Power supply analysis method and analysis system for a motherboard

Abstract

The application provides a power supply analysis method and analysis system of a mainboard, relates to the technical field of mainboards, and comprises a power supply system of a plurality of local mainboards. The power supply system comprises a plurality of distributed nodes and a master node for coordinating the distributed nodes. The method comprises the following steps: collecting, by each distributed node, working parameters of the local mainboard where the distributed node is located, and preprocessing the working parameters; inputting the preprocessed working parameters into a PID controller configured in the distributed node, to generate a preliminary control output; sending, by each distributed node, the preliminary control output and the working parameters to the master node, and obtaining, by the master node, adjusted PID parameters and a final control output by using an adaptive fuzzy logic controller of the master node; evaluating, according to the adjusted PID parameters and the final control output, a local running state of the local mainboard where each distributed node is located; and sending, by each distributed node, the local running state to the master node, and judging, by the master node, a global running state of the power supply system according to preset state indexes.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of mainboards, and in particular to a power supply analysis method and system for mainboards. BACKGROUND

[0002] In modern computer systems, the mainboard as a core component, its power supply stability and performance are directly related to the running efficiency and reliability of the entire system. With the rapid development of computer technology, the design of the mainboard is increasingly complex, and the power supply demand is also rising, which puts higher requirements on the management of the power supply system. The traditional power supply management method often adopts centralized control, that is, a single control unit is responsible for monitoring and adjusting the state of the entire power supply system. However, this method has slow response speed, low control accuracy and other problems when facing large-scale, multi-node power supply systems, and it is difficult to meet the needs of modern computer systems for power supply stability and flexibility.

[0003] Therefore, it is necessary to provide a power supply analysis method and system for mainboards to solve the above technical problems. SUMMARY

[0004] To solve the above technical problems, the present application provides a power supply analysis method and system for mainboards, which adopts a distributed power supply management method, combines an adaptive fuzzy logic controller and a PID controller, and can realize accurate control, intelligent optimization and real-time state evaluation of large-scale, multi-node power supply systems.

[0005] The present application provides a power supply analysis method for mainboards, applied to a power supply system including a plurality of local mainboards, the power supply system including distributed nodes corresponding to being configured in each local mainboard and a master node for coordinating each distributed node, wherein each distributed node is configured with a PID controller, and the master node is configured with an adaptive fuzzy logic controller, the analysis method comprising the following steps:

[0006] Each distributed node respectively collects the working parameters of the local mainboard where it is located, and pre-processes the working parameters;

[0007] The pre-processed working parameters are input into the PID controller configured in the distributed node to generate a preliminary control output;

[0008] Each distributed node sends the preliminary control output and working parameters to the master node, and uses the adaptive fuzzy logic controller of the master node to dynamically adjust the PID parameters to obtain adjusted PID parameters, and optimizes the preliminary control output of each distributed node to generate a final control output;

[0009] Each distributed node evaluates the local running state of the local mainboard according to the adjusted PID parameters and the final control output;

[0010] Each distributed node sends the local running state to the master node, and the master node determines the global running state of the power supply system according to a preset state index.

[0011] Preferably, each distributed node respectively collects the working parameters of the local motherboard where the distributed node is located, and pre-processes the working parameters, including:

[0012] Each distributed node monitors and collects the working parameters of the local motherboard where the distributed node is located in real time through a built-in sensor module;

[0013] The collected working parameters are filtered to remove noise and interference signals;

[0014] The filtered working parameters are normalized to convert to a unified dimension and range;

[0015] The normalized working parameters are feature extracted to obtain feature values.

[0016] Preferably, the pre-processed working parameters are input into a PID controller configured by the distributed node to generate a preliminary control output, including:

[0017] Each distributed node formats the pre-processed working parameters according to the input requirements of the PID controller;

[0018] The formatted working parameters are input into the PID controller, and the PID controller calculates the input working parameters in real time according to a preset control algorithm to obtain a calculation result;

[0019] The PID controller generates a corresponding preliminary control output according to the calculation result, wherein the preliminary control output is used to adjust the power supply state of the local motherboard;

[0020] The power supply of the local motherboard is adjusted in real time according to the preliminary control output to preliminarily control the power supply state of the local motherboard.

[0021] Preferably, each distributed node sends the preliminary control output and the working parameters to the master node, and uses an adaptive fuzzy logic controller of the master node to dynamically adjust the PID parameters to obtain adjusted PID parameters, and optimizes the preliminary control output of each distributed node to generate a final control output, including:

[0022] The preliminary control output and the working parameters are converted into corresponding membership degrees using a predefined membership function;

[0023] According to the fuzzy rules in the predefined fuzzy rule base and in combination with the membership evaluation of the activation degree of each fuzzy rule, the output fuzzy set of all fuzzy rules is aggregated to form a total output fuzzy set;

[0024] The total output fuzzy set is converted into an output value using the barycenter method, and the output value is used as an adjusted PID parameter;

[0025] According to the adjusted PID parameter, the preliminary control output of each distributed node is adjusted to obtain a final control output.

[0026] Preferably, the adjustment of the preliminary control output of each distributed node according to the adjusted PID parameter to obtain a final control output comprises:

[0027] Each distributed node receives the adjusted PID parameter issued by the master node, and compares the received adjusted PID parameter with the currently configured PID parameter to identify the parameter item to be updated;

[0028] According to the identified parameter item to be updated, the PID controller is updated;

[0029] The PID controller after parameter update re-calculates according to the new PID parameter and the currently monitored working parameter to generate a final control output.

