Server-based hard disk common mode failure analysis method, device, equipment and medium

Abstract

The application relates to the technical field of magnetic disk, and discloses a hard disk common mode fault analysis method, device, equipment and medium based on a server, which comprises the following steps: determining a fault-related component according to pre-collected type and fault mode data of the hard disk of the server; determining a main fault factor based on the fault-related component; analyzing the main fault factor, establishing a fault model corresponding to the main fault factor, and determining a common mode fault factor of the server based on the fault model. According to the scheme, the type and fault mode of the hard disk of the server are classified, the hard disk common mode fault is considered, the hard disk working environment and the use mode are deeply analyzed, potential fault factors are effectively identified, corresponding fault models are respectively established according to the analysis of the main fault factors, the common mode failure risk is analyzed, the ability of identifying potential problems is improved, and a data basis is provided for subsequent targeted preventive measures.

Description

Technical Field

[0001] This invention relates to the field of disk technology, and specifically to a server-based hard disk common-mode fault analysis method, apparatus, device, and medium. Background Technology

[0002] With the rapid development of emerging industries such as cloud computing, artificial intelligence, and big data, the server industry has also entered a phase of rapid growth. More and more companies and industries are building their own data centers, leading to the widespread adoption of rack-mount servers. Among these servers, the hard drive is a critical component, and its reliability is paramount. According to statistics from a cloud service provider, the average annual failure rate for HDDs (Hard Disk Drives) is approximately 1.4%, while the average annual failure rate for SSDs (Solid State Drives) is around 1%. As the primary carrier of data storage, hard drive failures can lead to business delays or interruptions, system freezes or crashes, and even irrecoverable loss of critical data.

[0003] In related technologies, hard drive failure prediction often focuses on predicting the failure or lifespan of a single hard drive. This is mainly achieved by monitoring the hard drive's SMART (Self-Monitoring Analysis and Reporting Technology) parameters and using offline trained algorithms and models to predict the timing or probability of future hard drive failures. However, these technologies lack sufficient analysis of the specific causes of failures, especially when dealing with batch failures of hard drives from the same customer or data center. They lack analysis of common-mode failure risks, the ability to identify potential problems, and cannot provide strong support for failure prevention measures, R&D design, and testing improvement. Summary of the Invention

[0004] In view of this, the present invention provides a server-based hard disk common-mode fault analysis method, apparatus, device, and medium to solve the technical problem of lack of common-mode risk analysis and potential problem identification.

[0005] In a first aspect, the present invention provides a server-based hard disk common-mode fault analysis method, the method comprising: determining fault-related components based on pre-collected hard disk type and fault mode data of the server; determining major fault factors based on the fault-related components; analyzing the major fault factors, establishing a fault model corresponding to the major fault factors, and determining the common-mode fault factors of the server under test based on the fault model.

[0006] In conjunction with the first aspect, in one possible implementation of the first aspect, the fault-related components are determined according to the type and failure mode of the server's hard drive, including: determining the first module, the second module, and the third module based on the type of the server's hard drive and the functional category of the hard drive components; and determining the fault-related components corresponding to the first module, the second module, and the third module respectively based on the failure modes of the first module, the second module, and the third module.

[0007] In conjunction with the first aspect, in one possible implementation of the first aspect, the main failure factors are determined based on the fault-related components, including: determining the influencing factors of the fault-related components corresponding to each module and the correlation between the influencing factors based on the fault-related components corresponding to the first module, the second module, and the third module respectively; and determining the main failure factors of the corresponding module based on the correlation and influencing factors corresponding to each module respectively.

[0008] In conjunction with the first aspect, in one possible implementation of the first aspect, the main failure factors of the corresponding module are determined based on the correlation and influencing factors of each module, including: screening the influencing factors corresponding to the first module based on the correlation with the influencing factors of the first module, and determining the main influencing factors among them; analyzing the main influencing factors and determining the first influencing factor that generates the main influencing factors; and determining the main failure factors corresponding to the first module based on the main influencing factors and the first influencing factor.

[0009] In conjunction with the first aspect, in one possible implementation of the first aspect, the main failure factors of the corresponding module are determined based on the correlation and influencing factors of each module, including: based on the correlation with the influencing factors of the second module, analyzing the influencing factors corresponding to the second module, and determining the main failure factors corresponding to the second module.

[0010] In conjunction with the first aspect, in one possible implementation of the first aspect, the main failure factors of the corresponding module are determined based on the correlation and influencing factors of each module, including: determining environmental factors that are consistent with the working environment of the server based on the correlation with the influencing factors of the third module; and determining the main failure factors corresponding to the third module based on the environmental factors.

[0011] In conjunction with the first aspect, in one possible implementation of the first aspect, the analysis of the main failure factors and the establishment of failure models corresponding to the main failure factors include: analyzing the main failure factors and determining the types of parameter information corresponding to the main failure factors; in response to the parameter information corresponding to the main failure factors having corresponding thresholds, establishing failure judgment models corresponding to the main failure factors based on the corresponding thresholds; and in response to the parameter information corresponding to the main failure factors not having corresponding thresholds, establishing failure physical models corresponding to the main failure factors based on the parameter information corresponding to the main failure factors.

