High-frequency Switching Power Supply Operation Risk Monitoring Method and System

Abstract

The present application relates to the field of equipment monitoring technology, and provides a method and system for monitoring the operation risk of a high-frequency switching power supply, including: obtaining power demand information; conducting power consumption assessment, obtaining power supply information and power supply time zone information; optimizing the operation parameters of the high-frequency switching power supply based on the power supply information and power supply time zone information; obtaining operation parameter monitoring data, calculating the deviation between the operation parameter monitoring data and the operation parameter optimization result, and generating an operation risk coefficient; generating an operation safety risk warning signal; generating an operation abnormality risk warning signal; and performing operation risk monitoring based on the operation safety risk warning signal or the operation abnormality risk warning signal. This method can solve the technical problem that the traditional high-frequency switching power supply operation monitoring method has low quality due to its inability to analyze the correlation between the operation status and the operation task, and can improve the adaptability of the operation monitoring method to the operation task, thereby improving the operation monitoring quality.

Description

Technical Field

[0001] The present application relates to the technical field of equipment monitoring, and in particular to a method and system for monitoring the operation risks of a high-frequency switching power supply. Background Art

[0002] A high-frequency switching power supply, also known as a switching rectifier, is a device that converts alternating current (AC) into direct current (DC). Existing methods for monitoring the operation of high-frequency switching power supplies typically focus solely on their operating status, such as temperature, vibration, and audio. These methods fail to consider the correlation between the operating status and the task being performed, resulting in operational monitoring results that fail to meet pre-defined monitoring requirements.

[0003] In summary, the conventional high-frequency switching power supply operation monitoring method in the prior art is unable to analyze the correlation between the operation status and the operation task, resulting in a technical problem of low quality of high-frequency switching power supply operation monitoring. Summary of the Invention

[0004] Based on this, it is necessary to provide a high-frequency switching power supply operation risk monitoring method and system to address the above technical issues.

[0005] A method for monitoring the operation risk of a high-frequency switching power supply, the method comprising: obtaining power demand information, wherein the power demand information includes the power equipment position number and operation task information; performing power consumption assessment based on the power equipment position number and the operation task information, and obtaining power supply information and power supply time zone information; optimizing the operation parameters of the high-frequency switching power supply based on the power supply information and the power supply time zone information, and obtaining an operation parameter optimization result; when the power equipment is started, obtaining operation parameter monitoring data, calculating the deviation between the operation parameter monitoring data and the operation parameter optimization result, and generating an operation risk coefficient; when the operation parameter monitoring data is greater than the operation parameter optimization result, and the operation risk coefficient is greater than or equal to a first risk threshold, generating an operation safety risk warning signal; when the operation parameter monitoring data is less than the operation parameter optimization result, and the operation risk coefficient is greater than or equal to a second risk threshold, generating an operation abnormality risk warning signal; and performing operation risk monitoring of the high-frequency switching power supply based on the operation safety risk warning signal or the operation abnormality risk warning signal.

[0006] High-frequency switching power supply operation risk monitoring system, including:

[0007] An electricity demand information acquisition module, wherein the electricity demand information acquisition module is used to acquire electricity demand information, wherein the electricity demand information includes the position number of the electrical equipment and the operation task information;

[0008] An electricity consumption evaluation module, configured to evaluate electricity consumption based on the electrical equipment bit number and the operation task information, and obtain power supply information and power supply time zone information;

[0009] An operating parameter optimization module, configured to optimize operating parameters of the high-frequency switching power supply according to the power supply amount information and the power supply time zone information, and obtain an operating parameter optimization result;

[0010] An operation risk coefficient generation module, wherein the operation risk coefficient generation module is used to obtain operation parameter monitoring data when the electrical equipment is started, calculate the deviation between the operation parameter monitoring data and the operation parameter optimization result, and generate an operation risk coefficient;

[0011] an operation safety risk warning signal generation module, the operation safety risk warning signal generation module being configured to generate an operation safety risk warning signal when the operation parameter monitoring data is greater than the operation parameter optimization result and the operation risk coefficient is greater than or equal to a first risk threshold;

[0012] an abnormal operation risk warning signal generating module, the abnormal operation risk warning signal generating module being configured to generate an abnormal operation risk warning signal when the operating parameter monitoring data is less than the operating parameter optimization result and the operating risk coefficient is greater than or equal to a second risk threshold;

[0013] An operation risk monitoring module is used to monitor the operation risk of the high-frequency switching power supply according to the operation safety risk warning signal or the operation abnormality risk warning signal.

