Control method, system and equipment of communication direct-current power supply and medium

Abstract

The invention discloses a control method, system and device for a communication direct-current power supply and a medium, and the method comprises the steps: recognizing a circuit diagram of a to-be-controlled direct-current power supply module, and generating a topological circuit diagram of the direct-current power supply module according to a preset circuit element table; obtaining operation parameter information of the DC power supply module through the communication interface, and generating a first intelligent control model according to the topology circuit diagram and the operation parameter information; generating a second intelligent control model according to the topological circuit diagram and the first intelligent control model; based on the first intelligent control model and the second intelligent control model, obtaining an operation state monitoring result and a potential fault prediction result; dynamically adjusting the output power of the direct-current power supply module according to the operation state detection result and the potential fault prediction result, and transmitting an adjustment instruction through a communication interface; according to the invention, intelligent management and efficient communication capability of the DC power supply module are realized, and the operation efficiency and reliability of the data center are improved.

Description

Technical Field

[0001] The present application relates to the field of direct current power supply technology, and in particular to a control method, system, device and medium for a communication direct current power supply. Background Art

[0002] With the rapid development of information technology, data centers have become an important infrastructure in modern society. The stable operation of data centers depends on efficient and reliable power supply systems. In data centers, DC power modules are responsible for providing stable DC power to various key equipment to ensure the normal operation of the equipment. However, existing DC power modules have obvious deficiencies in intelligent management and communication capabilities, which to some extent affects the overall performance and reliability of data centers.

[0003] Current DC power modules rely mainly on fixed parameter settings and simple fault detection mechanisms, which are specifically manifested in the following two aspects: Insufficient intelligent management: Existing DC power modules can usually only provide basic voltage and current outputs and cannot be adjusted in time according to actual load conditions. This fixed-mode power management method is difficult to cope with the complex and changeable working environment of the data center, and is prone to power waste or insufficient power supply. Lack of communication capabilities: Most DC power modules do not have communication capabilities and cannot transmit operating parameter status information. This results in the inability of operation and maintenance personnel to obtain accurate information in a timely manner when a fault occurs, which increases the time for troubleshooting and repair and affects the stable operation of the data center. Summary of the invention

[0004] In order to achieve intelligent management and efficient communication capabilities of DC power supply modules in data centers and improve the operating efficiency and reliability of data centers, the present application provides a control method, system, device and medium for a communication DC power supply.

[0005] In the first aspect, the invention objective of the present application is achieved by adopting the following technical solutions: A control method for a communication DC power supply, comprising: a DC current module with a communication function, the method comprising: Identify the circuit diagram of the DC power module to be controlled, and generate a topological circuit diagram of the DC power module according to a preset circuit element table; Acquire operating parameter information of the DC power module through the communication interface, and generate a first intelligent control model according to the topological circuit diagram and the operating parameter information, wherein the first intelligent control model is used to simulate the performance of the DC power module under different working conditions; Generate a second intelligent control model according to the topological circuit diagram and the first intelligent control model, wherein the second intelligent control model includes intelligent load balancing and circuit fault prediction functions; Based on the first intelligent control model and the second intelligent control model, obtaining operation status monitoring results and potential fault prediction results; According to the operating status detection result and the potential fault prediction result, the output power of the DC power supply module is dynamically adjusted, and the adjustment instruction is transmitted through the communication interface.

[0006] By adopting the above technical solution, in the management of the data center, the present invention realizes intelligent management of the DC power supply module by identifying the circuit diagram of the DC power supply module to be controlled, generating a topological circuit diagram, and generating a first intelligent control model and a second intelligent control model in combination with the operating parameter information. The operating parameter information of the DC power supply module can be obtained in real time through the communication interface, and the adjustment instruction is transmitted to the intelligent monitoring terminal or user terminal and other preset management platforms that are connected to the DC power supply module in communication, thereby improving the user's management efficiency of the DC power supply system, and is conducive to ensuring that the operating state of the DC power supply module is always in the optimal state. By generating an intelligent control model including intelligent load balancing and circuit fault prediction functions, potential faults are discovered in advance and preventive measures are taken, thereby improving the reliability and stability of the DC power supply system. The output power of the DC power supply module is dynamically adjusted through the operating state detection result, which is conducive to efficient and real-time adjustment according to the load conditions of many electrical equipment in the data center. The dynamic operation management mechanism is conducive to saving electricity and reducing the situation of insufficient power supply, and the intelligent management mode is conducive to reducing operation and maintenance costs.

[0007] In a preferred example of the present application, the circuit diagram of the DC power supply module to be controlled is identified, and a topological circuit diagram of the DC power supply module is generated according to a preset circuit element table, specifically including: Identify the circuit diagram of the DC power module to be controlled, extract the electrical parameter information of the circuit elements, the key nodes and paths of the circuit, and determine the key paths of the power flow and signal flow based on the key nodes and paths of the circuit; Generate a topological circuit diagram of the DC power module according to the electrical parameter information of the circuit elements of the DC power module and a preset circuit element table, and input the circuit copper coverage rate information into the topological circuit diagram; The topology circuit diagram is optimized based on the critical paths of the power flow and the signal flow.

[0008] By adopting the above technical scheme, the electrical parameter information of the circuit element refers to the electrical characteristic parameters of each circuit element in the circuit diagram, such as resistance value, capacitance value, inductance value, diode forward voltage drop, etc.; the key nodes and paths of the circuit have an impact on the overall performance of the circuit; the key path is the main flow path of the current and signal; the topological circuit diagram is a graphical model reflecting the logical structure of the circuit based on the extracted electrical parameter information and the preset circuit element table; copper coverage rate information (i.e. the distribution and density of copper foil); the present invention uses a circuit analysis tool to identify the key nodes (such as power input terminal, load output terminal, important branch points) and key paths (such as main current path, signal transmission path) in the circuit, analyze the key paths of power flow and signal flow, and identify possible bottlenecks and optimization points; then optimize the topological circuit diagram, and the optimization goals may include reducing signal interference, electromagnetic interference, reducing power loss, improving heat dissipation, etc. According to the optimization results, the layout of the circuit elements is adjusted to improve the reasonable position of the elements on the key path, reduce unnecessary routing length and crossing, and the optimized topological circuit diagram is more stable and reliable in practical applications.

