Visual display heat dissipation fan and heat dissipation monitoring method

Abstract

The application provides a visual visual display cooling fan and a cooling monitoring method, and relates to the technical field of computer cooling. The method comprises the following steps: obtaining working performance data of a cooling fan, extracting performance change data and performance effect data; performing performance characteristic analysis based on a time dimension according to the performance change data, and forming performance change characteristic data; performing effect mapping analysis according to the performance effect data and in combination with the performance change characteristic data, and forming performance effect characteristic data; collecting real-time cooling data, performing performance monitoring analysis according to the performance effect characteristic data, and forming performance effect monitoring analysis result data; and forming performance monitoring display information according to the performance effect monitoring analysis result data. The method can realize more intuitive and effective real-time monitoring of the cooling fan, and improves the personalization and intelligentization of use.

Description

Technical Field

[0001] This invention relates to the field of computer heat dissipation technology, and more specifically, to a visual display cooling fan and a heat dissipation monitoring method. Background Technology

[0002] Computers, especially mainframes and computing base stations, consume a lot of power, resulting in significant heat generation. This heat can negatively impact computer performance, necessitating effective heat dissipation. Currently, there are two main methods for cooling computers: liquid cooling and air cooling. Liquid cooling utilizes a highly thermally conductive refrigerant to achieve efficient heat exchange. However, the use of refrigerant increases costs. Air cooling, on the other hand, achieves efficient heat exchange at a lower cost, effectively removing the large amount of heat generated by the computer and maintaining a stable operating temperature.

[0003] Of course, air cooling is mainly achieved by using cooling fans. Current cooling fans simply rotate their blades to accelerate airflow and remove heat. However, there is no intuitive and effective monitoring of the effect of cooling fans, especially the rotation of the blades. Therefore, it is impossible to accurately and reasonably analyze and judge the operating efficiency and heat dissipation effect of cooling fans.

[0004] Therefore, designing a visual display method for cooling fans and a method for monitoring cooling heat dissipation, which can enable more intuitive and effective real-time monitoring of cooling fans and improve the personalization and intelligence of their use, is an urgent problem to be solved. Summary of the Invention

[0005] The purpose of this invention is to provide a heat dissipation monitoring method. By acquiring data on different operating modes and durations of a cooling fan based on a time dimension, a mapping relationship is established between factors affecting its heat dissipation performance and power, as well as the heat dissipation effect. On one hand, it primarily considers the influence of time-related parameters, namely operating duration and operating mode, reducing the complexity of data analysis while ensuring the rationality of the relationship analysis on changes in cooling fan performance, thus improving the efficiency of data analysis. On the other hand, it unifies all parameters affecting cooling fan performance into a time dimension, integrating the effects of factors with a major impact on performance into the operating duration and the time-based changes in operating duration, ensuring both sufficiency and relative rationality in the analysis. This enables accurate and reasonable monitoring of abnormal changes in cooling fan performance, providing a data foundation for the visual management of cooling fans.

[0006] The present invention also aims to provide a visual display cooling fan. This fan can provide the necessary power to drive the fan blades via a USB data cable, and can also transmit data with the PCB integrated circuit component. At the same time, the visual display module on the PCB integrated circuit component can provide a reasonable and intuitive visual display of the parameter data and analysis data monitored by the cooling fan. This expands the function and application scenarios of the cooling fan in the field of computer heat dissipation, and brings customers a more intelligent and user-friendly experience.

[0007] In a first aspect, the present invention provides a heat dissipation monitoring method, comprising: acquiring the operating performance data of a cooling fan, extracting performance change data and performance effect data; performing time-based performance characteristic analysis based on the performance change data to form performance change characteristic data; performing effect mapping analysis based on the performance effect data and in combination with the performance change characteristic data to form performance effect characteristic data; collecting real-time heat dissipation data, and performing performance monitoring analysis based on the performance effect characteristic data to form performance effect monitoring analysis result data; and forming performance monitoring display information based on the performance effect monitoring analysis result data.

[0008] In this invention, the method establishes a mapping relationship between factors affecting the cooling performance of a cooling fan and its power and cooling effect by acquiring data on different operating modes and durations of the cooling fan based on a time dimension. On one hand, it primarily considers the influence of time-related parameters, namely operating duration and operating mode, reducing the complexity of data analysis while ensuring the rationality of the relationship analysis on the impact of changes in cooling fan performance, thus improving the efficiency of data analysis. On the other hand, it unifies all parameters affecting the cooling fan performance into a time dimension, that is, the effects of factors with a major impact on performance are integrated into the operating duration and the time-based changes in operating duration, ensuring both sufficiency and relative rationality in the analysis. This enables accurate and reasonable monitoring of abnormal changes in cooling fan performance, providing a data foundation for the visual management of cooling fans.

[0009] As one possible implementation, time-based performance characteristic analysis is performed based on performance change data to form performance change characteristic data. This includes: determining the cumulative operating time data of different cooling fans of the same type over time based on the performance change data, and forming a corresponding cumulative operating time change function A for the same type. n (t), where n represents the number of different cooling fans of the same type, and t represents the time parameter; based on the performance change data, the percentage change of the working time of different cooling fans of the same type in the time dimension is determined, forming the corresponding function R of the percentage change of the working time of the same type. n(t); Based on the performance change data, determine the power change data of different cooling fans of the same type over time, and form the corresponding power change data P of the same type. n (t); For different cooling fans of the same type, according to the corresponding cumulative change function A of the same type of working time. n (t), Function R representing the change in the proportion of similar working hours n (t) and similar power change data P n (t) is used to perform performance relationship analysis based on working time parameters to form performance relationship data of the same type; and to collect the performance relationship data of different cooling fans of the same type to form performance change characteristic data.

[0010] In this invention, to reasonably and accurately monitor the operating status of the cooling fan, it is necessary to establish reference comparison data on the normal performance and effect degradation of the cooling fan during use. It is understood that there are many factors affecting the performance and effect of the cooling fan, and these factors vary greatly. Collecting and processing data for each of these factors separately would result in a huge amount of data and increase the difficulty of analysis. However, considering the changes in the cooling fan's performance and effect, the most obvious impact is based on changes in time parameters. Many factors affecting performance and effect, such as the resistance of the circuit, the frictional performance of the mechanical structure, the quality of point contact, and the effectiveness of the controller, all change over time, exhibiting a significant cumulative effect. Therefore, a reasonable and in-depth analysis of the time parameters can be used to determine the impact of these multiple factors on the cooling fan's performance and effect through the cumulative effect over time. This application primarily considers two aspects regarding time parameters. Firstly, the actual operating time of the cooling fan. An increase in actual operating time inevitably leads to a decrease in the performance and effectiveness of the cooling fan. This decrease includes the cumulative effect of multiple factors over time. Of course, factors such as the frictional performance of the mechanical structure and the quality of point contacts also affect performance and effectiveness when the cooling fan is not operating. However, considering that most cooling fans are used in computers or workstations that operate for extended periods, prolonged shutdowns are rare, and the impact of these factors on performance and effectiveness during non-operating periods can be ignored. Secondly, the operating mode of the cooling fan, mainly the frequency of start-stop cycles. Frequent start-stop cycles and their intervals have a significant impact, especially on electrical performance. Therefore, the frequency of start-stop cycles needs to be considered. Here, the start-stop frequency is characterized by the change in the ratio of operating time to usage time. Combining these two time-based parameter data allows for the analysis of the cumulative effect of multiple factors on the performance and effectiveness of the cooling fan.

