5G communication base station equipment safety operation and maintenance management method based on AIOT

Abstract

The invention relates to the field of safety operation and maintenance, and discloses an AIOT-based 5G communication base station equipment safety operation and maintenance management method, which comprises the following steps of: firstly, acquiring operation and maintenance data of a 5G communication base station in a current region in real time through an Internet of Things sensor network; secondly, the collected operation and maintenance data are transmitted to a data processing center in a wired or wireless mode; then, cleaning, integrating and storing the operation and maintenance data received by the data processing center to form standardized data assets; afterwards, operation state analysis and early warning analysis are carried out on the standardized data assets, an abnormal operation coefficient and a fault early warning coefficient are obtained through calculation, and overall abnormality judgment is carried out on the 5G communication base station in the current region according to the abnormal operation coefficient and the fault early warning coefficient; and finally, adjusting the patrol frequency of the 5G communication base station with abnormal operation according to a judgment result, and carrying out fault early warning on the 5G communication base station with a fault trend.

Description

Technical Field

[0001] The present invention relates to the field of secure operation and maintenance, and specifically to a secure operation and maintenance management method for 5G communication base station equipment based on AIOT. Background Art

[0002] As the number and scale of 5G base stations increase, base station operation and maintenance management faces many challenges. On the one hand, base stations need to cover a wider area, including sparsely populated mountainous areas and rural areas, which increases the difficulty and cost of operation and maintenance. On the other hand, different levels of base stations have different operation and maintenance requirements. For example, VIP base stations require real-time monitoring and remote monitoring, while low-level base stations may require regular inspections. In addition, traditional operation and maintenance methods such as manual tower climbing monitoring are not only dangerous, but also inefficient.

[0003] AIOT, or artificial intelligence Internet of Things technology, integrates the data analysis and processing capabilities of artificial intelligence with the extensive perception and connection characteristics of the Internet of Things, opening up a new path for the safe operation and maintenance of 5G communication base station equipment. 5G communication base stations transmit signals from base station equipment to antennas through transmission cables, and then radiate them to the surrounding environment. The selection and quality of transmission cables directly affect the integrity and stability of the signals, and are an important part of 5G communication base stations.

[0004] Although AIOT technology provides real-time monitoring and early warning functions, some 5G communication base station equipment security operation and maintenance management systems still rely on inspections by operation and maintenance personnel to discover problems, and lack proactive early warning and intelligent decision-making capabilities; especially when responding to sudden changes in the external environment, the processing capacity of the operation and maintenance system is limited. Summary of the invention

[0005] The purpose of the present invention is to provide a 5G communication base station equipment security operation and maintenance management method based on AIOT to solve the above technical problems.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A 5G communication base station equipment security operation and maintenance management method based on AIOT, comprising:

[0008] S1. Collect the operation and maintenance data of 5G communication base stations in the current area in real time through the IoT sensor network;

[0009] S2, transmitting the collected operation and maintenance data to the data processing center via wired or wireless means;

[0010] S3. Clean, integrate and store the operation and maintenance data received by the data processing center to form standardized data assets;

[0011] S4. Perform operation status analysis and early warning analysis on the standardized data assets, and calculate the abnormal operation coefficient and the fault early warning coefficient respectively. According to the abnormal operation coefficient and the fault early warning coefficient, make an overall abnormal judgment on the 5G communication base stations in the current area;

[0012] S5. Adjust the patrol frequency of 5G communication base stations with abnormal operation according to the judgment results, and issue fault warnings for 5G communication base stations with fault trends.

[0013] As a further technical solution, the operation and maintenance data includes: transmission cable operation data, equipment operation data and environmental data around the transmission cable.

