A server component life estimation method and electronic device

Abstract

The application discloses a server component life estimation method and an electronic device, relates to the technical field of server maintenance, and is applied to a management controller and comprises the following steps: determining stress acceleration coefficients of a server component according to collected operation data of the target server component and a preset life acceleration model, then calculating a target life acceleration coefficient of the target server component through a preset weight and the stress acceleration coefficients, and converting actual working time of the target server into equivalent aging time through the target life acceleration coefficient, and then estimating the remaining life of the target server component through the equivalent aging time. In this way, the life of the server component can be estimated in multiple dimensions, so as to guarantee the estimation accuracy of the server component failure time.

Description

Technical Field

[0001] This application relates to the field of server maintenance technology, and in particular to a method for estimating the lifespan of server components and an electronic device. Background Technology

[0002] As the core equipment for information processing and data storage, the stable operation of servers directly affects business continuity. Failure of server components (such as processors, memory, hard drives, capacitors, power supplies, etc.) is the main cause of server downtime. Therefore, accurate prediction of component failure time is key to achieving predictive maintenance.

[0003] In current related technologies, the Baseboard Management Controller (BMC) only records the temperature, voltage, and current values ​​of key components, without recording operating time or predicting the remaining lifespan of each component. Therefore, current BMCs lack accurate conversion of actual operating time and fail to effectively transform actual operating time into an equivalent time that reflects the true degree of aging, which may lead to inaccurate predictions of remaining lifespan. Summary of the Invention

[0004] This application provides a method and electronic device for predicting the lifespan of server components. It can comprehensively predict the lifespan of server components through multi-dimensional stress to ensure the accuracy of the prediction of server component failure time.

[0005] This application provides a method for estimating the lifespan of server components, applied to a management controller, including:

[0006] Collect operational data from the target server components;

[0007] Using operational data, preset exponents corresponding to the target server components, and a preset lifetime acceleration model, the stress acceleration coefficients for each component are determined. The preset lifetime acceleration model is a model that uses exponentiation based on preset exponents to obtain the stress acceleration coefficients.

[0008] Based on each stress acceleration coefficient and its corresponding preset weight, the target lifetime acceleration coefficient of the target server component is determined.

[0009] The actual working time of the target server components is converted based on the target lifetime acceleration factor to convert the actual working time into equivalent aging time.

[0010] The remaining lifespan of the target server components is estimated based on the equivalent aging time to determine the remaining lifespan of the target server components.

[0011] This application also provides a server component lifespan prediction device, applied to a management controller, comprising:

[0012] The data acquisition module is used to collect operational data from the target server components.

[0013] The first acceleration coefficient determination module is used to determine the stress acceleration coefficients of the target server component using operating data, a preset exponent corresponding to the target server component, and a preset lifetime acceleration model; the preset lifetime acceleration model is a model that obtains stress acceleration coefficients by exponentiation based on a preset exponent.

[0014] The second acceleration coefficient determination module is used to determine the target lifetime acceleration coefficient of the target server component based on each stress acceleration coefficient and the corresponding preset weight.

[0015] The data conversion module is used to convert the actual working time of the target server components according to the target lifetime acceleration factor, so as to convert the actual working time into the equivalent aging time.

[0016] The lifetime estimation module is used to estimate the remaining lifetime of the target server component based on the equivalent aging time, so as to determine the remaining lifetime of the target server component.

[0017] This application also provides an electronic device, including: a memory for storing a computer program; and a processor for implementing the steps of any of the above-described server component lifetime estimation methods when executing the computer program.

[0018] This application also provides a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, it implements the steps of any of the above-described server component lifetime estimation methods.

[0019] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of any of the above-described server component lifetime estimation methods.

[0020] In this application, operational data of the target server component can be collected; using the operational data, the preset index corresponding to the target server component, and the preset lifetime acceleration model, the stress acceleration coefficients of the target server component can be determined; the preset lifetime acceleration model is a model that obtains the stress acceleration coefficients by exponentiation based on the preset index; based on each stress acceleration coefficient and the corresponding preset weight, the target lifetime acceleration coefficient of the target server component can be determined; the actual working time of the target server component can be converted according to the target lifetime acceleration coefficient to convert the actual working time into equivalent aging time; the remaining lifetime of the target server component can be estimated based on the equivalent aging time to determine the remaining lifetime of the target server component.