[0009] In a preferred example of the present application, the operation parameter information of the DC power module is obtained through the communication interface, and a first intelligent control model is generated according to the topological circuit diagram and the operation parameter information. The first intelligent control model is used to simulate the performance of the DC power module under different working conditions, specifically including: According to the operating parameter information, a finite element analysis algorithm is used to calculate the thermal distribution influence parameters of the DC power supply module; according to the operating parameter information and the electrical parameter information, a multi-physics field simulation software is used to calculate the parasitic element influence parameters of the parasitic elements of the DC power supply module, wherein the parasitic elements include parasitic capacitance and parasitic inductance; According to the heat distribution influencing parameters and the parasitic element influencing parameters, the comprehensive performance influencing parameters of the DC power supply module to be controlled are obtained; according to the topological circuit diagram and the comprehensive performance influencing parameters, a first intelligent control model is generated.

[0010] By adopting the above technical solution, the communication interface is an interface for exchanging data with the DC power supply module, which can be a serial communication interface (such as UART, SPI, I2C), Ethernet interface, USB interface; multi-physics field simulation software is simulation software that can simultaneously consider multiple physical phenomena (such as electromagnetic field, thermal field, mechanical field, etc.); parasitic elements are non-ideal elements in the circuit due to physical structure and material properties, such as parasitic capacitance and parasitic inductance; comprehensive performance influencing parameters can evaluate the comprehensive performance of the DC power supply module under different working conditions; specifically, the finite element analysis algorithm is used to calculate the thermal distribution influencing parameters, so that the DC power supply module can be accurately calculated through finite element analysis. The thermal distribution of the DC power module under different working conditions helps to identify potential thermal management problems, such as hot spots and poor heat dissipation; the multi-physics simulation software can accurately calculate the effects of parasitic capacitance and parasitic inductance, so that the model can efficiently understand, analyze and optimize the high-frequency characteristics and stability of the circuit; the first intelligent control model finally generated can combine the effects of thermal distribution and parasitic components with comprehensive performance influencing parameters to comprehensively evaluate the performance of the DC power module under different working conditions; the first intelligent control model generated based on these parameters can simulate the performance of the DC power module in actual operation, provide a scientific basis for dynamically adjusting the control strategy, and thus improve the reliability and efficiency of the system.

[0011] In a preferred example of the present application: the second intelligent control model is generated according to the topological circuit diagram and the first intelligent control model, and the second intelligent control model includes intelligent load balancing and circuit fault prediction functions, including: according to the comprehensive performance influencing parameters, using a genetic algorithm, optimizing the electrical parameters of the DC power supply module, and generating optimized comparative electrical parameter information; According to the optimized comparison electrical parameter information, updating the topological circuit diagram of the DC power supply module to generate a second topological circuit diagram; A multi-objective optimization algorithm is used to optimize the second topology circuit diagram, and a second intelligent control model is generated based on a deep learning algorithm combined with the optimized second topology circuit diagram and the first intelligent control model; the second intelligent control module is used to analyze the parameter operation data of the DC power supply module and automatically adjust the load distribution strategy.

[0012] By adopting the above technical solution, the genetic algorithm is an optimization algorithm based on natural selection and genetic mechanism, which is used to find the optimal solution; the multi-objective optimization algorithm includes multiple optimization objectives, such as minimizing temperature, maximizing efficiency, minimizing parasitic effects, etc.; the present invention uses a multi-objective optimization algorithm (such as NSGA-II, MOEA / D, etc.) to balance between multiple performance indicators (such as temperature, efficiency, stability, etc.) to further optimize the second topology circuit diagram; the genetic algorithm can search for the optimal solution within a specified global range to avoid local optimality, and can significantly improve the performance of the DC power supply module by optimizing electrical parameters, such as reducing temperature, improving efficiency, reducing parasitic effects, etc. The optimized electrical parameters are applied to the topology circuit diagram to generate a new second topology circuit diagram, which is conducive to ensuring the consistency of circuit structure and parameters, and provides an accurate model for subsequent performance evaluation and optimization, and the multi-objective optimization algorithm can balance between multiple performance indicators to ensure that the optimized circuit is optimal in multiple aspects; the deep learning algorithm combines the optimized second topology circuit diagram and the first intelligent control model, and the generated second intelligent control model has stronger intelligence and adaptability; the intelligent load balancing function can automatically adjust the load distribution strategy to ensure load balancing of each part and improve the overall efficiency of the system.

[0013] In a preferred example of the present application: the operation status monitoring results and potential fault prediction results are obtained based on the first intelligent control model and the second intelligent control model, specifically including: triggering intelligent control instructions based on the first intelligent control model and the second intelligent control model; Based on the intelligent control instruction, in the first intelligent control model and the second intelligent control model, a frequency domain analysis method is used to determine a resonant frequency range of the DC power supply module; Acquire the response characteristics of the DC power supply module at different frequencies by frequency scanning, and generate a frequency response curve; trigger a parameter monitoring instruction according to the frequency response curve combined with a preset frequency limit threshold, and obtain a first parameter detection result and a second parameter detection result respectively; An operation status detection result is obtained according to the first parameter detection result and the second parameter detection result; and a potential fault is predicted based on the operation status detection result and the corresponding historical operation status detection result to obtain a potential fault prediction result.

[0014] By adopting the above technical solution, the first intelligent control model is an initial intelligent control model, which is used for basic operation status monitoring and control; the second intelligent control model is a model that adds intelligent load balancing and circuit fault prediction functions on the basis of the first intelligent control model; the frequency limit threshold is a pre-set frequency range, which is used to determine whether the DC power supply module is within the normal working range; the first parameter detection result is a parameter detection result obtained based on the first intelligent control model; the second parameter detection result is a parameter detection result obtained based on the second intelligent control model; In a preferred example of the present application, after obtaining the operating parameter information of the DC power supply module through the communication interface and generating the first intelligent control model according to the topological circuit diagram and the operating parameter information, the method further includes: Acquire a detection area of ​​the data center, define the detection area as a response area, a focus area, and a lock area according to the power distribution position and supply characteristics, and assign different weight coefficients to each area; Using a clustering algorithm, all DC power modules in the data center are divided into corresponding response areas, focus areas, and lock areas to obtain area division results; Collect real-time operating parameters of DC power modules in data centers; According to the regional division results and the corresponding weight coefficients, an adaptive algorithm is used in combination with the real-time operation parameters to calculate the current regional score of each region; According to the current regional score of each area, the power status of each area is monitored in real time; when the score of any area exceeds the corresponding preset score threshold, a response prompt instruction is triggered to the preset user monitoring terminal.