[0014] The above-mentioned high-frequency switching power supply operation risk monitoring method and system can solve the technical problem that the traditional high-frequency switching power supply operation monitoring method cannot analyze the correlation between the operating status and the operation task, resulting in low quality of high-frequency switching power supply operation monitoring. First, power demand information is obtained, where the power demand information includes the power equipment position number and the operation task information; power consumption is evaluated based on the power equipment position number and the operation task information to obtain power supply information and power supply time zone information; based on the power supply information and the power supply time zone information, the operating parameters of the high-frequency switching power supply are optimized to obtain an operating parameter optimization result; when the power equipment is started, operating parameter monitoring data is obtained, and the deviation between the operating parameter monitoring data and the operating parameter optimization result is calculated to generate an operating risk coefficient; when the operating parameter monitoring data is greater than the operating parameter optimization result and the operating risk coefficient is greater than or equal to a first risk threshold, an operating safety risk warning signal is generated; when the operating parameter monitoring data is less than the operating parameter optimization result and the operating risk coefficient is greater than or equal to a second risk threshold, an operating abnormality risk warning signal is generated; and the high-frequency switching power supply operation risk monitoring is performed based on the operating safety risk warning signal or the operating abnormality risk warning signal. The adaptability of operation monitoring methods to work tasks can be improved, thereby improving the quality of operation monitoring.

[0015] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A flow chart of a method for monitoring the operation risk of a high-frequency switching power supply is provided for this application;

[0017] Figure 2 This application provides a flow chart of power consumption assessment in a method for monitoring the operation risk of a high-frequency switching power supply;

[0018] Figure 3 This application provides a flow chart of obtaining a concentrated value of operation duration in a method for monitoring the operation risk of a high-frequency switching power supply;

[0019] Figure 4 A structural diagram of a high-frequency switching power supply operation risk monitoring system is provided for this application.

[0020] Explanation of the accompanying drawings: electricity demand information acquisition module 1, electricity consumption assessment module 2, operation parameter optimization module 3, operation risk coefficient generation module 4, operation safety risk warning signal generation module 5, operation abnormality risk warning signal generation module 6, operation risk monitoring module 7. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0022] like Figure 1 As shown, the present application provides a method for monitoring the operation risk of a high-frequency switching power supply, comprising:

[0023] Step S100: obtaining power demand information, wherein the power demand information includes the power equipment position number and operation task information;

[0024] Specifically, first, power demand information is obtained. This information refers to the power demand information of multiple devices connected to the high-frequency power switch. This power demand information includes the power device position number and operation task information. The power device position number refers to the arrangement number of devices connected to the high-frequency power switch, which can be customized based on the number of devices. The operation task information includes the operation duration and required power. Obtaining this power demand information provides support for the next step of power consumption assessment.

[0025] Step S200: performing power consumption evaluation based on the power-consuming equipment number and the operation task information, and obtaining power supply information and power supply time zone information;

[0026] like Figure 2 As shown, in one embodiment, step S200 of the present application further includes:

[0027] Step S210: Counting historical operation records based on the electrical equipment bit number and the operation task information, wherein the historical operation records include multiple operation durations and multiple power supply records;

[0028] Specifically, first, historical electricity usage information is queried based on the electrical equipment ID and the task information, and historical operation records of the electrical equipment ID when performing the same task are retrieved. The historical operation records include multiple operation durations and multiple power supply records. The operation duration refers to the duration of a single historical task, and the power supply refers to the amount of electricity consumed by a single historical task. By obtaining these multiple operation durations and power supply records, raw data is provided for the next step of centralized value evaluation of operation duration and power supply.

[0029] Step S220: performing a centralized value evaluation on the plurality of operation durations, obtaining a centralized value of the operation durations, and setting the power supply time zone information;

[0030] like Figure 3 As shown, in one embodiment, step S220 of the present application further includes:

[0031] Step S221: performing an abnormality analysis on the i-th operation duration of the plurality of operation durations to obtain an abnormality factor of the i-th operation duration;

[0032] In one embodiment, step S221 of the present application further includes:

[0033] Step S2211: Obtaining a concentration evaluation coefficient, wherein the concentration evaluation coefficient is a positive integer and is less than or equal to floor(0.5*N), where N is the number of the plurality of job durations and floor(0.5*N) is a floor rounding function;

[0034] Step S2212: Calculating a deviation between the duration of the i-th operation and the other durations of the plurality of operation durations to obtain a plurality of duration deviations;

[0035] Step S2213: Filtering the maximum duration deviation that satisfies the concentration evaluation coefficient from the plurality of duration deviations from smallest to largest, and calculating the inverse thereof to generate the duration concentration of the i-th task;

[0036] Step S2214: Obtain the average concentration of the multiple operation durations, calculate the ratio between the average concentration and the ith operation duration concentration, and obtain the abnormal factor of the ith operation duration.

