the continuous duration, and judging whether the busyness of the service processing in the analysis period meets the requirement, if yes, entering the next step, and if no, determining that the analysis frequency does not belong to abnormal restarting frequency;
acquiring deviation amount of the processing business data volume of the base station in the analysis period and the maximum value of the processing business data volume, and determining the problem evaluation volume of the base station in the analysis period by combining the business processing busyness of the analysis period and the basic business processing busyness of the base station in the analysis period;
when the processing traffic data volume of the base station of the analysis period is not greater than the maximum value of the processing traffic data volume and the deviation amount from the maximum value of the processing traffic data volume is not less than a preset deviation:
and determining the problem evaluation amount of the analysis frequency through the deviation amount of the processing service data amount of the base station of the analysis period and the maximum value of the processing service data amount.
S3, based on the processed service data volume at the occurrence time of the abnormal restarting frequency, determining a service data volume interval matched with the abnormal restarting frequency, determining interval problem evaluation volume of the base station in different service data volume intervals according to the number of the abnormal restarting frequency, the problem evaluation volume and the occurrence time of different service data volume intervals, and determining comprehensive problem evaluation volume of the base station by combining the operation time of the base station in different service data volume intervals;
in a possible embodiment, as shown in fig. 4, the method for determining the interval problem assessment amount of the base station in the step S3 in different traffic data intervals is as follows:
s31, dividing the abnormal restarting frequency into a near abnormal frequency and a far abnormal frequency according to occurrence moments of different abnormal restarting frequencies, determining whether the business data volume interval is abnormal according to the number of the near abnormal frequencies of different business data volume intervals, if so, entering a next step, and if not, entering a step S33;
s32, determining the number and the number proportion of the recent abnormal attention frequency of the recent abnormal frequency according to the problem evaluation quantity of the recent abnormal frequency of different business data volume intervals, determining the recent interval problem evaluation quantity of different business data volume intervals by combining the number of the recent abnormal frequency of the different business data volume intervals and the problem evaluation quantity, determining whether the business data volume intervals are abnormal or not based on the recent interval problem evaluation quantity, if yes, determining the interval problem evaluation quantity of the business data volume intervals based on the recent interval problem evaluation quantity, and if no, entering the next step;
s33, determining the number and the number proportion of the long-term abnormal attention frequency of the long-term abnormal frequency according to the problem evaluation quantity of the long-term abnormal frequency of different business data volume intervals, and determining the long-term interval problem evaluation quantity of different business data volume intervals by combining the number of the long-term abnormal frequency of the different business data volume intervals and the problem evaluation quantity of the different long-term abnormal frequency;
s34, determining different distance duration between the long-term abnormal frequency and the current time and between the near-term abnormal frequency and the current time through the time of the long-term abnormal frequency and the time of the near-term abnormal attention frequency, and determining the interval problem evaluation quantity of the service data interval by combining the long-term interval problem evaluation quantity and the near-term interval problem evaluation quantity of the different service data interval.
Specifically, the abnormal restart frequency is divided into a recent abnormal frequency and a long-term abnormal frequency by occurrence moments of different abnormal restart frequencies, which specifically includes:
dividing the abnormal restarting frequency according to the occurrence time of different abnormal restarting frequencies and a preset time interval to obtain a dividing result, and dividing the abnormal restarting frequency into a near-term abnormal frequency and a far-term abnormal frequency based on the dividing result.
