Damage assessment of bending structures using support vector machine

M. Shimada, Akira Mita

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

10 Citations (Scopus)

Abstract

A damage detection method utilizing Support Vector Machine (SVM) for bending structures is proposed. The SVM was recently proposed as a new technique for pattern recognition. The SVM is a powerful pattern recognition tool applicable to complicated classification problems and is effectively utilized in the method. Based on the modal frequency changes, the damage location and its severity are defined by the SVM. In our previous studies, it was shown that our proposed method worked very well for structures modeled by shear frames. However, this modeling is only appropriate for lowrise building structures and is not appropriate for tall buildings. Therefore, it is our purpose here to extend the method to bending frames that are appropriate models for tall buildings. In the analytical evaluation, we constructed the finite element models to represent bending structures. Then, we conducted a series of experiments for verification. We could show that the damage detection method using SVM was also possible and effective for bending structures.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsM. Tomizuka
Pages923-930
Number of pages8
Volume5765
EditionPART 2
DOIs
Publication statusPublished - 2005
EventSmart Structures and Materials 2005 - Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems - San Diego, CA, United States
Duration: 2005 Mar 72005 Mar 10

Other

OtherSmart Structures and Materials 2005 - Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems
CountryUnited States
CitySan Diego, CA
Period05/3/705/3/10

Fingerprint

damage assessment
Support vector machines
Tall buildings
Damage detection
damage
pattern recognition
Pattern recognition
shear
evaluation
Experiments

Keywords

  • Damage detection
  • Modal analysis
  • Support vector machine
  • System identification

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

Shimada, M., & Mita, A. (2005). Damage assessment of bending structures using support vector machine. In M. Tomizuka (Ed.), Proceedings of SPIE - The International Society for Optical Engineering (PART 2 ed., Vol. 5765, pp. 923-930). [103] https://doi.org/10.1117/12.600840

Damage assessment of bending structures using support vector machine. / Shimada, M.; Mita, Akira.

Proceedings of SPIE - The International Society for Optical Engineering. ed. / M. Tomizuka. Vol. 5765 PART 2. ed. 2005. p. 923-930 103.

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

Shimada, M & Mita, A 2005, Damage assessment of bending structures using support vector machine. in M Tomizuka (ed.), Proceedings of SPIE - The International Society for Optical Engineering. PART 2 edn, vol. 5765, 103, pp. 923-930, Smart Structures and Materials 2005 - Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, San Diego, CA, United States, 05/3/7. https://doi.org/10.1117/12.600840
Shimada M, Mita A. Damage assessment of bending structures using support vector machine. In Tomizuka M, editor, Proceedings of SPIE - The International Society for Optical Engineering. PART 2 ed. Vol. 5765. 2005. p. 923-930. 103 https://doi.org/10.1117/12.600840
Shimada, M. ; Mita, Akira. / Damage assessment of bending structures using support vector machine. Proceedings of SPIE - The International Society for Optical Engineering. editor / M. Tomizuka. Vol. 5765 PART 2. ed. 2005. pp. 923-930
@inproceedings{2bb399693be241c293a8ce3ed0b9f6ab,
title = "Damage assessment of bending structures using support vector machine",
abstract = "A damage detection method utilizing Support Vector Machine (SVM) for bending structures is proposed. The SVM was recently proposed as a new technique for pattern recognition. The SVM is a powerful pattern recognition tool applicable to complicated classification problems and is effectively utilized in the method. Based on the modal frequency changes, the damage location and its severity are defined by the SVM. In our previous studies, it was shown that our proposed method worked very well for structures modeled by shear frames. However, this modeling is only appropriate for lowrise building structures and is not appropriate for tall buildings. Therefore, it is our purpose here to extend the method to bending frames that are appropriate models for tall buildings. In the analytical evaluation, we constructed the finite element models to represent bending structures. Then, we conducted a series of experiments for verification. We could show that the damage detection method using SVM was also possible and effective for bending structures.",
keywords = "Damage detection, Modal analysis, Support vector machine, System identification",
author = "M. Shimada and Akira Mita",
year = "2005",
doi = "10.1117/12.600840",
language = "English",
volume = "5765",
pages = "923--930",
editor = "M. Tomizuka",
booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",
edition = "PART 2",

}

TY - GEN

T1 - Damage assessment of bending structures using support vector machine

AU - Shimada, M.

AU - Mita, Akira

PY - 2005

Y1 - 2005

N2 - A damage detection method utilizing Support Vector Machine (SVM) for bending structures is proposed. The SVM was recently proposed as a new technique for pattern recognition. The SVM is a powerful pattern recognition tool applicable to complicated classification problems and is effectively utilized in the method. Based on the modal frequency changes, the damage location and its severity are defined by the SVM. In our previous studies, it was shown that our proposed method worked very well for structures modeled by shear frames. However, this modeling is only appropriate for lowrise building structures and is not appropriate for tall buildings. Therefore, it is our purpose here to extend the method to bending frames that are appropriate models for tall buildings. In the analytical evaluation, we constructed the finite element models to represent bending structures. Then, we conducted a series of experiments for verification. We could show that the damage detection method using SVM was also possible and effective for bending structures.

AB - A damage detection method utilizing Support Vector Machine (SVM) for bending structures is proposed. The SVM was recently proposed as a new technique for pattern recognition. The SVM is a powerful pattern recognition tool applicable to complicated classification problems and is effectively utilized in the method. Based on the modal frequency changes, the damage location and its severity are defined by the SVM. In our previous studies, it was shown that our proposed method worked very well for structures modeled by shear frames. However, this modeling is only appropriate for lowrise building structures and is not appropriate for tall buildings. Therefore, it is our purpose here to extend the method to bending frames that are appropriate models for tall buildings. In the analytical evaluation, we constructed the finite element models to represent bending structures. Then, we conducted a series of experiments for verification. We could show that the damage detection method using SVM was also possible and effective for bending structures.

KW - Damage detection

KW - Modal analysis

KW - Support vector machine

KW - System identification

UR - http://www.scopus.com/inward/record.url?scp=25144486099&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=25144486099&partnerID=8YFLogxK

U2 - 10.1117/12.600840

DO - 10.1117/12.600840

M3 - Conference contribution

VL - 5765

SP - 923

EP - 930

BT - Proceedings of SPIE - The International Society for Optical Engineering

A2 - Tomizuka, M.

ER -