[0014] As a further technical solution, the process of obtaining the abnormal operation coefficient includes:

[0015] Take each 5G communication base station in the current area as the center and divide the set range into a monitoring area;

[0016] The first The transmission cable operation data, equipment operation data and environmental data around the transmission cable processed in each monitoring area are used to obtain the transmission cable operation coefficient according to the preset rules. , Equipment operation coefficient And transmission cable environmental factor Then, substitute into the following formula:

[0017] Calculate the first Abnormal operation coefficient of monitoring area ;

[0018] In the formula is any sampling point; is the total number of sampling points; , , are the transmission cable operation coefficients of any sampling point , Equipment operation coefficient And transmission cable environmental factor Observed value of , , are the average values ​​of transmission cable operation coefficient, equipment operation coefficient and transmission cable environment coefficient, respectively. , , is the weight factor;

[0019] The abnormal operation coefficient of each monitoring area Substitute into the formula: Calculate the abnormal operation coefficient of the current area ;

[0020] In the formula For the The weight coefficient of each monitoring area is For the A judgment function to determine whether there is a fault trend in a monitoring area. is the total number of monitored areas.

[0021] As a further technical solution, the The judgment function of whether there is a fault trend in the monitoring area The expression is:

[0022] Jordi If there is a failure trend in the monitoring area, ;

[0023] In the formula is the number of monitoring areas with failure trends, , Respectively The maximum fault warning coefficient and minimum fault warning coefficient of each monitoring area, is the preset proportional coefficient;

[0024] Jordi If there is no failure trend in the monitoring area, .

[0025] As a further technical solution, the process of determining whether there is a fault trend in the monitoring area includes:

[0026] Obtain the time-varying curves of the transmission cable operation coefficient, equipment operation coefficient and transmission cable environmental coefficient of each monitoring area respectively , , ;

[0027] Substituting into the formula:

[0028] ;

[0029] Calculate the fault warning coefficient of each monitoring area ;

[0030] In the formula , are the left and right time points of the detection period, , , It is a reference curve obtained based on historical data analysis;

[0031] Fault warning coefficient With the preset fault warning threshold For comparison, if , then it is judged that there is a fault trend in the current monitoring area. If , it is judged that there is no fault trend in the current monitoring area.

[0032] As a further technical solution, the process of overall abnormality judgment of 5G communication base stations in the current area includes:

[0033] The calculated abnormal operation coefficient of the current area Bring in middle; The abnormal operation threshold preset for the system;

[0034] like , it is judged that there is no abnormal operation of the 5G communication base station in the current area as a whole;

[0035] like , it is judged that the overall operation of 5G communication base stations in the current area is abnormal.

[0036] As a further technical solution, the process of obtaining the transmission cable operation coefficient and the transmission cable environment coefficient in the current monitoring area is as follows:

[0037] The collected line swing amplitude , Minimum distance to surrounding objects , Cable sag Substituting into the formula: The transmission cable operation coefficient of the current monitoring area is calculated ;

[0038] In the formula , , are influencing factors and are constants. ;

[0039] The various environmental parameters collected in real time Substituting into the formula: The transmission cable environmental coefficient of the current monitoring area is calculated ;

[0040] In the formula is the total number of environmental parameters, For the The influencing factors of environmental parameters, is the reference value of the corresponding environmental parameter in the current monitoring area, are the observed values ​​of various environmental parameters;

[0041] The equipment operating factor The acquisition process is as follows: input the operating parameters of the equipment in each monitoring area into the pre-trained recurrent neural network model, and output the operating coefficient of the equipment .

[0042] As a further technical solution, the working process of S5 is:

[0043] If the overall operation of 5G communication base stations in the current area is abnormal, the monitoring area with failure trends will be marked;

[0044] Provide fault warnings for 5G communication base stations in the current monitoring area, increase the patrol frequency of the current monitoring area by 2 times, and increase the patrol frequency of the current area by 1 time;

[0045] If there is no overall operating abnormality in the 5G communication base stations in the current area, the monitoring areas with failure trends will be marked;

[0046] Issue fault warnings for 5G communication base stations in the current monitoring area, and increase the patrol frequency of the current monitoring area by 100%.

