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 low-rise 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.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Shimada and A. Mita "Damage assessment of bending structures using support vector machine", Proc. SPIE 5765, Smart Structures and Materials 2005: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, (17 May 2005); https://doi.org/10.1117/12.600840
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CITATIONS
Cited by 7 scholarly publications.
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KEYWORDS
Sensors

Structural health monitoring

Damage detection

Pattern recognition

Data modeling

Finite element methods

Neodymium

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