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Our research has two main theme areas. First, we are working on identification and control of dynamically sensitive structures which are vulnerable to natural (wind, earthquake) and man-made (e.g., machinery, pedestrian) dynamic forces. We are primarily interested in understanding the behaviour and condition of structures through sensor measurements, and to develop innovative means to control unwanted responses in dynamically sensitive structures. We are working on developing powerful system identification and parameter estimation algorithms using concepts of blind source separation, Kalman filtering, unsupervised classification, and time-frequency analysis. We have significant ongoing research on lightweight footbridges such as aluminum, where we are studying the dynamic effects of pedestrian loading and the deployment of autonomous vibration control systems.

The second theme area is in condition monitoring of civil and mechanical systems such as rotating mechanical equipment, bridges and water distribution networks. We are primarily interested in vibration and acoustic-based sensors to undertake condition assessment. We are working on signal processing, machine learning and reliability methods to develop novel detection, degradation and maintenance models to assist with maintenance and operations. Autonomous aerial vehicles are being assessed for their use in inspecting steel and concrete bridges to augment current inspection techniques where access is difficult.

In this webpage, you will find a summary of our key research themes, publications and information about our current team members.

Condition Monitoring of Civil and Mechanical Systems

Structural Dynamics, Identification and Control Group
University of Waterloo, CPH 1326G
200 University Avenue W.
Waterloo, ON, N2L 3G1