[0047] Beneficial effects of the present invention:

[0048] The present invention realizes comprehensive, real-time and accurate monitoring of the operating status of transmission cables in 5G communication base stations through an integrated operation and maintenance data management solution. Starting from data collection, it can capture the operating data of transmission cables, equipment status and base station surrounding environment information in real time, ensuring the integrity and accuracy of the data; then by accurately calculating the abnormal operation coefficient and the fault warning coefficient, the system can promptly discover the operating abnormalities and potential fault trends of 5G communication base stations. The early warning mechanism improves the accuracy and timeliness of fault warnings, and provides valuable response time for operation and maintenance personnel; finally, according to the analysis results, the operation and maintenance strategy can be flexibly adjusted, the patrol frequency can be optimized according to actual needs, and warnings can be issued for transmission cables with failure risks, which not only improves the pertinence and efficiency of patrol work, but also helps operation and maintenance personnel to take timely measures to prevent the occurrence of failures. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The present invention will be further described below in conjunction with the accompanying drawings.

[0050] Figure 1 It is a diagram of the method steps of the present invention. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] See also Figure 1 As shown, the present invention is a 5G communication base station equipment security operation and maintenance management method based on AIOT, comprising:

[0053] S1. Collect the operation and maintenance data of 5G communication base stations in the current area in real time through the IoT sensor network;

[0054] S2, transmitting the collected operation and maintenance data to the data processing center via wired or wireless means;

[0055] S3. Clean, integrate and store the operation and maintenance data received by the data processing center to form standardized data assets;

[0056] S4. Perform operation status analysis and early warning analysis on the standardized data assets, and calculate the abnormal operation coefficient and the fault early warning coefficient respectively. According to the abnormal operation coefficient and the fault early warning coefficient, make an overall abnormal judgment on the 5G communication base stations in the current area;

[0057] S5. Adjust the patrol frequency of 5G communication base stations with abnormal operation according to the judgment results, and issue fault warnings for 5G communication base stations with fault trends.

[0058] In this embodiment, by integrating operation and maintenance data collection, transmission, processing, analysis and application, comprehensive, real-time and accurate monitoring and management of the operation status of transmission cables are realized, and the operation data, equipment operation data and surrounding environment data of transmission cables in 5G communication base stations can be collected in real time, ensuring the comprehensiveness and accuracy of the data; at the same time, the data is efficiently transmitted to the data processing center by wired or wireless means, realizing the rapid collection and processing of data; the received data is then cleaned, integrated and standardized to form high-quality data assets, providing a reliable basis for subsequent analysis; subsequently, through operation status analysis and early warning analysis, the abnormal operation coefficient and fault early warning coefficient can be accurately calculated, so as to timely discover the operation abnormality and fault trend of 5G communication base stations, effectively improving the accuracy and timeliness of fault early warning; finally, according to the analysis results, the patrol frequency is flexibly adjusted, and the transmission cables with fault trends are warned, which not only improves the pertinence and efficiency of the patrol work, but also helps to take timely measures to prevent faults from occurring, ensure the safe and stable operation of the 5G communication network, and effectively improve the intelligence and refinement of the operation and maintenance management of 5G communication base stations.

[0059] The operation and maintenance data includes: transmission cable operation data, equipment operation data and environmental data around the transmission cable.

[0060] The process of obtaining the abnormal operation coefficient includes:

[0061] Take each 5G communication base station in the current area as the center and divide the set range into a monitoring area;

[0062] The first The transmission cable operation data, equipment operation data and environmental data around the transmission cable processed in each monitoring area are used to obtain the transmission cable operation coefficient according to the preset rules. , Equipment operation coefficient And transmission cable environmental factor Then, substitute into the following formula:

[0063] Calculate the first Abnormal operation coefficient of monitoring area ;

[0064] In the formula is any sampling point; is the total number of sampling points; , , are the transmission cable operation coefficients of any sampling point , Equipment operation coefficient And transmission cable environmental factor Observed value of , , are the average values ​​of transmission cable operation coefficient, equipment operation coefficient and transmission cable environment coefficient, respectively. , , is the weight factor;

[0065] The abnormal operation coefficient of each monitoring area Substitute into the formula: Calculate the abnormal operation coefficient of the current area ;

[0066] In the formula For the The weight coefficient of each monitoring area is For the A judgment function to determine whether there is a fault trend in a monitoring area. is the total number of monitored areas.