[0021] Therefore, the method of this application can determine the stress acceleration coefficients of the server components based on the collected operating data of the target server components and the preset lifespan acceleration model. Then, the target lifespan acceleration coefficient of the target server components is calculated using preset weights and each stress acceleration coefficient. The actual operating time of the target server is then converted into an equivalent aging time using the target lifespan acceleration coefficient, and the remaining lifespan of the target server components is estimated using the equivalent aging time. In this way, the lifespan of server components can be estimated through multi-dimensional stress synthesis, ensuring the accuracy of server component failure time prediction. Attached Figure Description

[0022] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 A flowchart of a server component lifespan estimation method provided in this application embodiment;

[0024] Figure 2 A schematic diagram of a server component lifespan prediction system provided in this application embodiment;

[0025] Figure 3 A flowchart illustrating a method for estimating the lifespan of a server component provided in this application embodiment;

[0026] Figure 4 This is a schematic diagram of a server component lifespan prediction device provided in an embodiment of this application. Detailed Implementation

[0027] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of this application.

[0028] It should be noted that, in the description of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. The terms "first," "second," etc., in this application are used to distinguish similar objects and are not used to describe a specific order or sequence.

[0029] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0030] Current technologies only record the temperature, voltage, and current values ​​of key components, without recording operating time or predicting the remaining lifespan of each component. Therefore, current BMCs lack accurate conversion of actual operating time and fail to effectively transform actual operating time into an equivalent time reflecting the true degree of aging, potentially leading to inaccurate remaining lifespan predictions.

[0031] To overcome the aforementioned technical problems, this application discloses a method and electronic device for predicting the lifespan of server components. This method can comprehensively predict the lifespan of server components through multi-dimensional stress, thereby ensuring the accuracy of the prediction of server component failure time.

[0032] See Figure 1 As shown, embodiments of this application provide a server component lifetime estimation method applied to a management controller. The method is described in detail below, in conjunction with its execution flow. The method includes:

[0033] Step S11: Collect the operating data of the target server components.

[0034] In this embodiment, it is necessary to collect the operating data of the target server component in the server in real time through the BMC, and then preprocess the operating data. Specifically, it is necessary to collect the electrical stress parameters, temperature parameters, and operating time parameters of the target server component in the target server based on a first preset time interval. It should be noted that the electrical stress parameters include the real-time operating voltage V and real-time operating current I of the target server component, and the temperature parameter is the real-time operating temperature T of the target server component. K Its unit is The working time parameter is the cumulative working time t under the current electrical stress and temperature, in hours, and the target server is the server where the management controller is located. Further, the collected parameters need to be preprocessed. Specifically, one of two types of electrical stress parameters needs to be selected as the target electrical stress parameter. This can be based on the component type of the target server component, selecting either the operating voltage or the operating current as the target electrical stress parameter. For example, if the target server component is a capacitor or chip, the real-time operating voltage can be selected as the target electrical stress parameter; if the target server component is a wire or solder joint, the real-time operating current can be used. Finally, the temperature parameter can be converted to Kelvin to obtain the target temperature parameter. In this way, the operating voltage or operating current matching the component type can be selected as the target electrical stress parameter based on the server component type, and the server component temperature also needs to be converted to Kelvin, thereby ensuring the rigor and accuracy of the server component lifespan prediction.

[0035] Step S12: Using the running data, the preset index corresponding to the target server component, and the preset lifetime acceleration model, determine the stress acceleration coefficients of the target server component; the preset lifetime acceleration model is a model that uses power operations based on the preset index to obtain the stress acceleration coefficients.

[0036] In this embodiment, the stress acceleration coefficients of the target server component are first determined using operational data, a preset index corresponding to the target server component, and a preset lifetime acceleration model. Specifically, the rated operating parameters of the target server component need to be determined, including the rated operating voltage. Rated operating current Rated operating temperature Its unit is Rated component life The unit is hours. It should be noted that the rated total life is the mean time to failure under rated stress.

