Structural Health Monitoring of a Vertical Lift Bridge Using Vibration Data

An objective decision-making criterion is developed for condition assessment of the new Memorial Bridge connecting Portsmouth, New Hampshire to Kittery, Main, United States. The analysis is based on the normalized energy of acceleration signals obtained from a series of accelerometers permanently deployed along the bridge. In the present paper, a Wavelet Packet Transform (WPT) is used as a means to decompose the measured signals with an arbitrary time-frequency resolution. A unique aspect of this approach is the coupling of various techniques in an effort to enhance the discrimination between vibration-based data recorded from different states of the structure. Firstly, the wavelet packet component that represents the most dominant patterns of variation of the signal properties is determined through wavelet analysis. Secondly, the wavelet packet component normalized coefficient is computed for each sensor. Finally, the mean coefficient obtained from the entire set of sensors in each day is calculated for further investigations through a control chart analysis. A statistical framework is developed to train a baseline model in the early age of the bridge when the condition is undamaged. The principal theory behind the methodology relies on assumption that the variations of the extracted features between the estimated control limits correspond mainly to normal operating conditions of the bridge. Therefore, the exceedance of future indicators from the enclosure signifies the presence of unusual sources of variability. The proposed approach is analytically verified through a Finite Element (FE) model of the bridge subjected to structural damage in one of its diagonals. Results indicate a significant distinction between undamaged and damaged responses of the bridge.



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