Solid state disk fault detection method and device

Abstract

The invention relates to the technical field of solid state disks, and discloses a solid state disk fault detection method and device, and the method comprises the steps: obtaining an information tree of a target solid state disk in a running process; the information tree takes the target solid state disk as a root node, takes a memory block of the target solid state disk as a father node of the root node, and takes attribute information of the memory block as a leaf node of the father node; determining a detection result of each memory block in the target solid state disk based on a first similarity between each memory block in the target solid state disk and a corresponding preset fault memory block; if the detection result of the target memory block is in a fault state, positioning fault root cause information of the target memory block based on a second similarity between each piece of attribute information in the target memory block and corresponding preset fault attribute information; the target memory block is any memory block of the target solid state disk. According to the method, the fault root cause of the solid state disk can be quickly positioned, and an accurate decision is made for the solid state disk.

Description

Technical Field

[0001] The present invention relates to the technical field of solid state hard disks, and in particular to a solid state hard disk fault detection method and device thereof. Background Art

[0002] With the rapid development of information technology, solid state drives (SSDs) have been widely used in personal computers, servers, data centers, and other fields due to their advantages such as high-speed read and write performance, low power consumption, and shock resistance. However, the reliability problem of solid state drives is also becoming increasingly prominent. Therefore, it is necessary to detect solid state drive faults to ensure the normal operation of solid state drives. In the existing solid state drive fault detection process, a large non-directional fault detection model is often used to locate the fault of the solid state drive, as well as a fault detection method based on link call relationships and a fault detection method based on machine learning algorithms to locate the root cause of the fault. However, the large non-directional fault detection model requires large sample analysis, long sampling time, and complex algorithms, which is not conducive to the rapid location of solid state drive faults. The root causes of solid state drive faults obtained by the above fault detection methods all have large deviations, resulting in the inability to accurately analyze the root causes of solid state drive faults, and thus the inability to accurately perform solid state drive fault detection. Summary of the invention

[0003] The present invention provides a solid state hard disk fault detection method and device thereof, which are used to quickly locate the root cause of the solid state hard disk fault so as to quickly make an accurate decision on the solid state hard disk.

[0004] In a first aspect, the present invention provides a solid state drive fault detection method, comprising:

[0005] Obtaining an information tree of the target solid-state drive during operation; the information tree has the target solid-state drive as a root node, a memory block of the target solid-state drive as a parent node of the root node, and attribute information of the memory block as a leaf node of the parent node;

[0006] Determining a detection result of each memory block in the target solid-state hard disk based on a first similarity between each memory block in the target solid-state hard disk and its corresponding preset faulty memory block;

[0007] If the detection result of the target memory block is a fault state, the root cause information of the fault of the target memory block is located based on the second similarity between each attribute information in the target memory block and its corresponding preset fault attribute information; the target memory block is any memory block of the target solid state drive.

[0008] According to the solid state drive fault detection method provided by the present invention, the specific calculation formula of the first similarity is as follows:

[0009]

[0010] Among them, S(A, B i ) represents the first similarity, A represents the target memory block, B i represents the i-th preset fault memory block, n represents the number of preset fault memory blocks, represents the preset weight, f(·) represents the feature encoder of the memory block, which is pre-built based on the neural network, f(A) represents the feature value of the target memory block extracted based on the feature encoder, and f(B i ) represents the feature value of the i-th preset fault memory block extracted based on the feature encoder, indicating that sim(f(A), f(B i )) represents the difference between f(A) and f(B i ), exp represents the exponential function with the natural constant e as the base.

[0011] According to the solid state drive fault detection method provided by the present invention, the detection result of each memory block in the target solid state drive is determined based on the first similarity between each memory block in the target solid state drive and its corresponding preset faulty memory block, including:

[0012] If the first similarity of the target memory block is greater than a preset similarity, determining that the detection result of the target memory block is a fault state;

[0013] If the first similarity of the target memory block is less than or equal to a preset similarity, it is determined that the detection result of the target memory block is in a normal state.