[0037] Furthermore, if the target stress parameter is the operating voltage, then the target electrical stress parameter and the rated operating voltage need to be input into the first preset life acceleration model. The output of the first preset life acceleration model is used as the electrical stress acceleration coefficient of the target server component. The first preset life acceleration model is a life acceleration model based on voltage and a preset first exponent. The output of the first preset life acceleration model is a value obtained by exponentiation of the ratio between the operating voltage and the rated operating voltage. Therefore, the expression of the first preset life acceleration model is:

[0038] ;

[0039] Among them, AF V The first preset life acceleration model outputs the electrical stress acceleration coefficient, which is also the voltage acceleration coefficient. V is the working voltage, V0 is the rated working voltage, and n is the preset first exponent, which is also the voltage acceleration factor. The voltage acceleration factor is determined by the component type and is obtained through manufacturer experimental data.

[0040] On the other hand, if the target stress parameter is the operating current, then the target electrical stress parameter and the rated operating current need to be input into the second preset life acceleration model. The output of the second preset life acceleration model is used as the electrical stress acceleration coefficient of the target server component. The second preset life acceleration model is a life acceleration model based on current and a preset second exponent. The output of the second preset life acceleration model is a value obtained by exponentiation of the ratio between the operating current and the rated operating current. Therefore, the expression of the second preset life acceleration model is:

[0041] ;

[0042] Among them, AF I The second preset life acceleration model outputs the electrical stress acceleration coefficient, which is also the current acceleration coefficient. I is the working voltage, I0 is the rated working voltage, and m is the preset second exponent, which is also the current acceleration factor. The current acceleration factor is determined by the component type and is obtained through manufacturer experimental data.

[0043] The next step requires calculating the temperature acceleration factor. Specifically, the target temperature parameter and the rated operating temperature need to be input into the third preset lifespan acceleration model. This third preset lifespan acceleration model is an Arrhenius model, and its output is used as the temperature acceleration factor for the target server component. This third preset lifespan acceleration model is a lifespan acceleration model based on temperature and a preset third exponent. It should be noted that the output of the third preset lifespan acceleration model is a value obtained by exponentiation with the natural constant as the base and the preset third exponent as the exponent. The preset third exponent is the product of the target ratio and the target difference. The target ratio is the ratio of the activation energy of the target server component to the preset constant, and the target difference is the difference between the reciprocal of the rated operating temperature and the reciprocal of the target temperature parameter. Therefore, the expression for the third preset lifespan acceleration model is:

[0044] ;

[0045] Among them, AF T The temperature acceleration coefficient output by the third preset lifetime acceleration model, e is the natural constant, and E aLet k be the activation energy corresponding to the target server component, and k be a preset constant, i.e., the Boltzmann constant. ), Rated operating temperature, T K This refers to the real-time operating temperature of the target server components.

[0046] In this way, the combined effects of temperature and electrical stress on server components can be considered, and the lifespan of server components can be comprehensively estimated through multi-dimensional stress, so as to ensure the accuracy of the estimated time of failure of server components.

[0047] Step S13: Based on each stress acceleration coefficient and the corresponding preset weight, determine the target lifetime acceleration coefficient of the target server component.

[0048] In this embodiment, after obtaining the temperature acceleration coefficient and the electrical stress acceleration coefficient, it is necessary to calculate the target lifetime acceleration coefficient of the target server component based on the temperature acceleration coefficient and the electrical stress acceleration coefficient. Specifically, it is first necessary to determine the preset temperature weight and preset electrical stress weight corresponding to the target server component. The preset temperature weight and preset electrical stress weight are dynamically determined based on the component characteristics. ω T The preset temperature weight has a value range of (0, 1), ω E The preset electrical stress weight has a value range of (0, 1), and the preset temperature weight and preset electrical stress weight satisfy preset constraints. The preset constraints stipulate that the sum of the preset temperature weight and the preset electrical stress weight is 1. For temperature-sensitive components such as processors and memory, ω can be taken as... T =0.7, ω E =0.3, for electrical stress-sensitive weights such as capacitors and power supplies, ω can be taken as 0.3. T =0.4, ω E =0.6.