[0011] As one possible implementation, for different cooling fans of the same type, the cumulative change function A based on the corresponding working time of the same type can be used. n(t), Function R representing the change in the proportion of similar working hours n (t) and similar power change data P n (t) is used to perform performance relationship analysis based on the working time parameter, forming similar performance relationship data, including: randomly determining M time points during the usage time of the cooling fan and recording them as analysis time points. And based on power change data P of the same type n (t) Determine the analysis time point power at corresponding time points m represents the sequential number of the different time points determined; for different analysis time points The cumulative change function A of the same type of work duration n (t) determines the time point from the start of use to the analysis point. The corresponding function for truncation of cumulative change in the duration of similar work. From the function R of the change in the proportion of the same type of working hours n (t) determines the time point from the start of use to the analysis point. The corresponding function for extracting the percentage change of the same type of working hours Based on different analysis time points Based on the corresponding cumulative change function of similar working hours Extract the function of the change in the proportion of the same type of working hours and power at time points The following power interception relationships were determined: Where P0 is the rated power of the cooling fan, U k U represents the cumulative effect correlation over time. k =α0+(α1) 1 +…+(α k ) k α k V is the cumulative impact factor over time. i V represents the correlation between the proportion of time spent and the duration of the equation. i =β0+(β1) 1 +…+(β i ) i ,β i The cumulative impact factor over time is used; a tolerance-based verification and adjustment analysis is performed on the power impact relationship to generate performance relationship data for the same type of cooling fan.

[0012] In this invention, the impact of different cooling fans on performance and effectiveness over time parameters varies due to differences in operating methods and durations, resulting in different performance and effectiveness degradations. Therefore, it is necessary to determine the impact separately. Considering that analyzing the relationship between performance and effectiveness solely over total duration would ignore short-term performance fluctuations, especially those caused by changes in usage frequency, this application employs a segmented extraction method to obtain cumulative effect data of different durations and establish separate impact relationships. Verification analysis is then used to determine whether there are relationship data consistent with the overall trend of cooling fan performance degradation. It should be noted that to avoid arbitrarily selected adjacent time points causing similarity in results, a certain time interval can be agreed upon for each analysis time point. For the two impact correlation formulas on working duration and working time percentage, since they essentially reflect the cumulative effect of multiple factors on cooling fan performance and effectiveness over time parameters, they are not simple linear relationships and are therefore expressed as powers. When determining the terms in the impact correlation formulas, this can be done by extracting data from multiple time points within the extracted time period to form analytical relationships. Of course, the extracted time point data must ensure that there are at least two terms in the impact correlation formulas. The power can be determined based on the actual situation; a higher power indicates higher accuracy, but also increases the complexity of obtaining it. Therefore, it should be determined based on the actual accuracy requirements. For cooling fans, performance changes are mainly reflected in power consumption. Therefore, two time-based parameter data are correlated with power data to characterize performance changes.

[0013] As one possible implementation, a tolerance-based verification and adjustment analysis is performed on the impact of intercepted power to generate performance relationship data for the same type of cooling fan, including: arbitrarily determining the same analysis time point within the usage time of the cooling fan. Any three different verification time points T test And obtain each verification time point T. test The corresponding verification function for the cumulative change in the duration of similar work. Verify the function of the change in the proportion of the same type of working hours and verification power P test Based on the verification time point T test The corresponding verification function for the cumulative change in the duration of similar work. Verify the function of changing proportion of similar working hours By combining the influence of different cutoff powers, the corresponding verification time point T was determined. test Corresponding calculated power Based on different verification time points T test Corresponding calculated power and verification power P testThe following verification and adjustment analysis was performed to assess the impact of different cutoff powers: If a cutoff power impact relationship exists, such that the three verification time points T... test Calculate power Same verification power P test If the sum of the differences does not exceed the verification tolerance value, then the fitted power influence relationship formed by averaging and fitting all the required power influence relationships using the same influence relationship formula is determined as the performance relationship data of the same type of cooling fan. If there is no power cutoff relationship, then the three verification time points T test Calculated power Same verification power P test If the sum of the differences exceeds the validation tolerance, then the analysis will be repeated for M non-repeating time points. The selection of [a specific method] determines new different cutoff power influence relationships until a cutoff power influence relationship exists that makes the three verification time points T [equal to the previous one]. test Calculate power Same verification power P test The sum of the differences does not exceed the verification tolerance value. The newly formed power influence relationships that meet the requirements are all fitted using the same influence relationship formula. The resulting fitted power influence relationship is then used as the performance relationship data for the same type of cooling fan.

[0014] In this invention, considering the arbitrariness of the analysis time points, which may affect the accuracy of the analysis, verification and adjustment are necessary for the performance relationship established for the cooling fan. The verification and adjustment method involves arbitrarily acquiring three more verification time points and comparing the power data corresponding to these time points with the power data determined based on the performance relationship. Since the performance relationship provides m data points, applicability verification can be performed. That is, performance relationships that meet the requirements are determined as reasonable relationship data. If multiple performance relationships are satisfied, the same type of influence correlation is subjected to function-based averaging fitting. This involves determining the function curve of each influence correlation, obtaining the average value on each coordinate, and then fitting it to form the corresponding influence correlation. Finally, it is expressed using the same performance relationship as the corresponding performance relationship data of the same type. If no performance relationship meets the requirements, considering the impact of the arbitrariness of m on the establishment of the performance relationship, m analysis time points are re-acquired, and the entire process from performance relationship to verification analysis is reprocessed until a performance relationship that meets the requirements appears. The verification tolerance value can be set according to the actual situation or determined based on big data analysis. It should be noted that the difference between different types of performance relationship data lies in the different usage methods and usage durations. "Same type" means that the cooling fan is working in the same way, that is, the computer and the usage environment are the same or similar.

[0015] As one possible implementation, performance effect data is generated by performing effect mapping analysis based on performance effect data and performance change characteristic data. This includes: determining the time-based cooling effect data of different cooling fans of the same type based on the performance effect data, thus generating the cooling effect change data G for the same type of cooling fan. n (t); Map the data on changes in the same type of heat dissipation effect to the corresponding data on the same type of performance relationship based on the time dimension to form the corresponding performance effect feature data of the same type; collect the performance effect feature data of the same type corresponding to all different cooling fans of the same type to form performance effect feature data.

[0016] In this invention, it is understood that power data is primarily a characterization of the electrical performance of a cooling fan. The ultimate goal of a cooling fan is to convert electrical energy into kinetic energy to drive heat dissipation. Meeting power requirements does not necessarily guarantee the desired effect. Therefore, mapping the fan's cooling effect to power data is necessary to provide a reference for simultaneous analysis of electrical performance and cooling effect during subsequent monitoring and analysis. Here, the cooling effect is expressed as the amount of heat dissipated per unit time, mapping the heat dissipation rate to the corresponding power change data over time, forming a complete performance-effect relationship data.