In another possible embodiment, the method for determining the interval problem assessment amount of the base station in the different traffic data interval in the step S3 is as follows:
when the number of the abnormal restarting frequencies of the service data volume interval is smaller than the preset restarting frequency number, determining the interval problem evaluation quantity of the service data volume interval according to the number of the abnormal restarting frequencies;
when the number of the abnormal restarting frequencies in the service data volume interval is not smaller than the preset restarting frequency number, dividing the abnormal restarting frequency into a near-term abnormal frequency and a far-term abnormal frequency through different occurrence moments of the abnormal restarting frequency;
determining the number and the number proportion of the recent abnormal attention frequency of the recent abnormal frequency according to the problem evaluation quantity of the recent abnormal frequency of the different business data volume intervals, determining the recent interval problem evaluation quantity of the different business data volume intervals by combining the number and the problem evaluation quantity of the recent abnormal frequency of the different business data volume intervals, determining whether the business data volume intervals are abnormal or not based on the recent interval problem evaluation quantity, if yes, determining the interval problem evaluation quantity of the business data volume intervals based on the recent interval problem evaluation quantity, and if no, entering the next step;
determining the number and the number proportion of the long-term abnormal attention frequency of the long-term abnormal frequency according to the problem evaluation quantity of the long-term abnormal frequency of different business data volume intervals, and determining the long-term interval problem evaluation quantity of different business data volume intervals by combining the number of the long-term abnormal frequency of the different business data volume intervals and the problem evaluation quantity of the different long-term abnormal frequency;
and determining the distance duration between different long-term abnormal frequencies and the current time and the distance duration between the recent abnormal frequencies and the current time according to the time of the long-term abnormal frequencies and the time of the recent abnormal frequencies, and determining the interval problem assessment amount of the service data interval by combining the long-term interval problem assessment amount and the recent interval problem assessment amount of the different service data interval.
In a possible embodiment, the method for determining the comprehensive problem assessment amount of the base station in the step S3 is:
and determining the weight value of the interval problem evaluation quantity of different service data intervals according to the operation time length of the base station in the different service data intervals and the deviation quantity of the different service data intervals and the rated processing service data of the base station, and determining the comprehensive problem evaluation quantity of the base station by combining the interval problem evaluation quantity of the different service data intervals.
S4, determining the busyness of the data processing of the base station according to the operation time length of the base station in a preset service data volume interval and the processing service data volume in the operation time length, and determining whether operation and maintenance management is needed or not according to the comprehensive problem evaluation quantity.
It can be appreciated that, in combination with the comprehensive problem assessment, determining whether operation and maintenance management is needed specifically includes:
and determining the busyness threshold value of the base station according to the comprehensive problem evaluation value, and determining whether operation and maintenance management is needed according to the data processing busyness of the base station.
On the other hand, as shown in fig. 5, the present invention provides a base station operation and maintenance management system, and the base station operation and maintenance management method is characterized by comprising:
the system comprises a reliability evaluation module, a restarting frequency division module, a base station evaluation module and an operation and maintenance management module;
the reliability evaluation module is responsible for acquiring the number of times of automatic restarting of the base station in different dates within the recorded time, and determining the basic operation reliability of the base station by combining the environmental temperatures of different dates;
the restarting frequency dividing module is responsible for acquiring occurrence time of different automatic restarting times, and carrying out problem evaluation of different automatic restarting times and determination of abnormal restarting frequency according to the processing business data volume of the base station in the latest preset time period of the occurrence time of the different automatic restarting times and the ambient temperature;
the base station evaluation module is responsible for determining a service data volume interval matched with the abnormal restart frequency based on the processed service data volume at the occurrence time of the abnormal restart frequency, determining interval problem evaluation amounts of the base station in different service data volume intervals according to the number of the abnormal restart frequency, the problem evaluation amounts and the occurrence time of the abnormal restart frequency in different service data volume intervals, and determining comprehensive problem evaluation amounts of the base station by combining the operation time of the base station in the different service data volume intervals;
the operation and maintenance management module is responsible for determining the busyness of the data processing of the base station according to the operation time length of the base station in a preset service data volume interval and the processing service data volume in the operation time length, and determining whether operation and maintenance management is needed or not according to the comprehensive problem evaluation quantity.
