Optimal partitioning of ultrasonic data for fatigue damage detection

Dheeraj Sharan Singh, Soumik Sarkar, Shalabh Gupta, Asok Ray

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

Abstract

This paper presents an analytical tool for online fatigue damage detection in polycrystalline alloys that are commonly used in mechanical structures. The underlying theory is built upon symbolic dynamic filtering (SDF) that optimally partitions time series data for feature extraction and pattern classification. The proposed method has been experimentally validated on a fatigue test apparatus that is equipped with ultrasonics sensors and a traveling optical microscope for fatigue damage detection.

Original languageEnglish (US)
Title of host publicationProceedings of the 2011 American Control Conference, ACC 2011
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages798-803
Number of pages6
ISBN (Print)9781457700804
DOIs
StatePublished - 2011

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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