[0067] The present invention provides a method for obtaining the abnormal operation coefficient of each 5G communication base station. First, by pre-dividing a plurality of monitoring areas, the situation in each monitoring area is detected in a targeted manner, and then the formula is used:

[0068] Calculate the first Abnormal operation coefficient of monitoring area , substitute Calculate the abnormal operation coefficient of the current area ; Obviously, it can be seen from the formula that the larger the abnormal operation coefficient of each monitoring area, the greater the possibility that there is a fault in the 5G communication base station in the monitoring area. By calculating the variance of three parameters: the operation of the transmission cable itself, the surrounding environment and the operation of the equipment, a more accurate abnormal operation of the 5G communication base station can be obtained. Compared with the technical solution that only considers the operation of the 5G communication base station itself, the present invention comprehensively considers the external environment and the operation of the equipment, and comprehensively reflects the actual operation of the 5G communication base station from multiple aspects, thereby improving the effective utilization of operation and maintenance data assets and providing a solid data foundation for the subsequent adjustment of the patrol frequency.

[0069] The process of determining whether there is a fault trend in the monitoring area includes:

[0070] Obtain the time-varying curves of the transmission cable operation coefficient, equipment operation coefficient and transmission cable environmental coefficient of each monitoring area respectively , , ;

[0071] Substituting into the formula:

[0072] ;

[0073] Calculate the fault warning coefficient of each monitoring area ;

[0074] In the formula , are the left and right time points of the detection period, , , It is a reference curve obtained based on historical data analysis;

[0075] Fault warning coefficient With the preset fault warning threshold For comparison, if , then it is judged that there is a fault trend in the current monitoring area. If , it is judged that there is no fault trend in the current monitoring area;

[0076] The said The judgment function of whether there is a fault trend in the monitoring area The expression is:

[0077] Jordi If there is a failure trend in the monitoring area, ;

[0078] In the formula is the number of monitoring areas with failure trends, , Respectively The maximum fault warning coefficient and minimum fault warning coefficient of each monitoring area, is the preset proportional coefficient;

[0079] Jordi If there is no failure trend in the monitoring area, .

[0080] The present invention provides a method for judging whether there is a fault trend of a 5G communication base station in each monitoring area, and dynamically adjusts the degree of influence on the abnormal operation coefficient of each monitoring area according to the judgment result, so as to accurately reflect the abnormal operation situation in the current area; the specific process is as follows:

[0081] By formula The fault warning coefficient of each monitoring area is calculated Obviously, if The larger the value, the greater the deviation between the operation coefficient curve of the transmission cable and the reference curve. For example, the greater the deviation between the line swing amplitude, the minimum surrounding object distance, and the cable sag and the reference value, the higher the probability that the line will have a wind deflection flashover fault, an ice load fault, or an overload fault; therefore, the greater the probability that the transmission cable will have an operation fault; The larger the value, the greater the deviation between the equipment's operating coefficient curve and the reference curve, and therefore the greater the probability that the transmission cable will have an operating failure. The larger the value is, the greater the deviation between the transmission cable environmental coefficient curve and the reference curve is. For example, the lower the temperature, the easier it is for the transmission cable to freeze, or the higher the temperature, the easier it is for the insulation to age. Therefore, the greater the probability of an operational failure of the transmission cable. The fault warning coefficient of each monitoring area is obtained by combining the above three aspects of deviation, which can actually reflect the fault development trend of each monitoring area, reduce the probability of false alarm of subsequent transmission cable fault warnings, and provide sufficient response time for technical maintenance of transmission cables.

[0082] The process of overall abnormality judgment of 5G communication base stations in the current area includes:

[0083] The calculated abnormal operation coefficient of the current area Bring in middle; The abnormal operation threshold preset for the system;

[0084] like , it is judged that there is no abnormal operation of the 5G communication base station in the current area as a whole;

[0085] like , it is judged that the overall operation of 5G communication base stations in the current area is abnormal.

[0086] In this embodiment, through the above technical solution, the actually calculated overall abnormal operation coefficient of the 5G communication base station in the current area can be compared with the abnormal operation threshold preset by the system, and a judgment is made as to whether there is any abnormal operation in the entire current area based on the comparison. Obviously, if , it indicates that the 5G communication base station in the current area is operating abnormally as a whole. , it is judged that there is no operating abnormality in the overall 5G communication base station in the current area.