[0014] According to the solid state drive fault detection method provided by the present invention, the specific calculation formula of the second similarity is as follows:

[0015]

[0016] Among them, P(u j , c j ) represents the second similarity of the jth attribute information in the target memory block, u j represents the jth preset fault attribute information, c j Indicates the jth attribute information in the target memory block. represents the average attribute value of the jth preset fault attribute information, U represents the set of preset fault attribute information, P(·) represents the attribute encoder of the attribute information, which is pre-built based on the neural network, and P(u j ) represents the attribute value of the j-th preset fault attribute information extracted based on the attribute encoder, P(c j) represents the attribute value of the jth attribute information in the target memory block extracted based on the attribute encoder, sim(P(u j ), P(c j )) represents P(u j ) and P(c j ), represents the attribute value of the associated attribute information of the j-th preset fault attribute information, represents the average attribute value of the j-th preset fault attribute information, Represents a preset attribute value. Obtain attribute values ​​of multiple fault causes of the jth preset fault attribute information from the historical fault attribute information, and determine the average of the attribute values ​​of the multiple fault causes as the average attribute value of the jth preset fault attribute information.

[0017] According to the solid state drive fault detection method provided by the present invention, after locating the fault root cause information of the target memory block, the method further includes:

[0018] Determine a repairability score based on the first similarity and the second similarity;

[0019] If the repairability score is greater than or equal to a preset threshold, determining that the target memory block is repairable;

[0020] If the repairability score is less than the preset threshold, it is determined that the target memory block is not repairable.

[0021] According to the solid state drive fault detection method provided by the present invention, the calculation formula for determining the repairability score based on the first similarity and the second similarity is as follows:

[0022] Q = α*S(A, B i )+(1-α)*P(u j , c j );

[0023] Wherein, Q represents the repairability score, α represents the fault weight value, and generally, the fault weight value α can be set to 0.55-0.8.

[0024] In a second aspect, the present invention further provides a solid state hard disk fault detection device, comprising:

[0025] An acquisition module, used to acquire an information tree of a target solid-state drive during operation; the information tree has the target solid-state drive as a root node, a memory block of the target solid-state drive as a parent node of the root node, and attribute information of the memory block as a leaf node of the parent node;

[0026] A first fault detection module, configured to determine a detection result of each memory block in the target solid-state hard disk based on a first similarity between each memory block in the target solid-state hard disk and its corresponding preset faulty memory block;

[0027] The second fault detection module is used to locate the root cause information of the target memory block if the detection result of the target memory block is a fault state based on the second similarity between each attribute information in the target memory block and its corresponding preset fault attribute information; the target memory block is any memory block of the target solid state drive.

[0028] In a third aspect, the present invention further provides an electronic device, comprising: a memory for storing a computer software program; a processor for reading and executing the computer software program, thereby implementing the solid state drive fault detection method as described in the first aspect above.

[0029] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium, wherein the storage medium stores a computer software program, and when the computer software program is executed by a processor, the solid-state hard disk fault detection method as described in the first aspect above is implemented.

[0030] In a fifth aspect, the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the solid state drive fault detection method as described in the first aspect above.

[0031] The solid-state hard disk fault detection method provided by the present invention, during the fault detection process, unfolds the operation process of the solid-state hard disk in the form of an information tree, so that the information of each memory block in the solid-state hard disk and the various attribute information under each memory block can be clearly obtained, and then based on the first similarity between each memory block and its corresponding preset fault memory block, and the second similarity between each attribute information in the memory block and its corresponding preset fault attribute information, the root cause information of the fault of the memory block is located, so that the root cause of the fault of the solid-state hard disk can be quickly located, so as to quickly make an accurate decision on the solid-state hard disk. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 is a flow chart of a solid state drive fault detection method provided by an embodiment of the present invention;

[0033] Figure 2 is a schematic diagram of the structure of an information tree provided by an embodiment of the present invention;

[0034] Figure 3 is a structural schematic diagram of a solid state hard disk fault detection device provided by an embodiment of the present invention;

[0035] Figure 4A schematic diagram of an electronic device according to an embodiment of the present invention;

[0036] Figure 5 A schematic diagram of an embodiment of a computer-readable storage medium provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0038] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0039] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration or explanation". Any embodiment described as "for example" in the present invention is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any technician in the field to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in the present invention.

[0040] Optional, see Figure 1 , Figure 1 : is a flow chart of the solid state hard disk fault detection method provided by the present invention. The execution subject of the solid state hard disk fault detection method provided by the present invention can be a fault detection device. Therefore, the solid state hard disk fault detection method includes the following steps:

[0041] Step 10, obtaining the information tree of the target solid state drive during operation.

