Ambient data analysis for robust and efficient structural identification

Jian Zhang; Franklin Moon; Ahmet Aktan

doi:10.1117/12.816123

30 March 2009 Ambient data analysis for robust and efficient structural identification

Jian Zhang, Franklin Moon, Ahmet Aktan

Proceedings Volume 7292, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2009; 729237 (2009) https://doi.org/10.1117/12.816123
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2009, San Diego, California, United States

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.

Citation Download Citation

Jian Zhang, Franklin Moon, and Ahmet Aktan "Ambient data analysis for robust and efficient structural identification", Proc. SPIE 7292, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2009, 729237 (30 March 2009); https://doi.org/10.1117/12.816123

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