[0030] Preferably, the evaluation of the local running state of the local motherboard by each distributed node according to the adjusted PID parameter and the final control output comprises:

[0031] Each distributed node monitors and records the change of the working parameter of the local motherboard in real time according to the adjusted PID parameter and the final control output;

[0032] Each distributed node evaluates the voltage stability, current stability, temperature monitoring and load condition of the local motherboard according to a preset state evaluation model to generate a local running state report;

[0033] Each distributed node sends the local running state report to the master node for global state evaluation.

[0034] Preferably, the evaluation of the voltage stability, current stability, temperature monitoring and load condition of the local motherboard by each distributed node according to a preset state evaluation model to generate a local running state report comprises:

[0035] Each distributed node evaluates the voltage stability according to the change range and fluctuation value of the input voltage and output voltage;

[0036] Each distributed node evaluates the current stability according to the change range and fluctuation value of the current.

[0037] Each distributed node evaluates whether the temperature is within a preset safety range according to the temperature change of the temperature monitoring position;

[0038] Each distributed node evaluates whether the load is within a preset reasonable range according to the change of the load;

[0039] Each distributed node generates a local running state report according to the evaluation result, wherein the local running state report contains the values of each evaluation and the evaluation conclusion.

[0040] Preferably, the local running state of each distributed node is sent to the master node, and the master node judges the global running state of the power supply system according to a preset state index, including:

[0041] The master node compares the local running state report of each distributed node with the corresponding threshold in a preset state index set to obtain the local running state evaluation result of each local motherboard, wherein the preset state index set includes a voltage stability threshold, a current stability threshold, a temperature safety threshold and a load reasonableness threshold;

[0042] The master node generates a global running state report of the power supply system by comprehensively considering the local running state evaluation results of all distributed nodes, and judges the global running state of the power supply system according to the global running state report, wherein the global running state includes a stable state, an abnormal state and a performance insufficient state;

[0043] If the judgment result is the stable state, the master node continues to monitor the running of the power supply system;

[0044] If the judgment result is the abnormal state and the performance insufficient state, the master node generates corresponding adjustment instructions and sends them to the related distributed nodes to re-adjust the PID parameters.

[0045] The application also provides a power supply analysis system of a motherboard for executing the power supply analysis method of the motherboard, which is applied to a power supply system including a plurality of local motherboards, the power supply system including distributed nodes corresponding to the local motherboards and a master node for coordinating the distributed nodes, wherein each distributed node is configured with a PID controller, and the master node is configured with an adaptive fuzzy logic controller, and the analysis system includes:

[0046] A parameter processing module is configured to collect the working parameters of the local motherboard of each distributed node and pre-process the working parameters;

[0047] A preliminary control module is configured to input the pre-processed working parameters into the PID controller of the distributed node to generate a preliminary control output;

[0048] An adjustment and optimization module is configured to send the preliminary control output and the working parameters to the master node by each distributed node, and to dynamically adjust the PID parameters by using the adaptive fuzzy logic controller of the master node to obtain adjusted PID parameters, and to optimize the preliminary control output of each distributed node to generate a final control output.

[0049] A local running state evaluation module is configured to evaluate the local running state of the local motherboard by each distributed node according to the adjusted PID parameters and the final control output.

[0050] A global running state judgment module is configured to send the local running state to the master node by each distributed node, and to judge the global running state of the power supply system by the master node according to a preset state index.

[0051] Compared with the related art, the power supply analysis method and analysis system for a motherboard provided by the application have the following beneficial effects:

[0052] The application realizes distributed monitoring and control of the power supply system by configuring distributed nodes in each local motherboard. Each distributed node has functions of data acquisition, preliminary control and state evaluation, can acquire working parameters of the local motherboard in real time, and can generate preliminary control output by preprocessing. The preliminary control output and the working parameters are then sent to the master node for global coordination and optimization.

[0053] At the master node level, an adaptive fuzzy logic controller is usually used to realize dynamic adjustment and optimization of PID (proportional-integral-derivative) controller parameters. The adaptive fuzzy logic controller can intelligently adjust the PID parameters according to the preliminary control output and the working parameters sent by the distributed nodes, in combination with a predefined membership function and a fuzzy rule base, so as to realize fine control of the power supply system. This control method not only improves the control precision, but also enhances the adaptability and robustness of the system.

[0054] In addition, each distributed node can also evaluate the local running state of the local motherboard according to the adjusted PID parameters and the final control output. By monitoring and recording the changes of the working parameters in real time, and comprehensively evaluating the voltage stability, the current stability, the temperature monitoring and the load condition according to a preset state evaluation model, the distributed node can generate a detailed local running state report and send it to the master node. The master node can judge the global running state of the power supply system according to the report in combination with corresponding threshold values in a preset state index set.

[0055] In summary, by using the distributed power supply management method, combining the adaptive fuzzy logic controller and the PID controller, the precise control, intelligent optimization and real-time state evaluation of the large-scale and multi-node power supply system can be realized. BRIEF DESCRIPTION OF DRAWINGS

[0056] Figure 1 A flow chart of a power supply analysis method of a mainboard provided by the present application is shown in the figure.

