Health diagnostics with unexampled faulty states using a two-fold classification method

Prasanna Tamilselvan, Pingfeng Wang, Ramkumar Jayaraman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

System health diagnostics provides diversified benefits such as improved safety, improved reliability and reduced costs for the operation and maintenance of engineered systems. Successful health diagnostics requires the knowledge of system failures. However, with an increasing complexity it is extraordinarily difficult to have a well-tested system so that all potential faulty states can be realized and studied at product testing stage. Thus, real time health diagnostics requires automatic detection of unexampled faulty states through the sensory signals to avoid sudden catastrophic system failures. This paper presents a hybrid inference approach (HIA) for structural health diagnosis with unexampled faulty states, which employs a two-fold inference process comprising of preliminary statistical learning based anomaly detection and artificial intelligence based health state classification for real time condition monitoring. The HIA is able to identify and isolate the unexampled faulty states through interactively detecting the deviation of sensory data from the known health states and forming new health states autonomously. The proposed approach takes the advantages of both statistical approaches and artificial intelligence based techniques and integrates them together in a unified diagnosis framework. The performance of proposed HIA is demonstrated with a power transformer and roller bearing health diagnosis case studies, where Mahalanobis distance serves as a representative statistical inference approach.

Original languageEnglish (US)
Title of host publicationPHM 2012 - 2012 IEEE Int. Conf. on Prognostics and Health Management:Enhancing Safety, Efficiency, Availability, and Effectiveness of Systems Through PHM Technology and Application,Conference Program
DOIs
StatePublished - Nov 6 2012
Externally publishedYes
Event2012 IEEE International Conference on Prognostics and Health Management: Enhancing Safety, Efficiency, Availability, and Effectiveness of Systems Through PHM Technology and Application, PHM 2012 - Denver, CO, United States
Duration: Jun 18 2012Jun 21 2012

Publication series

NamePHM 2012 - 2012 IEEE Int. Conf.on Prognostics and Health Management: Enhancing Safety, Efficiency, Availability, and Effectiveness of Systems Through PHM Technology and Application, Conference Program

Other

Other2012 IEEE International Conference on Prognostics and Health Management: Enhancing Safety, Efficiency, Availability, and Effectiveness of Systems Through PHM Technology and Application, PHM 2012
Country/TerritoryUnited States
CityDenver, CO
Period6/18/126/21/12

Keywords

  • artificial intelligence
  • hybrid inference approach
  • mahalanobis distance

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Biomedical Engineering
  • Mathematical Physics

Fingerprint

Dive into the research topics of 'Health diagnostics with unexampled faulty states using a two-fold classification method'. Together they form a unique fingerprint.

Cite this