[0015] By adopting the above technical solution, the monitoring area of ​​the data center is defined and divided into different areas. By assigning different weight coefficients to each area to reflect its importance in power management, the power status of the data center can be managed and monitored more finely. Among them, the response area is an area that requires immediate response, usually including key equipment and high-load equipment; the focus area is an area that requires special attention, usually including important but non-critical equipment; the lock area is an area that requires long-term monitoring, usually including general equipment; the clustering algorithm can automatically divide the DC power module into different areas, reducing the error and subjectivity of manual division; the current area score of each area is calculated by combining the real-time operating parameters and weight coefficients through the adaptive algorithm, so as to comprehensively evaluate the operating status of each area; the adaptive algorithm can dynamically adjust parameters according to real-time data to improve the accuracy of the evaluation; finally, the power status of each area is monitored in real time according to the current area score. When the score of any area exceeds the preset score threshold, a response prompt instruction is generated in time and sent to the preset user monitoring terminal; it is helpful for operation and maintenance personnel to take measures quickly to prevent the spread of faults and improve the response speed and processing efficiency of the system.

[0016] In a preferred example of the present application, the real-time operating parameters include voltage, current, power, temperature and the number of historical faults; the adaptive algorithm adopts formula (1): S i =α i V i +β i I i +γ i P i +δ i T i +θ i H i (1) Among them, S i is the regional score of the i-th region, i represents different regional identifiers, α i , β i , γ i , δ i ,θ i is a coefficient adjusted according to the needs of the data center and historical data; V i is the voltage of the ith region, I i is the current in the ith region, P i is the power of the ith region, T i is the temperature of the ith region, H i is the number of historical failures in the ith region.

[0017] By adopting the above technical solution, the importance of different parameters is determined according to the specific needs of the data center; for example, voltage and current may be more important for key equipment, while temperature and the number of historical failures may be more important for long-term stability; different weight coefficients α are set for each area i , β i , γ i , δ i ,θ i , ensuring that the weight coefficient can reflect the importance and impact of different parameters; using formula (1) to comprehensively consider voltage, current, power, temperature and the number of historical faults, calculate the regional score of each area; this helps to comprehensively evaluate the operating status of each area and provide a scientific basis for decision-making.

[0018] In the second aspect, the invention objective of the present application is achieved by adopting the following technical solutions: A control system for a communication DC power supply is applied to a control method for a communication DC power supply as described above, and the system comprises: A circuit diagram generating module, used for identifying the circuit diagram of the DC power module to be controlled, and generating a topological circuit diagram of the DC power module according to a preset circuit element table; A first intelligent control model generating module, used for acquiring operating parameter information of the DC power supply module through the communication interface, and generating a first intelligent control model according to the topological circuit diagram and the operating parameter information, wherein the first intelligent control model is used for simulating the performance of the DC power supply module under different working conditions; A second intelligent control model generating module, used to generate a second intelligent control model according to the topological circuit diagram and the first intelligent control model, wherein the second intelligent control model includes intelligent load balancing and circuit fault prediction functions; A monitoring result and prediction result acquisition module, used to obtain operation status monitoring results and potential fault prediction results based on the first intelligent control model and the second intelligent control model; The dynamic adjustment module is used to dynamically adjust the output power of the DC power supply module according to the operating status detection result and the potential fault prediction result, and transmit the adjustment instruction through the communication interface.

[0019] By adopting the above technical solution, in the management of the data center, the present invention realizes intelligent management of the DC power supply module by identifying the circuit diagram of the DC power supply module to be controlled, generating a topological circuit diagram, and generating a first intelligent control model and a second intelligent control model in combination with the operating parameter information. The operating parameter information of the DC power supply module can be obtained in real time through the communication interface, and the adjustment instruction is transmitted to the intelligent monitoring terminal or user terminal and other preset management platforms that are connected to the DC power supply module in communication, thereby improving the user's management efficiency of the DC power supply system, and is conducive to ensuring that the operating state of the DC power supply module is always in the optimal state. By generating an intelligent control model including intelligent load balancing and circuit fault prediction functions, potential faults are discovered in advance and preventive measures are taken, thereby improving the reliability and stability of the DC power supply system. The output power of the DC power supply module is dynamically adjusted through the operating state detection result, which is conducive to efficient and real-time adjustment according to the load conditions of many electrical equipment in the data center. The dynamic operation management mechanism is conducive to saving electricity and reducing the situation of insufficient power supply, and the intelligent management mode is conducive to reducing operation and maintenance costs.

[0020] In the third aspect, the invention objective of the present application is achieved by adopting the following technical solutions: A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned control method of a communication DC power supply when executing the computer program.

[0021] In a fourth aspect, the invention objective of the present application is achieved by adopting the following technical solutions: A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the control method of the above-mentioned communication DC power supply are implemented.