[0037] Specifically, an abnormal analysis is performed on the i-th operation duration of the multiple operation durations, where the i-th operation duration is any one of the multiple operation durations. First, a concentration evaluation coefficient is obtained, where the value of the concentration evaluation coefficient is a positive integer less than or equal to floor(0.5*N), where N is the number of operation durations and floor(0.5*N) is a floor rounding function. Then, based on the i-th operation duration, the i-th operation duration is subtracted from the other operation durations in the multiple operation durations except the i-th operation duration to obtain multiple duration deviations, where the duration deviation is the difference between the other operation durations and the i-th operation duration. Then, based on the concentration evaluation coefficient, the multiple duration deviations are screened from near to far to obtain the maximum duration deviation that meets the concentration evaluation coefficient, and the inverse of the maximum duration deviation is used as the i-th operation duration concentration to obtain the i-th operation duration concentration. Then, the average concentration of the multiple job durations is obtained, and the average concentration of the job duration is the average value of the multiple job duration concentrations. Then, the ratio of the average concentration of the job duration to the i-th job duration concentration is used as the i-th job duration abnormality factor to obtain the i-th job duration abnormality factor.

[0038] Step S222: when the abnormal factor of the i-th operation duration is less than or equal to the abnormal factor threshold, deleting the i-th operation duration from the multiple operation durations;

[0039] Step S223: When the abnormal factor of the i-th operation duration is greater than the abnormal factor threshold, the i-th operation duration is added to the centralized value evaluation duration, the average of the centralized value evaluation duration is calculated, and the centralized value of the operation duration is obtained.

[0040] Specifically, obtain the abnormal factor threshold, which can be customized by those skilled in the art. Compare the abnormal factor of the i-th operation duration according to the abnormal factor threshold. When the abnormal factor of the i-th operation duration is less than or equal to the abnormal factor threshold, it indicates that the deviation of the i-th operation duration from the overall operation duration is large, and the i-th operation duration is deleted from the multiple operation durations. When the abnormal factor of the i-th operation duration is greater than the abnormal factor threshold, it indicates that the deviation value of the i-th operation duration is small and within a reasonable range, and the i-th operation duration is added to the centralized value evaluation duration. Then, the average value of the multiple operation durations in the centralized value evaluation duration is calculated, and the average calculation result is used as the centralized value of the operation duration, and the centralized value of the operation duration is used as the power supply time zone information. By obtaining the power supply time zone information, support is provided for the next step of optimizing the operating parameters of the high-frequency switching power supply.

[0041] Step S230: performing a centralized value evaluation on the plurality of power supply records, obtaining a centralized value of power supply, and setting the power supply information.

[0042] Specifically, a centralized value evaluation is performed on the multiple power supply records to obtain a centralized value of power supply, and the centralized value of power supply is used as the power supply information. The centralized value evaluation process of the power supply records is the same as the centralized value evaluation method of the operation market duration, and for the sake of brevity, it will not be repeated here.

[0043] Step S300: Optimizing operating parameters of a high-frequency switching power supply according to the power supply amount information and the power supply time zone information, and obtaining an operating parameter optimization result;

[0044] In one embodiment, step S300 of the present application further includes:

[0045] Step S310: The high-frequency switching power supply operating parameters include the on-pulse width and the switching operating frequency;

[0046] Step S320: constructing a power supply evaluation model of the high-frequency switching power supply based on the conduction pulse width and the switch operating frequency;

[0047] Step S330: Randomly assigning values to the on-pulse width and the switch operating frequency to obtain on-pulse width assignment results and switch operating frequency assignment results;

[0048] Step S340: When the on-pulse width assignment result and the switch operating frequency assignment result meet the duty cycle expectation, the on-pulse width assignment result, the switch operating frequency assignment result, and the power supply time zone information are input into the power supply evaluation model to obtain a power supply evaluation result;

[0049] Specifically, the operating parameters of the high-frequency switching power supply are optimized based on the power supply information and the power supply time zone information. The operating parameters of the high-frequency switching power supply include the on-pulse width and the switching operating frequency. The on-pulse width represents the duration of a single on-pulse of the high-frequency switching power supply, and the switching operating frequency represents the number of on-pulses per unit time. Based on the on-pulse width and the switching operating frequency, a power supply evaluation model for the high-frequency switching power supply is constructed. The power supply evaluation model is configured to evaluate and analyze the on-pulse width, the switching operating frequency, and the power supply time zone information, and output a power supply evaluation result. Random values are then assigned to the on-pulse width and the switching operating frequency to obtain on-pulse width and switching operating frequency assignment results. A preset expected duty cycle is obtained. The expected duty cycle represents the ratio of the on-pulse duration to the off-pulse duration of the high-frequency switching power supply. The specific value of the duty cycle can be customized by those skilled in the art based on the type of high-frequency switching power supply. When the on-pulse width assignment result and the switch operating frequency assignment result meet the duty cycle expectation, the on-pulse width assignment result, the switch operating frequency assignment result, and the power supply time zone information are input into the power supply evaluation model to obtain a power supply evaluation result. Obtaining this power supply evaluation result provides support for the next step of obtaining the operating parameter optimization result of the high-frequency switching power supply.