[0087] The process of obtaining the transmission cable operation coefficient and the transmission cable environment coefficient in the current monitoring area is as follows:

[0088] The collected line swing amplitude , Minimum distance to surrounding objects , Cable sag Substituting into the formula: The transmission cable operation coefficient of the current monitoring area is calculated Through the above method, it is obvious that the larger the line swing amplitude, the more abnormal the transmission cable is, and the smaller the minimum surrounding object distance is, the more abnormal the transmission cable is and the more likely it is to fail. The larger it is, the greater the load on the transmission cable, and the more likely it is to fail;

[0089] In the formula , , are influencing factors and are constants. ;

[0090] The various environmental parameters collected in real time Substituting into the formula: The transmission cable environmental coefficient of the current monitoring area is calculated ;

[0091] In the formula is the total number of environmental parameters, For the The influencing factors of environmental parameters, is the reference value of the corresponding environmental parameter in the current monitoring area, is the observed value of each environmental parameter; first, each environmental parameter is substituted into the reference value for ratio calculation, and then the deviation value is calculated after comparison with 1. Obviously, the larger the deviation, the higher the abnormality of the current environmental parameter. Then, each environmental parameter is accumulated and calculated, so that the real-time change of each parameter can be sensitively reflected, thereby obtaining an accurate transmission cable environmental coefficient;

[0092] The equipment operating factor The acquisition process is as follows: input the operating parameters of the equipment in each monitoring area into the pre-trained recurrent neural network model, and output the operating coefficient of the equipment The establishment and training of the recurrent neural network model is a conventional prior art, so no further details will be given here.

[0093] The working process of S5 is as follows:

[0094] If the overall operation of 5G communication base stations in the current area is abnormal, the monitoring area with failure trends will be marked;

[0095] Provide fault warnings for 5G communication base stations in the current monitoring area, increase the patrol frequency of the current monitoring area by 2 times, and increase the patrol frequency of the current area by 1 time;

[0096] If there is no overall operating abnormality in the 5G communication base stations in the current area, the monitoring areas with failure trends will be marked;

[0097] Issue fault warnings for 5G communication base stations in the current monitoring area, and increase the patrol frequency of the current monitoring area by 100%.

[0098] Through the above technical solution, it is possible to use the preliminary judgment process of whether the current area is operating abnormally as the basis for adjusting the patrol frequency of the current area, and then through the judgment process of fault warning in each monitoring area, the patrol frequency in the monitoring area can be increased in a targeted manner, thereby preventing faults from occurring and performing timely maintenance when faults occur, thereby improving the operating stability of 5G communication base stations.

[0099] It should be noted that the calculation formulas and various parameters involved in the calculations in the present invention have been dimensionally processed in advance, and the process of dimensionless processing is well known in the industry and will not be described here.

[0100] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A 5G communication base station equipment security operation and maintenance management method based on AIOT, characterized in that: include: S1. Collect the operation and maintenance data of 5G communication base stations in the current area in real time through the IoT sensor network; S2, transmitting the collected operation and maintenance data to the data processing center via wired or wireless means; S3. Clean, integrate and store the operation and maintenance data received by the data processing center to form standardized data assets; S4. Perform operation status analysis and early warning analysis on the standardized data assets, and calculate the abnormal operation coefficient and the fault early warning coefficient respectively. According to the abnormal operation coefficient and the fault early warning coefficient, make an overall abnormal judgment on the 5G communication base stations in the current area; S5. Adjust the patrol frequency of 5G communication base stations with abnormal operation according to the judgment results, and issue fault warnings for 5G communication base stations with fault trends.

2. According to the AIOT-based 5G communication base station equipment security operation and maintenance management method according to claim 1, it is characterized in that: The operation and maintenance data includes: transmission cable operation data, equipment operation data and environmental data around the transmission cable.