[0017] As one possible implementation, based on performance data, the time-based cooling effect data of different cooling fans of the same type is determined, forming a data G of cooling effect variation for the same type. n (t), including: for different cooling fans of the same type, determining the time-based operating temperature monitoring change function W based on performance data. n (t) and the ambient temperature monitoring change function H n (t); based on the monitoring change function W of the corresponding operating temperature of the cooling fan. n Using the ambient temperature monitoring change function t(t) and the heat dissipation change data L of the same type, we can determine the heat dissipation change data L. n (t), where L n (t)=C*Z*|W n (t)-H n (t)|, where C is the specific heat capacity of air and Z is the mass flow rate of the cooling fan; based on the heat dissipation variation data of the same type L n (t), determine the corresponding heat dissipation effect change data G of the same type. n (t), where G n (t) is L n (t) is the first derivative of the time parameter.

[0018] In this invention, the heat dissipation effect is characterized by the heat dissipation rate. Since the heat dissipation varies due to performance changes at different operating times, the heat dissipation rate also changes over time, showing a temporal correlation with power changes. The heat dissipation rate is primarily related to ambient temperature and operating temperature over time. Simultaneously, the airflow provided by the fan is also data related to the fan speed; these all possess temporal characteristics. Therefore, obtaining these parameters at corresponding time points allows for the determination of the corresponding heat dissipation rate.

[0019] One possible implementation involves collecting real-time heat dissipation data and performing performance monitoring and analysis based on performance effect characteristic data to generate performance effect monitoring and analysis results data, including: extracting the cumulative change function A of the real-time operating time of the cooling fan based on the real-time heat dissipation data. time (t), Real-time working hours percentage change function R time (t), Real-time power P time and real-time heat dissipation rate g time According to the cumulative change function A of real-time working duration time (t) and the function R of real-time working hours percentage change time (t), and combined with performance change characteristic data, determine the real-time calculated power P. cal According to real-time power P time Based on performance characteristic data, the real-time mapped heat dissipation rate g was determined. cal According to real-time power P time Real-time heat dissipation rate g time Real-time calculation of power P cal and real-time mapped heat dissipation rate g cal Performance monitoring and analysis are conducted to generate performance effect monitoring and analysis results data.

[0020] In this invention, after obtaining the performance and effect relationship feature data corresponding to different working modes and working durations under big data, it can be used to monitor the real-time data of the cooling fan. The monitoring and analysis method is to determine the corresponding calculated power based on the cooling fan's working duration change data and working time percentage change data at the current time, combined with the matched performance and effect relationship feature data of working mode and working duration. Then, the corresponding mapped heat dissipation rate is determined through mapping relationship. Finally, the two matched parameters are compared with the real-time power and real-time heat dissipation rate to determine whether the current cooling fan's performance and effect changes are normal. It is worth noting that the performance and effect relationship feature data corresponding to different working modes and working durations under big data is used as reference comparison data. In the initial stage of data collection, the average data can be used as the benchmark. That is, for the same working mode and working duration, the data in the middle can be selected as the corresponding representative feature data. The centrality can be determined by the magnitude of the power change rate, that is, data with a power change rate close to the average value is used as the representative feature data, making the subsequent analysis more reasonable and accurate.

[0021] As one possible implementation, based on the cumulative change function A of real-time working duration. time (t) and the function R of real-time working hours percentage change time (t), and combined with performance change characteristic data, determine the real-time calculated power P. cal This includes: a cumulative change function A based on real-time working duration. time (t) and the function R of real-time working hours percentage change time (t), determine the real-time equivalent cumulative amount of working hours Q corresponding to the current time point. time ,in, Among them, T time This represents the total real-time duration of the cooling fan from the start of its operation to the current time. For different performance relationship data of the same type, the total real-time duration T is used as the reference. time And the corresponding cumulative change function A of the same type of work duration n (t) and the function R of the change in the proportion of the same type of working hours n (t), determine the corresponding equivalent cumulative amount of the same type of working hours Q. n ,in, Based on different equivalent cumulative amounts of the same type of working hours Q n Determine the equivalent cumulative amount Q of real-time working hours. time The closest equivalent cumulative amount of similar working hours Q n And the corresponding performance relationship data of the same type are determined as monitoring and comparison data; based on the monitoring and comparison data, and combined with the real-time working duration cumulative change function A time (t) and the function R of real-time working hours percentage change time(t), determine the real-time calculated power P cal .

[0022] In this invention, determining the real-time calculated power first requires identifying the performance and effect relationship characteristic data that best matches the current cooling fan in terms of operating mode and duration. This is determined by comparing the cumulative effects of two time-parameter-based metrics of the same duration. Specifically, the performance and effect relationship characteristic data whose sum of the cumulative operating time value and the cumulative working time percentage value is closest to the corresponding total real-time duration is used as the reference data for analysis and comparison. It should be noted that although the sum of the cumulative operating time value and the cumulative working time percentage value is general, they are closely related. That is, the working time percentage decreases when the operating time remains constant, and increases when the operating time increases. Therefore, the sum of the cumulative operating time value and the cumulative working time percentage value will not be the same or close to the sum of the cumulative operating time value and the cumulative working time percentage value of the data with the matching operating mode and duration, even if there are other data with different operating modes and durations. Therefore, this method of matching judgment is reasonable and accurate.

[0023] As one possible implementation, based on the real-time power P time Real-time heat dissipation rate g time Real-time calculation of power P cal and real-time mapped heat dissipation rate g cal Performance monitoring and analysis are conducted to generate performance effect monitoring and analysis results data, including: when |P time -P cal |≤P pass And the absolute value |g time -g cal |≤g pass This will generate information indicating that the performance is normal.

[0024] The beneficial effects of the visual display cooling fan and heat dissipation monitoring method provided by this invention are as follows:

[0025] This method establishes a mapping relationship between factors affecting the cooling performance of a cooling fan and its power and cooling effect by acquiring data on different operating modes and durations based on a time dimension. On one hand, it primarily considers the impact of time-related factors such as operating duration and operating mode on the time parameter, reducing the complexity of data analysis while ensuring the rationality of the relationship analysis on changes in cooling fan performance, thus improving the efficiency of data analysis. On the other hand, it unifies all parameters affecting cooling fan performance into a time dimension, integrating the effects of factors with a major impact on performance into the operating duration and the time-based changes in operating duration, ensuring both sufficiency and relative rationality in the analysis. This enables accurate and reasonable monitoring of abnormal changes in cooling fan performance, providing a data foundation for the visual management of cooling fans.

[0026] This fan can provide the necessary power to drive the fan blades via a USB data cable, and also enable data transmission with the PCB integrated circuit components. At the same time, the visual display module on the PCB integrated circuit components can provide a reasonable and intuitive visual display of the parameters and analysis data monitored by the cooling fan, expanding the function and application scenarios of the cooling fan in the field of computer heat dissipation, and bringing customers a more intelligent and user-friendly experience. Attached Figure Description

[0027] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments of the present invention will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 A flowchart illustrating the steps of a heat dissipation monitoring method provided in an embodiment of the present invention;

[0029] Figure 2 This is a schematic diagram of the structure of a visual display cooling fan provided in an embodiment of the present invention;

[0030] Figure 3 This is an extended comparative schematic diagram of a visual display cooling fan provided as an embodiment of the present invention. Detailed Implementation

[0031] The technical solutions of the present invention will now be described with reference to the accompanying drawings in the embodiments of the present invention.