[0049] Furthermore, a power operation is performed with the temperature acceleration factor as the base and a preset temperature weight as the exponent to obtain the first calculation result. Then, a power operation is performed with the electrical stress acceleration factor as the base and a preset electrical stress weight as the exponent to obtain the second calculation result. Finally, a first product is calculated between the first and second calculation results, and this first product is used as the target lifetime acceleration factor for the target server component. Therefore, the expression for the target lifetime acceleration factor is as follows:

[0050] ;

[0051] Among them, AF 总 For target lifetime acceleration factor, AF T For temperature acceleration coefficient, ω T Preset temperature weights, AF EFor the electric stress acceleration coefficient, ω E As a preset electrical stress weight, and AF E For AF V or AF I .

[0052] In this way, weights can be set according to different server component types, making the final calculated target lifetime acceleration coefficient more compatible with the server component, thereby improving the accuracy of server component lifetime prediction.

[0053] Step S13: Convert the actual working time of the target server component according to the target lifetime acceleration factor to convert the actual working time into an equivalent aging time.

[0054] In this embodiment, the actual operating time of the target server component needs to be converted based on the calculated target lifetime acceleration factor to transform the actual operating time into an equivalent aging time. Specifically, a second product between the target lifetime acceleration factor and the actual operating time needs to be calculated, and this second product is used as the equivalent aging time corresponding to the actual operating time. In this way, the actual operating time of the target server component can be converted into the equivalent aging time under rated stress, thereby improving the accuracy of server component lifetime prediction.

[0055] Step S14: Estimate the remaining lifespan of the target server component based on the equivalent aging time to determine the remaining lifespan of the target server component.

[0056] In this embodiment, after obtaining the equivalent aging time, it is necessary to estimate the remaining lifespan of the target server component based on the obtained equivalent aging time to determine the remaining lifespan of the target server component. Specifically, it is necessary to calculate the sum between the equivalent aging time and the historical equivalent aging time to obtain the cumulative equivalent aging time. It should be noted that since the operating data of the server component is updated at regular intervals, it is necessary to summarize the equivalent aging time of the server component for each time period to obtain the cumulative equivalent aging time.

[0057] Furthermore, it is necessary to determine the rated lifespan of the target server component and the difference between the rated lifespan and the cumulative equivalent aging time. The ratio of this difference to the target lifespan acceleration factor is then used as the actual remaining lifespan of the target server component. In other words, if the operating stresses of the target component, such as temperature and electrical stress, remain at their current levels, the actual operating time corresponding to the remaining lifespan needs to be calculated based on the current target lifespan acceleration factor. If changes in operating stress are detected, such as increased temperature or voltage fluctuations, the target lifespan acceleration factor needs to be updated, and the component lifespan forecast needs to be recalculated. This allows for advance planning of component replacement based on the estimated server component lifespan, avoiding unexpected downtime.

[0058] In this embodiment, operational data of the target server component can be collected and preprocessed to obtain preprocessed operational data. Using the preprocessed operational data and a preset lifetime acceleration model, the temperature acceleration coefficient and electrical stress acceleration coefficient of the target server component are determined. Based on the temperature acceleration coefficient, electrical stress acceleration coefficient, and preset weights, the target lifetime acceleration coefficient of the target server component is determined. The actual operating time of the target server component is converted according to the target lifetime acceleration coefficient to convert the actual operating time into an equivalent aging time. The remaining lifetime of the target server component is estimated based on the equivalent aging time to determine the remaining lifetime of the target server component. Therefore, the method in this embodiment can preprocess the collected operational data of the server component, determine the temperature acceleration coefficient and electrical stress acceleration coefficient of the server component based on the obtained preprocessed operational data and a preset lifetime acceleration model, calculate the target lifetime acceleration coefficient of the target server component using preset weights and the above two parameters, convert the actual operating time of the target server component into an equivalent aging time using the target lifetime acceleration coefficient, and then estimate the remaining lifetime of the target server component using the equivalent aging time. In this way, on the one hand, the combined effects of temperature and electrical stress on server components can be considered, and the lifespan of server components can be comprehensively estimated through multi-dimensional stress to ensure the accuracy of the estimated time of failure of server components; on the other hand, weights corresponding to different server component types can be set according to different component types, so that the final calculated target lifespan acceleration coefficient is more matched with the server component, thereby improving the accuracy of server component lifespan estimation.