[0050] Step S350: When the power supply evaluation result is greater than the power supply information, the on-pulse width assignment result and the switch operating frequency assignment result are set as the operating parameter optimization result.

[0051] In one embodiment, step S350 of the present application further includes:

[0052] Step S351: setting a conduction pulse width constraint interval and a switch operating frequency constraint interval, performing M random assignments on the conduction pulse width and the switch operating frequency, and obtaining M groups of operation parameter assignment results, where M is an integer and M≥50;

[0053] Step S352: screening N groups of operating parameter assignment results that meet the expected duty cycle from the M operating parameter assignment results, where N is an integer, N≤M;

[0054] Step S353: inputting the N groups of operating parameter assignment results into the power supply evaluation model in sequence to obtain N power supply evaluation results;

[0055] Step S354: Filter the N groups of operating parameter assignment results whose N power supply evaluation results are greater than the power supply information to obtain L groups of operating parameter assignment results, where L is an integer and L≤N;

[0056] Specifically, a conduction pulse width constraint interval and a switch operating frequency constraint interval are set. The conduction pulse width constraint interval can be customized by those skilled in the art according to actual conditions, for example, 3-5 minutes. The switch operating frequency constraint interval can also be customized, for example, 5 times in 1 hour. Within the conduction pulse width constraint interval and the switch operating frequency constraint interval, the conduction pulse width and the switch operating frequency are randomly assigned M times to obtain M groups of operating parameter assignment results, where M is an integer greater than or equal to 50, and the specific value of M can be set as needed, for example, 100. Then, the M operating parameter assignment results are screened according to the duty cycle expectation, and N groups of operating parameter assignment results that meet the duty cycle expectation are screened from the M operating parameter assignment results, where N is an integer less than or equal to M. The N groups of operating parameter assignment results are sequentially input into the power supply evaluation model to obtain N power supply evaluation results. The N power supply evaluation results are screened according to the power supply information, and the N groups of operating parameter assignment results whose N power supply evaluation results are greater than the power supply information are extracted to obtain L groups of operating parameter assignment results, where L is an integer less than or equal to N. When the value of L is small, in order to improve the accuracy of the optimization result, it is necessary to expand the data of the L groups of operating parameter assignment results, thereby increasing the data capacity of the optimization parameters.

[0057] Step S355: Expand the L groups of operating parameter assignment results to obtain Q groups of operating parameter assignment results, where Q is an integer and Q≥80;

[0058] In one embodiment, step S355 of the present application further includes:

[0059] Step S3551: Obtaining the operating parameter adjustment step length constraint interval;

[0060] Step S3552: Expand the L groups of operating parameter assignment results according to the operating parameter adjustment step size constraint interval to obtain the operating parameter expansion result;

[0061] Step S3553: When the primary expansion result of the operating parameter is less than 80, perform secondary expansion on the primary expansion result of the operating parameter to obtain the secondary expansion result of the operating parameter;

[0062] Step S3554: Repeat the iteration to obtain the Q group operating parameter assignment results.

[0063] Specifically, the L groups of operating parameter assignment results are expanded, and the operating parameter adjustment step constraint interval is first obtained. The operating parameter adjustment step constraint interval can be customized based on the number of L. Then, the L groups of operating parameter assignment results are expanded once according to the operating parameter adjustment step constraint interval. The once expansion refers to multiplying the L groups of operating parameter assignment results by a preset step length to obtain the once expanded results of the operating parameters. The data volume of the once expanded results of the operating parameters is judged. When the once expanded results of the operating parameters are less than 80, the once expanded results of the operating parameters are expanded twice according to the preset step length to obtain the secondary expanded results of the operating parameters; the iteration is continuously performed until the number of operating parameters in the expanded results of the operating parameters is greater than or equal to 80, then the expansion is stopped, and the Q groups of operating parameter assignment results are obtained, where Q is an integer greater than or equal to 80. By expanding the operating parameter assignment results, the data volume can be expanded within a reasonable data expansion range, thereby improving the accuracy of the operating parameter optimization results.

[0064] Step S356: Optimizing the Q group operating parameter assignment results based on the power supply evaluation model to obtain the operating parameter optimization results.

[0065] Specifically, the Q groups of operating parameter assignment results are sequentially input into the power supply evaluation model to obtain Q power supply evaluation results, and then the optimization is performed from the Q power supply evaluation results. First, multiple power supply evaluation results that are greater than the power supply information are extracted from the Q power supply evaluation results. Then, the multiple power supply evaluation results are screened according to the preset deviation threshold, and the power supply evaluation results that meet the preset deviation threshold are extracted. Then, the duty cycle expectation is screened from the power supply evaluation results that meet the preset deviation threshold, and the operating parameters corresponding to the minimum duty cycle value that is greater than the duty cycle expectation are used as the operating parameter optimization results to obtain the operating parameter optimization results. By obtaining the operating parameter optimization results, the preset standard monitoring data of the high-frequency switching power supply can be accurately obtained, which provides support for the next step of comparing the real-time monitoring data of the operating parameters.

