Fault Detection in Hard Disk Drives Based on a Semi Parametric Model and Statistical Estimators

作者：Queiroz Lucas P; Gomes Joao Paulo P^*; Rodrigues Francisco Caio M; Brito Felipe T; Chaves Iago C; Leite Lucas G M; Machado Javam C

来源：New Generation Computing, 2018, 36(1): 5-19.

DOI：10.1007/s00354-017-0016-0

• Fault detection
• Hard disk drive
• Gaussian mixture model

Detecting faults in Hard Disk Drives (HDD) can lead to significant benefits to HDD manufacturers, users and storage system providers. As a consequence, several works have focused on the development of fault detection algorithms for HDDs. Recently, promising results were achieved by methods using SMART (Self-Monitoring Analysis and Reporting Technology) features and anomaly detection algorithms. In this work, we propose a method for fault detection on HDDs that uses a Gaussian Mixture to model the behavior of healthy HDDs. After obtaining the similarity between a given HDD and this statistical model, an anomaly is detected when a statistical estimator computed over these dissimilarities exceeds a threshold. In addition to the proposed method, we also conducted an extensive evaluation of different statistical estimators. The proposed method, named Fault Detection of HDDs based on GMM and statistical estimators (FDGE) was compared to state-of-the-art Fault detection methods and achieved the promising results.

• 出版日期2018-1