[0032] Computers, especially mainframes and computing base stations, consume a lot of power, resulting in significant heat generation. This heat can negatively impact computer performance, necessitating effective heat dissipation. Currently, there are two main methods for cooling computers: liquid cooling and air cooling. Liquid cooling utilizes a highly thermally conductive refrigerant to achieve efficient heat exchange. However, the use of refrigerant increases costs. Air cooling, on the other hand, achieves efficient heat exchange at a lower cost, effectively removing the large amount of heat generated by the computer and maintaining a stable operating temperature.

[0033] Of course, air cooling is mainly achieved by using cooling fans. Current cooling fans simply rotate their blades to accelerate airflow and remove heat. However, there is no intuitive and effective monitoring of the effect of cooling fans, especially the rotation of the blades. Therefore, it is impossible to accurately and reasonably analyze and judge the operating efficiency and heat dissipation effect of cooling fans.

[0034] refer to Figures 1-2 This invention provides a heat dissipation monitoring method.

[0035] A heat dissipation monitoring method specifically includes the following steps:

[0036] S1: Obtain the operating performance data of the cooling fan, and extract the performance change data and performance effect data.

[0037] The performance data primarily includes the performance data of different cooling fans of the same type. The performance variation data to be extracted involves the variation data of factors affecting the performance of the cooling fans and the variation data of corresponding performance parameters, so as to facilitate the subsequent extraction of reasonable interrelationship feature data. The performance effect data includes the heat dissipation effect data of different cooling fans, providing a reference for subsequent reasonable characterization of heat dissipation effect.

[0038] S2: Perform time-based performance characteristic analysis based on performance change data to generate performance change characteristic data.

[0039] Based on the performance change data, a time-based performance characteristic analysis is performed to generate performance change characteristic data, including: determining the cumulative operating time data of different cooling fans of the same type over the time dimension based on the performance change data, and generating a corresponding cumulative operating time change function A for the same type. n (t), where n represents the number of different cooling fans of the same type, and t represents the time parameter; based on the performance change data, the percentage change of the working time of different cooling fans of the same type in the time dimension is determined, forming the corresponding function R of the percentage change of the working time of the same type. n(t); Based on the performance change data, determine the power change data of different cooling fans of the same type over time, and form the corresponding power change data P of the same type. n (t); For different cooling fans of the same type, according to the corresponding cumulative change function A of the same type of working time. n (t), Function R representing the change in the proportion of similar working hours n (t) and similar power change data P n (t) is used to perform performance relationship analysis based on working time parameters to form performance relationship data of the same type; and to collect the performance relationship data of different cooling fans of the same type to form performance change characteristic data.

[0040] To accurately monitor the operating status of cooling fans, it is necessary to establish reference and comparative data on the normal performance and effectiveness degradation of cooling fans during use. It is understandable that many factors, of various types, affect the performance and effectiveness of cooling fans. Collecting and processing data for each of these factors separately would result in a massive amount of data and significantly increase the difficulty of analysis. However, considering the changes in cooling fan performance, the most obvious impact is based on time-related parameters. Many factors affecting performance and effectiveness, such as circuit resistance, the frictional properties of mechanical structures, point contact quality, and controller effectiveness, change over time, exhibiting a significant cumulative effect. Therefore, a reasonable and in-depth analysis of time parameters can determine the impact of these multiple factors on the performance and effectiveness of cooling fans through the cumulative effect over time. This application primarily considers two aspects regarding time parameters. Firstly, the actual operating time of the cooling fan. An increase in actual operating time inevitably leads to a decrease in the performance and effectiveness of the cooling fan. This decrease includes the cumulative effect of multiple factors over time. Of course, factors such as the frictional performance of the mechanical structure and the quality of point contacts also affect performance and effectiveness when the cooling fan is not operating. However, considering that most cooling fans are used in computers or workstations that operate for extended periods, prolonged shutdowns are rare, and the impact of these factors on performance and effectiveness during non-operating periods can be ignored. Secondly, the operating mode of the cooling fan, mainly the frequency of start-stop cycles. Frequent start-stop cycles and their intervals have a significant impact, especially on electrical performance. Therefore, the frequency of start-stop cycles needs to be considered. Here, the start-stop frequency is characterized by the change in the ratio of operating time to usage time. Combining these two time-based parameter data allows for the analysis of the cumulative effect of multiple factors on the performance and effectiveness of the cooling fan.

[0041] For different cooling fans of the same type, according to the corresponding cumulative change function A of the same type of working time n (t), Function R representing the change in the proportion of similar working hoursn (t) and similar power change data P n (t) is used to perform performance relationship analysis based on the working time parameter, forming similar performance relationship data, including: randomly determining M time points during the usage time of the cooling fan and recording them as analysis time points. And based on power change data P of the same type n (t) Determine the analysis time point power at corresponding time points m represents the sequential number of the different time points determined; for different analysis time points The cumulative change function A of the same type of work duration n (t) determines the time point from the start of use to the analysis point. The corresponding function for truncation of cumulative change in the duration of similar work. From the function R of the change in the proportion of the same type of working hours n (t) determines the time point from the start of use to the analysis point. The corresponding function for extracting the percentage change of the same type of working hours Based on different analysis time points Based on the corresponding cumulative change function of similar working hours Extract the function of the change in the proportion of the same type of working hours and power at time points The following power interception relationships were determined: Where P0 is the rated power of the cooling fan, U k H represents the cumulative effect of duration. k =α0+(α1) 1 +…+(α k ) k α k V is the cumulative impact factor over time. i V represents the correlation between the proportion of time spent and the duration of the equation. i =β0+(β1) 1 +…+(β i ) i ,β i The cumulative impact factor over time is used; a tolerance-based verification and adjustment analysis is performed on the power impact relationship to generate performance relationship data for the same type of cooling fan.

[0042] The impact of time parameters on the performance and effectiveness of different cooling fans varies due to differences in operating methods and durations, leading to different performance and effectiveness degradations. Therefore, it is necessary to determine the impact separately. Analyzing the relationship between performance and effectiveness solely based on the total duration would overlook short-term performance fluctuations, especially those caused by changes in usage frequency. Therefore, this application employs a segmented extraction method to obtain cumulative effect data of different durations and establish separate impact relationships. Verification analysis is then used to determine whether there are relationship data consistent with the overall trend of cooling fan performance degradation. It should be noted that to avoid arbitrarily selected adjacent time points causing similarity in results, a certain time interval can be agreed upon for each analysis time point. For the two impact correlation formulas on operating duration and working time percentage, since they essentially reflect the cumulative effect of multiple factors on the performance and effectiveness of cooling fans over time parameters, they are not simple linear relationships. Therefore, they are expressed in a power-law form. When determining the terms in the impact correlation formulas, it can be determined by extracting data from multiple time points within the extracted time period to form analytical relationships. Of course, the extracted time point data must ensure that there are at least two terms in the impact correlation formulas. The power can be determined based on the actual situation; a higher power indicates higher accuracy, but also increases the complexity of obtaining it. Therefore, it should be determined based on the actual accuracy requirements. For cooling fans, performance changes are mainly reflected in power consumption. Therefore, two time-based parameter data are correlated with power data to characterize performance changes.

