Communication power supply control system and method based on 5G communication

Abstract

The application discloses a communication power supply control system and method based on 5G communication, and relates to the technical field of power supply control.The technical problems of insufficient energy efficiency optimization precision and missing primary early warning risk identification are solved.The application realizes load grading identification, adopts a differentiated voltage regulation strategy, improves the comprehensive energy efficiency of the system, establishes a four-level abnormality grading standard, uses a differentiated strategy, improves the self-healing rate of general abnormalities, shortens the response time of serious / urgent abnormalities, reduces the equipment failure rate, avoids fault escalation and safety accidents, performs three-dimensional analysis on time trends, parameter changes and associated abnormalities on slight abnormalities through a comprehensive processing analysis module, combines weight assignment and comprehensive score quantification risk levels, identifies potential fault trends in advance, changes the operation and maintenance mode from post-repair to pre-prevention, and reduces unplanned downtime.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power supply control, in particular to a communication power supply control system and method based on 5G communication. BACKGROUND

[0002] With the rapid development of 5G communication, edge computing and other technologies, as the core infrastructure to ensure the stable operation of communication networks, the requirements for the stability of communication power supply, energy efficiency optimization capability and abnormal disposal efficiency continue to improve.

[0003] According to the patent with the application number CN202310566606.0, a communication power supply control system and method are disclosed, which comprises a battery pack, a DC bus bar positive pole, a DC bus bar negative pole, a DC contactor and a double relay. The positive pole of the battery pack is connected with the DC bus bar positive pole. The moving contact of the DC contactor is connected with the DC bus bar negative pole, and the static contact is connected with the negative pole of the battery pack. The first end of the control coil of the DC contactor is connected with the DC bus bar positive pole, and the second end is connected with the first static contact and the second static contact of the double relay. The first moving contact of the double relay is connected with the negative pole of the battery pack, and the second moving contact is connected with the DC bus bar negative pole. After the control system is powered on and initialized, the double relay is closed to connect the negative pole of the battery pack with the DC bus bar negative pole.

[0004] The prior art adopts a fixed output voltage strategy, which fails to dynamically adjust the output voltage according to the load current, resulting in excessive redundant energy consumption in low load scenarios and insufficient cable voltage drop compensation in high load scenarios. At the same time, the abnormal level division is ambiguous, and a one-size-fits-all alarm mode is adopted, lacking differentiated disposal strategies. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides a communication power supply control system and method based on 5G communication, which solves the problems of insufficient energy efficiency optimization precision and lack of primary early warning risk identification.

[0006] To achieve the above purpose, the present application realizes the following technical scheme: a communication power supply control system based on 5G communication, comprising:

[0007] A communication power supply state analysis module is used to collect voltage, current and temperature working parameters of the communication power supply, analyze normal parameters under normal working state of the communication power supply based on historical data, generate a state normal signal and transmit it to the normal state monitoring module if the working parameters are within the normal parameter interval, and generate a state abnormal signal and transmit it to the abnormal state processing module if the working parameters are not within the normal parameter interval.

[0008] The normal state monitoring module is configured to analyze the acquired normal state signal, compare the load current of the communication power supply with a preset threshold, and generate a low-load optimization signal or a high-load optimization signal.

[0009] The low-load optimization signal is processed, the difference between the corrected output voltage and the current output voltage of the communication power supply is calculated, and the low-load adjustment information is generated based on the difference as the adjustment standard.

[0010] The abnormal state processing module is configured to process the acquired abnormal state signal, confirm the abnormal parameters in the working parameters, and generate a single parameter abnormal signal or a multi-parameter abnormal signal according to the type of the abnormal parameters, determine the abnormal level, and process based on different abnormal levels to generate abnormal processing information transmitted to the control management information output module.

[0011] The comprehensive processing and analysis module is configured to process the primary warning information corresponding to the slight abnormality transmitted by the abnormal state processing module, comprehensively analyze from three aspects of time trend, parameter change and associated abnormality, assign different risk levels, calculate the comprehensive score, identify the risk according to the comprehensive score, and generate a risk warning signal for the medium risk and high risk and transmit it to the control management information output module.

