Operational modal analysis of a steel-frame, low-rise building with L-shaped construction

Rodrigo Sarlo; Pablo A. Tarazaga; Mary E. Kasarda

doi:10.1117/12.2260340

12 April 2017 Operational modal analysis of a steel-frame, low-rise building with L-shaped construction

Rodrigo Sarlo, Pablo A. Tarazaga, Mary E. Kasarda

Proceedings Volume 10168, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2017; 101682H (2017) https://doi.org/10.1117/12.2260340
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2017, Portland, Oregon, United States

Abstract

The Goodwin Hall Smart Infrastructure facility at Virginia Tech is a five-story “smart building" with an integrated network of 213 wired accelerometers. We utilize a subset of 68 sensors to perform high-resolution Operational Modal Analysis (OMA) of the structure under windy conditions. The low-rise, L-shaped construction and high mass, high stiffness properties of Goodwin Hall provide a unique case study in comparison to typical cases of building OMA in literature, which generally feature high-rise buildings with rectangular architectures. Our work focuses on data acquisition and feature extraction, which are two critical steps within a complete structural health monitoring approach. Our detailed methodology establishes guidelines for sensor selection and data processing applicable to this and more general cases. Modal parameters extraction using Stochastic Subspace Identification shows the first four natural frequencies, damping values, participation factors and mode shapes of the building. We hypothesize that high damping values and large differences in the participation of fundamental modes are related to the nature of the wind excitation.

Conference Presentation

Citation Download Citation

Rodrigo Sarlo, Pablo A. Tarazaga, and Mary E. Kasarda "Operational modal analysis of a steel-frame, low-rise building with L-shaped construction", Proc. SPIE 10168, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2017, 101682H (12 April 2017); https://doi.org/10.1117/12.2260340

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