[0066] Step S400: When the electrical equipment is started, the operating parameter monitoring data is obtained, the deviation between the operating parameter monitoring data and the operating parameter optimization result is calculated, and an operating risk coefficient is generated;

[0067] Specifically, when the electrical equipment connected to the high-frequency switching power supply is started, the operating parameters of the high-frequency switching power supply are monitored to obtain operating parameter monitoring data. The operating parameter monitoring data includes the on-pulse width and the switch operating frequency. The on-pulse width and the switch operating frequency in the operating parameter monitoring data are respectively subtracted from the on-pulse width and the switch operating frequency in the operating parameter optimization result to obtain the on-pulse width deviation and the switch operating frequency deviation to generate an operating risk coefficient. The method for generating the operating risk coefficient can be customized. For example: set weight values of 0.4 and 0.6 for the on-pulse width deviation and the switch operating frequency deviation respectively, then multiply the on-pulse width deviation and the switch operating frequency deviation by the corresponding weight values and add them up, and use the sum as the operating risk coefficient. By generating the operating risk coefficient, support is provided for the next step of generating an early warning signal.

[0068] Step S500: When the operating parameter monitoring data is greater than the operating parameter optimization result, and the operating risk coefficient is greater than or equal to a first risk threshold, an operating safety risk warning signal is generated;

[0069] Specifically, when the operating parameter monitoring data is greater than the operating parameter optimization result, a first risk threshold is obtained. The first risk threshold can be customized according to actual conditions. The operating risk coefficient is judged according to the first risk threshold. When the operating risk coefficient is greater than or equal to the first risk threshold, an operating safety risk warning signal is generated. The operating safety risk warning signal indicates that when the switching frequency of the high-frequency switching power supply is high and the on-pulse width is large, the duty cycle of the high-frequency switching power supply is high, and overheating and strong electromagnetic interference are prone to occur, so the operating safety will be affected.

[0070] Step S600: When the operating parameter monitoring data is less than the operating parameter optimization result, and the operating risk coefficient is greater than or equal to a second risk threshold, generating an abnormal operation risk warning signal;

[0071] Specifically, when the operating parameter monitoring data is less than the operating parameter optimization result, a second risk threshold is obtained. The second risk threshold can be customized by a person skilled in the art based on actual conditions, and the operating risk coefficient is judged according to the second risk threshold. When the operating risk coefficient is greater than or equal to the second risk threshold, an abnormal operation risk warning signal is generated. The abnormal operation risk warning signal is used to characterize that when the switching frequency of the high-frequency switching power supply is low and the on-pulse width is low, the duty cycle is low. At this time, the equipment may not be powered in time, which will cause abnormal impact on the operation of the equipment.

[0072] Step S700: performing operation risk monitoring of a high-frequency switching power supply according to the operation safety risk warning signal or the operation abnormality risk warning signal.

[0073] Specifically, the high-frequency switching power supply is finally subjected to operational risk monitoring based on the operational safety risk warning signal or the operational abnormality risk warning signal. This method solves the technical problem of low quality of conventional high-frequency switching power supply operational monitoring methods, which cannot analyze the correlation between the operational status and the task. This method can improve the compatibility of the operational monitoring method with the task, thereby improving the operational monitoring quality.

[0074] In one embodiment, Figure 4 The system provides a high-frequency switching power supply operation risk monitoring system, including: a power demand information acquisition module 1, a power consumption assessment module 2, an operation parameter optimization module 3, an operation risk coefficient generation module 4, an operation safety risk warning signal generation module 5, an operation abnormality risk warning signal generation module 6, and an operation risk monitoring module 7, wherein:

[0075] An electricity demand information acquisition module 1 is used to acquire electricity demand information, wherein the electricity demand information includes the position number of the electrical equipment and the operation task information;

[0076] An electricity consumption evaluation module 2 is used to evaluate electricity consumption according to the electrical equipment bit number and the operation task information, and obtain power supply information and power supply time zone information;

[0077] An operating parameter optimization module 3 is configured to optimize the operating parameters of the high-frequency switching power supply according to the power supply amount information and the power supply time zone information, and obtain an operating parameter optimization result;

[0078] An operation risk coefficient generating module 4 is configured to obtain operation parameter monitoring data when the electrical equipment is started, calculate the deviation between the operation parameter monitoring data and the operation parameter optimization result, and generate an operation risk coefficient;

[0079] An operation safety risk warning signal generating module 5 is configured to generate an operation safety risk warning signal when the operation parameter monitoring data is greater than the operation parameter optimization result and the operation risk coefficient is greater than or equal to a first risk threshold;

[0080] An abnormal operation risk warning signal generating module 6 is configured to generate an abnormal operation risk warning signal when the operating parameter monitoring data is less than the operating parameter optimization result and the operating risk coefficient is greater than or equal to a second risk threshold;

[0081] The operation risk monitoring module 7 is used to monitor the operation risk of the high-frequency switching power supply according to the operation safety risk warning signal or the operation abnormality risk warning signal.