[0043] A tolerance-based verification and adjustment analysis was performed on the impact of intercepted power to generate performance relationship data for the same type of cooling fan, including: arbitrarily determining the same analysis time point within the usage time of the cooling fan. Any three different verification time points T test And obtain each verification time point T. test The corresponding verification function for the cumulative change in the duration of similar work. Verify the function of changing proportion of similar working hours and verification power P test Based on the verification time point T test The corresponding verification function for the cumulative change in the duration of similar work. Verify the function of changing proportion of similar working hours By combining the influence of different cutoff powers, the corresponding verification time point T was determined. test Corresponding calculated power Based on different verification time points T test Corresponding calculated power and verification power P testThe following verification and adjustment analysis was performed to assess the impact of different cutoff powers: If a cutoff power impact relationship exists, such that the three verification time points T... test Calculate power Same verification power P test If the sum of the differences does not exceed the verification tolerance value, then the fitted power influence relationship formed by averaging and fitting all the required power influence relationships using the same influence relationship formula is determined as the performance relationship data of the same type of cooling fan. If there is no power cutoff relationship, then the three verification time points T test Calculated power Same verification power P test If the sum of the differences exceeds the validation tolerance, then the analysis will be repeated for M non-repeating time points. The selection of [a specific method] determines new different cutoff power influence relationships until a cutoff power influence relationship exists that makes the three verification time points T [equal to the previous one]. test Calculate power Same verification power P test The sum of the differences does not exceed the verification tolerance value. The newly formed power influence relationships that meet the requirements are all fitted using the same influence relationship formula. The resulting fitted power influence relationship is then used as the performance relationship data for the same type of cooling fan.

[0044] Regarding the performance relationship established for the cooling fan, considering that the arbitrariness of the analysis time point may affect the accuracy of the analysis, verification and adjustment are necessary. The verification and adjustment method here is to arbitrarily obtain three more verification time points and compare the power data corresponding to these time points with the power data determined based on the performance relationship. Of course, since the performance relationship provides m data points, applicability verification can be performed. That is, performance relationships that meet the requirements are determined as reasonable relationship data. If multiple performance relationships are satisfied, the same type of influence correlation is subjected to function-based averaging fitting. That is, the function curve of each influence correlation is determined, the average value on each coordinate is obtained, and then fitted to form the corresponding influence correlation. Finally, it is expressed using the same performance relationship, which is the corresponding performance relationship data of the same type. If no performance relationship meets the requirements, considering the impact of the arbitrariness of m on the establishment of the performance relationship, m more analysis time points are obtained, and the entire process from performance relationship to verification analysis is reprocessed until a performance relationship that meets the requirements appears. The verification tolerance value can be set according to the actual situation or determined based on big data analysis. It should be noted that the difference between different types of performance relationship data lies in the different usage methods and usage durations. "Same type" means that the cooling fan is working in the same way, that is, the computer and the usage environment are the same or similar.

[0045] S3: Based on the performance effect data and combined with the performance change characteristic data, perform effect mapping analysis to form performance effect characteristic data.

[0046] Based on performance data and combined with performance change characteristic data, an effect mapping analysis is performed to form performance effect characteristic data, including: determining the time-based heat dissipation effect data of different cooling fans of the same type based on the performance data, forming the heat dissipation effect change data G of the same type. n (t); Map the data on changes in the same type of heat dissipation effect to the corresponding data on the same type of performance relationship based on the time dimension to form the corresponding performance effect feature data of the same type; collect the performance effect feature data of the same type corresponding to all different cooling fans of the same type to form performance effect feature data.

[0047] Understandably, for cooling fans, power data primarily characterizes the fan's electrical performance. However, the ultimate goal of a cooling fan is to convert electrical energy into kinetic energy to drive the fan and dissipate heat. Meeting power requirements doesn't necessarily guarantee the desired effect. Therefore, mapping the fan's cooling effect to power data is essential, providing a reference for simultaneous analysis of electrical performance and cooling effectiveness during later monitoring and analysis. Here, cooling effect is expressed as the amount of heat dissipated per unit time, mapping the heat dissipation rate to corresponding power changes over time, forming a complete data structure of performance and effect.

[0048] Based on performance data, the time-based cooling performance data of different cooling fans of the same type was determined, forming the cooling performance variation data G for the same type. n (t), including: for different cooling fans of the same type, determining the time-based operating temperature monitoring change function W based on performance data. n (t) and the ambient temperature monitoring change function H n (t); based on the monitoring change function W of the corresponding operating temperature of the cooling fan. n (t) and the ambient temperature monitoring change function H n (t), determine the heat dissipation variation data L of the same type. n (t), where L n (t)=C*Z*|W n (t)-H n (t)|, where C is the specific heat capacity of air and Z is the mass flow rate of the cooling fan; based on the heat dissipation variation data of the same type L n (t), determine the corresponding heat dissipation effect change data G of the same type. n (t), where G n (t) is L n (t) is the first derivative of the time parameter.

[0049] The heat dissipation effect is characterized by the heat dissipation rate. Since the heat dissipation varies due to performance changes over different operating times, the heat dissipation rate also changes over time, showing a temporal correlation with power changes. The heat dissipation rate is primarily related to ambient temperature and operating temperature over time. Simultaneously, the airflow provided by the fan is also related to the fan speed; these parameters all exhibit temporal characteristics. Therefore, obtaining these parameters at a given time point allows for the determination of the corresponding heat dissipation rate.

[0050] S4: Collect real-time heat dissipation data and perform performance monitoring and analysis based on performance effect characteristic data to generate performance effect monitoring and analysis result data.

[0051] Real-time heat dissipation data is collected, and performance monitoring and analysis are performed based on performance effect characteristic data to generate performance effect monitoring and analysis results data, including: extracting the cumulative change function A of the real-time working time of the cooling fan based on the real-time heat dissipation data. time (t), Real-time working hours percentage change function R time (t), Real-time power P time and real-time heat dissipation rate g time According to the cumulative change function A of real-time working duration time (t) and the function R of real-time working hours percentage change time (t), and combined with performance change characteristic data, determine the real-time calculated power P. cal According to real-time power P time Based on performance characteristic data, the real-time mapped heat dissipation rate g was determined. cal According to real-time power P time Real-time heat dissipation rate g time Real-time calculation of power P cal and real-time mapped heat dissipation rate g cal Performance monitoring and analysis are conducted to generate performance effect monitoring and analysis results data.

[0052] After obtaining the performance and effect relationship characteristic data corresponding to different working methods and durations under big data, it can be used to monitor the real-time data of cooling fans. The monitoring and analysis method is to determine the corresponding calculated power based on the changes in the working duration and working time ratio of the cooling fan at the current time, combined with the performance and effect relationship characteristic data of the matching working methods and durations. Then, the corresponding mapped heat dissipation rate is determined through mapping relationship. Finally, the two matched parameters are compared with the real-time power and real-time heat dissipation rate to determine whether the current performance and effect changes of the cooling fan are normal. It is worth noting that the performance and effect relationship characteristic data corresponding to different working methods and durations under big data is used as reference comparison data. In the initial stage of data collection, the average data can be used as the benchmark. That is, for the same working method and duration, the middle data can be selected as the corresponding representative characteristic data. The centrality can be determined by the magnitude of the power change rate. That is, data with a power change rate close to the average value is used as the representative characteristic data, making the subsequent analysis more reasonable and accurate.