[0042] In an embodiment of the present invention, during the operation of the solid-state hard disk, the memory blocks of the solid-state hard disk and the attribute information of the memory blocks are expanded in the form of an information tree. Therefore, it can be understood that the information tree is a node tree with the target solid-state hard disk as the root node, the memory block of the target solid-state hard disk as the parent node of the root node, and the attribute information of the memory block as the leaf node of the parent node.

[0043] In one embodiment, the target solid state drive X includes memory block 1, memory block 2 and memory block 3, each memory block includes a storage module, a control module, a cache module, a power management module and an interface module. Therefore, the target solid state drive X is taken as the root node, the memory block 1, the memory block 2 and the memory block 3 are taken as the parent nodes under the root node branch, and the storage module, the control module, the cache module, the power management module and the interface module are taken as the leaf nodes under the parent node branch. The information tree is as follows: Figure 2 As shown, Figure 2 It is a schematic diagram of the structure of the information tree provided by an embodiment of the present invention.

[0044] Therefore, when the solid-state hard disk is in operation, the fault detection device obtains the information tree of any target solid-state hard disk in operation.

[0045] Step 20, determining a detection result of each memory block in the target solid state drive based on a first similarity between each memory block in the target solid state drive and its corresponding preset faulty memory block.

[0046] Further, the fault detection device calculates a first similarity between each memory block in the target solid-state hard disk and its corresponding preset fault memory block, and determines a detection result of each memory block in the target solid-state hard disk according to the first similarity between each memory block in the target solid-state hard disk and its corresponding preset fault memory block, wherein the specific calculation formula of the first similarity is as follows:

[0047]

[0048] Among them, S(A, B i ) represents the first similarity, A represents the target memory block, B i represents the i-th preset fault memory block, n represents the number of preset fault memory blocks, represents the preset weight, f(·) represents the feature encoder of the memory block, which is pre-built based on the neural network, f(A) represents the feature value of the target memory block extracted based on the feature encoder, and f(B i ) represents the feature value of the i-th preset fault memory block extracted based on the feature encoder, indicating that sim(f(A), f(B i )) represents the difference between f(a) and f(B I), exp represents the exponential function with the natural constant e as the base.

[0049] In one embodiment, based on a first similarity between each memory block in the target solid-state drive and its corresponding preset faulty memory block, a detection result of each memory block in the target solid-state drive is determined, including: if the first similarity of the target memory block is greater than a preset similarity, the fault detection device determines that the detection result of the target memory block is a faulty state, wherein the preset similarity is set according to the type of the solid-state drive.

[0050] Furthermore, if the first similarity of the target memory block is less than or equal to the preset similarity, the fault detection device determines that the detection result of the target memory block is normal, wherein the target memory block is any memory block of the target solid state drive.

[0051] Step 30: If the detection result of the target memory block is a fault state, the fault root cause information of the target memory block is located based on the second similarity between each attribute information in the target memory block and its corresponding preset fault attribute information.

[0052] Further, if it is determined that the detection result of the target memory block is a fault state, the fault detection device calculates the second similarity between each attribute information in the target memory block and its corresponding preset fault attribute information, and locates the fault root cause information of the target memory block according to the second similarity between each attribute information in the target memory block and its corresponding preset fault attribute information. In one embodiment, the specific calculation formula of the second similarity is as follows:

[0053]

[0054] Among them, P(u j , c j ) represents the second similarity of the jth attribute information in the target memory block, u j represents the jth preset fault attribute information, c j Indicates the jth attribute information in the target memory block. represents the average attribute value of the jth preset fault attribute information, U represents the set of preset fault attribute information, P(·) represents the attribute encoder of the attribute information, which is pre-built based on the neural network, and P(u j ) represents the attribute value of the j-th preset fault attribute information extracted based on the attribute encoder, P(c j ) represents the attribute value of the jth attribute information in the target memory block extracted based on the attribute encoder, sim(P(u j ), P(c j )) represents P(u j ) and P(c j), represents the attribute value of the associated attribute information of the j-th preset fault attribute information, represents the average attribute value of the j-th preset fault attribute information, Represents a preset attribute value. Obtain attribute values ​​of multiple fault causes of the jth preset fault attribute information from the historical fault attribute information, and determine the average of the attribute values ​​of the multiple fault causes as the average attribute value of the jth preset fault attribute information.