[0082] In one embodiment, the system further comprises:

[0083] A historical operation record statistics module, the historical operation record statistics module is used to count historical operation records according to the electrical equipment bit number and the operation task information, wherein the historical operation records include multiple operation durations and multiple power supply records;

[0084] a centralized value evaluation module, configured to perform centralized value evaluation on the plurality of operation durations, obtain a centralized value of the operation durations, and set the power supply time zone information;

[0085] A power supply concentration value acquisition module is configured to perform concentration value evaluation on the plurality of power supply records, acquire a power supply concentration value, and set the power supply information.

[0086] In one embodiment, the system further comprises:

[0087] a duration abnormality factor acquisition module, the duration abnormality factor acquisition module being configured to perform abnormality analysis on an i-th operation duration of the plurality of operation durations to acquire an abnormality factor for the i-th operation duration;

[0088] a duration deletion module, configured to delete the i-th job duration from the plurality of job durations when the i-th job duration abnormality factor is less than or equal to an abnormality factor threshold;

[0089] The operation duration centralized value acquisition module is used to add the i-th operation duration to the centralized value evaluation duration when the i-th operation duration abnormality factor is greater than the abnormality factor threshold, calculate the average of the centralized value evaluation duration, and obtain the operation duration centralized value.

[0090] In one embodiment, the system further comprises:

[0091] A concentration evaluation coefficient acquisition module, wherein the concentration evaluation coefficient acquisition module is used to obtain a concentration evaluation coefficient, wherein the concentration evaluation coefficient is a positive integer and is less than or equal to floor(0.5*N), where N is the number of multiple job durations and floor(0.5*N) is a floor rounding function;

[0092] a duration deviation obtaining module, configured to obtain a plurality of duration deviations by calculating a deviation between the duration of the i-th operation and the other durations of the plurality of operations;

[0093] a duration concentration generation module, the duration concentration generation module being configured to select, from the plurality of duration deviations, from smallest to largest, a maximum duration deviation that satisfies the concentration evaluation coefficient, and calculate the inverse thereof, to generate a duration concentration of the i-th task;

[0094] The duration abnormality factor acquisition module is used to obtain the average of the operation duration concentrations of the multiple operation durations, calculate the ratio with the i-th operation duration concentration, and obtain the i-th operation duration abnormality factor.

[0095] In one embodiment, the system further comprises:

[0096] An operating parameter summary module, wherein the operating parameters of the high-frequency switching power supply include a conduction pulse width and a switching operating frequency;

[0097] A power supply evaluation model construction module, the power supply evaluation model construction module is used to construct a power supply evaluation model of the high-frequency switching power supply based on the conduction pulse width and the switch operating frequency;

[0098] A random assignment module, the random assignment module is used to randomly assign the conduction pulse width and the switch operating frequency, and obtain a conduction pulse width assignment result and a switch operating frequency assignment result;

[0099] a power supply evaluation result acquisition module, configured to input the on-pulse width assignment result, the switch operating frequency assignment result, and the power supply time zone information into the power supply evaluation model to acquire a power supply evaluation result when the on-pulse width assignment result and the switch operating frequency assignment result meet the duty cycle expectation;

[0100] An operating parameter optimization result setting module is used to set the on-pulse width assignment result and the switch operating frequency assignment result as the operating parameter optimization result when the power supply evaluation result is greater than the power supply information.

[0101] In one embodiment, the system further comprises:

[0102] A random assignment module is used to set a conduction pulse width constraint interval and a switch operating frequency constraint interval, perform M random assignments on the conduction pulse width and the switch operating frequency, and obtain M groups of operation parameter assignment results, where M is an integer and M ≥ 50;

[0103] an assignment result screening module, the assignment result screening module being configured to screen N groups of operation parameter assignment results that meet the duty cycle expectation from the M operation parameter assignment results, where N is an integer, N≤M;

[0104] a power supply evaluation result acquisition module, configured to sequentially input the N groups of operating parameter assignment results into the power supply evaluation model to obtain N power supply evaluation results;

[0105] an operating parameter assignment result acquisition module, the operating parameter assignment result acquisition module being configured to filter the N groups of operating parameter assignment results whose N power supply evaluation results are greater than the power supply information, and acquire L groups of operating parameter assignment results, where L is an integer and L≤N;

[0106] An assignment result expansion module, configured to expand the L groups of operation parameter assignment results to obtain Q groups of operation parameter assignment results, where Q is an integer, and Q ≥ 80;

[0107] An operating parameter optimization result acquisition module is used to optimize the Q group operating parameter assignment results based on the power supply evaluation model to obtain the operating parameter optimization result.

