Affiliations: Università degli Studi di Roma La Sapienza,
Dipartimento di Ingegneria Strutturale e Geotecnica, Via Eudossiana, 18, 00184
Roma, Italy | Department of Civil Engineering and Engineering
Mechanics, Columbia University, 636A S. W. Mudd Building, 500 West 120th
Street, New York, NY, USA | Department of Civil Engineering and Engineering
Mechanics, Columbia University, 640 S. W. Mudd Building, 500 West 120th Street,
New York, NY, USA
Abstract: This paper presents an experimental study of frequency and time
domain identification algorithms and discusses their effectiveness in
structural health monitoring of frame structures using acceleration input and
response data. Three algorithms were considered: 1) a frequency domain
decomposition algorithm (FDD), 2) a time domain Observer Kalman IDentification
algorithm (OKID), and 3) a subsequent physical parameter identification
algorithm (MLK). Through experimental testing of a four-story steel frame model
on a uniaxial shake table, the inherent complications of physical
instrumentation and testing are explored. Primarily, this study aims to provide
a dependable first-order and second-order identification of said test structure
in a fully instrumented state. Once the characteristics (i.e. the stiffness
matrix) for a benchmark structure have been determined, structural damage can
be detected by a change in the identified structural stiffness matrix. This
work also analyzes the stability of the identified structural stiffness matrix
with respect to fluctuations of input excitation magnitude and frequency
content in an experimental setting.
Keywords: System identification, damage detection, health monitoring, ERA, OKID, FDD, experimental, shake table, vibration
