Online anomaly detection for hard disk drives based on mahalanobis distance

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

88 Scopus Citations
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Author(s)

  • Yu Wang
  • Qiang Miao
  • Eden W. M. Ma
  • Kwok-Leung Tsui
  • Michael G. Pecht

Detail(s)

Original languageEnglish
Article number6423861
Pages (from-to)136-145
Journal / PublicationIEEE Transactions on Reliability
Volume62
Issue number1
Online published30 Jan 2013
Publication statusPublished - Mar 2013

Abstract

A hard disk drive (HDD) failure may cause serious data loss and catastrophic consequences. Online health monitoring provides information about the degradation trend of the HDD, and hence the early warning of failures, which gives us a chance to save the data. This paper developed an approach for HDD anomaly detection using Mahalanobis distance (MD). Critical parameters were selected using failure modes, mechanisms, and effects analysis (FMMEA), and the minimum redundancy maximum relevance (mRMR) method. A self-monitoring, analysis, and reporting technology (SMART) data set is used to evaluate the performance of the developed approach. The result shows that about 67% of the anomalies of failed drives can be detected with zero false alarm rate, and most of them can provide users with at least 20 hours during which to backup the data. © 1963-2012 IEEE.

Research Area(s)

  • Hard disk drive, Mahalanobis distance, online anomaly detection, self-monitoring, analysis, and reporting technology

Citation Format(s)

Online anomaly detection for hard disk drives based on mahalanobis distance. / Wang, Yu; Miao, Qiang; Ma, Eden W. M. et al.
In: IEEE Transactions on Reliability, Vol. 62, No. 1, 6423861, 03.2013, p. 136-145.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review