[0012] The control management information output module is configured to display the acquired low-load adjustment information, high-load adjustment information, abnormal processing information and risk warning signal to the corresponding management personnel.

[0013] The normal state monitoring module generates the low-load adjustment information in the following manner:

[0014] According to the formula U 低，输出 =U 目标终端 +I×R+K, the corrected output voltage U 低，输出 is calculated, wherein K is the minimum redundant voltage, U 目标终端 is the lower limit of the rated value of the communication power supply, the output voltage U of the current communication power supply is acquired, the difference between the corrected output voltage and the output voltage is calculated, and the difference is used as the adjustment standard to generate the low-load adjustment information.

[0015] The normal state monitoring module generates the high-load adjustment information in the following manner:

[0016] The resistance value R 基准 of the cable at 20℃ is acquired, the temperature coefficient of the cable is acquired, and the real-time temperature T 实时Then, according to formula R 实时 =R 基准 +[1+ ×(T 实时 -T 基准 The real-time resistance R is calculated. 实时 Furthermore, the obtained real-time resistance R 实时 Substitute into formula U 高，输出 =U 目标终端 +I×R 实时 The corrected output voltage U is calculated. 高，输出 Simultaneously, it calculates the difference between the voltage and the current communication power supply output voltage U, and uses the difference as the adjustment standard to generate high load adjustment information.

[0017] The exception handling module determines the exception level in the following way:

[0018] Identify abnormal parameters in the working parameters and generate different signals according to the type of abnormal parameter, including single parameter abnormal signals or multi-parameter abnormal signals. At the same time, determine the abnormality level according to the different types of abnormal parameters. If a single parameter deviates slightly, it is classified as a minor abnormality; if a single parameter deviates significantly, it is classified as a general abnormality; if multiple parameters deviate, it is classified as a serious abnormality; and if a critical parameter deviates, it is classified as an emergency abnormality.

[0019] The exception handling module generates exception handling information in the following way:

[0020] For general anomalies, a medium-level early warning message is generated, and a preliminary self-repair procedure is initiated, which includes parameter adaptive adjustment and component restart / switching; for severe anomalies, a high-level early warning message is generated immediately, and the risk source is precisely cut off according to the anomaly type; for emergency anomalies, the highest-level early warning mechanism is triggered, and the abnormal power circuit is immediately cut off. If an emergency backup power supply is provided, the power supply is automatically switched within 10ms, and all parameters before and after the fault are automatically recorded for 30 minutes.

[0021] The time trend analysis in the comprehensive processing and analysis module is as follows:

[0022] Using time t1 as a period, the total number of similar warnings and the time interval between each warning are counted. If the total number of warnings is ≤1 or the interval is ≥15 days and does not shorten, it is judged as low risk in time trend; if the total number of warnings is 2-3 and the interval gradually shortens, it is judged as medium risk in time trend; if the total number of warnings is ≥4 or the interval is ≤7 days and continues to shorten, it is judged as high risk in time trend.

[0023] The parameter change analysis of the comprehensive processing and analysis module is as follows:

[0024] The parameter values of the effective early warning are arranged in chronological order to form a change sequence, and the deviation degree and the change rate are calculated, the deviation degree is the difference between the latest parameter and the threshold value, and the change rate is the rising amplitude of the parameter per unit time, the difference is greater than or equal to 5 DEG C and the daily average rising rate is less than or equal to 0.05 DEG C per day, which is determined as low risk of parameter change; 3 DEG C is less than the difference and the daily average rising rate is greater than 0.05 DEG C per day and less than or equal to 0.1 DEG C per day, which is determined as medium risk of parameter change; the difference is less than 3 DEG C or the daily average rising rate is greater than 0.1 DEG C per day, which is determined as high risk of parameter change.

[0025] The associated abnormality analysis of the comprehensive processing analysis module is specifically:

[0026] The abnormal parameters and their corresponding associated parameters are obtained, only single parameter abnormality and no abnormality of associated parameters are determined as no risk of association; there are some associated parameters synchronously abnormal, which is determined as medium risk of association; all associated parameters are synchronously abnormal, which is determined as high risk of association.