[0022] In summary, the present application includes at least one of the following beneficial technical effects: 1. In the management of a data center, the present invention realizes intelligent management of a DC power supply module by identifying a circuit diagram of a DC power supply module to be controlled, generating a topological circuit diagram, and generating a first intelligent control model and a second intelligent control model in combination with operating parameter information. The operating parameter information of the DC power supply module can be obtained in real time through a communication interface, and an adjustment instruction can be transmitted to a preset management platform such as an intelligent monitoring terminal or a user terminal that is connected to the DC power supply module in communication, thereby improving the user's management efficiency of the DC power supply system, and facilitating ensuring that the operating state of the DC power supply module is always in an optimal state. By generating an intelligent control model including intelligent load balancing and circuit fault prediction functions, potential faults can be discovered in advance and preventive measures can be taken, thereby improving the reliability and stability of the DC power supply system. The output power of the DC power supply module can be dynamically adjusted through the operating state detection result, which is conducive to efficient and real-time adjustment according to the load conditions of numerous electrical equipment in the data center. The dynamic operation management mechanism is conducive to saving electric energy and reducing the situation of insufficient power supply, and the intelligent management mode is conducive to reducing operation and maintenance costs; 2. In the management of the data center, the present invention realizes intelligent management of the DC power supply module by identifying the circuit diagram of the DC power supply module to be controlled, generating a topological circuit diagram, and generating a first intelligent control model and a second intelligent control model in combination with the operating parameter information. The operating parameter information of the DC power supply module can be obtained in real time through the communication interface, and the adjustment instruction can be transmitted to the intelligent monitoring terminal or user terminal and other preset management platforms that are connected to the DC power supply module in communication, thereby improving the user's management efficiency of the DC power supply system, and ensuring that the operating state of the DC power supply module is always in the optimal state. By generating an intelligent control model including intelligent load balancing and circuit fault prediction functions, potential faults can be discovered in advance and preventive measures can be taken to improve the reliability and stability of the DC power supply system. The output power of the DC power supply module can be dynamically adjusted according to the operating state detection results, which is conducive to efficient and real-time adjustment according to the load conditions of many electrical equipment in the data center. The dynamic operation management mechanism is conducive to saving electricity and reducing the situation of insufficient power supply, and the intelligent management mode is conducive to reducing operation and maintenance costs; 3. Define the monitoring area of ​​the data center and divide it into different areas. By assigning different weight coefficients to each area to reflect its importance in power management, the power status of the data center can be managed and monitored more finely. Among them, the response area is an area that requires immediate response, usually containing key equipment and high-load equipment; the focus area is an area that requires special attention, usually containing important but non-critical equipment; the lock area is an area that requires long-term monitoring, usually containing general equipment; the clustering algorithm can automatically divide the DC power module into different areas, reducing the error and subjectivity of manual division; the current area score of each area is calculated by combining the real-time operating parameters and weight coefficients through the adaptive algorithm, so as to comprehensively evaluate the operating status of each area; the adaptive algorithm can dynamically adjust parameters according to real-time data to improve the accuracy of the evaluation; finally, the power status of each area is monitored in real time according to the current area score. When the score of any area exceeds the preset score threshold, a response prompt instruction is generated in time and sent to the preset user monitoring terminal; it helps operation and maintenance personnel to take measures quickly to prevent the spread of faults and improve the response speed and processing efficiency of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flow chart of a control method of a communication DC power supply in one embodiment of the present application; Figure 2 This is an application example diagram of a DC power supply module of a communication DC power supply in one embodiment of the present application; Figure 3 This is a flowchart of step S1 in a method for controlling a communication DC power supply in one embodiment of the present application; Figure 4 This is a flow chart of step S2 in a method for controlling a communication DC power supply in one embodiment of the present application; Figure 5 This is a flow chart after step S2 in a method for controlling a communication DC power supply in one embodiment of the present application; Figure 6 It is a schematic diagram of a device in an embodiment of the present application.

[0024] Explanation of the accompanying drawings: 1. Power supply protection circuit; 11. Transient surge protection subcircuit; 12. Anti-reverse protection subcircuit; 13. Overcurrent and overvoltage protection subcircuit; 131. Overvoltage detection unit; 132. Overcurrent detection unit; 133. NAND gate unit; 134. Current sampling unit; 135. Protection switch unit; 2. Temperature monitoring circuit; 3. Main control circuit; 4. Buck circuit. DETAILED DESCRIPTION

[0025] The present application is further described in detail below in conjunction with the accompanying drawings.

[0026] In one embodiment, if Figure 1 As shown, the present application discloses a control method for a communication DC power supply, which specifically includes the following steps: S1: Identify the circuit diagram of the DC power module to be controlled, and generate a topological circuit diagram of the DC power module according to a preset circuit component table.

[0027] In this embodiment, the DC power supply module is designed with a communication interface and can communicate with an external system over a network and exchange data; that is, the DC power supply module can receive external instructions and send its own status information through the communication interface to achieve remote monitoring and control of the DC power supply module; the topological circuit diagram is a graphic model that can reflect the logical relationship between the various parts of the circuit.

[0028] Specifically, identifying the circuit diagram of the DC power supply module to be controlled refers to the process of automatically or manually identifying the internal circuit structure of the DC power supply module through software tools or hardware devices, including identifying the position, type and connection relationship of all circuit elements; for example, using circuit analysis software to import or manually draw the circuit diagram of the DC power supply module; automatically extracting key components in the circuit (such as resistors, capacitors, diodes, etc.) and their parameters (such as resistance value, capacitance value, withstand voltage value, etc.); recording the connection method between components to construct the logical structure of the circuit; and using the extracted component parameters and connection information to generate a topological circuit diagram that reflects the logical structure of the circuit.

[0029] like Figure 2 As shown, Figure 2 Taking the circuit diagram shown as an example, the DC power supply module comprises a power protection circuit 1, a temperature monitoring circuit 2, a step-down circuit 4 and a main control circuit 3, wherein the power protection circuit 1 is used to take protection measures for the DC power supply circuit according to the current and voltage conditions of the DC power supply circuit, the temperature monitoring circuit 2 is coupled to the power protection circuit 1, the output end of the temperature monitoring circuit 2 is coupled to the main control circuit 3, the temperature monitoring circuit 2 is used to obtain the temperature signal of the electronic device in the DC power supply circuit in real time, and output it to the main control circuit 3, and the output end of the main control circuit 3 is electrically connected to a heat dissipation device.

[0030] like Figure 2As shown, the power protection circuit 1 includes a transient surge protection subcircuit 11, an anti-reverse protection subcircuit 12 and an overcurrent and overvoltage protection subcircuit 13. The transient surge protection subcircuit 11 includes a voltage stabilizing diode TV1; the anti-reverse protection subcircuit 12 includes a diode D1, a MOS tube Q1, a resistor R1 and a resistor R2; the overcurrent and overvoltage protection subcircuit 13 includes an overcurrent detection unit 132, an overvoltage detection unit 131, a NAND gate unit 133, a current sampling unit 134 and a protection switch unit 135; the overvoltage detection unit 131 includes a comparator U2A, the non-inverting input terminal of the comparator U2A is coupled with a threshold voltage, and the inverting input terminal is coupled to a DC power supply circuit, the NAND gate unit 133 includes a chip U3, and the protection switch unit 135 includes a transistor Q3 and a MOS tube Q2. When receiving a signal from the NAND gate circuit 133, the protection switch unit 135 will output a low level through the chip U3 to trigger the protection switch unit 135.