[0057] Figure 2 A module structure diagram of a power supply analysis system of a mainboard provided by the present application is shown in the figure. DETAILED DESCRIPTION

[0058] The present application will be further described below in conjunction with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not to limit the present application. In addition, it should be noted that only the parts related to the present application are shown in the drawings for the convenience of description, not all the structures. Furthermore, the embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0059] In addition, it should be noted that only the parts related to the present application are shown in the drawings for the convenience of description, not all the contents. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow chart describes each operation (or step) as a sequential process, many of the operations can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operations are completed, but can also have additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0060] Embodiment one

[0061] The present application provides a power supply analysis method of a mainboard, which is applied to a power supply system including a plurality of local mainboards. The power supply system is composed of a plurality of distributed nodes and a master node, each distributed node is configured in each local mainboard, and the master node is responsible for coordinating and managing all distributed nodes.

[0062] Among them, the distributed node is responsible for real-time monitoring and collecting the working parameters of the local mainboard where it is located, and performing preprocessing, preliminary control and local state evaluation.

[0063] The distributed node is equipped with a variety of sensors, including voltage sensors, current sensors, temperature sensors and load sensors, which are installed at key positions of the mainboard, such as power input end, key circuit node, heat dissipation area and load connection point.

[0064] The processor of the distributed node is responsible for processing the data collected by the sensor, executing the PID control algorithm, generating the preliminary control output, and communicating with the master node.

[0065] The distributed node communicates with the sensor module through an internal communication interface (including but not limited to SPI, I2C), and communicates with the master node through a network interface (including but not limited to Ethernet, CAN bus).

[0066] The master node is responsible for coordinating and managing all distributed nodes, receiving the preliminary control output and working parameters from each distributed node, using an adaptive fuzzy logic controller to dynamically adjust the PID parameters, generating the final control output, and evaluating the global operating state of the power supply system.

[0067] The processor of the master node is responsible for processing data from each distributed node, executing the adaptive fuzzy logic control algorithm, generating adjustment instructions, and issuing them to the relevant distributed nodes.

[0068] Similarly, the master node communicates with each distributed node through a network interface (such as Ethernet, CAN bus), collects data and issues control instructions.

[0069] Reference Figure 1 The analysis method includes the following steps:

[0070] S1: Each distributed node collects the working parameters of the local motherboard it is located on and pre-processes the working parameters.

[0071] Specifically, step S1 includes the following steps:

[0072] S11: Each distributed node monitors and collects the working parameters of the local motherboard it is located on in real time through the built-in sensor module.

[0073] In the power supply system, real-time monitoring of working parameters is the basis for ensuring stable operation of the system. The sensor module includes voltage sensors, current sensors, temperature sensors, and load sensors for collecting various working parameters on the motherboard.

[0074] Sensor module configuration: Each distributed node is equipped with multiple sensors such as voltage sensors, current sensors, temperature sensors, and load sensors, which are installed at key locations on the motherboard such as power input, key circuit nodes, heat dissipation areas, and load connection points.

[0075] The sensor module collects working parameters at a high frequency (such as multiple times per second) to ensure real-time and accuracy of data. The collected electrical parameters are transmitted to the processor of the distributed node through an internal communication interface (such as SPI, I2C) for subsequent processing.

[0076] S12: Filtering the collected working parameters to remove noise and interference signals.

[0077] In this embodiment, filters including low-pass filters, high-pass filters, band-pass filters and digital filters (such as IIR filters and FIR filters) are used, and the collected electrical parameters are input into the selected filter to filter out high-frequency noise and low-frequency interference. For example, a low-pass filter is used to remove high-frequency noise, and a high-pass filter is used to remove low-frequency drift.

[0078] In addition, the filter cutoff frequency and other parameters need to be set according to the actual application scenario and sensor characteristics to achieve the best filtering effect.

[0079] S13: Normalizing the filtered working parameters to convert them into a unified dimension and range.

[0080] In this embodiment, the normalization range is determined according to actual needs, and the range between 0 and 1 is usually selected. During processing, a linear normalization formula is used to convert the filtered working parameters into the specified range. Finally, all filtered working parameters are converted according to the normalization formula to obtain normalized data.

[0081] S14: Perform feature extraction on the normalized working parameters to obtain feature values.

[0082] In this embodiment, appropriate features are selected according to actual needs. Common features include mean, variance, peak value, frequency component, etc.

[0083] For the load sensor, the mean, variance, peak value and frequency content of the load current, as well as the corresponding characteristics of the load voltage and load power can be extracted.

[0084] The normalized operating parameters are calculated to extract the required characteristic values. For example, the mean and variance of the voltage value are calculated, the peak value and frequency component of the current value are extracted, and the mean and variance of the load current and load voltage are calculated.

[0085] The extracted eigenvalues ​​are combined into eigenvectors for subsequent control and analysis.

[0086] S2: Input the preprocessed working parameters into the PID controller configured in the distributed nodes to generate preliminary control output.

[0087] Specifically, step S2 includes the following steps:

[0088] S21: Each distributed node formats the pre-processed working parameters according to the input requirements of the PID controller.

[0089] In this embodiment, each distributed node formats the pre-processed working parameters according to the input requirements of the PID controller. This is because in practical applications, the data formats collected by different types of sensors may not be consistent, and the PID controller needs input data in a specific format to operate correctly. In order to ensure that the PID controller can accurately process these data, the processor of the distributed node will perform necessary format conversion on the pre-processed working parameters, such as converting voltage values from millivolts to volts, converting current values from milliamperes to amperes, or converting temperature values from Celsius to Kelvin, etc.