[0012] In conjunction with the first aspect, in one possible implementation of the first aspect, the parameter information corresponding to the main failure factors includes: the read / write head flight altitude, and the step of establishing a fault determination model corresponding to the main failure factors based on the corresponding thresholds includes:

[0013] A fault diagnosis model corresponding to the flight altitude of the magnetic head is established using the following formula:

[0014]

[0015] in, H FAFH-T Indicates the threshold for the flight altitude of the magnetic head. Indicates the first i The first disk j The flight altitude of each magnetic head Indicates the first i The average flight altitude of all heads on a single disk. a This indicates the deviation of the parameter.

[0016] In conjunction with the first aspect, in one possible implementation of the first aspect, the parameter information corresponding to the main fault factor includes: the number of bad sectors, and the step of establishing fault judgment models corresponding to the main fault factors based on corresponding thresholds includes:

[0017] A fault determination model corresponding to the number of bad sectors is established using the following formula:

[0018]

[0019] in, H Glist-T This indicates the threshold for the number of bad sectors. Indicates the first i The number of bad sectors on each disk. Indicates the first i Disks T The number of bad sectors at time 2. Indicates the first i Disks T The number of bad sectors at time 1. bThis indicates the deviation of the parameter.

[0020] In conjunction with the first aspect, in one possible implementation of the first aspect, the parameter information corresponding to the main fault factor includes: high-frequency vibration, and the step of establishing fault judgment models corresponding to the main fault factors based on corresponding thresholds includes:

[0021] A fault diagnosis model corresponding to high-frequency vibration is established using the following formula:

[0022]

[0023] in, H fre-T Indicates the high-frequency vibration threshold. This indicates the vibration frequency of the hard disk.

[0024] In conjunction with the first aspect, in one possible implementation of the first aspect, the parameter information corresponding to the main failure factor includes: impact, and the step of establishing a failure determination model corresponding to the main failure factor based on the corresponding threshold includes:

[0025] A fault determination model corresponding to the impact is established using the following formula:

[0026]

[0027] in, H G-T Indicates the impact threshold. Indicates disk shock G value.

[0028] In conjunction with the first aspect, in one possible implementation of the first aspect, the parameter information corresponding to the main fault factor includes: voltage, and the step of establishing a fault physical model corresponding to the main fault factor based on the parameter information corresponding to the main fault factor includes:

[0029] A physical model for the degradation of the floating gate oxide layer is established using the following formula:

[0030]

[0031] in, OF TDDB This represents the physical model of the fault corresponding to the degradation of the floating gate oxide layer. r Represents electric field acceleration. v h This represents the actual voltage of the floating gate oxide layer. v n Indicates the standard voltage of the floating gate oxide layer. t ox This indicates the thickness of the oxide layer on the floating gate.

[0032] In conjunction with the first aspect, in one possible implementation of the first aspect, the parameter information corresponding to the main fault factor includes: current, and the step of establishing a fault physical model corresponding to the main fault factor based on the parameter information corresponding to the main fault factor includes:

[0033] The fault physics model corresponding to hot carrier injection is established using the following formula:

[0034]

[0035] in, OF HCI This represents the physical model of the fault corresponding to hot carrier injection. I subh Indicates the actual substrate current. I subn This indicates the substrate standard current.

[0036] In conjunction with the first aspect, in one possible implementation of the first aspect, the parameter information corresponding to the main failure factor includes: temperature, and the step of establishing a fault physical model corresponding to the main failure factor based on the parameter information corresponding to the main failure factor includes:

[0037] A physical model of the failure corresponding to solder joint fatigue is established using the following formula:

[0038]

[0039] in, OF T This represents the physical model of the failure corresponding to solder joint fatigue. T n This indicates the disk's operating temperature when the environmental dimension is c. T h This indicates the actual operating temperature of the disk.

[0040] In conjunction with the first aspect, in one possible implementation of the first aspect, the step of determining the common-mode failure factor of the server under test based on the failure model includes: obtaining parameter information corresponding to the main failure factor of the server under test; and determining the common-mode failure factor of the server under test based on the parameter information and the corresponding failure model.

[0041] In conjunction with the first aspect, in one possible implementation of the first aspect, obtaining parameter information corresponding to the main fault factors of the server under test includes: obtaining parameter information corresponding to the main fault factors of the server under test based on offline and / or online methods.

[0042] Secondly, the present invention provides a server-based hard disk common-mode fault analysis device, the device comprising: a component determination module, used to determine fault-related components based on pre-collected hard disk type and fault mode data of the server; a factor determination module, used to determine the main fault factors based on the fault-related components; and a model building module, used to analyze the main fault factors, build a fault model corresponding to the main fault factors, and determine the common-mode fault factors of the server under test based on the fault model.

[0043] In conjunction with the second aspect, in one possible implementation of the first aspect, the apparatus further includes: an information acquisition module for acquiring parameter information corresponding to the main fault factors of the server under test; and a common-mode factor determination module for determining the common-mode fault factors of the server under test based on the parameter information and the corresponding fault model.

[0044] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the server-based hard disk common-mode fault analysis method of the first aspect or any corresponding embodiment described above.

[0045] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the server-based hard disk common-mode fault analysis method of the first aspect or any corresponding embodiment described above.