[0055] Therefore, it can be understood that the fault detection device determines the attribute information with a second similarity greater than a preset similarity as the fault root cause information of the memory block of the target solid state drive, wherein the preset similarity is set according to the type of the target solid state drive.

[0056] Continuing with the above embodiment, if the first similarity of the memory block 1 of the target solid state drive X is greater than or equal to the preset similarity, and the second similarity of the storage module and the cache module in the memory block 1 is greater than or equal to the preset similarity, then it is determined that the root cause information of the failure of the memory block 1 is the failure of the storage module and the cache module.

[0057] In the process of fault detection, the embodiment of the present invention unfolds the operation process of the solid-state hard disk in the form of an information tree, so that the information of each memory block in the solid-state hard disk and the various attribute information under each memory block can be clearly obtained, and then the root cause information of the fault of the memory block is located according to the first similarity between each memory block and its corresponding preset fault memory block, and the second similarity between each attribute information in the memory block and its corresponding preset fault attribute information, so that the root cause of the fault of the solid-state hard disk can be quickly located, so as to quickly make an accurate decision on the solid-state hard disk.

[0058] In one embodiment, after locating the root cause information of the target memory block, the method further includes:

[0059] Based on the first similarity and the second similarity, a repairability score is determined; if the repairability score is greater than or equal to a preset threshold, the target memory block is determined to be repairable; if the repairability score is less than the preset threshold, the target memory block is determined to be unrepairable.

[0060] Optionally, the fault detection device calculates a repairability score of the target memory block according to the first similarity and the second similarity. The specific calculation formula of the repairability score is as follows:

[0061] Q = α*S(A, B i )+(1-α)*P(u j , c j )

[0062] Among them, Q represents the repairability score, α represents the fault weight value, and generally, the fault weight value α can be set to 0.55-0.8.

[0063] Further, the fault detection device determines whether the repairable score is greater than or equal to a preset threshold, wherein the preset threshold is set according to the type of the target solid-state drive. Further, if it is determined that the repairable score is greater than or equal to the preset threshold, the fault detection device determines that the target memory block is repairable, that is, the fault problem of the target memory block is minor and can be repaired. Further, if the repairable score is less than the preset threshold, the fault detection device determines that the target memory block is unrepairable, that is, the fault problem of the target memory block is major and cannot be repaired, that is, the target memory block is completely damaged.

[0064] The embodiment of the present invention determines the repairability score through the first similarity and the second similarity, and determines the repairability of the target memory block according to the repairability score, so that an accurate decision can be made on the solid state drive.

[0065] The solid state drive fault detection device provided by the present invention is described below. The solid state drive fault detection device described below and the solid state drive fault detection method described above can be referred to each other.

[0066] See also Figure 3 , Figure 3 A schematic diagram of the structure of a solid state drive fault detection device provided by an embodiment of the present invention, the solid state drive fault detection device comprises:

[0067] The acquisition module 310 is used to acquire an information tree of the target solid state drive during operation; the information tree has the target solid state drive as a root node, the memory block of the target solid state drive as a parent node of the root node, and the attribute information of the memory block as a leaf node of the parent node;

[0068] A first fault detection module 320, configured to determine a detection result of each memory block in the target solid state drive based on a first similarity between each memory block in the target solid state drive and its corresponding preset faulty memory block;

[0069] The second fault detection module 330 is used to locate the root cause information of the target memory block if the detection result of the target memory block is a fault state based on the second similarity between each attribute information in the target memory block and its corresponding preset fault attribute information; the target memory block is any memory block of the target solid state drive.

[0070] The solid-state hard disk fault detection device provided by the present invention, during the fault detection process, unfolds the operation process of the solid-state hard disk in the form of an information tree, so that the information of each memory block in the solid-state hard disk and the various attribute information under each memory block can be clearly obtained, and then based on the first similarity between each memory block and its corresponding preset fault memory block, and the second similarity between each attribute information in the memory block and its corresponding preset fault attribute information, the root cause information of the fault of the memory block is located, so that the root cause of the fault of the solid-state hard disk can be quickly located, so as to quickly make an accurate decision on the solid-state hard disk.