[0090] In addition, it is also necessary to integrate the data collected by different sensors into a unified input vector, so that the PID controller can consider the influence of multiple variables at the same time. Through formatting processing, it ensures that the input data format of the PID controller is unified and meets the design requirements, thereby improving the reliability and accuracy of the control system.

[0091] S22: Input the formatted working parameters into the PID controller, and the PID controller performs real-time calculation on the input working parameters according to the pre-set control algorithm to obtain the calculation result.

[0092] In this embodiment, the PID controller is a feedback controller widely used in industrial control field, which realizes accurate control of target variables through the combination of proportional (P), integral (I) and derivative (D) parts.

[0093] In this process, the PID controller first reads the formatted working parameters, and then performs proportional, integral and derivative operations on these parameters according to the pre-set proportional coefficient (Kp), integral time constant (Ti) and derivative time constant (Td). The proportional part is used to quickly respond to the current error, the integral part is used to eliminate the steady-state error, and the derivative part is used to predict the future error trend and adjust in advance. The PID controller generates a control signal through the comprehensive calculation of these three parts, which reflects how to adjust the power supply state to make the working parameters close to the pre-set target value. In this way, the PID controller can effectively reduce the fluctuations in the power supply system and improve the stability and response speed of the system.

[0094] S23: The PID controller generates a corresponding preliminary control output according to the calculation result, wherein the preliminary control output is used to adjust the power supply state of the local motherboard.

[0095] In this embodiment, the generated preliminary control output is a specific embodiment of the PID controller calculation result, which indicates how to adjust certain parameters in the power supply system, such as voltage, current or power, etc., to achieve the expected control target.

[0096] For example, if the calculation result shows that the current voltage is too low, the PID controller will generate a preliminary control output to increase the voltage; if the calculation result shows that the current load is too high, the PID controller will generate a preliminary control output to reduce the current.

[0097] These preliminary control outputs are applied to the local motherboard through the actuators of the distributed nodes, such as power regulators, switching elements, etc., to achieve preliminary adjustment of the power supply state. The generation of preliminary control outputs not only depends on the calculation results of the PID controller, but also depends on the pre-set control strategy and constraints to ensure that the control action is effective and safe. Through the application of preliminary control outputs, the distributed nodes can autonomously adjust the power supply state of the local motherboard to a certain extent, laying the foundation for subsequent optimization control.

[0098] S24: Real-time adjustment of the power supply of the local motherboard according to the preliminary control output to preliminarily control the power supply state of the local motherboard.

[0099] In this embodiment, once the preliminary control output is generated, the distributed nodes will immediately execute these control instructions to adjust the power supply state of the local motherboard.

[0100] For example, if the preliminary control output indicates to increase the voltage, the distributed nodes will achieve this goal by adjusting the output voltage of the power supply module; if the preliminary control output indicates to reduce the current, the distributed nodes will achieve this goal by adjusting the current limit. These adjustments are made in real time, i.e. the distributed nodes will continuously adjust the power supply parameters according to the output of the PID controller to ensure that the working parameters of the local motherboard always remain within the ideal range. Through real-time adjustment, the distributed nodes can quickly respond to changes in the power supply system, reduce problems caused by external interference or internal fluctuations, and thus improve the stability and reliability of the power supply system. In addition, real-time adjustment also helps to prevent potential failures and protect the motherboard from damage.

[0101] S3: Each distributed node sends the preliminary control output and the working parameters to the master node, and uses the adaptive fuzzy logic controller of the master node to dynamically adjust the PID parameters to obtain adjusted PID parameters, and optimizes the preliminary control output of each distributed node to generate a final control output.

[0102] Specifically, step S3 includes the following steps:

[0103] S31: Convert the preliminary control output and the working parameters into corresponding membership degrees using predefined membership functions.

[0104] The preliminary control outputs and working parameters are converted into corresponding membership degrees using predefined membership functions. This is because in fuzzy logic control, input data needs to be converted into the form of fuzzy sets for fuzzy reasoning. Membership functions define the degree of membership of input data in fuzzy sets, i.e., map specific numerical values to a membership degree value between 0 and 1. Through membership functions, preliminary control outputs and working parameters can be converted into the form of fuzzy sets, providing a basis for subsequent fuzzy reasoning.

[0105] In implementation, according to actual needs, multiple membership functions are defined, each corresponding to a fuzzy set. For example, for voltage values, three fuzzy sets of "low voltage", "medium voltage", and "high voltage" can be defined, each corresponding to a membership function.

[0106] Wherein the membership function can use, including but not limited to, triangular, trapezoidal or Gaussian type.

[0107] The preliminary control outputs and working parameters are input into the corresponding membership functions, and the membership degrees of each parameter in each fuzzy set are calculated. For example, for voltage values, the membership degrees in the three fuzzy sets of "low voltage", "medium voltage", and "high voltage" are calculated.

[0108] S32: According to the fuzzy rules in the predefined fuzzy rule base and in combination with the membership degrees, the activation degree of each fuzzy rule is evaluated, and the output fuzzy sets of all fuzzy rules are aggregated to form a total output fuzzy set.

[0109] In this embodiment, a set of fuzzy rules is defined, each rule describing the relationship between input membership degrees and output fuzzy sets. For example, a rule can be expressed as: "If voltage is low and current is high, then output is to increase voltage".

[0110] The fuzzy rule base is determined by expert experience and experimental data, containing multiple rules, each covering different input conditions.

[0111] According to the input membership degrees, the activation degree of each fuzzy rule is evaluated. The activation degree reflects the degree to which the input conditions meet the rule, and is usually calculated using minimum operation or multiplication operation.