[0059] In a preferred embodiment, the obtained cumulative equivalent aging time needs to be used as the new historical equivalent aging time, and the process jumps to the step of collecting the operating data of the target server component based on the second preset time interval to perform the next round of server component lifespan estimation. Further, a preset index corresponding to the target server component needs to be determined based on its current lifespan stage, and the current lifespan stage of the target server component needs to be monitored based on its actual remaining lifespan. If a change in the current lifespan stage of the target server component is detected, the preset index is adjusted to obtain a new preset index corresponding to the changed lifespan stage. Specifically, since lifespan estimation needs to be performed at regular intervals, and the aging rates of the same batch of server components may differ, for each server component, the estimated actual remaining lifespan of the server component can be used to determine whether the server component is in the early, middle, or old stage of its lifespan, and the preset first index corresponding to the first preset lifespan acceleration model, the preset second index corresponding to the second preset lifespan acceleration model, and the preset third index corresponding to the third preset lifespan acceleration model can be dynamically adjusted according to each stage. Furthermore, the system can automatically trigger parameter optimization every 100 hours of accumulated data, ensuring that the model always matches the actual aging characteristics of the components. This allows for dynamic adjustment of the preset index corresponding to the lifespan acceleration model, thereby effectively guaranteeing the accuracy of server component lifespan predictions.

[0060] As a preferred embodiment, such as Figure 2 The diagram shows the system architecture for a server component lifespan prediction method. The lifespan prediction system includes a data acquisition module, a parameter preprocessing module, an acceleration factor calculation module, an equivalent time calculation module, a fault prediction module, and an early warning output module. The data acquisition module, integrated into the BMC, is used to collect the electrical stress parameters, temperature parameters, and actual operating time of the target server component in real time and obtain the component's rated parameters. The parameter preprocessing module converts the temperature parameters to Kelvin and determines the electrical stress acceleration factor, such as voltage or current, based on the component type. The acceleration factor calculation module calculates the temperature acceleration factor AF based on a third preset lifespan acceleration model. T The electrical stress acceleration factor AF is calculated based on either the first or second preset lifetime acceleration model. E And calculate the total acceleration coefficient AF 总 The equivalent time calculation module is used to calculate the actual working time and the total acceleration coefficient AF. 总 The equivalent aging time is calculated and accumulated to obtain the cumulative equivalent aging time; the fault prediction module is used to calculate the remaining life based on the rated component life and the cumulative equivalent aging time, and combines the total acceleration factor AF. 总The module estimates the actual remaining operating time and failure time. The early warning output module sends the estimated failure time and remaining lifespan information to the server management platform. When the remaining lifespan is lower than a preset threshold, such as 10% of the rated total lifespan, an early warning is triggered.

[0061] As a preferred embodiment, such as Figure 3 The diagram shows the specific processing flowchart for the server component lifespan prediction method. Taking a real-world example, the target server component is selected as the server motherboard, which is an electrically stress-sensitive component with a rated operating voltage V0 = 12V and a rated operating temperature T0 = 40°C. (T) 0_K =313.15K); activation energy E a =0.8eV, preset first exponent n=6, rated life L0=70000h. Real-time operating data of this component collected by the BMC is: current operating voltage V=13V, operating temperature T=45℃. (T) 0_K =318.15K). Based on component characteristics and historical fault data, the weights are determined as follows: ω T =0.4 (temperature weight), ω E =0.6 (electrical stress weight). Based on the above parameters, the stress acceleration coefficient can be calculated. The stress acceleration coefficient corresponding to this component is the temperature acceleration coefficient and the electrical stress acceleration coefficient. The calculated temperature acceleration coefficient is 1.576, and the electrical stress acceleration coefficient is 1.594. This means the aging rate at the current temperature is 1.576 times that at the rated temperature, and the aging rate at the current voltage is 1.594 times that at the rated voltage. The calculated target life acceleration coefficient is 1.618. This means that under the combined effect of the current temperature and voltage, the capacitor's aging rate is 1.618 times that under rated stress. In other words, one hour of operation is equivalent to 1.618 hours of aging under rated stress. Taking one month of operation as an example, the equivalent aging time is 1164.96 hours, and the remaining lifespan is 68835.04 hours. If the remaining lifespan is lower than the preset threshold, an alarm will be triggered.

