Health indices based on morphology and complexity measures of vibration signals for machine condition monitoring and prognostics

B. Samanta, C. Nataraj

Research output: Contribution to book or proceedingConference articlepeer-review

Abstract

The paper presents health indices (HI) for monitoring and prognostics of machine condition. HI are developed using morphology and entropy based complexity measures of machine vibration signals. The indices are compared with a recently introduced energy based feature and the commonly used statistical measure of signal kurtosis. The procedure of extracting HI is illustrated first using the simulated response of a simple gear model with tooth crack. Next the HI extraction process is applied to the experimental vibration data of a helicopter drivetrain gearbox with a seeded tooth fault. The effectiveness of the extracted HI is compared for gear condition monitoring and prognostics.

Original languageEnglish
Title of host publicationAnnual Conference of the Prognostics and Health Management Society, PHM 2009
PublisherPrognostics and Health Management Society
ISBN (Electronic)9781936263004
StatePublished - 2009
EventAnnual Conference of the Prognostics and Health Management Society, PHM 2009 - San Diego, United States
Duration: Sep 27 2009Oct 1 2009

Publication series

NameAnnual Conference of the Prognostics and Health Management Society, PHM 2009

Conference

ConferenceAnnual Conference of the Prognostics and Health Management Society, PHM 2009
Country/TerritoryUnited States
CitySan Diego
Period09/27/0910/1/09

Fingerprint

Dive into the research topics of 'Health indices based on morphology and complexity measures of vibration signals for machine condition monitoring and prognostics'. Together they form a unique fingerprint.

Cite this