[0112] For example, for the rule "If voltage is low and current is high, then output is to increase voltage", if the membership degree of voltage is 0.8 and the membership degree of current is 0.7, then the activation degree of the rule is 0.7 (taking the minimum value).

[0113] According to the activation degree of each rule, the corresponding output fuzzy set is aggregated to form a total output fuzzy set. The aggregation method usually uses maximum operation or weighted average operation.

[0114] For example, if the activation degree of rule 1 is 0.7, the corresponding output fuzzy set is "increase voltage", the activation degree of rule 2 is 0.5, and the corresponding output fuzzy set is "maintain voltage", then the total output fuzzy set is the maximum or weighted average of the two.

[0115] S33: Convert the total output fuzzy set into an output value using the barycenter method, and use the output value as the adjusted PID parameter.

[0116] In this embodiment, the barycenter method is a commonly used method for defuzzifying a fuzzy set. A specific numerical output is obtained by calculating the barycenter of the fuzzy set. The calculation formula is:

[0117]

[0118] where x is a point in the output fuzzy set, μ is the membership degree of the point, and y is the output value. i i

[0119] The output value y calculated by the barycenter method is used as the adjusted PID parameter. For example, if the calculated output value is 0.8, it means that the proportional coefficient Kp of the PID controller needs to be increased by 0.8.

[0120] S34: Adjust the preliminary control output of each distributed node according to the adjusted PID parameter to obtain the final control output.

[0121] Specifically, it includes:

[0122] Each distributed node receives the adjusted PID parameter issued by the master node, compares the received adjusted PID parameter with the currently configured PID parameter, and identifies the parameter item to be updated.

[0123] In this embodiment, each distributed node receives the adjusted PID parameter issued by the master node, compares the received adjusted PID parameter with the currently configured PID parameter, and identifies the parameter item to be updated.

[0124] For example, if the PID parameter issued by the master node is Kp=0.8, Ki=0.5, and Kd=0.3, and the currently configured PID parameter is Kp=0.6, Ki=0.4, and Kd=0.2, then Kp and Ki need to be updated.

[0125] According to the identified parameter item to be updated, the PID controller is updated.

[0126] In this embodiment, the PID controller is updated according to the identified parameter item to be updated. The updated PID parameter will be used for subsequent control calculation.​​

[0127] For example, the updated PID parameters are Kp = 0.8, Ki = 0.5, and Kd = 0.3.

[0128] The parameter-updated PID controller recalculates based on the new PID parameters and the current real-time monitored operating parameters to generate the final control output.

[0129] In this embodiment, the parameter-updated PID controller recalculates based on the new PID parameters and the current real-time monitored operating parameters to generate the final control output.

[0130] For example, the PID controller recalculates a more accurate control signal based on the new PID parameters and the current voltage, current, and other parameters to adjust the power supply state of the local motherboard.

[0131] S4: Each distributed node evaluates the local running state of the local motherboard according to the adjusted PID parameters and the final control output.

[0132] Specifically, step S4 includes the following steps:

[0133] S41: Each distributed node monitors and records the changes in the operating parameters of the local motherboard in real time according to the adjusted PID parameters and the final control output.

[0134] In the power supply system, real-time monitoring and recording of the changes in the operating parameters of the local motherboard is an important link to ensure stable operation of the system. Through real-time monitoring, any abnormal situation can be discovered and recorded in time, providing data support for subsequent state evaluation and fault diagnosis. In addition, real-time monitoring can also help the distributed node verify the control effect and ensure that the power supply state is always in the best state.

[0135] In implementation, the processor of the distributed node continuously reads the operating parameters collected by the sensor module, including voltage, current, temperature, and load, and compares each read data with the adjusted PID parameters and the final control output to verify the control effect.

[0136] The distributed node records each collected operating parameter and its change in the local storage to form time series data, including voltage value, current value, temperature value, load current, load voltage, and load power.

[0137] The distributed node sends the recorded data to the master node through the network interface at regular intervals for global state evaluation by the master node.

[0138] S42: Each distributed node evaluates the voltage stability, current stability, temperature monitoring, and load condition of the local motherboard according to the preset state evaluation model, and generates a local running state report.

[0139] State evaluation is a key step to ensure the stable operation of the power supply system. By evaluating the voltage stability, current stability, temperature monitoring, and load condition of the local motherboard, potential problems can be discovered in a timely manner, and appropriate measures can be taken for adjustment. The state evaluation model usually includes a series of preset evaluation indicators and thresholds to determine whether each parameter is within the normal range.

[0140] Specific implementation content

[0141] Voltage stability evaluation:

[0142] The distributed node evaluates the voltage stability according to the change range and fluctuation value of the input voltage and output voltage. If the voltage fluctuation exceeds the preset threshold, the system will record this abnormal situation.

[0143] Current stability evaluation:

[0144] The distributed node evaluates the current stability according to the change range and fluctuation value of the current. If the current fluctuation exceeds the preset threshold, the system will record this abnormal situation.

[0145] Temperature monitoring:

[0146] The distributed node evaluates whether the temperature is within the preset safe range according to the temperature change at the temperature monitoring location. If the temperature exceeds the preset safe range, the system will record this abnormal situation.

[0147] Load condition evaluation:

[0148] The distributed node evaluates whether the load is within the preset reasonable range according to the change of the load. If the load exceeds the preset reasonable range, the system will record this abnormal situation.