Through the above embodiments, the present invention has the following beneficial effects:
1. the basic operation reliability of the base station is determined according to the number of automatic restarting times of the base station on different dates and the environmental temperature on different dates in the recording time, so that the operation reliability of the base station is estimated from the angle of automatic restarting, the base station with insufficient operation reliability is screened during the fault germination period, and meanwhile, the screening of the number of automatic restarting times caused by overhigh environmental temperature is realized by comprehensively combining the influence of the environmental temperature, and the reliability of the estimation is improved.
2. By performing the problem evaluation of the number of different automatic restarts and the determination of the abnormal restart frequency according to the processing traffic data volume and the ambient temperature of the base station in the latest preset time period of the occurrence time of the number of different automatic restarts, the influence of the external conditions caused by the ambient temperature of the number of different automatic restarts on the operation reliability is considered, and the influence of the processing traffic data volume in a certain time on the operation reliability is also considered, so that the screening and the identification of the abnormal restart from a plurality of angles are realized.
3. The method and the system realize the evaluation of the real running state of the base station from the problem conditions of different business data volume intervals by determining the comprehensive problem evaluation quantity of the base station according to the interval problem evaluation quantity of the different business data volume intervals and the running time of the base station of the different business data volume intervals, fully consider the difference of the correlation degree between the problem severity of the different business data volume intervals and the real running state of the base station, and lay a foundation for the screening of the base station which needs operation and maintenance management in a differentiated mode.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus, devices, non-volatile computer storage medium embodiments, the description is relatively simple, as it is substantially similar to method embodiments, with reference to the section of the method embodiments being relevant.
The foregoing describes specific embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
The foregoing is merely one or more embodiments of the present description and is not intended to limit the present description. Various modifications and alterations to one or more embodiments of this description will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, or the like, which is within the spirit and principles of one or more embodiments of the present description, is intended to be included within the scope of the claims of the present description.
Claims (11)
1. The base station operation and maintenance management method is characterized by comprising the following steps:
acquiring the number of times of automatic restarting of a base station in different dates within a recording time, determining the basic operation reliability of the base station by combining the environmental temperatures of different dates, and entering the next step when the basic operation reliability does not meet the requirement;
acquiring occurrence moments of different automatic restarting times, and carrying out problem evaluation of different automatic restarting times and determination of abnormal restarting frequency according to the processing business data volume of a base station in the latest preset time period of the occurrence moments of the different automatic restarting times and the environmental temperature;
determining a service data volume interval matched with the abnormal restarting frequency based on the processed service data volume at the occurrence time of the abnormal restarting frequency, determining interval problem evaluation quantity of the base station in different service data volume intervals according to the quantity and the problem evaluation quantity of the abnormal restarting frequency in different service data volume intervals and the occurrence time, and determining comprehensive problem evaluation quantity of the base station by combining the operation time of the base station in different service data volume intervals;
and determining the data processing busyness of the base station according to the operation time length of the base station in a preset service data volume interval and the processing service data volume in the operation time length, and determining whether operation and maintenance management is needed or not according to the comprehensive problem evaluation quantity.
2. The base station operation and maintenance management method according to claim 1, wherein the number of automatic restarts of the base station at different dates within a recording time is determined by a reading result of an operation log of the base station.
3. The base station operation and maintenance management method according to claim 1, wherein the method for determining the basic operation reliability of the base station is:
determining the total number of automatic restarting times of the base station in the recording time based on the number of the automatic restarting times of the base station in different dates in the recording time, judging whether the total number of the automatic restarting times is smaller than a preset number of times, if so, determining that the basic operation reliability of the base station meets the requirement, and if not, entering the next step;
determining the reliable temperature date of the base station through the environment temperatures of different dates, determining the screening total times of automatic restarting of the base station based on the reliable temperature date, judging whether the screening total times meet the requirement, if so, entering the next step, and if not, determining that the basic operation reliability of the base station does not meet the requirement;
determining the environment temperature abnormality degree values of different reliable temperature dates through the environment temperatures of different dates, determining the reliability evaluation amounts of different reliable temperature dates by combining the automatic restarting times of the different reliable temperature dates, determining the abnormal dates through the reliability evaluation amounts of different reliable temperature dates, judging whether the quantity of the abnormal dates meets the requirements, if so, entering the next step, and if not, determining that the basic operation reliability of the base station does not meet the requirements;
the basic operation reliability of the base station is determined through the reliability evaluation quantity of different reliable temperature dates, the number of the reliable temperature dates, the screening total number of automatic restarting of the base station and the number of abnormal dates.