[0046] The technical solution of this invention has the following advantages:

[0047] This invention provides a server-based hard drive common-mode failure analysis method, apparatus, device, and medium. The method utilizes pre-collected data on server hard drive types and failure modes to identify fault-related components and key failure factors. Through analysis of these key failure factors, a corresponding failure model is established, and based on the failure model, the common-mode failure factors of the server under test are determined. In this process, by classifying the server's hard drive types and failure modes, and focusing on common-mode failures, a thorough analysis of the hard drive's operating environment and usage patterns effectively identifies potential failure factors. Based on the analysis of key failure factors, corresponding failure models are established for each key failure factor, thereby enabling the analysis of common-mode failure risks, improving the ability to identify potential problems, and providing a data foundation for subsequent targeted preventative measures. Furthermore, the established failure models corresponding to the key failure factors provide strong support for improving fault prevention measures, R&D design, and testing processes, thereby further enhancing server reliability and stability, ensuring business continuity and data security. Attached Figure Description

[0048] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0049] Figure 1 This is a flowchart illustrating a server-based hard disk common-mode fault analysis method according to an embodiment of the present invention.

[0050] Figure 2 This is a schematic diagram of the change in magnetic head height according to an embodiment of the present invention;

[0051] Figure 3 This is a schematic diagram illustrating the change in the number of bad sectors on a disk according to an embodiment of the present invention;

[0052] Figure 4 This is a structural block diagram of a server-based hard disk common-mode fault analysis device according to an embodiment of the present invention;

[0053] Figure 5 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0055] According to an embodiment of the present invention, a server-based hard disk common-mode fault analysis method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0056] This embodiment provides a server-based hard disk common-mode fault analysis method, such as... Figure 1 As shown, the method includes the following steps:

[0057] S101. Based on the pre-collected data on the type and failure mode of the server's hard drives, identify the components related to the failure.

[0058] Specifically, determining the fault-related components based on the type and failure mode of the server's hard drives means identifying the fault-related components from the perspective of common hard drive failures. This involves classifying the server's hard drives by type and failure mode to identify the common components involved in batch hard drive failures within the same customer or data center.

[0059] S102. Based on the fault-related components, determine the main fault factors.

[0060] Specifically, determining the main failure factors based on fault-related components means, after identifying the fault-related components, analyzing the influencing factors of faulty components under each category of hard drives and the relationships between these factors to determine the main failure factors. In other words, from the perspective of hard drive common-mode failure, determining the main factors causing failures in the server operating environment under different categories.

[0061] S103. Analyze the main failure factors, establish a failure model corresponding to the main failure factors, and determine the common mode failure factors of the server under test based on the failure model.

[0062] Specifically, analyzing the main failure factors and establishing corresponding failure models means creating a separate failure model for each main failure factor. This allows the server's hard drive to identify related problems when facing common failure issues, providing strong support for improving fault prevention measures, R&D design, and testing processes. Ultimately, this enhances the server's reliability and stability, ensuring business continuity and data security.

[0063] This invention provides a method, apparatus, device, and medium for server-based hard drive common-mode failure analysis. The method utilizes the type and failure mode of the server's hard drives to identify fault-related components and key failure factors. Through analysis of these key failure factors, a corresponding failure model is established. In this process, by classifying the server's hard drive types and failure modes, and focusing on common-mode failures, a thorough analysis of the hard drive's operating environment and usage patterns effectively identifies potential failure factors. Based on the analysis of the key failure factors, corresponding failure models are established for each factor, thereby enabling the analysis of common-mode failure risks, improving the ability to identify potential problems, and providing a data foundation for subsequent targeted preventative measures. Furthermore, the established failure models corresponding to the key failure factors provide strong support for improving fault prevention measures, R&D design, and testing processes, thereby further enhancing server reliability and stability, ensuring business continuity, and data security.

[0064] In one alternative implementation, the fault-related components are determined based on the type and failure mode of the server's hard drive, including:

[0065] Based on the type of hard drive in the server and the functional categories of the hard drive components, the first module, the second module, and the third module are determined; based on the failure modes of the first module, the second module, and the third module, the fault-related components corresponding to the first module, the second module, and the third module are determined respectively.

[0066] Specifically, server hard drives include HDDs and SSDs, and their functions include control and storage modules. Table 1 below exemplarily illustrates the process of classifying server hard drives based on their component functions.

[0067] Table 1

[0068]

[0069] Specifically, the first module can be an HDD storage module, the second module can be an SSD storage module, and the third module can be a control module. This embodiment does not impose specific limitations on this and can be configured according to actual operating conditions. It should be understood that the PCBA plays a primary control role in both the HDD and SSD control modules; therefore, the HDD and SSD control modules are combined into a single module, namely the third module. For ease of explanation, the following description will use the first module as the HDD storage module, the second module as the SSD storage module, and the third module as the control module.

[0070] Specifically, the failure modes of the first module include: head damage and bad sectors on the disk; the failure modes of the second module include: charge changes in the double-layer floating gate NMOS transistor of the flash memory chip and degradation of the floating gate oxide layer; and the failure modes of the third module include: solder joint fatigue of the PCBA.

[0071] Specifically, based on the failure modes of the first module, determining the fault-related components corresponding to the first module means determining the corresponding components that can cause the corresponding failure modes. That is, the fault-related component corresponding to head damage is the head, and the fault-related component corresponding to bad sectors on the disk is the disk.

