Optimal partitioning of ultrasonic data for fatigue damage detection

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

doi:10.1109/acc.2011.5991263

Optimal partitioning of ultrasonic data for fatigue damage detection

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

Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English (US)
Title of host publication	Proceedings of the 2011 American Control Conference, ACC 2011
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	798-803
Number of pages	6
ISBN (Print)	9781457700804
DOIs	https://doi.org/10.1109/acc.2011.5991263
State	Published - 2011

Publication series

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

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering

Access to Document

10.1109/acc.2011.5991263

Cite this

@inproceedings{1dc0da82721443c39c5417adf5fe99ed,

title = "Optimal partitioning of ultrasonic data for fatigue damage detection",

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.",

author = "Singh, {Dheeraj Sharan} and Soumik Sarkar and Shalabh Gupta and Asok Ray",

year = "2011",

doi = "10.1109/acc.2011.5991263",

language = "English (US)",

isbn = "9781457700804",

series = "Proceedings of the American Control Conference",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "798--803",

booktitle = "Proceedings of the 2011 American Control Conference, ACC 2011",

address = "United States",

}

Optimal partitioning of ultrasonic data for fatigue damage detection. / Singh, Dheeraj Sharan; Sarkar, Soumik; Gupta, Shalabh et al.
Proceedings of the 2011 American Control Conference, ACC 2011. Institute of Electrical and Electronics Engineers Inc., 2011. p. 798-803 5991263 (Proceedings of the American Control Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Optimal partitioning of ultrasonic data for fatigue damage detection

AU - Singh, Dheeraj Sharan

AU - Sarkar, Soumik

AU - Gupta, Shalabh

AU - Ray, Asok

PY - 2011

Y1 - 2011

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=80053164842&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80053164842&partnerID=8YFLogxK

U2 - 10.1109/acc.2011.5991263

DO - 10.1109/acc.2011.5991263

M3 - Conference contribution

AN - SCOPUS:80053164842

SN - 9781457700804

T3 - Proceedings of the American Control Conference

SP - 798

EP - 803

BT - Proceedings of the 2011 American Control Conference, ACC 2011

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Optimal partitioning of ultrasonic data for fatigue damage detection

Abstract

Publication series

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this