4. The operation and maintenance management method of a base station according to claim 1, wherein when the basic operation reliability satisfies a requirement, it is determined that the operation state of the base station is reliable, and it is determined that operation and maintenance management of the base station is not necessary.
5. The operation and maintenance management method of a base station according to claim 1, wherein the preset time period is determined according to an average value of the amount of the processed service data of the base station at different times, and the larger the average value of the amount of the processed service data of the base station at different times is, the longer the preset time period is.
6. The method for operation and maintenance management of a base station according to claim 1, wherein the abnormal restart frequency is determined according to a problem evaluation value of the base station, and wherein when the problem evaluation value of the base station is within a preset interval, an analysis frequency corresponding to the problem evaluation value is determined as the abnormal restart frequency.
7. The base station operation and maintenance management method according to claim 1, wherein the method for determining the interval problem evaluation amount of the base station in different traffic data intervals is as follows:
s31, dividing the abnormal restarting frequency into a near abnormal frequency and a far abnormal frequency according to occurrence moments of different abnormal restarting frequencies, determining whether the business data volume interval is abnormal according to the number of the near abnormal frequencies of different business data volume intervals, if so, entering a next step, and if not, entering a step S33;
s32, determining the number and the number proportion of the recent abnormal attention frequency of the recent abnormal frequency according to the problem evaluation quantity of the recent abnormal frequency of different business data volume intervals, determining the recent interval problem evaluation quantity of different business data volume intervals by combining the number of the recent abnormal frequency of the different business data volume intervals and the problem evaluation quantity, determining whether the business data volume intervals are abnormal or not based on the recent interval problem evaluation quantity, if yes, determining the interval problem evaluation quantity of the business data volume intervals based on the recent interval problem evaluation quantity, and if no, entering the next step;
s33, determining the number and the number proportion of the long-term abnormal attention frequency of the long-term abnormal frequency according to the problem evaluation quantity of the long-term abnormal frequency of different business data volume intervals, and determining the long-term interval problem evaluation quantity of different business data volume intervals by combining the number of the long-term abnormal frequency of the different business data volume intervals and the problem evaluation quantity of the different long-term abnormal frequency;
s34, determining different distance duration between the long-term abnormal frequency and the current time and between the near-term abnormal frequency and the current time through the time of the long-term abnormal frequency and the time of the near-term abnormal attention frequency, and determining the interval problem evaluation quantity of the service data interval by combining the long-term interval problem evaluation quantity and the near-term interval problem evaluation quantity of the different service data interval.
8. The base station operation and maintenance management method according to claim 7, wherein the abnormal restart frequency is divided into a near-term abnormal frequency and a far-term abnormal frequency by occurrence moments of different abnormal restart frequencies, specifically comprising:
dividing the abnormal restarting frequency according to the occurrence time of different abnormal restarting frequencies and a preset time interval to obtain a dividing result, and dividing the abnormal restarting frequency into a near-term abnormal frequency and a far-term abnormal frequency based on the dividing result.
9. The base station operation and maintenance management method according to claim 1, wherein the method for determining the comprehensive problem assessment amount of the base station is as follows:
and determining the weight value of the interval problem evaluation quantity of different service data intervals according to the operation time length of the base station in the different service data intervals and the deviation quantity of the different service data intervals and the rated processing service data of the base station, and determining the comprehensive problem evaluation quantity of the base station by combining the interval problem evaluation quantity of the different service data intervals.