[0072] Specifically, based on the fault modes of the second module, determining the fault-related components corresponding to the second module means determining the corresponding components that can cause the corresponding fault modes. That is, the fault-related components corresponding to the charge change and the degradation of the floating gate oxide layer of the flash memory chip double-layer floating gate NMOS transistor are: NMOS-like double-layer floating gate MOS transistors.

[0073] Specifically, based on the failure modes of the third module, determining the fault-related components corresponding to the third module means determining the corresponding components that can cause the corresponding failure modes. That is, the fault-related components corresponding to the solder joint fatigue of the PCBA are the solder joints in the PCBA.

[0074] In one alternative implementation, determining the main failure factors based on fault-related components includes:

[0075] Based on the fault-related components corresponding to the first, second, and third modules respectively, determine the influencing factors of the fault-related components for each module and the correlation between the influencing factors; based on the correlation and influencing factors corresponding to each module respectively, determine the main fault factors of the corresponding module.

[0076] Specifically, determining the influencing factors of the fault-related components corresponding to each module and the correlation between these factors, based on the fault-related components corresponding to the first, second, and third modules respectively, means determining the influencing factors of the fault-related components corresponding to each module and determining the correlation between these factors.

[0077] Specifically, the influencing factors of the fault-related components corresponding to the first module include: head flight height, number of bad sectors, and bit error rate. Among these, head flight height (FAFH Passive Clearance) is a key indicator measuring the distance between the head and the disk platter. Abnormal flight height may cause the head to contact the platter, affecting the stability of data reading. The number of bad sectors (G-list) refers to the areas of the disk platter that cannot be read or written due to physical damage or magnetic degradation. An increase in bad sectors may directly affect the reliability and data integrity of the hard drive. The bit error rate reflects the frequency of erroneous bits during data transmission or storage; a high bit error rate usually indicates a decrease in the reliability of the storage medium. The relationship between head flight height, number of bad sectors, and bit error rate is a promoting relationship; that is, abnormal head flight height promotes an increase in the number of bad sectors, which in turn promotes an increase in the bit error rate. Figure 2 , Figure 3 As shown, the facilitative relationship between abnormal head flight altitude and abnormal number of bad sectors is illustrated.

[0078] Specifically, the influencing factors of the fault-related components corresponding to the second module include: TDDB (Time Dependent Breakdown) and Hot Carrier Injection. TDDB is a lossy breakdown that occurs after a certain period of time when the applied electric field is lower than the breakdown voltage of the gate oxide layer. Hot carrier injection is the injection of high-energy carriers into the gate through the oxide layer under the action of an electric field, leading to the degradation of the transistor's electrical characteristics. The relationship between TDDB and hot carrier injection is competitive.

[0079] Specifically, the influencing factors of the fault-related components corresponding to the third module include: solder joint thermal fatigue and mechanical fatigue. Solder joint thermal fatigue occurs because solder joints, PCBs, and components have different coefficients of thermal expansion. Temperature changes around the solder joint can cause stress accumulation, leading to fatigue failure. Mechanical fatigue occurs because continuous vibration causes repeated mechanical stress on the solder joint, resulting in the growth of microcracks and ultimately poor contact or complete fracture. The correlation between solder joint thermal fatigue and mechanical fatigue is cumulative damage.

[0080] In one optional implementation, the main failure factors of each module are determined based on the correlation and influencing factors corresponding to each module, including:

[0081] Based on the correlation with the influencing factors of the first module, the influencing factors corresponding to the first module are screened, and the main influencing factors are identified; the main influencing factors are analyzed to identify the first influencing factor that generates the main influencing factors; based on the main influencing factors and the first influencing factor, the main failure factors corresponding to the first module are identified.

[0082] Specifically, since the relationship between head flight altitude, number of bad sectors and bit error rate is a promoting one, that is, abnormal head flight altitude promotes an increase in the number of bad sectors, which in turn promotes an increase in bit error rate, abnormal head flight altitude should be regarded as the main influencing factor when screening the influencing factors corresponding to the first module.

[0083] Specifically, abnormal head flight altitude malfunctions are usually caused by internal particulate contamination in the HDD or by external mechanical stress. Regarding internal particulate contamination, since the distance between the head and the disk is approximately 5-10 nm, fine particles can easily impact the head under the influence of the high-speed rotating disk, causing abnormal head flight altitude. Currently, HDDs are mainly sealed helium disks, and particulate contamination is affected by the manufacturer's manufacturing process; monitoring methods for particulate contamination are lacking, and the probability of its occurrence is relatively low. External mechanical stress refers to high-frequency noise or vibration causing head resonance or external impact, and this has a relatively high probability of occurrence. Therefore, the primary influencing factor is high-frequency vibration or impact.

[0084] Specifically, determining the main fault factors corresponding to the first module based on the main influencing factors and the first influencing factor means taking the main influencing factors and the first influencing factor together as the main fault factors corresponding to the first module. That is, the main fault factors corresponding to the first module include: abnormal head flight altitude, abnormal number of bad sectors, abnormal high-frequency vibration, and abnormal impact.

[0085] In one optional implementation, the main failure factors of each module are determined based on the correlation and influencing factors corresponding to each module, including:

[0086] Based on the correlation between the factors affecting the second module and the factors affecting the second module, the main failure factors corresponding to the second module are analyzed and determined.

