Operational Modal Parameter Estimation from Short Time-Data Series

Operational Modal Analysis (OMA) is a technique of extracting modal parameters of a system from output responses only. It is an emerging field in structural dynamics and has been applied to complex structures that are often difficult to analyze using traditional Experimental Modal Analysis (EMA) techniques. Since the input information is unavailable in OMA, the technique makes use of certain assumptions about the input excitation to the system and the data processing methods used by current OMA algorithms are based on these assumptions. However, in some real-world scenarios not only the forcing function to the system violates these assumptions but also the time data series of system response is short in length and buried under noise. In such cases, ensemble averaging techniques for filtering out noise are rendered ineffective and the current OMA algorithms which utilize power spectrum and correlation functions result in inconsistent modal parameters, especially modal damping. This research develops a time domain operational modal parameter estimation (MPE) method based on describing the total system response as a Nonlinear Auto Regressive process with eXogenous input (NARX) wherein the linear part of the model describes the response of the structure and the nonlinear terms fit the noise present in data series. The method is developed in line with the concept of Unified Matrix Polynomial Approach (UMPA) and utilizes a set of least squares solutions to compute modal parameters. ii Acknowledgements The idea of travelling 8000 miles across the globe and starting a new life to earn a Masters' degree, although felt quite overwhelming at the onset of the journey, has finally proven to be fruitful as I am finishing this thesis. Several people are to be thanked for making this experience a highly rewarding and memorable one. Firstly, I would like to express my gratitude to Dr. Allemang and Dr. Phillips who not only taught, helped, advised and guided me in the technical matters at every step of this quest but also understood me at a personal level and motivated me to better myself. One of the most stand-out features of their pedagogy is their attention to detail. I for one will never forget that .' transposes the matrix. It has truly been an honor to learn from these individuals and I will forever cherish their tutelage. I sincerely hope to learn and work with them again. I would like to acknowledge The Boeing Company and UC-SDRL for providing …