10. The method for operation and maintenance management of a base station according to claim 1, wherein determining whether operation and maintenance management is required in combination with the comprehensive problem assessment comprises:
and determining the busyness threshold value of the base station according to the comprehensive problem evaluation value, and determining whether operation and maintenance management is needed according to the data processing busyness of the base station.
11. A base station operation and maintenance management system, adopting a base station operation and maintenance management method according to any one of claims 1-10, characterized in that it specifically comprises:
the system comprises a reliability evaluation module, a restarting frequency division module, a base station evaluation module and an operation and maintenance management module;
the reliability evaluation module is responsible for acquiring the number of times of automatic restarting of the base station in different dates within the recorded time, and determining the basic operation reliability of the base station by combining the environmental temperatures of different dates;
the restarting frequency dividing module is responsible for acquiring occurrence time of different automatic restarting times, and carrying out problem evaluation of different automatic restarting times and determination of abnormal restarting frequency according to the processing business data volume of the base station in the latest preset time period of the occurrence time of the different automatic restarting times and the ambient temperature;
the base station evaluation module is responsible for determining a service data volume interval matched with the abnormal restart frequency based on the processed service data volume at the occurrence time of the abnormal restart frequency, determining interval problem evaluation amounts of the base station in different service data volume intervals according to the number of the abnormal restart frequency, the problem evaluation amounts and the occurrence time of the abnormal restart frequency in different service data volume intervals, and determining comprehensive problem evaluation amounts of the base station by combining the operation time of the base station in the different service data volume intervals;
the operation and maintenance management module is responsible for determining the busyness of the data processing of the base station according to the operation time length of the base station in a preset service data volume interval and the processing service data volume in the operation time length, and determining whether operation and maintenance management is needed or not according to the comprehensive problem evaluation quantity.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117970036A (en) * | 2024-03-29 | 2024-05-03 | 杭州欣美成套电器制造有限公司 | Power distribution network cable equipment state evaluation method and system |
| CN118411148A (en) * | 2024-05-10 | 2024-07-30 | 国网河南省电力公司信息通信分公司 | A method and system for automatically generating inspection strategies for operation and maintenance management |
| CN119166485A (en) * | 2024-11-19 | 2024-12-20 | 杭银消费金融股份有限公司 | A method and system for evaluating and analyzing the operating status of a processing system |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107517472A (en) * | 2017-08-10 | 2017-12-26 | 京信通信系统(中国)有限公司 | A kind of method for protecting base station state and base station |
| US20180107826A1 (en) * | 2016-10-18 | 2018-04-19 | Qualcomm Incorporated | Techniques for trusted application fuzzing mitigation |
| US20180121312A1 (en) * | 2016-10-28 | 2018-05-03 | Advanced Micro Devices, Inc. | System and method for energy reduction based on history of reliability of a system |
| CN108334433A (en) * | 2018-01-31 | 2018-07-27 | 努比亚技术有限公司 | Restart localization method, mobile terminal and readable storage medium storing program for executing based on power managed |
| CN109165110A (en) * | 2018-07-27 | 2019-01-08 | 努比亚技术有限公司 | Mobile terminal restarts localization method, mobile terminal and computer readable storage medium |
