Damage detection is an important application of structural health monitoring. With the recent development of sensing technology, additional information about structures, angular velocity, has become available. In this paper, the angular velocity signals obtained from gyroscopes are modeled as an autoregressive (AR) model. The damage sensitive features (DSFs) are defined as a function of the AR coefficients. It is found that the mean values of the DSF for the damaged and undamaged signals are different. Also, we show that the angular velocity- based AR model has a linear relationship with the acceleration-based AR model. To test the proposed damage detection method, the algorithm has been tested with the experimental data from a recent shake table test where the damage is introduced systemically. The results indicate that the change of DSF means is statistically significant, and the angular velocity-based DSFs are sensitive to damage.
Yizheng Liao, Anne S. Kiremidjian, Ram Rajagopal, and Chin-Hsiung Loh, "Angular velocity-based structural damage detection," Proc. SPIE 9803, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2016, 98031N (Presented at SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring: March 22, 2016; Published: 20 April 2016); https://doi.org/10.1117/12.2219398.
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