[0031] S2: Obtain operating parameter information of the DC power module through the communication interface, and generate a first intelligent control model according to the topological circuit diagram and the operating parameter information, wherein the first intelligent control model is used to simulate the performance of the DC power module under different working conditions.

[0032] In this embodiment, the communication interface includes but is not limited to RS-232, USB, and Ethernet interfaces; the operating parameter information includes but is not limited to output voltage, output current, internal temperature, and fan speed; the first intelligent control model is based on the topological circuit diagram and real-time operating parameters to establish a mathematical model that can simulate the performance of the DC power supply module under different working conditions for performance evaluation and optimization.

[0033] Specifically, a performance simulation model of the DC power supply module is established using simulation software in combination with the topological circuit diagram and real-time operating parameters; the performance of the module in various situations is evaluated by simulating the circuit behavior under different working conditions.

[0034] S3: Generate a second intelligent control model according to the topological circuit diagram and the first intelligent control model, wherein the second intelligent control model includes intelligent load balancing and circuit fault prediction functions.

[0035] In this embodiment, the second intelligent control model is based on the first intelligent control model, and adds the functions of intelligent load balancing and circuit fault prediction to achieve a higher level of management and maintenance; Specifically, based on the first intelligent control model, an intelligent load balancing algorithm is introduced to ensure that the power module can evenly distribute the output power under multi-load conditions to improve overall efficiency; a fault prediction algorithm is introduced to identify possible fault points in advance by analyzing historical data and real-time data to reduce the risk of unexpected downtime.

[0036] S4: Based on the first intelligent control model and the second intelligent control model, obtain operation status monitoring results and potential fault prediction results.

[0037] In this embodiment, the operation status monitoring result is that the first intelligent control model and the second intelligent control model are respectively based on real-time analysis of the operation status information of the DC power supply module, including but not limited to load rate, temperature trend, voltage fluctuation, etc.

[0038] S5: According to the operation status detection result and the potential fault prediction result, dynamically adjust the output power of the DC power supply module, and transmit the adjustment instruction through the communication interface.

[0039] Specifically, when it is detected that the module is in a non-optimal working state, instructions are sent through the communication interface according to the model recommendation to adjust the output power of the module. That is, through a pre-set communication protocol, the adjustment instructions are encoded and sent to the DC power supply module through the communication interface. Through remote control, efficient management of the module is achieved and the operating process is simplified.

[0040] In one embodiment, if Figure 3 As shown, in step S1, the circuit diagram of the DC power module to be controlled is identified, and a topological circuit diagram of the DC power module is generated according to a preset circuit element table, specifically including: S11: Identify the circuit diagram of the DC power module to be controlled, extract the electrical parameter information of the circuit elements, the key nodes and paths of the circuit, and determine the key paths of the power flow and the signal flow based on the key nodes and paths of the circuit.

[0041] In this embodiment, the electrical parameter information includes electrical characteristic parameters of circuit elements, such as resistance value, capacitance value, inductance value, diode forward voltage drop, etc.; key nodes of the circuit include power input terminal, load output terminal, important branch points, etc., and the paths include main current paths and signal transmission paths; based on the key nodes and paths, the main flow paths of current and signals are determined, that is, the key paths of power flow and signal flow are determined.

[0042] S12: generating a topological circuit diagram of the DC power module according to the electrical parameter information of the circuit elements of the DC power module and a preset circuit element table, and inputting the circuit copper coverage rate information into the topological circuit diagram.

[0043] In this embodiment, the topological circuit diagram should include all key components of the DC power supply module and their connection relationships; the circuit copper coverage information is the distribution and density information of the copper foil on the circuit board; the circuit copper coverage information is input into the topological circuit diagram to reflect the physical properties of the actual circuit board; the copper coverage information can be obtained through the circuit board design file (such as the Gerber file), and the distribution of the copper foil is marked in the topological circuit diagram.

[0044] S13: Optimize the topology circuit diagram based on the critical paths of power flow and signal flow.

[0045] In this embodiment, the critical path is optimized according to the critical paths of power flow and signal flow, and the topological circuit diagram is optimized. The optimization goals include reducing signal interference, reducing power loss, improving heat dissipation performance, etc. Then, the component layout is adjusted, that is, the layout of circuit components is adjusted according to the optimization results to ensure that the component positions on the critical path are reasonable and to reduce unnecessary routing lengths and crossings. The optimized topological circuit diagram is verified by simulation tools to ensure that the optimization measures effectively improve the performance and reliability of the circuit.

[0046] In one embodiment, if Figure 4 As shown, in step S2, the operating parameter information of the DC power module is obtained through the communication interface, and a first intelligent control model is generated according to the topological circuit diagram and the operating parameter information. The first intelligent control model is used to simulate the performance of the DC power module under different working conditions, and specifically includes: S21: Calculate the thermal distribution influencing parameters of the DC power supply module using a finite element analysis algorithm according to the operating parameter information.

[0047] Specifically, the operating parameters of the DC power module, such as input voltage, output voltage, current, temperature, etc., are obtained in real time through the communication interface; then, the finite element analysis software (such as ANSYS, COMSOL, etc.) is used to calculate the thermal distribution of the DC power module under different working conditions based on the acquired operating parameter information. This includes the distribution of the temperature field, the location of hot spots, and the heat dissipation path; then, the thermal distribution influencing parameters, such as the maximum temperature rise, average temperature, and temperature gradient, are extracted from the finite element analysis results.

[0048] S22: Calculate parasitic component influence parameters of parasitic components of the DC power module using multi-physics field simulation software according to the operating parameter information and the electrical parameter information, where the parasitic components include parasitic capacitance and parasitic inductance.

[0049] Specifically, electrical parameter information of circuit elements, such as resistance, capacitance, and inductance, is extracted from the topological circuit diagram, and then multi-physics simulation is performed: multi-physics simulation software (such as CST Microwave Studio, HFSS, etc.) is used to combine operating parameter information and electrical parameter information to calculate the influence of parasitic capacitance and parasitic inductance in the DC power supply module; parasitic element influence parameters are parasitic element influence parameters extracted from the simulation results, such as parasitic capacitance, parasitic inductance, and parasitic resistance.

[0050] S23: Obtain comprehensive performance influencing parameters of the DC power supply module to be controlled according to the heat distribution influencing parameters and the parasitic element influencing parameters; generate a first intelligent control model according to the topological circuit diagram and the comprehensive performance influencing parameters.