[0108] In one embodiment, the system further comprises:

[0109] A step length constraint interval acquisition module, wherein the step length constraint interval acquisition module is used to obtain the step length constraint interval for adjusting the operating parameters;

[0110] A primary expansion module, configured to expand the L groups of operating parameter assignment results according to the operating parameter adjustment step constraint interval to obtain the operating parameter primary expansion results;

[0111] A secondary expansion module, configured to perform a secondary expansion on the primary expansion result of the operating parameter when the primary expansion result of the operating parameter is less than 80, to obtain a secondary expansion result of the operating parameter;

[0112] An operating parameter assignment result acquisition module is used to repeatedly iterate and acquire the Q groups of operating parameter assignment results.

[0113] In summary, this application provides a method and system for monitoring the operation risks of a high-frequency switching power supply, which has the following technical effects:

[0114] 1. The method solves the technical problem that the traditional high-frequency switching power supply operation monitoring method cannot analyze the correlation between the operating status and the operation task, resulting in low quality of high-frequency switching power supply operation monitoring. It can improve the adaptability of the operation monitoring method to the operation task, thereby improving the operation monitoring quality.

[0115] 2. By expanding the results of the operation parameter assignment, the amount of data can be expanded within a reasonable data expansion range, thereby improving the accuracy of the operation parameter optimization results.

[0116] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0117] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for monitoring the operation risk of a high-frequency switching power supply, characterized in that: include: Obtaining power demand information, wherein the power demand information includes the power equipment position number and operation task information; Perform power consumption evaluation based on the power-consuming equipment position number and the operation task information to obtain power supply information and power supply time zone information; Optimizing the operating parameters of the high-frequency switching power supply according to the power supply amount information and the power supply time zone information, and obtaining an operating parameter optimization result; When the electric equipment is started, the operating parameter monitoring data is obtained, the deviation between the operating parameter monitoring data and the operating parameter optimization result is calculated, and the operating risk coefficient is generated; When the operating parameter monitoring data is greater than the operating parameter optimization result, and the operating risk coefficient is greater than or equal to a first risk threshold, generating an operating safety risk warning signal; When the operating parameter monitoring data is less than the operating parameter optimization result, and the operating risk coefficient is greater than or equal to a second risk threshold, generating an abnormal operation risk warning signal; Performing high-frequency switching power supply operation risk monitoring according to the operation safety risk warning signal or the operation abnormality risk warning signal; Optimizing the operating parameters of the high-frequency switching power supply according to the power supply amount information and the power supply time zone information to obtain the operating parameter optimization results includes: The operating parameters of the high-frequency switching power supply include the on-pulse width and the switching operating frequency; Constructing a power supply evaluation model of the high-frequency switching power supply based on the conduction pulse width and the switch operating frequency; Randomly assigning values to the on-pulse width and the switch operating frequency to obtain an on-pulse width assignment result and a switch operating frequency assignment result; When the on-pulse width assignment result and the switch operating frequency assignment result meet the duty cycle expectation, the on-pulse width assignment result, the switch operating frequency assignment result and the power supply time zone information are input into the power supply evaluation model to obtain a power supply evaluation result; When the power supply evaluation result is greater than the power supply information, the on-pulse width assignment result and the switch operating frequency assignment result are set as the operating parameter optimization result.

2. The method according to claim 1, wherein Performing a power consumption assessment based on the power-consuming equipment number and the operation task information to obtain power supply information and power supply time zone information includes: According to the electrical equipment bit number and the operation task information, historical operation records are counted, wherein the historical operation records include multiple operation durations and multiple power supply records; Performing a centralized value evaluation on the plurality of operation durations, obtaining a centralized value of the operation durations, and setting the power supply time zone information; A centralized value evaluation is performed on the plurality of power supply amount records, a power supply amount centralized value is obtained, and the power supply amount information is set.

3. The method according to claim 2, wherein Performing a centralized value evaluation on the multiple operation durations to obtain a centralized value of the operation durations includes: Performing an abnormality analysis on the i-th operation duration of the multiple operation durations to obtain an abnormality factor of the i-th operation duration; When the abnormal factor of the i-th operation duration is less than or equal to the abnormal factor threshold, deleting the i-th operation duration from the multiple operation durations; When the abnormal factor of the i-th operation duration is greater than the abnormal factor threshold, the i-th operation duration is added to the centralized value evaluation duration, the average of the centralized value evaluation duration is calculated, and the centralized value of the operation duration is obtained.

