Detecting faults in structures using time-frequency techniques

S. Pon Varma; Antonia Papandreou-Suppappola; S. B. Suppappola

Detecting faults in structures using time-frequency techniques

S. Pon Varma, Antonia Papandreou-Suppappola, S. B. Suppappola

Electrical Engineering

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

11 Scopus citations

Abstract

In this paper, we investigate various methods of classifying time-varying signals. In particular, we are interested in detecting acoustic emissions that may occur in concrete structures during imminent failure. This important classification problem will result in detecting and separating the distress signal from other natural or man made acoustic signals. Due to the time-varying nature of the signals, we employ several time-frequency based classification methods proposed in the literature. We also propose a new automatic classification method that is based on the matching pursuit algorithm, and we demonstrate its superior performance using real data.

Original language	English (US)
Title of host publication	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Pages	3593-3596
Number of pages	4
Volume	6
State	Published - 2001
Event	2001 IEEE Interntional Conference on Acoustics, Speech, and Signal Processing - Salt Lake, UT, United States Duration: May 7 2001 → May 11 2001

Other

Other	2001 IEEE Interntional Conference on Acoustics, Speech, and Signal Processing
Country/Territory	United States
City	Salt Lake, UT
Period	5/7/01 → 5/11/01

ASJC Scopus subject areas

Electrical and Electronic Engineering
Signal Processing
Acoustics and Ultrasonics

Cite this

@inproceedings{3f7d2f4a410649baa05979b412ca3601,

title = "Detecting faults in structures using time-frequency techniques",

abstract = "In this paper, we investigate various methods of classifying time-varying signals. In particular, we are interested in detecting acoustic emissions that may occur in concrete structures during imminent failure. This important classification problem will result in detecting and separating the distress signal from other natural or man made acoustic signals. Due to the time-varying nature of the signals, we employ several time-frequency based classification methods proposed in the literature. We also propose a new automatic classification method that is based on the matching pursuit algorithm, and we demonstrate its superior performance using real data.",

author = "{Pon Varma}, S. and Antonia Papandreou-Suppappola and Suppappola, {S. B.}",

year = "2001",

language = "English (US)",

volume = "6",

pages = "3593--3596",

booktitle = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

note = "2001 IEEE Interntional Conference on Acoustics, Speech, and Signal Processing ; Conference date: 07-05-2001 Through 11-05-2001",

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TY - GEN

T1 - Detecting faults in structures using time-frequency techniques

AU - Pon Varma, S.

AU - Papandreou-Suppappola, Antonia

AU - Suppappola, S. B.

PY - 2001

Y1 - 2001

N2 - In this paper, we investigate various methods of classifying time-varying signals. In particular, we are interested in detecting acoustic emissions that may occur in concrete structures during imminent failure. This important classification problem will result in detecting and separating the distress signal from other natural or man made acoustic signals. Due to the time-varying nature of the signals, we employ several time-frequency based classification methods proposed in the literature. We also propose a new automatic classification method that is based on the matching pursuit algorithm, and we demonstrate its superior performance using real data.

AB - In this paper, we investigate various methods of classifying time-varying signals. In particular, we are interested in detecting acoustic emissions that may occur in concrete structures during imminent failure. This important classification problem will result in detecting and separating the distress signal from other natural or man made acoustic signals. Due to the time-varying nature of the signals, we employ several time-frequency based classification methods proposed in the literature. We also propose a new automatic classification method that is based on the matching pursuit algorithm, and we demonstrate its superior performance using real data.

UR - http://www.scopus.com/inward/record.url?scp=0034841572&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0034841572&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0034841572

VL - 6

SP - 3593

EP - 3596

BT - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

T2 - 2001 IEEE Interntional Conference on Acoustics, Speech, and Signal Processing

Y2 - 7 May 2001 through 11 May 2001

ER -

Detecting faults in structures using time-frequency techniques

Abstract

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ASJC Scopus subject areas

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