[0053] Based on the real-time working duration cumulative change function A time (t) and the function R of real-time working hours percentage change time (t), and combined with performance change characteristic data, determine the real-time calculated power P. cal This includes: a cumulative change function A based on real-time working duration. time (t) and the function R of real-time working hours percentage change time(t), determine the real-time equivalent cumulative amount of working hours Q corresponding to the current time point. time ,in, Among them, T time This represents the total real-time duration of the cooling fan from the start of its operation to the current time. For different performance relationship data of the same type, the total real-time duration T is used as the reference. time And the corresponding cumulative change function A of the same type of work duration n (t) and the function R of the change in the proportion of the same type of working hours n (t), determine the corresponding equivalent cumulative amount of the same type of working hours Q. n ,in, Based on different equivalent cumulative amounts of the same type of working hours Q n Determine the equivalent cumulative amount Q of real-time working hours. time The closest equivalent cumulative amount of similar working hours Q n And the corresponding performance relationship data of the same type are determined as monitoring and comparison data; based on the monitoring and comparison data, and combined with the real-time working duration cumulative change function A time (t) and the function R of real-time working hours percentage change time (t), determine the real-time calculated power P cal .

[0054] Determining the real-time calculated power first requires identifying the performance and effect characteristics that best match the current cooling fan's operating mode and duration. This is done by comparing the cumulative effects of two time-based parameters of the same duration. Specifically, the performance and effect characteristics whose sum of the cumulative operating time value and the cumulative working time percentage over the corresponding total real-time duration is closest are used as reference data for analysis and comparison. It should be noted that although the sum of the cumulative operating time value and the cumulative working time percentage is general, they are closely related. That is, the working time percentage decreases when the operating time remains constant, and increases when the operating time increases. Therefore, the sum of the cumulative operating time value and the cumulative working time percentage will not be the same or close to the sum of the cumulative operating time value and the cumulative working time percentage value of the data with the matching operating mode and duration, even if there are other data with different operating modes and durations. Therefore, this method of matching is reasonable and accurate.

[0055] According to the real-time power P time Real-time heat dissipation rate g time Real-time calculation of power P cal and real-time mapped heat dissipation rate g cal Performance monitoring and analysis are conducted to generate performance effect monitoring and analysis results data, including: when |P time -P cal |≤P pass And the absolute value |g time -gcal |≤g pass Then, normal performance information is generated; when |P time -P cal |>P pass And the absolute value |g time -g cal |≤g pass Then an energy consumption anomaly information is generated; when |P time -P cal |≤P pass And the absolute value |g time -g cal |>g pass This generates information about abnormal heat dissipation; when |P time -P cal |>P pass And the absolute value |g time -g cal |>g pass This will generate work error information.

[0056] The monitoring and analysis of performance and effectiveness mainly involves comparing power and heat dissipation rate. If both power and heat dissipation rate are within reasonable ranges, it indicates that the cooling fan performance, although changing, is within a normal range. If the power is outside the reasonable range, it indicates increased power consumption and a rapid performance decline. It's important to note that this application focuses on cooling fans with constant power; a decrease in actual operating power directly indicates performance degradation. For cooling fans with variable power during operation, the initial power needs to be adjusted adaptively under different conditions. If the heat dissipation rate is outside the range, it suggests that dust accumulation may be hindering the efficiency of converting electrical energy into mechanical energy. If both power and heat dissipation rate are outside the range, it indicates that the cooling fan is malfunctioning.

[0057] S5: Based on the performance monitoring and analysis results, generate performance monitoring display information.

[0058] Different analysis results can be converted into text, indicator signals, etc. for output display, which can more intuitively and accurately confirm the working status and effect of the cooling fan.

[0059] The present invention also provides a visual display cooling fan, which includes: fan blades, fan frame, PCB integrated circuit assembly, base, and USB data cable; the PCB integrated circuit assembly is disposed on the base; the fan frame is disposed on the base and fastened to the base; the fan blades are rotatably connected to a motor on the PCB integrated circuit assembly; the USB data cable is located on one side of the base and connected to the PCB integrated circuit assembly, and the visual display module of the PCB integrated circuit assembly is disposed on opposite sides of the base.

[0060] The structure consisting of the fan blades, fan frame, and base is the basic part of the entire device. Its main function is to drive airflow through the rotation of the fan blades, thereby achieving heat dissipation. It may employ a traditional method of driving the fan blades with a motor. In this invention, it serves as the carrier for the visual display and the main body of the heat dissipation technology.

[0061] The visual display module on the PCB integrated circuit assembly is a key component for realizing visualization functions. It provides visual communication, potentially through the integration of a small display screen, such as a liquid crystal display (LCD) or an organic light-emitting diode (OLED) display, to display images, text, and other information. The displayed content can be customized according to different needs, such as displaying device temperature, device operating status, or user-defined information. The heat dissipation monitoring method provided by this invention can be used to output and display monitoring and analysis results, making the performance and effectiveness of the cooling fan more intuitive.

[0062] A USB cable is a widely used interface for data transmission and power supply in electronic devices. Here, the USB cable powers a visual display module. This means that no additional complex power wiring is required; as long as the device has a usable USB port, power can be supplied to the display module.

[0063] In traditional cooling fan applications, achieving visualization functionality often requires the separate design and installation of the cooling fan, independent display module, and their respective power supply systems, resulting in numerous internal wiring and a complex structure. This invention integrates the cooling fan, visualization display module, and power supply module into a single unit, significantly reducing the number of internal components and wiring connections, resulting in a more compact and streamlined overall structure. For example, in space-constrained electronic device enclosures, this highly integrated design allows for easy installation without taking up excessive space, avoiding the heat dissipation risks and maintenance difficulties caused by cluttered wiring.

[0064] The integrated design allows the entire device to be installed and disassembled as a single unit, significantly reducing installation difficulty. It also makes operation easier for non-professionals. In terms of maintenance, when problems arise, there's no need to separately troubleshoot the connections between the cooling fan, display module, and power supply module; only the entire integrated device needs inspection and repair, improving maintenance efficiency. For example, in data centers, a large number of server devices require cooling fans. Using this highly integrated, visualized cooling fan allows maintenance personnel to quickly install and replace equipment, reducing downtime.

[0065] Due to its neat wiring and simplified structure, this invention can better adapt to various application scenarios. It can be easily integrated and used in fields such as personal computers, AI computing servers, industrial control equipment, and smart homes. For example, in smart home environments, small smart appliances such as air purifiers and humidifiers can be easily equipped with this visualized cooling fan, without affecting the overall appearance and spatial layout of the device, while achieving both heat dissipation and visualization functions.