[0027] The comprehensive processing analysis module assigns different risk levels from low to high as 1, 2 and 3 in turn, and calculates the comprehensive score according to the formula comprehensive score = (time trend risk * weight one) + (parameter change risk * weight two) + (associated abnormality risk * weight three), the comprehensive score is less than or equal to 1.5, which is determined as low risk; the comprehensive score is 1.6-2.5, which is determined as medium risk; and the comprehensive score is greater than or equal to 2.6, which is determined as high risk.

[0028] The communication power supply control method based on 5G communication specifically includes the following steps:

[0029] Step one, collect the voltage, current and temperature working parameters of the communication power supply, analyze the normal parameters of the communication power supply under the normal working state based on the historical data, extract the historical parameters of the communication power supply in the period of no fault and full load stability greater than or equal to 99.9%, calculate the normal fluctuation range of each parameter by using the 3 sigma principle to obtain the normal parameters, compare the working parameters with the normal parameters, if the working parameters are in the normal parameter interval, generate a normal state signal, if the working parameters are not in the normal parameter interval, generate an abnormal state signal;

[0030] Step two, analyze the obtained normal state signal, compare the load current of the communication power supply with the preset threshold value, if the load current is less than or equal to 30% of the rated current, it is determined that the communication power supply is in low load working and a low load optimization signal is generated; if the load current is greater than or equal to 70% of the rated current, it is determined that the communication power supply is in high load working and a high load optimization signal is generated, a low load optimization signal or a high load optimization signal is generated;

[0031] Step 3: Process the low load optimization signal, calculate the difference between the corrected output voltage and the current communication power supply output voltage, and use the difference as the adjustment standard to generate low load adjustment information. Process the high load optimization signal, correct the resistance in real time through the temperature sensor, calculate and output the corrected output voltage, calculate the difference between the corrected output voltage and the current communication power supply output voltage, and use the difference as the adjustment standard to generate high load adjustment information.

[0032] Step 4: Process the acquired abnormal status signals, identify the abnormal parameters in the working parameters, and generate single-parameter abnormal signals or multi-parameter abnormal signals according to the type of abnormal parameters. At the same time, determine the abnormal level, process it based on different abnormal levels, and generate abnormal processing information.

[0033] Step 5: Process the primary warning information corresponding to minor anomalies transmitted by the abnormal status processing module. Analyze it comprehensively from three aspects: time trend, parameter changes, and associated anomalies. After assigning values ​​to different risk levels, calculate the comprehensive score. Based on the comprehensive score, identify risks and generate risk warning signals for medium and high risks.

[0034] This invention provides a communication power control system and method based on 5G communication. Compared with the prior art, it has the following advantages:

[0035] This invention improves overall system energy efficiency by implementing load classification and identification and adopting differentiated voltage regulation strategies. It establishes a four-level anomaly classification standard and adopts targeted differentiated strategies to improve the self-healing rate of general anomalies, shorten the response time of severe / emergency anomalies, reduce equipment failure rate, and avoid fault escalation and safety accidents. Through a comprehensive processing and analysis module, it performs three-dimensional analysis of minor anomalies in terms of time trends, parameter changes, and related anomalies. Combined with weighting and comprehensive scoring, it quantifies the risk level, identifies potential fault trends in advance, and transforms the operation and maintenance mode from post-repair to pre-prevention, reducing unplanned downtime. Attached Figure Description

[0036] Figure 1 This is a system block diagram of the present invention;

[0037] Figure 2 This is a diagram illustrating the steps and methods of the present invention. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] First embodiment

[0040] Please refer to Figure 1 The application provides a communication power control system based on 5G communication, comprising a communication power state analysis module, an abnormal state processing module, a normal state monitoring module, a comprehensive processing analysis module and a control management information output module, and combining Figure 1 It can be known that the information between the above functional modules is unidirectional transmission.