[0062] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method.

[0063] See Figure 4 As shown, an embodiment of this application provides a server component lifespan prediction device, applied to a management controller, comprising:

[0064] Data acquisition module 11 is used to collect operating data of the target server components;

[0065] The first acceleration coefficient determination module 12 is used to determine the stress acceleration coefficients of the target server component using running data, a preset exponent corresponding to the target server component, and a preset lifetime acceleration model; the preset lifetime acceleration model is a model that obtains stress acceleration coefficients by exponentiation based on a preset exponent.

[0066] The second acceleration coefficient determination module 13 is used to determine the target lifetime acceleration coefficient of the target server component based on each stress acceleration coefficient and the corresponding preset weight.

[0067] The data conversion module 14 is used to convert the actual working time of the target server component according to the target lifetime acceleration factor, so as to convert the actual working time into the equivalent aging time.

[0068] The lifetime estimation module 15 is used to estimate the remaining lifetime of the target server component based on the equivalent aging time, so as to determine the remaining lifetime of the target server component.

[0069] In some embodiments, the data preprocessing module 11 may specifically include:

[0070] The data acquisition unit is used to acquire electrical stress parameters, temperature parameters, and working time parameters of the target server components in the target server based on a first preset time interval; the target server is the server where the management controller is located.

[0071] In some embodiments, the server component lifespan estimation device may further include:

[0072] The parameter selection unit is used to select either the operating voltage or the operating current as the target electrical stress parameter from the electrical stress parameters based on the component type of the target server component.

[0073] The parameter conversion unit is used to convert temperature parameters into Kelvin temperatures to obtain the target temperature parameters.

[0074] In some embodiments, the first acceleration coefficient determining module 12 may specifically include:

[0075] The rated parameter determination unit is used to determine the rated operating parameters of the target server components; the rated operating parameters include the rated operating voltage, rated operating current, and rated operating temperature.

[0076] The first feature parameter determination unit is used to input the target electrical stress parameter and the rated operating voltage into the first preset life acceleration model if the target electrical stress parameter is the operating voltage, so as to use the output of the first preset life acceleration model as the electrical stress acceleration coefficient of the target server component; the first preset life acceleration model is a life acceleration model based on voltage and a preset first exponent for life acceleration.

[0077] The second feature parameter determination unit is used to input the target electrical stress parameter and the rated operating current into the second preset life acceleration model if the target electrical stress parameter is the operating current, so as to use the output of the second preset life acceleration model as the electrical stress acceleration coefficient of the target server component; the second preset life acceleration model is a life acceleration model based on current and a preset second exponent for life acceleration.

[0078] The third characteristic parameter determination unit is used to input the target temperature parameter and the rated operating temperature into the third preset life acceleration model, so as to use the output of the third preset life acceleration model as the temperature acceleration coefficient of the target server component; the third preset life acceleration model is a life acceleration model based on temperature and a preset third index to accelerate life.

[0079] In some embodiments, the output of the first preset life acceleration model is a value obtained by exponentiation of the ratio between the operating voltage and the rated operating voltage; the output of the second preset life acceleration model is a value obtained by exponentiation of the ratio between the operating current and the rated operating current.

[0080] Among them, the preset first index and the preset second index are coefficients preset based on the component type.

[0081] In some embodiments, the preset third index is the product of the target ratio and the target difference; the target ratio is the ratio of the activation energy corresponding to the target server component to a preset constant; and the target difference is the difference between the reciprocal of the rated operating temperature and the reciprocal of the target temperature parameter.

[0082] In some embodiments, the second acceleration coefficient determining module 13 may specifically include:

[0083] The weight determination unit is used to determine the preset temperature weight and preset electrical stress weight corresponding to the target server component.

[0084] The data processing unit is used to perform a power operation with the temperature acceleration coefficient as the base and the preset temperature weight as the exponent to obtain a first calculation result, and to perform a power operation with the electric stress acceleration coefficient as the base and the preset electric stress weight as the exponent to obtain a second calculation result.