[0149] The distributed node generates a local running state report according to the above evaluation results, wherein the local running state report contains the evaluation values and conclusions of each evaluation, such as voltage fluctuation value, current fluctuation value, temperature change value, and load change value.

[0150] S43: Each distributed node sends the local running state report to the master node, so that the master node can perform global state evaluation.

[0151] In this embodiment, the local operation status report contains the evaluation results of the distributed node on the parameters of the local motherboard, and these reports need to be sent to the master node for global state evaluation. Global state evaluation is a key step to ensure the stable operation of the entire power supply system. By integrating the local operation status reports of all distributed nodes, the master node can comprehensively understand the operation status of the system and take corresponding measures for adjustment.

[0152] In implementation, the distributed node sends the local operation status report to the master node through the network interface, and the data transmission is usually performed in a periodic manner to ensure that the master node can obtain the latest status report in real time.

[0153] The local operation status report usually includes the following contents: voltage stability evaluation result, current stability evaluation result, temperature monitoring result, load condition evaluation result, and the values and evaluation conclusions of each evaluation.

[0154] By sending the local operation status report to the master node, the distributed node can ensure that the master node can obtain the latest status information in time, so as to perform comprehensive global state evaluation. This helps the master node to discover and handle potential problems in the system in time, and ensures the stability and reliability of the entire power supply system.

[0155] S5: Each distributed node sends the local operation status to the master node, and the master node judges the global operation status of the power supply system according to the preset state index.

[0156] Specifically, step S5 includes the following steps:

[0157] S51: The master node compares the local operation status report of each distributed node with the corresponding threshold in the preset state index set to obtain the local operation status evaluation result of each local motherboard, wherein the preset state index set includes voltage stability threshold, current stability threshold, temperature safety threshold and load rationality threshold.

[0158] In the global state evaluation of the power supply system, the master node needs to integrate the local operation status reports of all distributed nodes to judge the operation status of the entire system. The local operation status report contains the evaluation results of each distributed node on the voltage stability, current stability, temperature monitoring and load condition of the local motherboard. In order to perform effective global evaluation, the master node needs to compare these local evaluation results with the thresholds in the preset state index set, so as to obtain the local operation status evaluation result of each local motherboard.

[0159] In implementation, the master node receives the local operation status reports sent by each distributed node through the network interface. These reports contain evaluation values and conclusions of voltage stability, current stability, temperature monitoring, and load conditions.

[0160] The master node compares each local operation status report of each distributed node with the thresholds in the preset state index set. The preset state index set includes voltage stability thresholds, current stability thresholds, temperature safety thresholds, and load rationality thresholds.

[0161] For example, for voltage stability, the master node checks whether the change range and fluctuation value of the input voltage and output voltage are within the preset threshold range. If they exceed the threshold, it indicates poor voltage stability.

[0162] For current stability, the master node checks whether the change range and fluctuation value of the current are within the preset threshold range. If they exceed the threshold, it indicates poor current stability.

[0163] For temperature monitoring, the master node checks whether the temperature change at the temperature monitoring location is within the preset safety range. If it exceeds the threshold, it indicates that the temperature is too high or too low.

[0164] For load conditions, the master node checks whether the load change is within the preset reasonable range. If it exceeds the threshold, it indicates that the load is too high or too low.

[0165] According to the results of threshold comparison, the master node generates the local operation status evaluation results of each local motherboard. The evaluation results can be divided into three levels: normal, warning, and abnormal. For example, if a certain index exceeds the threshold, the evaluation result may be marked as warning or abnormal.

[0166] By comparing the local operation status reports of each distributed node with the thresholds in the preset state index set, the master node can accurately evaluate the operation status of each local motherboard. This not only helps to discover potential problems in a timely manner, but also provides reliable data support for subsequent global state evaluation. In addition, the threshold comparison process is highly automated, reducing manual intervention and improving the efficiency and accuracy of evaluation.

[0167] S52: The master node generates a global operation status report of the power supply system by synthesizing the local operation status evaluation results of all distributed nodes, and determines the global operation status of the power supply system according to the global operation status report, wherein the global operation status includes stable state, abnormal state, and performance insufficient state.

[0168] If the determination result is stable state, the master node continues to monitor the operation of the power supply system.

[0169] If the judgment result is abnormal state and performance deficiency state, the master node generates corresponding adjustment instructions and issues them to the relevant distributed nodes to re-adjust the PID parameters.

[0170] After completing the local running state evaluation of each local motherboard, the master node needs to further integrate the evaluation results of all distributed nodes to generate a global running state report of the power supply system. The global running state report reflects the overall running condition of the entire power supply system, including stable state, abnormal state and performance deficiency state. According to the global running state report, the master node decides whether to take further control measures, such as re-adjusting the PID parameters.

[0171] In implementation, the master node summarizes the local running state evaluation results of all distributed nodes to form a comprehensive global running state report. The report includes the evaluation results of voltage stability, current stability, temperature monitoring and load condition of each local motherboard.

[0172] According to the summarized data, the master node comprehensively evaluates the global running state of the entire power supply system. The evaluation process can include the following aspects:

[0173] Voltage stability: Check the voltage stability evaluation results of all local motherboards to determine whether there is a situation of excessive voltage fluctuation.

[0174] Current stability: Check the current stability evaluation results of all local motherboards to determine whether there is a situation of excessive current fluctuation.

[0175] Temperature monitoring: Check the temperature monitoring results of all local motherboards to determine whether there is a situation of excessively high or low temperature.

