MISES: A New Modal Identification Tool for Pedestrian Bridges

In order to characterize the dynamic properties of bridges, many modal identification methods have been developed, which have been thoroughly published and evaluated. Some have even also been incorporated into commercial software. While the academic examples and implementations often lack in generalizability and visualization, the commercial software systems are confined to certain sets of methods and are proprietary. Therefore, a new modal identification and serviceability assessment tool for pedestrian bridges was recently developed in collaboration between TU Berlin and the University Waterloo for academic use. This software tool can be used for instruction and includes measurement data processing, visualization and several algorithms to undertake system identification. A unique feature is that it is the first of its kind for pedestrian bridge applications for serviceabilityassessment. As the software's intended use is educational, it was designed to be modular, flexible, and easily extended, so that scientists and students could add new methods easily. In addition to popular modal identification methods, this tool also provides new advanced signal processing methods such as blind source separation and its more advanced underdetermined version (PARAFAC) for modal identification to address specific issues such as narrow band harmonics arising in pedestrian bridges.

In this paper, the basic ideas of this software are explained and an overview of its features is given. To validate the tool, one numerical example and the results of field data from a pedestrian bridge are presented.