[0066] This fan can provide the necessary power to drive the fan blades via a USB data cable, and also enable data transmission with the PCB integrated circuit components. At the same time, the visual display module on the PCB integrated circuit components can provide a reasonable and intuitive visual display of the parameters and analysis data monitored by the cooling fan, expanding the function and application scenarios of the cooling fan in the field of computer heat dissipation, and bringing customers a more intelligent and user-friendly experience.

[0067] like Figure 3 It should also be noted that while cooling fans are primarily used to dissipate heat from computers or workstations, considering different types of heat dissipation, the cooling fans can be expanded according to the actual situation, i.e., providing different numbers of fan blades. Correspondingly, the matching base, fan frame, and PCB integrated circuit components should also be expanded accordingly. Of course, due to the change in the type of heat dissipation, when performing heat dissipation-based monitoring, the performance data that generates performance change characteristic data and performance effect characteristic data must also be matched to the data of the computer being cooled to ensure the accuracy and rationality of the monitoring and analysis.

[0068] In summary, the beneficial effects of the visual display cooling fan and heat dissipation monitoring method provided by the embodiments of the present invention are as follows:

[0069] This method establishes a mapping relationship between factors affecting the cooling performance of a cooling fan and its power and cooling effect by acquiring data on different operating modes and durations based on a time dimension. On one hand, it primarily considers the impact of time-related factors such as operating duration and operating mode on the time parameter, reducing the complexity of data analysis while ensuring the rationality of the relationship analysis on changes in cooling fan performance, thus improving the efficiency of data analysis. On the other hand, it unifies all parameters affecting cooling fan performance into a time dimension, integrating the effects of factors with a major impact on performance into the operating duration and the time-based changes in operating duration, ensuring both sufficiency and relative rationality in the analysis. This enables accurate and reasonable monitoring of abnormal changes in cooling fan performance, providing a data foundation for the visual management of cooling fans.

[0070] This fan can provide the necessary power to drive the fan blades via a USB data cable, and also enable data transmission with the PCB integrated circuit components. At the same time, the visual display module on the PCB integrated circuit components can provide a reasonable and intuitive visual display of the parameters and analysis data monitored by the cooling fan, expanding the function and application scenarios of the cooling fan in the field of computer heat dissipation, and bringing customers a more intelligent and user-friendly experience.

[0071] In the embodiments of this application, "instruction" can include direct and indirect instructions, as well as explicit and implicit instructions. The information indicated by a certain piece of information is called the information to be instructed. In the specific implementation process, there are many ways to instruct the information to be instructed, such as, but not limited to, directly instructing the information to be instructed, such as the information to be instructed itself or its index. It can also indirectly instruct the information to be instructed by instructing other information, where there is a relationship between the other information and the information to be instructed. It can also instruct only a part of the information to be instructed, while the other parts are known or pre-agreed upon. For example, the instruction of specific information can be achieved by using a pre-agreed (e.g., protocol-defined) arrangement of various pieces of information, thereby reducing instruction overhead to some extent. At the same time, common parts of various pieces of information can be identified and uniformly indicated to reduce the instruction overhead caused by individually indicating the same information.

[0072] Furthermore, the specific indication method can also be any existing indication method, such as, but not limited to, the above-mentioned indication methods and their various combinations. Specific details of various indication methods can be found in existing technologies, and will not be repeated here. As described above, for example, when multiple pieces of information of the same type need to be indicated, the indication methods for different pieces of information may differ. In the specific implementation process, the required indication method can be selected according to specific needs. This application embodiment does not limit the selected indication method; therefore, the indication methods involved in this application embodiment should be understood to cover various methods that enable the party to be indicated to obtain the information to be indicated.

[0073] It should be understood that the information to be indicated can be sent as a whole or divided into multiple sub-information messages sent separately, and the sending period and / or timing of these sub-information messages can be the same or different. The specific sending method is not limited in this application embodiment. The sending period and / or timing of these sub-information messages can be predefined, for example, according to a protocol, or configured by the sending device by sending configuration information to the receiving device.

[0074] "Predefined" or "pre-configured" can be achieved by pre-saving corresponding codes, tables, or other means that can be used to indicate relevant information in the device. This application does not limit the specific implementation method. "Saving" can refer to saving in one or more memories. These memories can be separate installations or integrated into the encoder, decoder, processor, or communication device. Alternatively, some memories can be separately installed, while others are integrated into the decoder, processor, or communication device. The type of memory can be any form of storage medium, and this application does not limit this.

[0075] The “protocol” mentioned in the embodiments of this application may refer to a protocol family in the field of communication, a standard protocol with a similar protocol family frame structure, or a related protocol applied to future communication systems. The embodiments of this application do not specifically limit this.

[0076] In the embodiments of this application, descriptions such as "when," "under the circumstances," "if," and "if" all refer to the device making corresponding processing under certain objective circumstances, and are not limited to a specific time. They do not require the device to make a judgment action during implementation, nor do they imply any other limitations.

[0077] In the description of the embodiments of this application, unless otherwise stated, " / " indicates that the objects before and after are in an "or" relationship. For example, A / B can represent A or B. "And / or" in the embodiments of this application is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone, where A and B can be singular or plural. Furthermore, in the description of the embodiments of this application, unless otherwise stated, "multiple" refers to two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple. Additionally, to facilitate a clear description of the technical solutions of the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first," "second," etc., do not limit the quantity or order of execution, and that "first," "second," etc., are not necessarily different. Furthermore, in the embodiments of this application, words such as "exemplary" or "for example" are used to indicate that something is being used as an example, illustration, or description. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner for ease of understanding.

[0078] It should be understood that the processor in the embodiments of this application can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0079] It should also be understood that the memory in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DRRAM).

[0080] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0081] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0082] In this application, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or multiple items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0083] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0084] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0085] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0086] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0087] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0088] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0089] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0090] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A heat dissipation monitoring method, characterized in that, include: Obtain the operating performance data of the cooling fan, and extract the performance change data and performance effect data; Based on the performance change data, a time-based performance characteristic analysis is performed to form performance change characteristic data. Based on the performance effect data and combined with the performance change characteristic data, an effect mapping analysis is performed to form performance effect characteristic data; Real-time heat dissipation data is collected, and performance monitoring and analysis are performed based on the performance effect characteristic data to generate performance effect monitoring and analysis result data. Based on the performance effect monitoring and analysis result data, performance monitoring display information is generated. Specifically, time-based performance characteristic analysis is performed based on the performance change data to generate performance change characteristic data, including: determining the cumulative working time data of different cooling fans of the same type over time based on the performance change data, and generating a corresponding cumulative working time change function for the same type. , n represents the number of different cooling fans of the same type, and t represents the time parameter; Based on the performance change data, the percentage change in the working time of different cooling fans of the same type over time was determined, and a corresponding function for the percentage change in the working time of the same type was formed. Based on the performance change data, the power change data of different cooling fans of the same type over time is determined, forming corresponding power change data for the same type. For different cooling fans of the same type, the cumulative change function of the corresponding working time is used. The function for the change in the proportion of the same type of working hours and the power change data of the same type The performance relationship analysis based on the working time parameter is performed to form the performance relationship data of the same type; the performance relationship data of the same type corresponding to different cooling fans of the same type are collected to form the performance change characteristic data.

