Structural Health Monitoring of the Pitt River Bridge in British Columbia, Canada

Carlos Ventura (1) , Palle Andersen (2) , Laurent Mevel (3) , Michael Döhler (3)

1 UBC - University of British Columbia
2 SVIBS - Structural Vibration Solutions
3 I4S - Statistical Inference for Structural Health Monitoring

Vibration based damage detection of engineering structures has become an important issue for maintenance operations on transport infrastructure. Research in vibration based structural damage detection has been rapidly expanding from classic modal parameter estimation to modern operational monitoring. Methodologies from control engineering have been adopted and converted for the application on Civil Engineering structures. In this paper a statistical null space based damage detection algorithm is presented. This technique compares a current structural (possibly damaged) state to a reference state by a chi-squared (χ2) test, once the test parameters are established in the reference state. This is an efficient way to detect changes in the modal parameters (natural frequencies, damping ratios, mode shapes) of a structure without actually computing them. The χ2 test needs the ambient output-only vibration data of the structural state to be tested, a null space matrix determining the structural behavior in the reference state and the residual covariance, also determined in the reference state, and is a fully automated algorithm. The proposed method is tested on the Pitt River Bridge in Canada. The bridge opened on October 4, 2009. Since 2011 the bridge has been monitored as part of the British Columbia Smart Infrastructure Monitoring System (BCSIMS). The system has been performing daily measurements and the methods proposed in this paper have been tested using this data.

Domaines: Dynamique, vibrations; Applications [stat.AP]

Carlos Ventura, Palle Andersen, Laurent Mevel, Michael Döhler. Structural Health Monitoring of the Pitt River Bridge in British Columbia, Canada. WCSCM - 6th World Conference on Structural Control and Monitoring, Jul 2014, Barcelona, Spain. ⟨hal-01011750⟩