[0085] The acceleration factor determination unit is used to calculate the first product between the first calculation result and the second calculation result, so as to use the first product as the target lifetime acceleration factor of the target server component.

[0086] In some embodiments, the data conversion module 14 may specifically include:

[0087] The equivalent aging time determination unit is used to calculate the second product between the target life acceleration coefficient and the actual working time, so as to use the second product as the equivalent aging time corresponding to the actual working time.

[0088] In some embodiments, the lifetime estimation module 15 may specifically include:

[0089] The cumulative equivalent aging time calculation unit is used to calculate the sum between the equivalent aging time and the historical equivalent aging time to obtain the cumulative equivalent aging time.

[0090] The difference calculation unit is used to determine the rated component life corresponding to the target server component and to determine the difference between the rated component life and the cumulative equivalent aging time.

[0091] The actual remaining lifetime determination unit is used to take the ratio between the difference result and the target lifetime acceleration factor as the actual remaining lifetime of the target server component.

[0092] In some embodiments, the server component lifespan estimation device may further include:

[0093] The step jump unit is used to take the cumulative equivalent aging time as the new historical equivalent aging time, and jump to the step of collecting the operating data of the target server component based on the second preset time interval, so as to perform the next round of server component life prediction.

[0094] In some embodiments, the server component lifespan estimation device may further include:

[0095] An index determination unit is used to determine the preset index corresponding to the target server component based on the current lifespan stage of the target server component;

[0096] A lifespan stage monitoring unit is used to monitor whether the current lifespan stage of the target server component has changed based on the actual remaining lifespan.

[0097] An index adjustment unit is used to adjust the preset index if a change in the current lifespan stage of the target server component is detected, so as to obtain a new preset index corresponding to the changed lifespan stage.

[0098] For a description of the features in the embodiment corresponding to the server component lifespan prediction device, please refer to the relevant description of the embodiment corresponding to the server component lifespan prediction method, which will not be repeated here.

[0099] Embodiments of this application also provide an electronic device, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the server component lifetime estimation method embodiments described above.

[0100] Embodiments of this application also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the steps in any of the above-described server component lifetime estimation method embodiments when it runs.

[0101] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0102] Embodiments of this application also provide a computer program product, which includes a computer program that, when executed by a processor, implements the steps in any of the above-described server component lifetime estimation method embodiments.

[0103] Embodiments of this application also provide another computer program product, including a non-volatile computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps in any of the above-described server component lifetime estimation method embodiments.

[0104] Those skilled in the art will further 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, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. 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.

[0105] The foregoing has provided a detailed description of a server component lifespan estimation and electronic device provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only intended to help understand the method and core ideas of this application. It should be noted that those skilled in the art can make various improvements and modifications to this application without departing from its principles, and these improvements and modifications also fall within the protection scope of the claims of this application.

Claims

1. A method of server component life prediction, the method comprising: The application is applied to a management controller, comprising: collecting running data of a target server component; determining stress acceleration coefficients of the target server component by using the running data, preset indexes corresponding to the target server component, and a preset life acceleration model; the preset life acceleration model is a model for performing power operation based on the preset indexes to obtain the stress acceleration coefficients; determining a target life acceleration coefficient of the target server component based on the stress acceleration coefficients and corresponding preset weights; transforming an actual working time of the target server component according to the target life acceleration coefficient to transform the actual working time into an equivalent aging time; estimating a remaining life of the target server component based on the equivalent aging time to determine the remaining life of the target server component; wherein the collecting of the running data of the target server component comprises: collecting an electrical stress parameter, a temperature parameter, and a working time parameter of the target server component in a target server based on a first preset time interval; the target server is a server where the management controller is located; correspondingly, before the determining of the stress acceleration coefficients of the target server component by using the running data, the preset indexes corresponding to the target server component, and the preset life acceleration model, the method further comprises: selecting a working voltage or a working current as a target electrical stress parameter from the electrical stress parameter based on a component type of the target server component; converting the temperature parameter into a Kelvin temperature to obtain a target temperature parameter; wherein the determining of the stress acceleration coefficients of the target server component by using the running data, the preset indexes corresponding to the target server component, and the preset life acceleration model comprises: determining rated running parameters of the target server component; the rated running parameters include a rated working voltage, a rated working current, and a rated working temperature; if the target electrical stress parameter is the working voltage, inputting the target electrical stress parameter and the rated working voltage into a first preset life acceleration model to take an output corresponding to the first preset life acceleration model as an electrical stress acceleration coefficient of the target server component; the first preset life acceleration model is a life acceleration model for life acceleration based on a voltage and a preset first index; if the target electrical stress parameter is the working current, inputting the target electrical stress parameter and the rated working current into a second preset life acceleration model to take an output corresponding to the second preset life acceleration model as an electrical stress acceleration coefficient of the target server component; the second preset life acceleration model is a life acceleration model for life acceleration based on a current and a preset second index; inputting the target temperature parameter and the rated working temperature into a third preset life acceleration model to take an output corresponding to the third preset life acceleration model as a temperature acceleration coefficient of the target server component; the third preset life acceleration model is a life acceleration model for life acceleration based on a temperature and a preset third index.