[0176] Load condition: Check the load condition of all local motherboards to determine whether there is a situation of excessively high or low load.

[0177] According to the results of comprehensive evaluation, the master node judges the global running state of the power supply system. The global running state can be divided into the following:

[0178] Stable state: If the voltage stability, current stability, temperature monitoring and load condition of all local motherboards are within the pre-set normal range and do not exceed the threshold, the master node will judge that the power supply system is in a stable state.

[0179] Abnormal state: If the voltage stability, current stability, temperature monitoring or load condition of part of the local motherboards exceeds the pre-set threshold, but the number is small and the impact is not great, the master node will judge that the power supply system is in an abnormal state. For example, the voltage fluctuation of a certain local motherboard is large, but the parameters of other motherboards are normal.

[0180] Performance deficiency state: if the voltage stability, current stability, temperature monitoring or load condition of multiple local motherboards exceed the preset threshold and have a significant impact, the master node will judge that the power supply system is in a performance deficiency state. For example, the temperature of multiple local motherboards is too high and the load is too large.

[0181] If the judgment result is stable state, the master node will continue to monitor the operation of the power supply system and maintain the current control strategy.

[0182] If the judgment result is abnormal state, the master node will generate corresponding adjustment instructions and issue them to the relevant distributed nodes to re-adjust the PID parameters. The adjustment instructions include increasing or decreasing voltage, adjusting current limit and other specific measures.

[0183] If the judgment result is performance deficiency state, the master node will generate more urgent adjustment instructions, including increasing more cooling measures, reducing load or starting backup power supply, etc., to restore normal operation as soon as possible

[0184] By comprehensively evaluating the local running state of all distributed nodes, the master node can fully understand the running state of the entire power supply system, and timely discover and handle potential problems. The global running state report provides a clear system running profile for system administrators, which helps to develop reasonable maintenance and optimization strategies. In addition, the adjustment instructions generated by the master node according to the global running state report can effectively optimize the running state of the system and improve the stability and reliability of the power supply system.

[0185] Embodiment two

[0186] The application also provides a motherboard power supply analysis system and a motherboard power supply analysis method for execution, which are applied to a power supply system including multiple local motherboards. The power supply system includes distributed nodes corresponding to the local motherboards and a master node for coordinating the distributed nodes. Each distributed node is configured with a PID controller, and the master node is configured with an adaptive fuzzy logic controller. Referring to Figure 2 As shown, the analysis system includes:

[0187] The parameter processing module 100 is used for each distributed node to collect the working parameters of the local motherboard where it is located, and to pre-process the working parameters.

[0188] The preliminary control module 200 is used for inputting the pre-processed working parameters into the PID controller configured in the distributed node to generate a preliminary control output.

[0189] The adjustment and optimization module 300 is configured to send the preliminary control output and the working parameter of each distributed node to the master node, and dynamically adjust the PID parameter by using the adaptive fuzzy logic controller of the master node to obtain an adjusted PID parameter, and optimize the preliminary control output of each distributed node to generate a final control output.

[0190] The local running state evaluation module 400 is configured to evaluate the local running state of the local mainboard of each distributed node according to the adjusted PID parameter and the final control output.

[0191] The global running state judgment module 500 is configured to send the local running state of each distributed node to the master node, and judge the global running state of the power supply system according to a preset state index by the master node.

[0192] The present application is described with reference to flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device realize a function specified in one or more flows and / or blocks in the flowcharts and / or block diagrams. Figure 1 The function specified in one or more flows and / or blocks Figure 1 The device for realizing the function specified in one or more flows and / or blocks.

[0193] Those skilled in the art can understand that all or part of the steps in the above-mentioned embodiments can be completed by instructing the relevant hardware by means of a program, and the program can be stored in a computer readable storage medium, including Read-Only Memory (ROM), Random Access Memory (RAM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), One-time Programmable Read-Only Memory (OTPROM), Electrically-Erasable Programmable Read-Only Memory (EEPROM), Compact Disc Read-Only Memory (CD-ROM) or other optical disk storage, magnetic disk storage, magnetic tape storage, or any other medium that can be used to carry or store data in a computer readable manner.

[0194] It should also be noted that the terms "comprising", "containing", or any other variant thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements, but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the statement "comprising a" does not exclude the existence of additional identical elements in the process, method, article, or apparatus that includes the element.

Claims

1. A power supply analysis method of a master board, applied to a power supply system including a plurality of local master boards, characterized in that, The power supply system comprises distributed nodes corresponding to the local mainboards and a master node for coordinating the distributed nodes, wherein each distributed node is configured with a PID controller, and the master node is configured with an adaptive fuzzy logic controller, and the analysis method comprises the following steps: Each distributed node collects the working parameters of the local mainboard where it is located and pre-processes the working parameters; The pre-processed working parameters are input into the PID controller configured in the distributed node to generate a preliminary control output; Each distributed node sends the preliminary control output and the working parameters to the master node, and uses the adaptive fuzzy logic controller of the master node to dynamically adjust the PID parameters to obtain adjusted PID parameters, and optimizes the preliminary control output of each distributed node to generate a final control output; Each distributed node evaluates the local running state of the local mainboard according to the adjusted PID parameters and the final control output; Each distributed node sends the local running state to the master node, and the master node judges the global running state of the power supply system according to the preset state index.

