A Fault Detection Method for Hard Disk Drives Based on Mixture of Gaussians and Nonparametric Statistics

作者：Queiroz Lucas P; Rodrigues Francisco Caio M; Gomes Joao Paulo P^*; Brito Felipe T; Chaves Iago C; Paula Manoel Rui P; Salvador Marcos R; Machado Javam C

来源：IEEE Transactions on Industrial Informatics, 2017, 13(2): 542-550.

DOI：10.1109/TII.2016.2619180

• Fault detection
• Gaussian mixture model (GMM)
• hard disk drive (HDD)

Hard Disk Drives (HDD) failure prediction is a challenging topic that has attracted much attention in recent years. Predicting failures in HDD may avoid losing data thus improving data reliability. Previous works on failure prediction are based on parametric approaches that model healthy drives with a Gaussian distribution. Although they achieved good results, the Gaussianity assumption may not hold true. The following work proposes a method for fault detection in HDD based on a Gaussian Mixture Model. A self-monitoring, analysis, and reporting technology dataset is used to evaluate the proposed method. Results show that the method outperforms previous works in both fault detection and time before failure.

• 出版日期2017-4