[0071] In one embodiment, the specific calculation formula of the first similarity is as follows:

[0072]

[0073] Among them, S(A, B i ) represents the first similarity, A represents the target memory block, B i represents the i-th preset fault memory block, n represents the number of preset fault memory blocks, represents the preset weight, f(·) represents the feature encoder of the memory block, which is pre-built based on the neural network, f(A) represents the feature value of the target memory block extracted based on the feature encoder, and f(B i ) represents the feature value of the i-th preset fault memory block extracted based on the feature encoder, indicating that sim(f(A), f(B i )) represents the difference between f(A) and f(B i ), exp represents the exponential function with the natural constant e as the base.

[0074] In one embodiment, the first fault detection module 320 is further configured to:

[0075] If the first similarity of the target memory block is greater than the preset similarity, determining that the detection result of the target memory block is a fault state;

[0076] If the first similarity of the target memory block is less than or equal to the preset similarity, it is determined that the detection result of the target memory block is in a normal state.

[0077] In one embodiment, the specific calculation formula of the second similarity is as follows:

[0078]

[0079] Among them, P(u j , c j ) represents the second similarity of the jth attribute information in the target memory block, u j represents the jth preset fault attribute information, c jIndicates the jth attribute information in the target memory block. represents the average attribute value of the jth preset fault attribute information, U represents the set of preset fault attribute information, P(·) represents the attribute encoder of the attribute information, which is pre-built based on the neural network, and P(u j ) represents the attribute value of the j-th preset fault attribute information extracted based on the attribute encoder, P(c j ) represents the attribute value of the jth attribute information in the target memory block extracted based on the attribute encoder, sim(P(u j ), P(c j )) represents P(u j ) and P(c j ), represents the attribute value of the associated attribute information of the j-th preset fault attribute information, represents the average attribute value of the j-th preset fault attribute information, Represents a preset attribute value. Obtain attribute values ​​of multiple fault causes of the jth preset fault attribute information from the historical fault attribute information, and determine the average of the attribute values ​​of the multiple fault causes as the average attribute value of the jth preset fault attribute information.

[0080] In one embodiment, the solid state drive fault detection device is further used for:

[0081] Determining a repairability score based on the first similarity and the second similarity;

[0082] If the repairability score is greater than or equal to the preset threshold, the target memory block is determined to be repairable;

[0083] If the repairability score is less than a preset threshold, the target memory block is determined to be unrepairable.

[0084] In one embodiment, the calculation formula of the repairability score is as follows:

[0085] Q = α*S(A, B i )+(1-α)*P(u j , c j );

[0086] Wherein, Q represents the repairability score, α represents the fault weight value, and generally, the fault weight value α can be set to 0.55-0.8.

[0087] See also Figure 4 , Figure 4 Schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 4As shown, an embodiment of the present invention provides an electronic device 400, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, the following steps are implemented:

[0088] Obtaining an information tree of the target solid state drive during operation; the information tree has the target solid state drive as a root node, a memory block of the target solid state drive as a parent node of the root node, and attribute information of the memory block as a leaf node of the parent node;

[0089] Determine a detection result of each memory block in the target solid-state hard disk based on a first similarity between each memory block in the target solid-state hard disk and its corresponding preset faulty memory block;

[0090] If the detection result of the target memory block is a fault state, the root cause information of the target memory block is located based on the second similarity between each attribute information in the target memory block and its corresponding preset fault attribute information; the target memory block is any memory block of the target solid state drive.

[0091] In one embodiment, the specific calculation formula of the first similarity is as follows:

[0092]

[0093] Among them, S(A, B i ) represents the first similarity, A represents the target memory block, B i represents the i-th preset fault memory block, n represents the number of preset fault memory blocks, represents the preset weight, f(·) represents the feature encoder of the memory block, which is pre-built based on the neural network, f(A) represents the feature value of the target memory block extracted based on the feature encoder, and f(B i ) represents the feature value of the i-th preset fault memory block extracted based on the feature encoder, indicating that sim(f(A), f(B i )) represents the difference between f(A) and f(B i ), exp represents the exponential function with the natural constant e as the base.