2. The power supply analysis method of a mainboard according to claim 1, wherein, The working parameters of the local mainboard where each distributed node is located are collected and pre-processed, including: Each distributed node monitors and collects the working parameters of the local mainboard where it is located in real time through the built-in sensor module; The collected working parameters are filtered to remove noise and interference signals; The filtered working parameters are normalized to convert to a unified dimension and range; The normalized working parameters are feature extracted to obtain feature values.

3. The power supply analysis method of claim 2, wherein, The pre-processed working parameters are input into the PID controller configured in the distributed node to generate a preliminary control output, including: Each distributed node formats the pre-processed working parameters according to the input requirements of the PID controller; The formatted working parameters are input into the PID controller, and the PID controller calculates the input working parameters in real time according to the preset control algorithm to obtain a calculation result; The PID controller generates a corresponding preliminary control output according to the calculation result, wherein the preliminary control output is used to adjust the power supply state of the local mainboard; The power supply of the local mainboard is adjusted in real time according to the preliminary control output to preliminarily control the power supply state of the local mainboard.

4. The power supply analysis method of claim 3, wherein, Each distributed node sends the preliminary control output and the working parameters to the master node, and uses the adaptive fuzzy logic controller of the master node to dynamically adjust the PID parameters to obtain adjusted PID parameters, and optimizes the preliminary control output of each distributed node to generate a final control output, including: The preliminary control output and the working parameters are converted into corresponding membership degrees using predefined membership functions; The activation degree of each fuzzy rule is evaluated according to the fuzzy rules in the predefined fuzzy rule base and combined with the membership degrees, the output fuzzy set of all fuzzy rules is aggregated to form a total output fuzzy set; The total output fuzzy set is converted into an output value using a barycenter method, and the output value is used as an adjusted PID parameter; The preliminary control output of each distributed node is adjusted according to the adjusted PID parameter, and a final control output is obtained.

5. The power supply analysis method of a mainboard according to claim 4, wherein, The adjustment of the preliminary control output of each distributed node according to the adjusted PID parameter to obtain the final control output comprises: Each distributed node receives the adjusted PID parameter issued by the master node, and compares the received adjusted PID parameter with the currently configured PID parameter to identify the parameter item to be updated; According to the identified parameter item to be updated, the PID controller is updated; The PID controller after parameter updating re-calculates according to the new PID parameter and the current real-time monitored working parameter to generate the final control output.

6. The power supply analysis method of a mainboard according to claim 5, wherein, The local running state of each distributed node according to the adjusted PID parameter and the final control output comprises: Each distributed node monitors and records the change of the working parameter of the local motherboard in real time according to the adjusted PID parameter and the final control output; Each distributed node evaluates the voltage stability, current stability, temperature monitoring and load condition of the local motherboard according to the preset state evaluation model, and generates a local running state report; Each distributed node sends the local running state report to the master node for global state evaluation.

7. The power supply analysis method of a mainboard according to claim 6, wherein, The evaluation of the voltage stability, current stability, temperature monitoring and load condition of the local motherboard according to the preset state evaluation model by each distributed node to generate a local running state report comprises: Each distributed node evaluates the voltage stability according to the change range and fluctuation value of the input voltage and output voltage; Each distributed node evaluates the current stability according to the change range and fluctuation value of the current; Each distributed node evaluates whether the temperature is within the preset safety range according to the temperature change of the temperature monitoring position; Each distributed node evaluates whether the load is within the preset reasonable range according to the change of the load; Each distributed node generates a local running state report according to the evaluation result, wherein the local running state report contains the evaluation values and evaluation conclusions of each evaluation.

8. The power supply analysis method of a mainboard according to claim 7, wherein, The local running state of each distributed node is sent to the master node, and the global running state of the power supply system is determined by the master node according to the preset state index, comprising: The master node compares the local running state report of each distributed node with the corresponding threshold in the preset state index set to obtain the local running state evaluation result of each local motherboard, wherein the preset state index set includes a voltage stability threshold, a current stability threshold, a temperature safety threshold and a load rationality threshold; The master node generates a global running state report of the power supply system by comprehensively evaluating the local running state evaluation results of all distributed nodes, and determines the global running state of the power supply system according to the global running state report, wherein the global running state includes a stable state, an abnormal state and a performance insufficient state; If the determination result is the stable state, the master node continues to monitor the running of the power supply system. If the result is abnormal state and insufficient performance state, the master node generates corresponding adjustment instructions and sends them to the relevant distributed nodes to re-adjust the PID parameters.

9. A power supply analysis system for a main board for performing a power supply analysis method for a main board according to any one of claims 1 to 8, applied to a power supply system including a plurality of local main boards, characterized by The power supply system comprises distributed nodes respectively configured in local mainboards and a master node for coordinating the distributed nodes, wherein each distributed node is configured with a PID controller and the master node is configured with an adaptive fuzzy logic controller, and the analysis system comprises: a parameter processing module for collecting and pre-processing working parameters of the local mainboard by each distributed node; a preliminary control module for inputting the pre-processed working parameters into the PID controller of the distributed node to generate a preliminary control output; an adjustment and optimization module for sending the preliminary control output and working parameters to the master node, dynamically adjusting the PID parameters by the adaptive fuzzy logic controller of the master node to obtain adjusted PID parameters, and optimizing the preliminary control output of each distributed node to generate a final control output; a local running state evaluation module for each distributed node to evaluate the local running state of the local mainboard according to the adjusted PID parameters and the final control output; a global running state judgment module for each distributed node to send the local running state to the master node, and the master node to judge the global running state of the power supply system according to preset state indicators.

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