[0087] Specifically, the relationship between TDDB (Temporally Targeted Deposition) and reactive thermal carriers is competitive. The NMOS-like double-layer floating-gate MOSFETs used in SSD flash memory chips serve as the basic storage cells, and their write and erase operations rely on electron injection and extraction from the floating gate layer. The write operation involves applying a positive voltage to the control electrode to allow electrons to pass through the insulating layer into the floating gate layer, while the erase operation involves applying a positive voltage to the substrate to extract electrons from the floating gate layer. The read operation determines the stored data by detecting the floating gate layer voltage (i.e., the number of electrons). For example, in TLC (Triple-Level Cell) flash memory, each storage cell can store three bits of information, meaning it has eight different threshold voltage states to represent eight different data states. Because TLC flash memory requires extremely high voltage control precision, any problem leading to electron leakage or injection into the insulating layer can result in data errors. Degradation of the floating gate oxide layer can cause electron leakage from the insulating layer, typically due to physical and chemical changes in the oxide material under long-term electric field conditions. Hot carrier injection occurs when high-energy electrons are injected into the insulating layer under a high electric field. This can lead to interface trap formation and oxide layer degradation during long-term device operation. These two phenomena compete with each other in TLC flash memory because they both affect the stability of electrons in the floating gate layer, thus impacting data storage and retrieval. Therefore, the main failure factors corresponding to the second module include floating gate oxide layer degradation and hot carrier injection.

[0088] In one optional implementation, the main failure factors of each module are determined based on the correlation and influencing factors corresponding to each module, including:

[0089] Based on the correlation between the factors affecting the third module, environmental factors that are consistent with the server's working environment are identified; based on the environmental factors, the main failure factors corresponding to the third module are identified.

[0090] Specifically, the relationship between solder joint thermal fatigue and mechanical fatigue is one of cumulative damage, namely thermal fatigue caused by temperature changes and vibration fatigue caused by vibration. Solder joint thermal fatigue refers to the fatigue damage caused by cyclic thermal stress due to changes in ambient temperature and the component's own workload during operation. This is because the different coefficients of thermal expansion between the PCB and the electronic component lead to cracks in the solder joint. These cracks propagate along the interface between the solder and the pad, and between the component and the solder, ultimately resulting in solder joint fracture.

[0091] Specifically, vibration fatigue refers to fatigue damage to solder joints caused by repeated strain of the solder joint material under periodic mechanical vibration. This fatigue damage is usually caused by the periodic bending deformation of PCBs and electronic components under vibration, resulting in stress on the solder joints. The stress level is related to the load intensity and frequency.

[0092] Specifically, based on the correlation between the factors influencing the third module, the environmental factors that are consistent with the working environment of the server are determined by the correlation between thermal fatigue and mechanical fatigue of solder joints as damage accumulation, and the temperature and vibration factors that are consistent with the working environment of the server are determined.

[0093] Specifically, both thermal fatigue and vibration fatigue failure mechanisms of solder joints lead to fatigue damage, eventually resulting in cracks and ruptures. The relationship between them is that the damage accumulates. In a stable working environment like a server, where the environment is usually well-controlled in a computer room, the probability of vibration is low. Therefore, thermal fatigue is often the main cause of failure. Thus, the main failure factor corresponding to the third module is thermal fatigue of solder joints.

[0094] In one optional implementation, the main failure factors are analyzed, and a failure model corresponding to the main failure factors is established, including:

[0095] Analyze the main failure factors and determine the types of parameter information corresponding to the main failure factors; in response to the parameter information corresponding to the main failure factors having corresponding thresholds, establish failure judgment models corresponding to the main failure factors based on the corresponding thresholds; in response to the parameter information corresponding to the main failure factors not having corresponding thresholds, establish failure physical models corresponding to the main failure factors based on the parameter information corresponding to the main failure factors.

[0096] Specifically, analyzing the main failure factors and determining the type of parameter information corresponding to the main failure factors means that after determining the main failure factors of the corresponding modules, collecting the parameter information corresponding to the main failure factors, and establishing different types of failure models according to the type of parameter information. The types of failure models include: failure determination models and failure physical models.

[0097] Specifically, the parameter information corresponding to the main failure factors are as follows: abnormal head flight altitude corresponds to head flight altitude, abnormal number of bad sectors corresponds to number of bad sectors, abnormal high-frequency vibration corresponds to high-frequency vibration, abnormal impact corresponds to impact, floating gate oxide layer degradation corresponds to voltage, hot carrier injection corresponds to current, and solder joint thermal fatigue corresponds to temperature.

[0098] In one optional implementation, the parameter information corresponding to the main failure factor includes: the read / write head flight altitude, and the step of establishing a failure judgment model corresponding to the main failure factor based on the corresponding threshold includes:

[0099] A fault diagnosis model corresponding to the flight altitude of the magnetic head is established using the following formula:

[0100]

[0101] in, HFAFH-T Indicates the threshold for the flight altitude of the magnetic head. Indicates the first i The first disk j The flight altitude of each magnetic head Indicates the first i The average flight altitude of all heads on a single disk. a This indicates the deviation of the parameter.

[0102] Specifically, H FAFH-T The parameter deviation is usually determined by the characteristics of the HDD and can be selected according to the actual operating conditions. For example, it can be 95 angstroms or other values. The parameter deviation is used to indicate the parameter differences between different heads and different HDDs. a It can be 10%, 15% or other values, which can be selected according to the actual working conditions. This embodiment does not make a specific limitation on this.