4. The method according to claim 3, wherein Performing an abnormality analysis on the duration of the i-th operation to obtain an abnormality factor of the i-th operation duration includes: Obtaining a concentration evaluation coefficient, where the concentration evaluation coefficient is a positive integer and is less than or equal to floor(0.5*K), where K is the number of the plurality of job durations, and floor(0.5*K) is a floor rounding function; Based on the i-th operation duration, a deviation is calculated from other operation durations of the plurality of operation durations to obtain a plurality of duration deviations; The maximum duration deviation that satisfies the concentration evaluation coefficient is selected from the plurality of duration deviations from smallest to largest, and the inverse is obtained to generate the duration concentration of the i-th task; An average of the concentrations of the multiple operation durations is obtained, and the ratio is calculated with the concentration of the i-th operation duration to obtain an abnormal factor of the i-th operation duration.

5. The method according to claim 1, wherein Also includes: Setting a conduction pulse width constraint interval and a switch operating frequency constraint interval, performing M random assignments on the conduction pulse width and the switch operating frequency, and obtaining M groups of operating parameter assignment results, where M is an integer and M ≥ 50; Screening N groups of operating parameter assignment results that meet the expected duty cycle from the M groups of operating parameter assignment results, where N is an integer, N≤M; Inputting the N groups of operating parameter assignment results into the power supply evaluation model in sequence to obtain N power supply evaluation results; Filter the N groups of operating parameter assignment results whose N power supply evaluation results are greater than the power supply information to obtain L groups of operating parameter assignment results, where L is an integer and L≤N; Expanding the L groups of operating parameter assignment results to obtain Q groups of operating parameter assignment results, where Q is an integer, Q ≥ 80; An optimization is performed based on the power supply evaluation model from the Q group operating parameter assignment results to obtain the operating parameter optimization result.

6. The method according to claim 5, wherein Expand the L groups of operating parameter assignment results to obtain Q groups of operating parameter assignment results, where Q is an integer, Q ≥ 80, including: Get the operating parameter adjustment step constraint interval; Expanding the L groups of operating parameter assignment results once according to the operating parameter adjustment step size constraint interval to obtain an operating parameter expansion result; When the primary expansion result of the operating parameter is less than 80, performing a secondary expansion on the primary expansion result of the operating parameter to obtain a secondary expansion result of the operating parameter; Repeat the iteration to obtain the Q group of operating parameter assignment results.

7. High-frequency switching power supply operation risk monitoring system, characterized in that: The steps for implementing the high-frequency switching power supply operation risk monitoring method according to any one of claims 1 to 6 include: An electricity demand information acquisition module, wherein the electricity demand information acquisition module is used to acquire electricity demand information, wherein the electricity demand information includes the position number of the electrical equipment and the operation task information; An electricity consumption evaluation module, configured to evaluate electricity consumption based on the electrical equipment bit number and the operation task information, and obtain power supply information and power supply time zone information; An operating parameter optimization module, configured to optimize operating parameters of the high-frequency switching power supply according to the power supply amount information and the power supply time zone information, and obtain an operating parameter optimization result; An operation risk coefficient generation module, wherein the operation risk coefficient generation module is used to obtain operation parameter monitoring data when the electrical equipment is started, calculate the deviation between the operation parameter monitoring data and the operation parameter optimization result, and generate an operation risk coefficient; an operation safety risk warning signal generation module, the operation safety risk warning signal generation module being configured to generate an operation safety risk warning signal when the operation parameter monitoring data is greater than the operation parameter optimization result and the operation risk coefficient is greater than or equal to a first risk threshold; an abnormal operation risk warning signal generating module, the abnormal operation risk warning signal generating module being configured to generate an abnormal operation risk warning signal when the operating parameter monitoring data is less than the operating parameter optimization result and the operating risk coefficient is greater than or equal to a second risk threshold; An operation risk monitoring module, the operation risk monitoring module is used to monitor the operation risk of the high-frequency switching power supply according to the operation safety risk warning signal or the operation abnormality risk warning signal; Wherein, the operating parameter optimization module further includes: An operating parameter unit, wherein the operating parameter unit refers to the operating parameters of the high-frequency switching power supply including the on-pulse width and the switching operating frequency; An evaluation model construction unit, configured to construct a power supply evaluation model of the high-frequency switching power supply based on the conduction pulse width and the switch operating frequency; A random assignment unit, configured to randomly assign values to the on-pulse width and the switch operating frequency, and obtain an on-pulse width assignment result and a switch operating frequency assignment result; an evaluation result acquisition unit, configured to input the on-pulse width assignment result, the switch operating frequency assignment result, and the power supply time zone information into the power supply evaluation model to acquire a power supply evaluation result when the on-pulse width assignment result and the switch operating frequency assignment result meet the duty cycle expectation; The optimization result obtaining unit is used to set the on-pulse width assignment result and the switch operating frequency assignment result as the operating parameter optimization result when the power supply evaluation result is greater than the power supply information.

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