Abstract: Civil structures, once built and released for use, are expected to fulfil operational standards for extended periods. The fact, a civil structure´s life, is determined by temporary deterioration, harsh ambient, misuse, destruction, and, eventual rehabilitation for current use or conservation for historical reasons. Initially, vibrational analysis with stationary sensors, broad logistics and a large array of sensors to provide densely detailed data were required. The next evolutionary step; the simplification of the while-under-use data-acquisition stage; better, faster, more detailed parameters for diagnosis. With the structure under normal operation, a stationary reference sensor, a mobile sensor able to travel through specific trajectories over the structure, deep computational data analysis provides better, deeper, clearer frequencies, mode shapes and damping ratios. A structural health monitoring system should be able to reliably assess structural wellness under operational conditions. Such are the benefits of a mobile sensor monitoring and diagnosis system. This paper utilizes the time–scale analysis method and the Continuous Wavelet Transform (CWT) through a complex Morlet wavelet to extract modal parameters from the signal responses. The theoretical development is validated by numeric simulations on a simply supported beam and by double experimental confirmation on a pedestrian bridge at Universidad del Valle, in Cali (Colombia), by the technique herein, and by a stationary sensor scheme.

Keywords: Modal Identification, Mobile Sensors, Time-Scale Analysis, Continuous Wavelet Transform.

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Published on 20/08/19

Licence: CC BY-NC-SA license

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