3. According to the AIOT-based 5G communication base station equipment security operation and maintenance management method according to claim 2, it is characterized in that: The process of obtaining the abnormal operation coefficient includes: Take each 5G communication base station in the current area as the center and divide the set range into a monitoring area; The first The transmission cable operation data, equipment operation data and environmental data around the transmission cable processed in each monitoring area are used to obtain the transmission cable operation coefficient according to the preset rules. , Equipment operation coefficient And transmission cable environmental factor Then, substitute into the following formula: Calculate the first Abnormal operation coefficient of monitoring area ; In the formula is any sampling point; is the total number of sampling points; , , are the transmission cable operation coefficients of any sampling point , Equipment operation coefficient And transmission cable environmental factor Observed value of , , are the average values ​​of transmission cable operation coefficient, equipment operation coefficient and transmission cable environment coefficient, respectively. , , is the weight factor; The abnormal operation coefficient of each monitoring area Substitute into the formula: Calculate the abnormal operation coefficient of the current area ; In the formula For the The weight coefficient of each monitoring area is For the A judgment function to determine whether there is a fault trend in a monitoring area. is the total number of monitored areas.

4. According to the AIOT-based 5G communication base station equipment security operation and maintenance management method of claim 3, it is characterized in that: The said The judgment function of whether there is a fault trend in the monitoring area The expression is: Jordi If there is a failure trend in the monitoring area, ; In the formula is the number of monitoring areas with failure trends, , Respectively The maximum fault warning coefficient and minimum fault warning coefficient of each monitoring area, is the preset proportional coefficient; Jordi If there is no failure trend in the monitoring area, .

5. According to the AIOT-based 5G communication base station equipment security operation and maintenance management method of claim 4, it is characterized in that: The process of determining whether there is a fault trend in the monitoring area includes: Obtain the time-varying curves of the transmission cable operation coefficient, equipment operation coefficient and transmission cable environmental coefficient of each monitoring area respectively , , ; Substituting into the formula: ； Calculate the fault warning coefficient of each monitoring area ; In the formula , are the left and right time points of the detection period, , , It is a reference curve obtained based on historical data analysis; Fault warning coefficient With the preset fault warning threshold For comparison, if , then it is judged that there is a fault trend in the current monitoring area. If , it is judged that there is no fault trend in the current monitoring area.

6. The AIOT-based 5G communication base station equipment security operation and maintenance management method according to claim 3 is characterized in that: The process of overall abnormality judgment of 5G communication base stations in the current area includes: The calculated abnormal operation coefficient of the current area Bring in middle; The abnormal operation threshold preset for the system; like , it is judged that there is no abnormal operation of the 5G communication base station in the current area as a whole; like , it is judged that the overall operation of 5G communication base stations in the current area is abnormal.

7. The AIOT-based 5G communication base station equipment security operation and maintenance management method according to claim 3 is characterized in that: The process of obtaining the transmission cable operation coefficient and the transmission cable environment coefficient in the current monitoring area is as follows: The collected line swing amplitude , minimum distance to surrounding objects , Cable sag Substituting into the formula: The transmission cable operation coefficient of the current monitoring area is calculated ; In the formula , , are influencing factors and are constants. ; The various environmental parameters collected in real time Substituting into the formula: The transmission cable environmental coefficient of the current monitoring area is calculated ; In the formula is the total number of environmental parameters, For the The influencing factors of environmental parameters, is the reference value of the corresponding environmental parameter in the current monitoring area, are the observed values ​​of various environmental parameters; The equipment operating factor The acquisition process is as follows: input the operating parameters of the equipment in each monitoring area into the pre-trained recurrent neural network model, and output the operating coefficient of the equipment .

8. The AIOT-based 5G communication base station equipment security operation and maintenance management method according to claim 1 is characterized in that: The working process of S5 is as follows: If the overall operation of 5G communication base stations in the current area is abnormal, the monitoring area with failure trends will be marked; Provide fault warnings for 5G communication base stations in the current monitoring area, increase the patrol frequency of the current monitoring area by 2 times, and increase the patrol frequency of the current area by 1 time; If there is no overall operating abnormality in the 5G communication base stations in the current area, the monitoring areas with failure trends will be marked; Issue fault warnings for 5G communication base stations in the current monitoring area, and increase the patrol frequency of the current monitoring area by 100%.

Images