[0051] In this embodiment, the heat distribution influencing parameters and the parasitic element influencing parameters are combined to evaluate the comprehensive performance of the DC power supply module under different working conditions; the comprehensive performance influencing parameters include the influence of temperature on component performance and the influence of parasitic elements on circuit stability.

[0052] Specifically, generating the first intelligent control model means generating the first intelligent control model based on the topological circuit diagram and comprehensive performance influencing parameters using machine learning or artificial intelligence algorithms (such as neural networks, support vector machines, etc.), which can simulate the performance of the DC power supply module under different working conditions and provide a basis for subsequent control strategies.

[0053] In one embodiment, in step S3, a second intelligent control model is generated according to the topological circuit diagram and the first intelligent control model, and the second intelligent control model includes intelligent load balancing and circuit fault prediction functions, including: S31: Optimize the electrical parameters of the DC power module using a genetic algorithm based on the comprehensive performance influencing parameters, and generate optimized comparative electrical parameter information.

[0054] In this embodiment, the thermal distribution influencing parameters and the parasitic component influencing parameters are used as inputs of the genetic algorithm; and optimization goals are set, such as minimizing temperature, maximizing efficiency, and minimizing parasitic effects; then, the optimal electrical parameter combination is searched through the genetic algorithm (such as selection, crossover, mutation, etc.) to obtain the optimized comparative electrical parameter information, and the optimized electrical parameter information is saved for subsequent circuit optimization.

[0055] S32: updating the topology circuit diagram of the DC power supply module according to the optimized comparison electrical parameter information, and generating a second topology circuit diagram.

[0056] Specifically, the optimized comparative electrical parameter information is applied to the corresponding elements in the topological circuit diagram; a second topological circuit diagram is generated according to the updated electrical parameters, and a new topological circuit diagram is generated to ensure the consistency of the circuit structure and parameters; the updated circuit diagram is verified by a simulation tool to ensure that its performance meets expectations.

[0057] S33: A multi-objective optimization algorithm is used to optimize the second topology circuit diagram, and a second intelligent control model is generated based on a deep learning algorithm combined with the optimized second topology circuit diagram and the first intelligent control model; the second intelligent control module is used to analyze the parameter operation data of the DC power supply module and automatically adjust the load distribution strategy.

[0058] In this embodiment, multi-objective optimization refers to the use of a multi-objective optimization algorithm (such as NSGA-II, MOEA / D, etc.) to balance multiple performance indicators (such as temperature, efficiency, stability, etc.) to further optimize the second topology circuit diagram; the second intelligent control model includes intelligent load balancing and circuit fault prediction functions, which can automatically adjust the load distribution strategy according to real-time operation data and predict potential circuit failures.

[0059] Specifically, in one embodiment, in step S4, based on the first intelligent control model and the second intelligent control model, the operation status monitoring result and the potential fault prediction result are obtained, which specifically includes: S41: triggering an intelligent control instruction based on the first intelligent control model and the second intelligent control model.

[0060] In this embodiment, the intelligent control instruction is an instruction generated by the intelligent control model and is used to control the operating state of the DC power supply module.

[0061] Specifically, according to the current operating status, the first intelligent control model and the second intelligent control model respectively generate intelligent control instructions, and the contents of the intelligent control instructions include but are not limited to adjusting load distribution, changing operating frequency, and starting fault detection; executing intelligent control instructions: sending the generated intelligent control instructions to the DC power supply module to control its operating status.

[0062] S42: Based on the intelligent control instruction, in the first intelligent control model and the second intelligent control model, a frequency domain analysis method is used to determine the resonant frequency range of the DC power supply module.

[0063] In this embodiment, the frequency domain analysis method refers to converting the time domain signal to the frequency domain through methods such as Fourier transform to analyze the frequency components of the signal; the resonant frequency range is the frequency interval in which the DC power supply module may resonate within a specific frequency range.

[0064] Specifically, by analyzing the frequency domain signal, it is determined in which frequency ranges the DC power module may resonate, so as to determine the resonant frequency range.

[0065] S43: Acquire the response characteristics of the DC power supply module at different frequencies through frequency scanning and generate a frequency response curve; trigger a parameter monitoring instruction according to the frequency response curve and a preset frequency limit threshold, and obtain a first parameter detection result and a second parameter detection result respectively.

[0066] In this embodiment, the parameter monitoring instruction is an instruction for monitoring specific parameters of the DC power supply module.

[0067] Specifically, frequency scanning refers to gradually changing the input frequency within a determined resonant frequency range, recording the response characteristics of the DC power supply module at different frequencies, and after the frequency scanning, plotting the response characteristics at different frequencies into a frequency response curve; then, based on the frequency response curve and the frequency limit threshold, generating parameter monitoring instructions, monitoring specific parameters, and executing the parameter monitoring instructions to obtain the first parameter detection result and the second parameter detection result, respectively.

[0068] S44: Obtaining an operation status detection result according to the first parameter detection result and the second parameter detection result; and predicting a potential fault based on the operation status detection result and the corresponding historical operation status detection result to obtain a potential fault prediction result.

[0069] In this embodiment, the first parameter detection result is a parameter detection result obtained based on the first intelligent control model; the second parameter detection result is a parameter detection result obtained based on the second intelligent control model; the potential fault prediction result is a potential fault condition predicted based on the current and historical operating status detection results; the operating status detection result is to generate the final operating status detection result, including but not limited to the status of key parameters such as voltage, current, and temperature.

[0070] Specifically, historical operating status detection results are collected and stored for comparative analysis, and based on the current operating status detection results and historical operating status detection results, machine learning algorithms (such as support vector machines, decision trees, etc.) are used to predict potential faults; then potential fault prediction results are generated, including fault type, probability of occurrence, recommended measures, etc.

[0071] In one embodiment, if Figure 5 As shown, after step S2, a control method for a communication DC power supply also includes: S201: obtaining a detection area of ​​a data center, defining the detection area as a response area, a focus area, and a lock area according to the power distribution location and supply characteristics, and assigning different weight coefficients to each area.