[0041] The communication power state analysis module is used to collect the working parameters of the communication power supply, wherein the working parameters include the voltage, current and temperature of the communication power supply, and the collected working parameters are analyzed, the corresponding normal parameters under the normal working state of the communication power supply are analyzed based on historical data, the historical parameters of the communication power supply in the period of no fault and full load stability ≥ 99.9% are extracted, the normal fluctuation range of each parameter is calculated by using the 3σ principle, the normal parameters are obtained, and the working parameters are compared with the normal parameters. If the working parameters exist in the normal parameter interval, it indicates that the communication power supply state is normal, and a state normal signal is generated, which is transmitted to the abnormal state processing module, otherwise if it does not exist in the normal parameter interval, it indicates that the communication power supply state is abnormal, and a state abnormal signal is generated, which is transmitted to the normal state monitoring module.

[0042] The normal state monitoring module is used to analyze the obtained state normal signal, and the load current of the communication power supply is obtained in a period of time t, and the load current is compared with a preset threshold value. If the load current ≤ 30%I 额定 , wherein I 额定 represents the rated current of the communication power supply, it indicates that the communication power supply is in low load working, and a low load optimization signal is generated, otherwise if the load current ≥ 70%I 额定 , it indicates that the communication power supply is in high load working, and a high load optimization signal is generated.

[0043] The generated low load optimization signal is processed, and the corrected output voltage U 低，输出 is calculated according to the formula U 目标终端 =U 低，输出 +I×R+K, wherein K is the minimum redundant voltage, U 目标终端 is the lower limit of the rated value of the communication power supply, the output voltage U of the current communication power supply is obtained at the same time, the difference between the corrected output voltage and the output voltage is calculated, and the difference is used as the adjustment standard to generate the low load adjustment information. After voltage adjustment, the terminal voltage Uterminal is collected in the next monitoring period t, to verify whether it is stable in the target range (low load 48-50V, high load 50-52V). If the deviation is > ± 0.5V, the adjustment difference is recalculated and optimized twice.

[0044] The generated high-load optimization signal is processed, the cable generates heat to cause the resistance to increase when the load is high, and the resistance R needs to be corrected in real time by the temperature sensor, and the specific correction method is as follows:

[0045] The resistance value R of the cable at the reference temperature (usually 20℃) is obtained 基准 , and R 基准 can be calculated according to the formula , wherein is the resistivity of the conductor, L is the length of the cable, S is the cross-sectional area of the cable, the temperature coefficient of the cable is obtained at the same time , and the real-time temperature T 实时 is obtained through the temperature sensor 实时 , then the real-time resistance R 基准 is calculated according to the formula R 实时 =R 基准 +[1+ ×(T 实时 -T 基准 )] further, the obtained real-time resistance R 实时 is substituted into the formula U 实时 =U 高，输出 +I×R 目标终端 , the corrected output voltage U 实时 is calculated, the difference between the corrected output voltage U 高，输出 and the current communication power supply output voltage U is calculated, and the difference is used as the adjustment standard to generate the high-load adjustment information.

[0046] Then, the generated low-load adjustment information and high-load adjustment information are transmitted to the control management information output module.

[0047] The control management information output module is used to display the obtained low-load adjustment information and high-load adjustment information to the corresponding management personnel.

[0048] Second embodiment

[0049] As the second embodiment of the application, it is implemented on the basis of the first embodiment, and the difference from the first embodiment is as follows:

[0050] An abnormal state processing module is configured to process the acquired state abnormal signal, confirm the abnormal parameter in the working parameter, and generate different signals according to the type of the abnormal parameter, specifically including a single parameter abnormal signal or a multi-parameter abnormal signal, and determine the abnormal level according to the type of the different abnormal parameters. If a single parameter deviates slightly, such as a temperature of 76℃ and a threshold of 80℃, the abnormality is classified as a slight abnormality. If a single parameter deviates significantly, such as a voltage of 45V and an interval of 46-56V, the abnormality is classified as a general abnormality. If multiple parameters deviate, such as a voltage of 59V and current over-limit, the abnormality is classified as a serious abnormality. If a fatal parameter deviates, such as output overvoltage ≥ 60V and battery short circuit, the abnormality is classified as an emergency abnormality. Corresponding abnormality classification information is generated, and different abnormality classifications are processed to generate abnormality processing information and transmit the abnormality processing information to a control management information output module.

