Disk failure prediction method, apparatus and device and computer readable storage medium

Abstract

The invention discloses a disk failure prediction method, which comprises the following steps: obtaining statistical feature sets of n statistical time points before the current time point, wherein each statistical feature set is obtained by calculating the SMART records in the statistical time window corresponding to each statistical time and N is a positive integer greater than 1; generating a statistical characteristic matrix by using the statistical characteristic set of n statistical moments; inputting the statistical characteristic matrix into the pre-trained disk fault prediction modelto predict the current disk state through the prediction model. It can be seen that the method generates a statistical characteristic matrix according to the SMART records before the current time so as to more accurately represent the characteristics of the disk, and further predicts the statistical characteristic matrix through a disk failure prediction model, thereby improving the accuracy of disk prediction. The invention also discloses a disk fault prediction apparatus and device and a computer readable storage medium, which can also realize the above technical effects.

Description

Technical field [0001] The present invention relates to the technical field of disk failure prediction, and more specifically, to a disk failure prediction method, device, equipment and computer-readable storage medium. Background technique [0002] Disk SMART (Self-Monitoring Analysis and Reporting Technology), namely "Self-Monitoring Analysis and Reporting Technology", monitors and monitors the operation of hard disk hardware such as heads, platters, motors, and circuits through detection instructions in the hard disk hardware. recording. The disk status can be detected through the recorded disk SMART information. The SMART information of a disk is usually collected by time. At present, when a disk failure is predicted based on the SMART information of the disk, only the current SMART value of the disk is analyzed, and the prediction effect is not accurate. [0003] Therefore, how to use the SMART information of the disk to accurately predict the disk is a problem that needs to...

AI Technical Summary

Problems solved by technology

The SMART information of the disk is usually collected by time. Currently, when predicting a disk failure based on the SMART information of the disk, it is only analyzed based on the SMART value of the disk at the current moment, and the prediction effect is not accurate.

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