| US20190173396A1 (en) * | 2016-12-26 | 2019-06-06 | Hitachi Industrial Equipment Systems Co., Ltd. | Power Conversion Device and Power Conversion Device System |
| CN110290546A (en) * | 2019-06-21 | 2019-09-27 | 京信通信系统(中国)有限公司 | Base station restart positioning method, device, base station equipment and storage medium |
| CN113868021A (en) * | 2021-09-16 | 2021-12-31 | 上海新炬网络信息技术股份有限公司 | A method based on detecting service status and automatically restarting |
| CN114143619A (en) * | 2021-11-25 | 2022-03-04 | 新华三技术有限公司成都分公司 | Base station over-temperature protection method and device and electronic equipment |
| CN115913898A (en) * | 2023-01-09 | 2023-04-04 | 浙江数思信息技术有限公司 | Internet of things terminal fault diagnosis method and medium based on machine learning algorithm |
| CN116106656A (en) * | 2022-11-18 | 2023-05-12 | 国网河南省电力公司 | A method for auxiliary identification of electrical equipment defects based on mobile application terminals |
| WO2023130974A1 (en) * | 2022-01-07 | 2023-07-13 | 华为技术有限公司 | Fault locating method and apparatus |
-
2023
- 2023-12-26 CN CN202311797491.2A patent/CN117479201B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180107826A1 (en) * | 2016-10-18 | 2018-04-19 | Qualcomm Incorporated | Techniques for trusted application fuzzing mitigation |
| US20180121312A1 (en) * | 2016-10-28 | 2018-05-03 | Advanced Micro Devices, Inc. | System and method for energy reduction based on history of reliability of a system |
| US20190173396A1 (en) * | 2016-12-26 | 2019-06-06 | Hitachi Industrial Equipment Systems Co., Ltd. | Power Conversion Device and Power Conversion Device System |
| CN107517472A (en) * | 2017-08-10 | 2017-12-26 | 京信通信系统(中国)有限公司 | A kind of method for protecting base station state and base station |
| CN108334433A (en) * | 2018-01-31 | 2018-07-27 | 努比亚技术有限公司 | Restart localization method, mobile terminal and readable storage medium storing program for executing based on power managed |
| CN109165110A (en) * | 2018-07-27 | 2019-01-08 | 努比亚技术有限公司 | Mobile terminal restarts localization method, mobile terminal and computer readable storage medium |
| CN110290546A (en) * | 2019-06-21 | 2019-09-27 | 京信通信系统(中国)有限公司 | Base station restart positioning method, device, base station equipment and storage medium |
| CN113868021A (en) * | 2021-09-16 | 2021-12-31 | 上海新炬网络信息技术股份有限公司 | A method based on detecting service status and automatically restarting |
| CN114143619A (en) * | 2021-11-25 | 2022-03-04 | 新华三技术有限公司成都分公司 | Base station over-temperature protection method and device and electronic equipment |
| WO2023130974A1 (en) * | 2022-01-07 | 2023-07-13 | 华为技术有限公司 | Fault locating method and apparatus |
| CN116106656A (en) * | 2022-11-18 | 2023-05-12 | 国网河南省电力公司 | A method for auxiliary identification of electrical equipment defects based on mobile application terminals |
| CN115913898A (en) * | 2023-01-09 | 2023-04-04 | 浙江数思信息技术有限公司 | Internet of things terminal fault diagnosis method and medium based on machine learning algorithm |
Non-Patent Citations (2)
| Title |
|---|
| 陈百利;: "基站动力综合保障系统研究", 电源世界, no. 03, 31 March 2017 (2017-03-31) * |
| 高建敏;: "客户侧质差智能网关自动识别重启方案", 中国新通信, no. 18, 20 September 2020 (2020-09-20) * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117970036A (en) * | 2024-03-29 | 2024-05-03 | 杭州欣美成套电器制造有限公司 | Power distribution network cable equipment state evaluation method and system |
| CN118411148A (en) * | 2024-05-10 | 2024-07-30 | 国网河南省电力公司信息通信分公司 | A method and system for automatically generating inspection strategies for operation and maintenance management |
| CN118411148B (en) * | 2024-05-10 | 2025-08-19 | 国网河南省电力公司信息通信分公司 | Automatic inspection strategy generation method and system for operation and maintenance management |
| CN119166485A (en) * | 2024-11-19 | 2024-12-20 | 杭银消费金融股份有限公司 | A method and system for evaluating and analyzing the operating status of a processing system |
| CN119166485B (en) * | 2024-11-19 | 2025-03-18 | 杭银消费金融股份有限公司 | A method and system for evaluating and analyzing the operating status of a processing system |
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