[0072] In this embodiment, the response zone is an area that requires immediate response, usually including critical equipment and high-load equipment; the attention zone is an area that requires special attention, usually including important but non-critical equipment; the lock zone is an area that requires long-term monitoring, usually including general equipment; the weight coefficient is a different importance coefficient assigned to each area, which is used to calculate the area score.

[0073] Specifically, the detection area is divided into response area, attention area and lock area according to the power distribution location and supply characteristics: the response area contains key equipment and high-load equipment, which requires immediate response; the attention area contains important but non-critical equipment, which requires special attention; the lock area contains general equipment, which requires long-term monitoring; and then each area is assigned a different weight coefficient to reflect its importance. For example, the response area has the highest weight coefficient, and the lock area has the lowest weight coefficient.

[0074] S202: using a clustering algorithm to divide all DC power modules of the data center into corresponding response areas, focus areas, and lock areas, and obtain area division results.

[0075] Specifically, the regional division result is the region to which each DC power module belongs obtained through a clustering algorithm; the physical location and power supply characteristic data of all DC power modules in the data center are collected; then a clustering algorithm (such as K-means, DBSCAN, etc.) is used to divide the DC power modules into response areas, attention areas and lock areas; the regional division result refers to the generation of the area to which each DC power module belongs, forming a regional division result.

[0076] S203: Collect real-time operating parameters of the DC power supply modules of the data center.

[0077] In this embodiment, the real-time operating parameters include voltage, current, power, temperature and the number of historical faults.

[0078] Specifically, the operating parameters of each DC power supply module, such as input voltage, output voltage, current, temperature, etc., are acquired in real time through the communication interface; and the real-time operating parameters are stored in the monitoring system of the data center to ensure the integrity and real-time nature of the data.

[0079] S204: According to the regional division results and the corresponding weight coefficients, an adaptive algorithm is used in combination with real-time operation parameters to calculate the current regional score of each region.

[0080] In this embodiment, the adaptive algorithm adopts formula (1): S i =α i V i +β i I i +γ i P i +δ i T i +θ i H i (1) Among them, S i is the regional score of the i-th region, i represents different regional identifiers, α i , βi , γ i , δ i ,θ i is a coefficient adjusted according to the needs of the data center and historical data; V i is the voltage of the ith region, I i is the current in the ith region, P i is the power of the ith region, T i is the temperature of the ith region, H i is the number of historical failures in the ith region.

[0081] Specifically, an adaptive algorithm (such as an adaptive filter, an adaptive neural network, etc.) is used to calculate the current regional score of each region according to the real-time operating parameters and the weight coefficient, and then the real-time operating parameters and the weight coefficient of each region are comprehensively considered to calculate the current regional score of each region.

[0082] For example, suppose we have a monitoring area with a voltage of 120V, a current of 5A, a power of 600W, a temperature of 30°C, and a health status of good (H i =1). We set the coefficient as: (α i =1, β i =1,γ i =1,δ i =1,θ i =1, then the score of the area is calculated as follows: S i =1*120+1*5+1*600+1*30+1*1=756, this score can be used to evaluate the power status of the area and compared with the scores of other areas to determine which areas may need more attention or adjustment.

[0083] S205: According to the current regional score of each area, the power status of each area is monitored in real time; when the score of any area exceeds the corresponding preset score threshold, a response prompt instruction is triggered to a preset user monitoring terminal.

[0084] Specifically, the power status of each area is first monitored in real time based on the calculated current area score; then a preset score threshold is set for each area to determine whether the score of the area exceeds the normal range; when the score of any area exceeds the preset score threshold, a response prompt instruction is generated and sent to the preset user monitoring terminal through the communication interface to remind the operation and maintenance personnel to take corresponding measures, which helps the operation and maintenance personnel to take measures quickly to prevent the spread of faults and improve the response speed and processing efficiency of the system.

[0085] It should be understood that the serial numbers of the steps in the above embodiments do not imply a sequence of execution. The execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0086] In one embodiment, a control system of a communication DC power supply is provided, and the control system of the communication DC power supply corresponds to a control method of a communication DC power supply in the above-mentioned embodiment.

[0087] A control system for a communication DC power supply includes a circuit diagram generation module, a first intelligent control model generation module, a second intelligent control model generation module, and a monitoring result and prediction result acquisition module. The detailed description of each functional module is as follows: a circuit diagram generation module, used to identify the circuit diagram of a DC power supply module to be controlled, and generate a topological circuit diagram of the DC power supply module according to a preset circuit element table; A first intelligent control model generating module, used to obtain operating parameter information of the DC power supply module through the communication interface, and generate a first intelligent control model according to the topological circuit diagram and the operating parameter information, wherein the first intelligent control model is used to simulate the performance of the DC power supply module under different working conditions; A second intelligent control model generating module, used to generate a second intelligent control model according to the topological circuit diagram and the first intelligent control model, wherein the second intelligent control model includes intelligent load balancing and circuit fault prediction functions; A monitoring result and prediction result acquisition module, used to obtain operation status monitoring results and potential fault prediction results based on the first intelligent control model and the second intelligent control model; The dynamic adjustment module is used to dynamically adjust the output power of the DC power supply module according to the operating status detection results and potential fault prediction results, and transmit the adjustment instructions through the communication interface.

[0088] For the specific definition of a control system of a communication DC power supply, please refer to the definition of a control method of a communication DC power supply in the above text, which will not be repeated here; each module in the control system of the above-mentioned communication DC power supply can be implemented in whole or in part by software, hardware and a combination thereof; each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0089] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 6As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store a topological circuit diagram, a first intelligent control model and a second intelligent control model, etc. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a control method for a communication DC power supply is implemented.

[0090] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements steps of a method for controlling a communication DC power supply when executing the computer program.

[0091] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of a control method of a communication direct current power supply are implemented.

[0092] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0093] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0094] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments may still be modified, or some of the features thereof may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for controlling a communication DC power supply, characterized in that: include: A direct current module with communication function, the method comprising: Identify the circuit diagram of the DC power module to be controlled, and generate a topological circuit diagram of the DC power module according to a preset circuit element table; Acquire operating parameter information of the DC power module through the communication interface, and generate a first intelligent control model according to the topological circuit diagram and the operating parameter information, wherein the first intelligent control model is used to simulate the performance of the DC power module under different working conditions; Generate a second intelligent control model according to the topological circuit diagram and the first intelligent control model, wherein the second intelligent control model includes intelligent load balancing and circuit fault prediction functions; Based on the first intelligent control model and the second intelligent control model, obtaining operation status monitoring results and potential fault prediction results; According to the operating status detection result and the potential fault prediction result, the output power of the DC power supply module is dynamically adjusted, and the adjustment instruction is transmitted through the communication interface.