[0051] For a slight abnormality, preliminary warning information is generated, and the information is transmitted to the comprehensive processing and analysis module for recording and scheduling subsequent routine inspection plans to confirm whether the abnormality persists or needs further processing.

[0052] For a general abnormality, the module generates intermediate warning information and starts a preliminary self-repair program. The self-repair process includes parameter adaptive adjustment, such as reducing the output voltage within the safe interval when there is mild overcurrent, such as reducing the output voltage from 57V to 55V in a 48V system, reducing the load power, restarting / switching components, such as automatically restarting the faulty sensor or switching to the backup sensor when there is a single sensor failure, and maintaining monitoring through multi-parameter cross verification.

[0053] If a serious abnormality is detected, the module immediately generates high-level warning information, accurately cuts off the risk source according to the type of the abnormality, preferentially cuts off non-core loads such as air conditioners and auxiliary monitoring equipment for module overheating / overloading, or reduces the power of core devices such as base station power emission to avoid burning out the faulty module, stops battery discharge and activates the backup module for battery under-voltage / rectifier module failure, and gradually cuts off secondary loads if the load capacity is insufficient to ensure power supply for core communication devices.

[0054] In the case of an emergency abnormality, the abnormal state processing module triggers the highest level of warning mechanism to immediately cut off the abnormal power circuit, such as cutting off the main power supply when there is overvoltage and disconnecting the battery circuit when there is a battery short circuit, to avoid the spread of faults. If an emergency backup power source such as a storage battery or a diesel generator is provided, the power supply is automatically switched within 10ms to ensure that core devices such as base station core boards and servers do not interrupt operation. All parameters within 30 minutes before and after the fault are automatically recorded.

[0055] The comprehensive processing and analysis module processes the acquired primary early warning information and performs a comprehensive analysis from three aspects: time trend, parameter changes, and correlation anomalies. For the time trend analysis, a time period of t1 is used, with the value of t1 set by the operator. The module counts the total number of similar early warnings and the time interval between each warning, and combines this with trend judgment rules to determine risk rating. If the total number of warnings is ≤1 or the interval is ≥15 days and does not shorten, it is judged as a low-risk time trend; if the total number of warnings is 2-3 and the interval gradually shortens, it is judged as a medium-risk time trend; if the total number of warnings is ≥4 or the interval is ≤7 days and continuously shortens, it is judged as a high-risk time trend.

[0056] For the analysis of parameter changes, the parameter values ​​of effective warnings are arranged in chronological order to form a change sequence. The degree of deviation and the rate of change are calculated. Specifically, the degree of deviation represents the difference between the latest parameter and the threshold, and the rate of change represents the increase in parameter value per unit time. The risk rating is determined by combining the two and the judgment rules. If the difference is ≥5℃ and the average daily increase rate is ≤0.05℃ / day, it is judged as low risk of parameter change. If 3℃≤difference<5℃ and 0.05℃ / day<average daily increase rate≤0.1℃ / day, it is judged as medium risk of parameter change. If the difference is <3℃ or the average daily increase rate is >0.1℃ / day, it is judged as high risk of parameter change.

[0057] For the analysis of correlation anomalies, abnormal parameters and their corresponding correlation parameters are obtained, and risk rating is performed in combination with correlation judgment rules. If only a single parameter is abnormal and the correlation parameters are not abnormal, the correlation is judged to be risk-free. If some correlation parameters are synchronously abnormal, the correlation is judged to be of medium risk. If all correlation parameters are synchronously abnormal, the correlation is judged to be of high risk.