2. The server component life estimation method of claim 1, wherein An output of the first preset life acceleration model is a value obtained by raising a ratio between the working voltage and the rated working voltage to a preset first index as an exponent; and an output of the second preset life acceleration model is a value obtained by raising a ratio between the working current and the rated working voltage to a preset second index as an exponent. The preset first index and the preset second index are coefficients preset based on the component type.

3. The server component life estimation method of claim 1, wherein, An output of the third preset life acceleration model is a value obtained by raising a natural constant to a preset third index as an exponent. The preset third index is a product of a target ratio and a target difference value; the target ratio is a ratio between a corresponding activation energy of the target server component and a preset constant; and the target difference value is a difference between a reciprocal of the rated working temperature and a reciprocal of the target temperature parameter.

4. The server component life estimation method of claim 1, wherein, The determining the target life acceleration coefficient of the target server component based on the stress acceleration coefficients and corresponding preset weights comprises: determining a preset temperature weight and a preset electrical stress weight corresponding to the target server component; performing an exponent operation on the temperature acceleration coefficient as a base and the preset temperature weight as an index to obtain a first operation result, and performing an exponent operation on the electrical stress acceleration coefficient as a base and the preset electrical stress weight as an index to obtain a second operation result; calculating a first product between the first operation result and the second operation result, and taking the first product as the target life acceleration coefficient of the target server component.

5. The server component life estimation method of claim 1, wherein, The converting the actual working time of the target server component according to the target life acceleration coefficient to convert the actual working time into an equivalent aging time comprises: calculating a second product between the target life acceleration coefficient and the actual working time, and taking the second product as the equivalent aging time corresponding to the actual working time.

6. The server component life estimation method according to any one of claims 1 to 5, characterized by, The estimating the remaining life of the target server component based on the equivalent aging time to determine the remaining life of the target server component comprises: calculating a sum value between the equivalent aging time and a historical equivalent aging time to obtain a cumulative equivalent aging time; determining a rated component life corresponding to the target server component, and determining a difference result between the rated component life and the cumulative equivalent aging time; taking a ratio between the difference result and the target life acceleration coefficient as an actual remaining life of the target server component.

7. The server component life estimation method of claim 6, wherein, After the estimating the remaining life of the target server component based on the equivalent aging time to determine the remaining life of the target server component, the method further comprises: taking the cumulative equivalent aging time as a new historical equivalent aging time, and jumping to the step of collecting the running data of the target server component based on a second preset time interval to perform a next round of server component life estimation.

8. The server component life estimation method of claim 6, wherein, Before the determining the stress acceleration coefficients of the target server component, the method further comprises: determining the preset index corresponding to the target server component based on a current life stage of the target server component; Correspondingly, the method further comprises: monitoring whether the current life stage of the target server component changes based on the actual remaining life; if it is monitored that the current life stage of the target server component changes, adjusting the preset index to obtain a new preset index corresponding to the changed life stage.

9. An electronic device, comprising: comprise: a memory for storing a computer program; a processor for executing the computer program to realize the steps of the server component life estimation method according to any one of claims 1 to 8.

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