2. A communication DC power supply control method according to claim 1, characterized in that: The step of identifying a circuit diagram of a DC power supply module to be controlled and generating a topological circuit diagram of the DC power supply module according to a preset circuit element table specifically includes: Identify the circuit diagram of the DC power module to be controlled, extract the electrical parameter information of the circuit elements, the key nodes and paths of the circuit, and determine the key paths of the power flow and signal flow based on the key nodes and paths of the circuit; Generate a topological circuit diagram of the DC power module according to the electrical parameter information of the circuit elements of the DC power module and a preset circuit element table, and input the circuit copper coverage rate information into the topological circuit diagram; The topology circuit diagram is optimized based on the critical paths of the power flow and the signal flow.

3. A communication DC power supply control method according to claim 2, characterized in that: The operation parameter information of the DC power module is obtained through the communication interface, and a first intelligent control model is generated according to the topological circuit diagram and the operation parameter information. The first intelligent control model is used to simulate the performance of the DC power module under different working conditions, and specifically includes: According to the operating parameter information, a finite element analysis algorithm is used to calculate the thermal distribution influence parameters of the DC power supply module; according to the operating parameter information and the electrical parameter information, a multi-physics field simulation software is used to calculate the parasitic element influence parameters of the parasitic elements of the DC power supply module, wherein the parasitic elements include parasitic capacitance and parasitic inductance; According to the heat distribution influencing parameters and the parasitic element influencing parameters, the comprehensive performance influencing parameters of the DC power supply module to be controlled are obtained; according to the topological circuit diagram and the comprehensive performance influencing parameters, a first intelligent control model is generated.

4. A communication DC power supply control method according to claim 3, characterized in that: The second intelligent control model is generated according to the topological circuit diagram and the first intelligent control model, wherein the second intelligent control model includes intelligent load balancing and circuit fault prediction functions, including: According to the comprehensive performance influencing parameters, using a genetic algorithm, optimizing the electrical parameters of the DC power supply module to generate optimized comparative electrical parameter information; According to the optimized comparison electrical parameter information, updating the topological circuit diagram of the DC power supply module to generate a second topological circuit diagram; A multi-objective optimization algorithm is used to optimize the second topology circuit diagram, and a second intelligent control model is generated based on a deep learning algorithm combined with the optimized second topology circuit diagram and the first intelligent control model; the second intelligent control module is used to analyze the parameter operation data of the DC power supply module and automatically adjust the load distribution strategy.

5. A communication DC power supply control method according to claim 1, characterized in that: The obtaining of the operation status monitoring result and the potential fault prediction result based on the first intelligent control model and the second intelligent control model specifically includes: triggering an intelligent control instruction based on the first intelligent control model and the second intelligent control model; Based on the intelligent control instruction, in the first intelligent control model and the second intelligent control model, a frequency domain analysis method is used to determine a resonant frequency range of the DC power supply module; Acquire the response characteristics of the DC power supply module at different frequencies by frequency scanning, and generate a frequency response curve; trigger a parameter monitoring instruction according to the frequency response curve combined with a preset frequency limit threshold, and obtain a first parameter detection result and a second parameter detection result respectively; An operation status detection result is obtained according to the first parameter detection result and the second parameter detection result; and a potential fault is predicted based on the operation status detection result and the corresponding historical operation status detection result to obtain a potential fault prediction result.

6. A communication DC power supply control method according to claim 1, characterized in that: After obtaining the operating parameter information of the DC power supply module through the communication interface and generating the first intelligent control model according to the topological circuit diagram and the operating parameter information, the method further includes: Acquire a detection area of ​​the data center, define the detection area as a response area, a focus area, and a lock area according to the power distribution position and supply characteristics, and assign different weight coefficients to each area; Using a clustering algorithm, all DC power modules in the data center are divided into corresponding response areas, focus areas, and lock areas to obtain area division results; Collect real-time operating parameters of DC power modules in data centers; According to the regional division results and the corresponding weight coefficients, an adaptive algorithm is used in combination with the real-time operation parameters to calculate the current regional score of each region; According to the current regional score of each area, the power status of each area is monitored in real time; when the score of any area exceeds the corresponding preset score threshold, a response prompt instruction is triggered to the preset user monitoring terminal.

7. A communication DC power supply control method according to claim 6, characterized in that: The real-time operating parameters include voltage, current, power, temperature and the number of historical faults; the adaptive algorithm adopts formula (1): S i =a i V i +b i I i +g i P i +d i T i +θ i H i (1) Among them, S i is the regional score of the i-th region, i represents different regional identifiers, α i , β i , γ i , δ i ,θ i is a coefficient adjusted according to the needs of the data center and historical data; V i is the voltage of the ith region, I i is the current in the ith region, P i is the power of the ith region, T i is the temperature of the ith region, H i is the number of historical failures in the ith region.

8. A control system for a communication DC power supply, characterized in that: A control method for a communication DC power supply according to any one of claims 1 to 7, wherein the system comprises: A circuit diagram generating module, used for identifying the circuit diagram of the DC power module to be controlled, and generating a topological circuit diagram of the DC power module according to a preset circuit element table; A first intelligent control model generating module, used for acquiring operating parameter information of the DC power supply module through the communication interface, and generating a first intelligent control model according to the topological circuit diagram and the operating parameter information, wherein the first intelligent control model is used for simulating the performance of the DC power supply module under different working conditions; A second intelligent control model generating module, used to generate a second intelligent control model according to the topological circuit diagram and the first intelligent control model, wherein the second intelligent control model includes intelligent load balancing and circuit fault prediction functions; A monitoring result and prediction result acquisition module, used to obtain operation status monitoring results and potential fault prediction results based on the first intelligent control model and the second intelligent control model; The dynamic adjustment module is used to dynamically adjust the output power of the DC power supply module according to the operating status detection result and the potential fault prediction result, and transmit the adjustment instruction through the communication interface.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the control method of a communication DC power supply as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of a method for controlling a communication DC power supply as described in any one of claims 1 to 7 are implemented.

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