[0058] Next, different risk levels are assigned values, from low to high: 1, 2, and 3. Then, the comprehensive score is calculated according to the formula: Comprehensive Score = (Time Trend Risk × Weight 1) + (Parameter Change Risk × Weight 2) + (Association Anomaly Risk × Weight 3). Risk identification is performed based on the comprehensive score. If the comprehensive score is ≤1.5, it is judged as low risk and no intervention is required. If the comprehensive score is 1.6-2.5, it is judged as medium risk. If the comprehensive score is ≥2.6, it is judged as high risk. Based on the medium and high risk determinations, a risk warning signal is generated and transmitted to the control management information output module.

[0059] The control management information output module is used to display the acquired anomaly handling information and risk warning signals to the corresponding management personnel.

[0060] Third Embodiment

[0061] As a third embodiment of the present invention, the focus is on combining the implementation processes of the first and second embodiments.

[0062] Fourth embodiment

[0063] Please see Figure 2 This application provides a communication power control method based on 5G communication, which specifically includes the following steps:

[0064] Step 1: Collect the voltage, current, and temperature operating parameters of the communication power supply. Analyze the normal parameters under normal operating conditions based on historical data. Extract the historical parameters of the communication power supply during the period of no faults and full-load stability ≥99.9%. Calculate the normal fluctuation range of each parameter using the 3σ principle to obtain the normal parameters. Compare the operating parameters with the normal parameters. If the operating parameters are within the normal parameter range, generate a normal status signal. If the operating parameters are not within the normal parameter range, generate an abnormal status signal. The specific processing method is the same as the processing process of the communication power supply status analysis module.

[0065] Step 2: Analyze the acquired normal status signal and compare the load current of the communication power supply with the preset threshold. If the load current is ≤30% of the rated current, it is determined that the communication power supply is working under low load and a low load optimization signal is generated. If the load current is ≥70% of the rated current, it is determined that the communication power supply is working under high load and a high load optimization signal is generated. The specific processing method is the same as the processing process of the normal status monitoring module.

[0066] Step 3: Process the low load optimization signal, calculate the difference between the corrected output voltage and the current communication power supply output voltage, and use the difference as the adjustment standard to generate low load adjustment information. Process the high load optimization signal, correct the resistance in real time through the temperature sensor, and calculate the corrected output voltage. Calculate the difference between the corrected output voltage and the current communication power supply output voltage, and use the difference as the adjustment standard to generate high load adjustment information. The specific processing method is the same as the processing process of the normal state monitoring module.

[0067] Step 4: Process the acquired abnormal status signals, confirm the abnormal parameters in the working parameters and generate single-parameter abnormal signals or multi-parameter abnormal signals according to the type of abnormal parameters. At the same time, determine the abnormal level and process it based on different abnormal levels to generate abnormal processing information. The specific processing method is the same as the processing process of the abnormal status monitoring module.

[0068] Step five, the primary warning information corresponding to the slight abnormality transmitted by the abnormal state processing module is processed, the time trend, parameter change and correlation abnormality are comprehensively analyzed, the different risk levels are valued and calculated, the risk is identified according to the comprehensive score, the risk warning signal is generated for the medium risk and the high risk, and the specific processing mode is the same as the processing process of the comprehensive processing and analysis module.

[0069] Part of the data in the above formula is dimensionless numerical calculation, and the contents not described in detail in the specification all belong to the prior art known to those skilled in the art.

[0070] The above examples are only used to illustrate the technical method of the present application and are not limited. Although the present application is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical method of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical method of the present application.