2. The heat dissipation monitoring method according to claim 1, characterized in that, For different cooling fans of the same type, the cumulative change function of the corresponding working time of the same type is used. The function for the change in the proportion of the same type of working hours And the power change data of the same type Performance relationship analysis based on working time parameters is performed to generate similar performance relationship data, including: randomly determining M time points during the usage time of the cooling fan and recording them as analysis time points. And based on the power change data of the same type Determine the analysis time point power at corresponding time points , m is the sequential number of the different time points determined; for different analysis time points The cumulative change function of the same type of work duration The time from the start of use to the analysis point was determined. The corresponding function for truncation of cumulative change in the duration of similar work. The function of changing the proportion of the same type of working hours The time from the start of use to the analysis point is determined in the middle. The corresponding function for extracting the proportion of the same type of working hours According to different analysis time points According to the corresponding cumulative change function of the same type of work duration, The function for extracting the proportion of the same type of working hours and the power at the time point The following relationships regarding the influence of intercepted power were determined: ,in, This refers to the rated power of the cooling fan. This indicates the correlation formula representing the cumulative effect of duration. , The cumulative impact factor over time. The expression indicating the influence of duration percentage on the correlation formula. , The cumulative impact factor over time is used; the intercepted power impact relationship is verified and adjusted based on tolerance to form the performance relationship data of the same type of cooling fan.

3. The heat dissipation monitoring method according to claim 2, characterized in that, The step of performing tolerance-based verification and adjustment analysis on the power interception relationship to form performance relationship data for the same type of cooling fan includes: arbitrarily determining the same analysis time point within the usage time of the cooling fan. Any three different verification time points And obtain each of the verification time points. The corresponding verification function for the cumulative change in the duration of similar work. Verify the function of the change in the proportion of the same type of working hours. and verify power According to the verification time point The corresponding verification function for the cumulative change in the duration of similar work. The verification function for the change in the proportion of the same type of working hours And by combining the different interception power influence relationships, the corresponding verification time points are determined. Corresponding calculated power According to different verification time points The corresponding calculated power and the verification power The following verification and adjustment analysis is performed on the different cutoff power influence relationships: If the cutoff power influence relationship exists, such that the three verification time points... The above calculation of power Same as the verification power If the sum of the differences does not exceed the verification tolerance value, then the fitted power influence relationship formed by averaging and fitting all the intercepted power influence relationships that meet the requirements with the same influence relationship formula is determined as the performance relationship data of the same type corresponding to the cooling fan. If the aforementioned power interception relationship does not exist, then the three verification time points... The above-described power calculation Same as the verification power If the sum of the differences exceeds the verification tolerance value, then the analysis will be repeated for M non-repeating time points. The selection determines new and different cutoff power influence relationships until a cutoff power influence relationship exists that makes the three verification time points... The above calculation of power Same as the verification power The sum of the differences does not exceed the verification tolerance value. The fitted power influence relationship formed by averaging and fitting all the newly formed, satisfactory power influence relationships using the same influence relationship formula is determined as the performance relationship data of the same type corresponding to the cooling fan. .

4. The heat dissipation monitoring method according to claim 3, characterized in that, The step of performing effect mapping analysis based on the performance effect data and the performance change characteristic data to form performance effect characteristic data includes: determining the time-based heat dissipation effect data of different cooling fans of the same type based on the performance effect data, and forming heat dissipation effect change data of the same type. Map the data on the changes in the heat dissipation effect of the same type to the corresponding performance relationship data of the same type based on the time dimension to form the corresponding performance effect feature data of the same type; collect the performance effect feature data of the same type corresponding to all different cooling fans of the same type to form the performance effect feature data.

5. The heat dissipation monitoring method according to claim 4, characterized in that, Based on the performance data, the time-based cooling performance data of different cooling fans of the same type is determined, forming data on the variation of cooling performance of the same type. This includes: for different cooling fans of the same type, determining the time-based operating temperature monitoring change function based on the performance data. and ambient temperature monitoring change function According to the operating temperature monitoring change function corresponding to the cooling fan. and the environmental temperature monitoring change function Determine the data on changes in heat dissipation for the same type. ,in, Where C is the specific heat capacity of air, and Z is the mass flow rate of the cooling fan; based on the heat dissipation variation data of the same type. Determine the corresponding heat dissipation effect change data of the same type. ,in, for The first derivative with respect to the time parameter.

6. The heat dissipation monitoring method according to claim 5, characterized in that, The process of collecting real-time heat dissipation data and performing performance monitoring and analysis based on the performance effect characteristic data to form performance effect monitoring and analysis result data includes: extracting the cumulative change function of the real-time working time of the cooling fan based on the real-time heat dissipation data. Real-time working hours percentage change function Real-time power and real-time heat dissipation rate According to the cumulative change function of the real-time working duration and the real-time working time percentage change function In conjunction with the aforementioned performance change characteristic data, the real-time calculation power is determined. According to the real-time power Based on the performance characteristic data, the real-time mapped heat dissipation rate is determined. According to the real-time power The real-time heat dissipation rate The real-time power calculation and the real-time mapped heat dissipation rate The performance is monitored and analyzed to generate the performance effect monitoring and analysis results data.

7. The heat dissipation monitoring method according to claim 6, characterized in that, The cumulative change function based on the real-time working duration and the real-time working time percentage change function In conjunction with the aforementioned performance change characteristic data, the real-time calculation power is determined. This includes: based on the cumulative change function of the real-time working duration. and the real-time working time percentage change function Determine the equivalent cumulative amount of real-time working hours corresponding to the current time point. ,in, ,in, This indicates the total real-time duration of the cooling fan from the start of its operation to the current time; for different performance relationship data of the same type, the total real-time duration is used as the basis for calculation. and the corresponding cumulative change function of the same type of working time and the function of change in the proportion of the same type of working hours Determine the equivalent cumulative amount of the same type of working hours. ,in, Based on different equivalent cumulative amounts of the same type of working hours Determine the equivalent cumulative amount of the real-time working hours. The closest equivalent cumulative amount of the same type of working hours The corresponding performance relationship data of the same type are determined as monitoring comparison data; based on the monitoring comparison data, and combined with the real-time working duration cumulative change function... and the real-time working time percentage change function The real-time calculation power is determined. .

8. The heat dissipation monitoring method according to claim 7, characterized in that, According to the real-time power The real-time heat dissipation rate The real-time power calculation and the real-time mapped heat dissipation rate The performance monitoring and analysis are performed to generate the performance effect monitoring and analysis result data, including: when ≤ and absolute value ≤ This will generate a message indicating that the performance is normal. when > and absolute value ≤ This will generate abnormal energy consumption information; when ≤ and absolute value > This will generate information about abnormal heat dissipation; when and absolute value This will generate work error information.

9. A visual display cooling fan and a heat dissipation monitoring method, employing the heat dissipation monitoring method according to any one of claims 1-8, characterized in that, include: Fan blades, fan frame, PCB integrated circuit assembly, base, USB data cable; the PCB integrated circuit assembly is mounted on the base; The fan frame is mounted on the base and fastened to the base; the fan blades are rotatably connected to the motor on the PCB integrated circuit assembly; the USB data cable is located on one side of the base and connected to the PCB integrated circuit assembly; the visual display module of the PCB integrated circuit assembly is disposed on opposite sides of the base.

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