Symbolic time series analysis of ultrasonic signals for fatigue damage monitoring in polycrystalline alloys

Shalabh Gupta, Asok Ray, Eric Keller

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

The paper presents the concept and experimental validation of an analytical tool for fatigue damage monitoring in polycrystalline alloys. Ultrasonic signals are utilized for early detection of fatigue damage during the crack initiation period. Small microstructural changes occurring inside the material during the initial stages of fatigue damage cause attenuation and distortion of transmitted waves at the receiver end. The anomaly detection algorithm is based on time series analysis of ultrasonic data and is built upon the principles of symbolic dynamics, information theory and statistical signal processing. Experiments have been conducted for both constant amplitude and block loading of 7075-T6 aluminium alloy compact specimens on a special-purpose test apparatus that is equipped with ultrasonics sensors and a travelling optical microscope for fatigue damage monitoring.

Original languageEnglish (US)
Article number040
Pages (from-to)1963-1973
Number of pages11
JournalMeasurement Science and Technology
Volume17
Issue number7
DOIs
StatePublished - Jul 1 2006

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Applied Mathematics

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