Claims

1. A communication power supply control system based on 5G communication, characterized in that, include: The communication power supply status analysis module is used to collect the voltage, current and temperature operating parameters of the communication power supply. Based on historical data analysis, it analyzes the normal parameters under normal operating conditions of the communication power supply. If the operating parameters are within the normal parameter range, a normal status signal is generated and transmitted to the normal status monitoring module; if the operating parameters are not within the normal parameter range, an abnormal status signal is generated and transmitted to the abnormal status processing module. The normal state monitoring module is used to analyze the acquired normal state signals, compare the load current of the communication power supply with a preset threshold, and generate a low load optimization signal or a high load optimization signal. The low-load optimization signal is processed, the difference between the corrected output voltage and the current communication power supply output voltage is calculated, and the difference is used as the adjustment standard to generate low-load adjustment information. The high-load optimization signal is processed, the resistance is corrected in real time through a temperature sensor, the corrected output voltage is calculated and output, and the difference between the corrected output voltage and the current communication power supply output voltage is calculated, and the difference is used as the adjustment standard to generate high-load adjustment information. The abnormal status processing module is used to process the acquired abnormal status signals, identify abnormal parameters in the working parameters and generate single-parameter abnormal signals or multi-parameter abnormal signals according to the type of abnormal parameters. At the same time, it determines the abnormal level, processes it based on different abnormal levels, and generates abnormal processing information to be transmitted to the control management information output module. The comprehensive processing and analysis module is used to process the primary early warning information corresponding to minor anomalies transmitted by the abnormal state processing module. It performs comprehensive analysis from three aspects: time trend, parameter change, and associated anomalies. After assigning values ​​to different risk levels, it calculates a comprehensive score, identifies risks based on the comprehensive score, generates risk warning signals for medium and high risks, and transmits them to the control management information output module. The control and management information output module is used to display the acquired low load adjustment information, high load adjustment information, abnormal handling information, and risk warning signals to the corresponding management personnel.

2. The communication power control system based on 5G communication according to claim 1, characterized in that, The normal state monitoring module generates low load adjustment information in the following way: According to formula U 低，输出 =U 目标终端 The corrected output voltage U is calculated by adding I×R+K. 低，输出 Where K is the minimum redundancy voltage, U 目标终端 The lower limit of the communication power supply rating is set, and the output voltage U corresponding to the current communication power supply is obtained. The difference between the corrected output voltage and the output voltage is calculated and used as the adjustment standard to generate low load adjustment information.

3. The communication power control system based on 5G communication according to claim 1, characterized in that, The normal state monitoring module generates high load adjustment information in the following way: Obtain the resistance value R of the cable at 20℃ 基准 At the same time, the temperature coefficient of the cable is obtained. And obtain the real-time temperature T through a temperature sensor. 实时 Then, according to formula R 实时 =R 基准 +[1+ ×(T 实时 -T 基准 The real-time resistance R is calculated. 实时 Furthermore, the obtained real-time resistance R 实时 Substitute into formula U 高，输出 =U 目标终端 +I×R 实时 The corrected output voltage U is calculated. 高，输出 Simultaneously, it calculates the difference between the voltage and the current communication power supply output voltage U, and uses the difference as the adjustment standard to generate high load adjustment information.

4. The communication power control system based on 5G communication according to claim 1, characterized in that, The exception handling module determines the exception level in the following way: Identify abnormal parameters in the working parameters and generate different signals according to the type of abnormal parameter, including single parameter abnormal signals or multi-parameter abnormal signals. At the same time, determine the abnormality level according to the different types of abnormal parameters. If a single parameter deviates slightly, it is classified as a minor abnormality; if a single parameter deviates significantly, it is classified as a general abnormality; if multiple parameters deviate, it is classified as a serious abnormality; and if a critical parameter deviates, it is classified as an emergency abnormality.

5. The communication power control system based on 5G communication according to claim 1, characterized in that, The exception handling module generates exception handling information in the following way: For general anomalies, a medium-level early warning message is generated, and a preliminary self-repair procedure is initiated, which includes parameter adaptive adjustment and component restart / switching; for severe anomalies, an advanced early warning message is generated immediately, and the risk source is precisely cut off according to the anomaly type. The highest level of early warning mechanism is triggered in case of emergency anomalies, and the abnormal power circuit is immediately cut off. If an emergency backup power supply is provided, the power supply will be automatically switched within 10ms. At the same time, all parameters before and after the fault are automatically recorded for 30 minutes.

6. The communication power control system based on 5G communication according to claim 1, characterized in that, The time trend analysis in the comprehensive processing and analysis module is as follows: Using time t1 as the period, the total number of similar warnings and the time interval between each warning are counted. If the total number is ≤1 or the interval is ≥15 days and does not shorten, it is judged as low risk in time trend. A total of 2-3 occurrences with gradually decreasing intervals is considered medium risk in terms of time trend; a total of ≥4 occurrences or an interval of ≤7 days with continuously decreasing intervals is considered high risk in terms of time trend.