[0103] In one optional implementation, the parameter information corresponding to the main fault factor includes: the number of bad sectors, and the step of establishing fault judgment models corresponding to the main fault factors based on corresponding thresholds includes:

[0104] A fault determination model corresponding to the number of bad sectors is established using the following formula:

[0105]

[0106] in, H Glist-T This indicates the threshold for the number of bad sectors. Indicates the first i The number of bad sectors on each disk. Indicates the first i Disks T The number of bad sectors at time 2. Indicates the first i Disks T The number of bad sectors at time 1. b This indicates the deviation of the parameter.

[0107] Specifically, H Glist-T Also determined by the characteristics of HDDs, the appropriate value can be selected based on actual operating conditions, such as 9000 or other values. b To represent the time dimension, it is usually in hours, for example, when the sampling period is 24 hours. b The value is usually set to 1. This embodiment does not impose a specific limitation on this value and can be set according to the actual working conditions.

[0108] In one optional implementation, the parameter information corresponding to the main fault factor includes: high-frequency vibration, and the step of establishing fault judgment models corresponding to the main fault factor based on the corresponding thresholds includes:

[0109] A fault diagnosis model corresponding to high-frequency vibration is established using the following formula:

[0110]

[0111] in, H fre-T Indicates the high-frequency vibration threshold. This indicates the vibration frequency of the hard disk.

[0112] Specifically, This information is typically obtained from sensors mounted on the back panel. H fre-T Typically, when the RV test corresponds to an impact of 5% or more on the HDD performance, the high-frequency vibration response is monitored to determine the impact. This is a vibration range and there may be multiple ranges. This embodiment does not make a specific limitation on this, such as 6% or 4% or more.

[0113] In one optional implementation, the parameter information corresponding to the main failure factor includes: impact, and the step of establishing a failure judgment model corresponding to the main failure factor based on the corresponding threshold includes:

[0114] A fault determination model corresponding to the impact is established using the following formula:

[0115]

[0116] in, H G-T Indicates the impact threshold. Indicates disk shock G value.

[0117] Specifically, This information is typically obtained from sensors mounted on the back panel. H G-T Typically, during a power-on impact test, the impact G value corresponds to an impact of 5% or more on the HDD. This embodiment does not specify a particular value, such as 6% or 4% or more.

[0118] In one optional implementation, the parameter information corresponding to the main fault factor includes: voltage, and the step of establishing a fault physical model corresponding to the main fault factor based on the parameter information corresponding to the main fault factor includes:

[0119] A physical model for the degradation of the floating gate oxide layer is established using the following formula:

[0120]

[0121] in, OF TDDB This represents the physical model of the fault corresponding to the degradation of the floating gate oxide layer. r Represents electric field acceleration. v h This represents the actual voltage of the floating gate oxide layer. v n Indicates the standard voltage of the floating gate oxide layer. t ox This indicates the thickness of the oxide layer on the floating gate.

[0122] Specifically, r When representing electric field acceleration, values ​​are typically taken as 1.8 for silicon dioxide, 1.3 for silicon nitride, and 1.1 for high-k dielectrics. v h When representing the actual voltage of the floating gate oxide layer, only values ​​greater than 1.2 times are typically extracted. v n The corresponding value is not specifically limited in this embodiment, such as 1.3 times or more than 1.5 times.

[0123] In one optional implementation, the parameter information corresponding to the main fault factor includes: current, and the step of establishing a fault physical model corresponding to the main fault factor based on the parameter information corresponding to the main fault factor includes:

[0124] The fault physics model corresponding to hot carrier injection is established using the following formula:

[0125]

[0126] in, OF HCI This represents the physical model of the fault corresponding to hot carrier injection. I subh Indicates the actual substrate current. I subn This indicates the substrate standard current.

[0127] Specifically, I subh When representing the actual substrate current, only values ​​greater than 1.02 are typically extracted. I subn The corresponding value is not specifically limited in this embodiment, such as 1.01 times or 1.04 times or more.

[0128] In one optional implementation, the parameter information corresponding to the main failure factor includes: temperature, and the step of establishing a failure physical model corresponding to the main failure factor based on the parameter information corresponding to the main failure factor includes:

[0129] A physical model of the failure corresponding to solder joint fatigue is established using the following formula:

[0130]

[0131] in, OF T This represents the physical model of the failure corresponding to solder joint fatigue. T n This indicates the disk's operating temperature when the environmental dimension is c. T h This indicates the actual operating temperature of the disk.

[0132] Specifically, the ambient temperature c is generally selected as 25 degrees Celsius. T h Only temperatures reaching 60 degrees Celsius are extracted. This embodiment does not specifically limit this. For example, temperature values ​​of 26, 30, or other values ​​can be selected, and temperatures reaching 50, 65, or other values ​​can be extracted.

[0133] In one optional implementation, the step of determining the common-mode failure factor of the server under test based on the failure model includes:

[0134] Obtain parameter information corresponding to the main failure factors of the server under test; Based on the parameter information and the corresponding failure model, determine the common mode failure factors of the server under test.

[0135] Specifically, the parameter information corresponding to the main failure factors is detailed in the relevant descriptions of the above embodiments, and will not be repeated here.