[0094] Determining a detection result of each memory block in the target solid-state drive based on a first similarity between each memory block in the target solid-state drive and its corresponding preset faulty memory block includes:

[0095] If the first similarity of the target memory block is greater than the preset similarity, determining that the detection result of the target memory block is a fault state;

[0096] If the first similarity of the target memory block is less than or equal to the preset similarity, it is determined that the detection result of the target memory block is in a normal state.

[0097] In one embodiment, the specific calculation formula of the second similarity is as follows:

[0098]

[0099] Among them, P(u j , c j ) represents the second similarity of the jth attribute information in the target memory block, u j represents the jth preset fault attribute information, c j Indicates the jth attribute information in the target memory block. represents the average attribute value of the jth preset fault attribute information, U represents the set of preset fault attribute information, P(·) represents the attribute encoder of the attribute information, which is pre-built based on the neural network, and P(u j ) represents the attribute value of the j-th preset fault attribute information extracted based on the attribute encoder, P(c j ) represents the attribute value of the jth attribute information in the target memory block extracted based on the attribute encoder, sim(P(u j ), P(c j )) represents P(u j ) and P(c j ), represents the attribute value of the associated attribute information of the j-th preset fault attribute information, represents the average attribute value of the j-th preset fault attribute information, Represents a preset attribute value. Obtain attribute values ​​of multiple fault causes of the jth preset fault attribute information from the historical fault attribute information, and determine the average of the attribute values ​​of the multiple fault causes as the average attribute value of the jth preset fault attribute information.

[0100] After locating the root cause of the target memory block, the following also applies:

[0101] Determining a repairability score based on the first similarity and the second similarity;

[0102] If the repairability score is greater than or equal to the preset threshold, the target memory block is determined to be repairable;

[0103] If the repairability score is less than a preset threshold, the target memory block is determined to be unrepairable.

[0104] In one embodiment, based on the first similarity and the second similarity, a calculation formula for determining the repairability score is as follows:

[0105] Q = α*S(A, B i )+(1-α)*P(u j , c j );

[0106] Wherein, Q represents the repairability score, α represents the fault weight value, and generally, the fault weight value α can be set to 0.55-0.8.

[0107] See also Figure 5 , Figure 5 Schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present invention. Figure 5 As shown, this embodiment provides a computer-readable storage medium 400, on which a computer program 411 is stored. When the computer program 411 is executed by a processor, the following steps are implemented:

[0108] Obtaining an information tree of the target solid state drive during operation; the information tree has the target solid state drive as a root node, a memory block of the target solid state drive as a parent node of the root node, and attribute information of the memory block as a leaf node of the parent node;

[0109] Determine a detection result of each memory block in the target solid-state hard disk based on a first similarity between each memory block in the target solid-state hard disk and its corresponding preset faulty memory block;

[0110] If the detection result of the target memory block is a fault state, the root cause information of the target memory block is located based on the second similarity between each attribute information in the target memory block and its corresponding preset fault attribute information; the target memory block is any memory block of the target solid state drive.

[0111] On the other hand, the present invention further provides a computer program product, the computer program product includes a computer program, the computer program can be stored in a non-transitory computer-readable storage medium, when the computer program is executed by a processor, the computer can execute the solid state drive fault detection method provided by the above methods, the method includes:

[0112] Obtaining an information tree of the target solid state drive during operation; the information tree has the target solid state drive as a root node, a memory block of the target solid state drive as a parent node of the root node, and attribute information of the memory block as a leaf node of the parent node;

[0113] Determine a detection result of each memory block in the target solid-state hard disk based on a first similarity between each memory block in the target solid-state hard disk and its corresponding preset faulty memory block;

[0114] If the detection result of the target memory block is a fault state, the root cause information of the target memory block is located based on the second similarity between each attribute information in the target memory block and its corresponding preset fault attribute information; the target memory block is any memory block of the target solid state drive.

[0115] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0116] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0117] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (apparatus), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0118] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0119] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1The steps for the functions specified in one or more boxes.

[0120] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0121] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A solid state hard disk fault detection method, characterized in that: include: Obtaining an information tree of the target solid-state drive during operation; the information tree has the target solid-state drive as a root node, a memory block of the target solid-state drive as a parent node of the root node, and attribute information of the memory block as a leaf node of the parent node; Determining a detection result of each memory block in the target solid-state hard disk based on a first similarity between each memory block in the target solid-state hard disk and its corresponding preset faulty memory block; If the detection result of the target memory block is a fault state, locating the fault root cause information of the target memory block based on the second similarity between each attribute information in the target memory block and its corresponding preset fault attribute information; The target memory block is any memory block of the target solid state drive.