7. The communication power control system based on 5G communication according to claim 1, characterized in that, The parameter change analysis of the comprehensive processing and analysis module is as follows: The parameter values ​​of the effective warnings are arranged in chronological order to form a change sequence. The degree of deviation and the rate of change are calculated. The degree of deviation is the difference between the latest parameter and the threshold. The rate of change is the increase of the parameter per unit time. If the difference is ≥5℃ and the daily average increase rate is ≤0.05℃ / day, it is judged as low risk of parameter change. If 3℃≤difference<5℃ and 0.05℃ / day<daily average increase rate≤0.1℃ / day, it is judged as medium risk of parameter change. If the difference is less than 3℃ or the daily rate of increase is greater than 0.1℃ / day, it is considered a high-risk parameter change.

8. The communication power control system based on 5G communication according to claim 1, characterized in that, The correlation anomaly analysis in the comprehensive processing and analysis module is as follows: Obtain the abnormal parameters and their corresponding related parameters. If only a single parameter is abnormal and no related parameters are abnormal, the association is determined to be risk-free. If some related parameters are synchronously abnormal, the association is determined to be of medium risk. If all related parameters are synchronously abnormal, the association is determined to be of high risk.

9. The communication power control system based on 5G communication according to claim 1, characterized in that, The comprehensive processing and analysis module assigns values ​​of 1, 2, and 3 to different risk levels in ascending order. The comprehensive score is calculated according to the formula: Comprehensive Score = (Time Trend Risk × Weight 1) + (Parameter Change Risk × Weight 2) + (Association Anomaly Risk × Weight 3). A comprehensive score ≤ 1.5 is judged as low risk. A composite score of 1.6-2.5 indicates a medium risk level. A score of ≥2.6 indicates a high risk level.

10. A communication power control method based on 5G communication, executed by the communication power control system according to any one of claims 1-9, characterized in that, The method specifically includes the following steps: Step 1: Collect the voltage, current, and temperature operating parameters of the communication power supply. Analyze the normal parameters under normal operating conditions based on historical data. Extract the historical parameters of the communication power supply during the period of no fault and full load stability ≥99.9%. Calculate the normal fluctuation range of each parameter using the 3σ principle to obtain the normal parameters. Compare the operating parameters with the normal parameters. If the operating parameters are within the normal parameter range, generate a normal status signal. If the operating parameters are not within the normal parameter range, generate an abnormal status signal. Step 2: Analyze the acquired normal status signal and compare the load current of the communication power supply with the preset threshold. If the load current is ≤30% of the rated current, it is determined that the communication power supply is working under low load and a low load optimization signal is generated; if the load current is ≥70% of the rated current, it is determined that the communication power supply is working under high load and a high load optimization signal is generated, and a low load optimization signal or a high load optimization signal is generated. Step 3: Process the low load optimization signal, calculate the difference between the corrected output voltage and the current communication power supply output voltage, and use the difference as the adjustment standard to generate low load adjustment information. Process the high load optimization signal, correct the resistance in real time through the temperature sensor, calculate and output the corrected output voltage, calculate the difference between the corrected output voltage and the current communication power supply output voltage, and use the difference as the adjustment standard to generate high load adjustment information. Step 4: Process the acquired abnormal status signals, identify the abnormal parameters in the working parameters, and generate single-parameter abnormal signals or multi-parameter abnormal signals according to the type of abnormal parameters. At the same time, determine the abnormal level, process it based on different abnormal levels, and generate abnormal processing information. Step 5: Process the primary warning information corresponding to minor anomalies transmitted by the abnormal status processing module. Analyze it comprehensively from three aspects: time trend, parameter changes, and associated anomalies. After assigning values ​​to different risk levels, calculate the comprehensive score. Based on the comprehensive score, identify risks and generate risk warning signals for medium and high risks.

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