[0136] Specifically, determining the common-mode failure factor of the server under test based on parameter information and corresponding fault models means inputting the acquired parameter information into the corresponding fault models respectively, thereby determining the common-mode failure factor of the server under test through their respective fault models. This can provide strong support for the improvement of fault prevention measures, R&D design and testing processes, thereby further improving the reliability and stability of the server and ensuring business continuity and data security.

[0137] In one optional implementation, obtaining parameter information corresponding to the main failure factors of the server under test includes:

[0138] The parameter information corresponding to the main failure factors of the test server is obtained through offline and / or online methods.

[0139] This embodiment also provides a server-based hard disk common-mode fault analysis device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0140] This embodiment provides a server-based hard disk common-mode fault analysis device, such as... Figure 4 As shown, it includes:

[0141] The component determination module 201 is used to determine the fault-related components based on the pre-collected data on the type and failure mode of the server's hard drives. For details, please refer to the description of step S101 in the above embodiments, which will not be repeated here.

[0142] The factor determination module 202 is used to determine the main fault factors based on fault-related components. For details, please refer to the description of step S102 in the above embodiments, which will not be repeated here.

[0143] The model building module 203 is used to analyze the main failure factors, establish failure models corresponding to the main failure factors, and determine the common-mode failure factors of the server under test based on the failure models. For details, please refer to the relevant description of step S103 in the above embodiments, which will not be repeated here.

[0144] In one alternative embodiment, the apparatus further includes:

[0145] The information acquisition module is used to acquire parameter information corresponding to the main fault factors of the server under test; the common-mode factor determination module is used to determine the common-mode fault factors of the server under test based on the parameter information and the corresponding fault model. For details, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0146] In this embodiment, the server-based hard disk common-mode fault analysis device is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0147] This invention also provides a computer device having the above-described features. Figure 4 The device shown is a server-based hard disk common-mode fault analysis device.

[0148] Please see Figure 5 , Figure 5This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 5 As shown, the computer device includes one or more processors 301, memory 302, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 3 Take processor 301 as an example.

[0149] Processor 301 may be a central processing unit, a network processor, or a combination thereof. Processor 301 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0150] The memory 302 stores instructions executable by at least one processor 301 to cause the at least one processor 301 to perform the method shown in the above embodiments.

[0151] Memory 302 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, memory 302 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, memory 302 may optionally include memory remotely located relative to processor 301, and this remote memory may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0152] The memory 302 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 302 may also include combinations of the above types of memory. The computer device also includes a communication interface 303 for communicating with other devices or communication networks.

[0153] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0154] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A server-based hard disk common-mode fault analysis method, characterized in that, The method includes: Based on the pre-collected data on the type and failure mode of the server's hard drives, identify the components related to the failure; Based on the aforementioned fault-related components, the main fault factors are determined; Analyze the main failure factors, establish a failure model corresponding to the main failure factors, and determine the common mode failure factors of the server under test based on the failure model. The first module is an HDD storage module, the second module is an SSD storage module, and the third module is a control module. The determination of the main failure factors based on the fault-related components includes: Based on the fault-related components corresponding to the first module, the second module, and the third module, the influencing factors of the fault-related components of each module and the correlation between the influencing factors are determined. Based on the correlation and influencing factors corresponding to each module, the main failure factors of the corresponding module are determined. The step of determining the main failure factors of each module based on the correlation and influencing factors corresponding to each module includes: Based on the correlation between the influencing factors of the first module, influencing factors corresponding to the first module are screened, and the main influencing factors are determined. Analyze the main influencing factors and determine the first influencing factor that generates the main influencing factors; Based on the main influencing factors and the first influencing factor, the main failure factors corresponding to the first module are determined.

2. The method according to claim 1, characterized in that, The step of determining the fault-related components based on the type and failure mode of the server's hard drive includes: Based on the type of hard drive of the server and the functional category of the hard drive components, the first module, the second module, and the third module are determined; Based on the fault modes of the first module, the second module, and the third module, fault-related components corresponding to the first module, the second module, and the third module are determined respectively.

3. The method according to claim 1, characterized in that, The step of determining the main failure factors of each module based on the correlation and influencing factors corresponding to each module includes: Based on the correlation between the influencing factors of the second module, the influencing factors corresponding to the second module are analyzed to determine the main failure factors corresponding to the second module.

4. The method according to claim 1, characterized in that, The step of determining the main failure factors of each module based on the correlation and influencing factors corresponding to each module includes: Based on the correlation between the influencing factors in the third module, environmental factors that are consistent with the working environment of the server are determined; Based on the aforementioned environmental factors, the main failure factors corresponding to the third module are determined.

5. The method according to claim 1, characterized in that, The analysis of the main failure factors and the establishment of failure models corresponding to the main failure factors include: Analyze the main failure factors to determine the type of parameter information corresponding to the main failure factors; In response to the parameter information corresponding to the main fault factors having corresponding thresholds, fault determination models corresponding to the main fault factors are established based on the corresponding thresholds. In response to the fact that the parameter information corresponding to the main fault factor does not have a corresponding threshold, a fault physical model corresponding to the main fault factor is established based on the parameter information corresponding to the main fault factor.

