Conference proceeding
Ambient data analysis for robust and efficient structural identification
Proceedings of SPIE, v 7292(1), pp 729237-729239
26 Mar 2009
Abstract
Various uncertainties involved in the structural modeling and experiment processes greatly limit the application of the system identification (St-Id) technology on the real-life structural health monitoring and risk-based decision making. An efficient St-Id method is proposed to accurately identify structural modal parameters by using ambient test data with various uncertainties. The random decrement technique is first applied to reduce random errors by averaging the test data. Subsequently, a high order Vector Backward Auto-Regressive (VBAR) model is proposed to identify structural modal parameters. The merit of the VBAR model is that it awards a determine way to separate the system modes consisting of structural parameters and the extraneous modes arising due to uncertainties. The ambient vibration data from a cantilever beam experiment is employed to demonstrate the effectiveness of the proposed St-Id method.
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1 citations in Scopus
Details
- Title
- Ambient data analysis for robust and efficient structural identification
- Creators
- Jian Zhang - Drexel University, Civil, Architectural, and Environmental EngineeringFranklin Moon - Drexel University, Civil, Architectural, and Environmental EngineeringAhmet Aktan - Drexel University, Civil, Architectural, and Environmental Engineering
- Publication Details
- Proceedings of SPIE, v 7292(1), pp 729237-729239
- Conference
- Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2009 (2009)
- Publisher
- Society of Photo-Optical Instrumentation Engineers (SPIE)
- Number of pages
- 3
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Scopus ID
- 2-s2.0-77955674592
- Other Identifier
- 991019173587704721