2. The solid state drive fault detection method according to claim 1, characterized in that: The specific calculation formula of the first similarity is as follows: Among them, S(A, B i ) represents the first similarity, A represents the target memory block, B i represents the i-th preset fault memory block, n represents the number of preset fault memory blocks, represents the preset weight, f(·) represents the feature encoder of the memory block, which is pre-built based on the neural network, f(A) represents the feature value of the target memory block extracted based on the feature encoder, and f(B i ) represents the feature value of the i-th preset fault memory block extracted based on the feature encoder, indicating that sim(f(A), f(B i )) represents the difference between f(A) and f(B i ), exp represents the exponential function with the natural constant e as the base.

3. The solid state drive fault detection method according to claim 1, characterized in that: The step of determining the detection result of each memory block in the target solid-state hard disk based on the first similarity between each memory block in the target solid-state hard disk and its corresponding preset faulty memory block comprises: If the first similarity of the target memory block is greater than a preset similarity, determining that the detection result of the target memory block is a fault state; If the first similarity of the target memory block is less than or equal to a preset similarity, it is determined that the detection result of the target memory block is in a normal state.

4. The solid state drive fault detection method according to claim 1, characterized in that: The specific calculation formula of the second similarity is as follows: Among them, P(u j , c j ) represents the second similarity of the jth attribute information in the target memory block, u j represents the jth preset fault attribute information, c j Indicates the jth attribute information in the target memory block. represents the average attribute value of the jth preset fault attribute information, U represents the set of preset fault attribute information, P(·) represents the attribute encoder of the attribute information, which is pre-built based on the neural network, and P(u j ) represents the attribute value of the j-th preset fault attribute information extracted based on the attribute encoder, P(c j ) represents the attribute value of the jth attribute information in the target memory block extracted based on the attribute encoder, sim(P(u j ), P(c j )) represents P(u j ) and P(c j ), represents the attribute value of the associated attribute information of the j-th preset fault attribute information, represents the average attribute value of the j-th preset fault attribute information, Represents a preset attribute value. Obtain attribute values ​​of multiple fault causes of the jth preset fault attribute information from the historical fault attribute information, and determine the average of the attribute values ​​of the multiple fault causes as the average attribute value of the jth preset fault attribute information.

5. The solid state drive fault detection method according to any one of claims 1 to 4, characterized in that: After locating the fault root cause information of the target memory block, the method further includes: Determine a repairability score based on the first similarity and the second similarity; If the repairability score is greater than or equal to a preset threshold, determining that the target memory block is repairable; If the repairability score is less than the preset threshold, it is determined that the target memory block is not repairable.

6. The solid state drive fault detection method according to claim 5, characterized in that: The calculation formula for determining the repairability score based on the first similarity and the second similarity is as follows: Q=α*S(A,B i )+(1-α)*P(u j ,c j ); Among them, Q represents the repairability score, α represents the fault weight value, and generally, the fault weight value α can be set to 0.55-0.

8.

7. A solid state hard disk fault detection device, characterized in that: include: An acquisition module, used to acquire an information tree of a target solid-state drive during operation; the information tree has the target solid-state drive as a root node, a memory block of the target solid-state drive as a parent node of the root node, and attribute information of the memory block as a leaf node of the parent node; A first fault detection module, configured to determine a detection result of each memory block in the target solid-state hard disk based on a first similarity between each memory block in the target solid-state hard disk and its corresponding preset faulty memory block; A second fault detection module, configured to locate the fault root cause information of the target memory block based on a second similarity between each attribute information in the target memory block and its corresponding preset fault attribute information if the detection result of the target memory block is a fault state; The target memory block is any memory block of the target solid state drive.

8. An electronic device, characterized in that: include: Memory for storing computer software programs; A processor is used to read and execute the computer software program, thereby implementing the solid state drive fault detection method as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium, characterized in that: The storage medium stores a computer software program, and when the computer software program is executed by the processor, the solid state drive fault detection method according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the solid state drive failure detection method according to any one of claims 1 to 6 is implemented.

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