6. The method according to claim 5, characterized in that, The parameter information corresponding to the main failure factors includes: the magnetic head flight altitude. The steps of establishing fault judgment models corresponding to the main failure factors based on the corresponding thresholds include: A fault determination model corresponding to the flight altitude of the magnetic head is established using the following formula: in, H FAFH-T Indicates the threshold for the flight altitude of the magnetic head. Indicates the first i The first disk j The flight altitude of each magnetic head Indicates the first i The average flight altitude of all heads on a single disk. a This indicates the deviation of the parameter.

7. The method according to claim 5, characterized in that, The parameter information corresponding to the main fault factors includes: the number of bad sectors. The step of establishing fault judgment models corresponding to the main fault factors based on the corresponding thresholds includes: A fault determination model corresponding to the number of bad sectors is established using the following formula: in, H Glist-T This indicates the threshold for the number of bad sectors. Indicates the first i The number of bad sectors on each disk. Indicates the first i Disks T The number of bad sectors at time 2. Indicates the first i Disks T The number of bad sectors at time 1. b This indicates the deviation of the parameter.

8. The method according to claim 5, characterized in that, The parameter information corresponding to the main fault factors includes: high-frequency vibration. The step of establishing fault judgment models corresponding to the main fault factors based on corresponding thresholds includes: A fault determination model corresponding to the high-frequency vibration is established using the following formula: in, H fre-T Indicates the high-frequency vibration threshold. This indicates the vibration frequency of the hard disk.

9. The method according to claim 5, characterized in that, The parameter information corresponding to the main failure factor includes: impact. The step of establishing a failure judgment model corresponding to the main failure factor based on the corresponding threshold includes: A fault determination model corresponding to the impact is established using the following formula: in, H G-T Indicates the impact threshold. Indicates disk shock G value.

10. The method according to claim 5, characterized in that, The parameter information corresponding to the main fault factor includes: voltage. The step of establishing a fault physical model corresponding to the main fault factor based on the parameter information corresponding to the main fault factor includes: A physical model for the degradation of the floating gate oxide layer is established using the following formula: in, AF TDDB This represents the physical model of the fault corresponding to the degradation of the floating gate oxide layer. r Represents electric field acceleration. v h This represents the actual voltage of the floating gate oxide layer. v n Indicates the standard voltage of the floating gate oxide layer. t ox This indicates the thickness of the oxide layer on the floating gate.

11. The method according to claim 5, characterized in that, The parameter information corresponding to the main fault factor includes: current. The steps of establishing fault physical models corresponding to the main fault factors based on the parameter information of the main fault factors include: The fault physics model corresponding to hot carrier injection is established using the following formula: in, AF HCI This represents the physical model of the fault corresponding to hot carrier injection. I subh Indicates the actual substrate current. I subn This indicates the substrate standard current.

12. The method according to claim 5, characterized in that, The parameter information corresponding to the main failure factor includes: temperature. The step of establishing a failure physical model corresponding to the main failure factor based on the parameter information corresponding to the main failure factor includes: A physical model of the failure corresponding to solder joint fatigue is established using the following formula: in, AF T This represents the physical model of the failure corresponding to solder joint fatigue. T n This indicates the disk's operating temperature when the ambient temperature is c. T h This indicates the actual operating temperature of the disk.

13. The method according to claim 1, characterized in that, The step of determining the common-mode failure factor of the server under test based on the failure model includes: Obtain the parameter information of the server under test corresponding to the main fault factors; Based on the parameter information and the corresponding fault model, the common-mode fault factor of the server under test is determined.

14. The method according to claim 13, characterized in that, The step of obtaining the parameter information corresponding to the server under test and the main failure factor includes: The parameter information corresponding to the main fault factors of the test server is obtained through offline and / or online methods.

15. A server-based hard disk common-mode fault analysis device, characterized in that, The device includes: The component identification module is used to identify fault-related components based on pre-collected data on the type and failure mode of the server's hard drives. A factor determination module is used to determine the main failure factors based on the fault-related components. The first module is an HDD storage module, the second module is an SSD storage module, and the third module is a control module. Determining the main failure factors based on the fault-related components includes: determining the influencing factors of each module's corresponding fault-related components and the correlation between these factors, based on the fault-related components corresponding to the first module, the second module, and the third module respectively; determining the main failure factors of the corresponding module based on the correlation and the influencing factors for each module respectively; further determining the main failure factors of the corresponding module based on the correlation and the influencing factors for each module includes: filtering influencing factors corresponding to the first module based on the correlation between the influencing factors of the first module, and determining the main influencing factors; analyzing the main influencing factors to determine the first influencing factor that generates the main influencing factors; and determining the main failure factor corresponding to the first module based on the main influencing factors and the first influencing factor. The model building module is used to analyze the main failure factors, build a failure model corresponding to the main failure factors, and determine the common failure factors of the server under test based on the failure model.

16. The apparatus according to claim 15, characterized in that, The device further includes: The information acquisition module is used to acquire parameter information of the server under test corresponding to the main fault factors; The common mode factor determination module is used to determine the common mode fault factor of the server under test based on the parameter information and the corresponding fault model.

17. A computer device, characterized in that, include: A memory and a processor are interconnected, the memory storing computer instructions, and the processor executing the computer instructions to perform the server-based hard disk common-mode fault analysis method according to any one of claims 1 to 14.

18. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the server-based hard disk common-mode fault analysis method according to any one of claims 1 to 14.

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