A framework for experimental determination of localised vertical pedestrian forces on full-scale structures using wireless attitude and heading reference systems
Journal of Sound and Vibration
Open Access funded by Engineering and Physical Sciences Research Council. Under a Creative Commons license: http://creativecommons.org/licenses/by/4.0/
A major weakness among loading models for pedestrians walking on flexible structures proposed in recent years is the various uncorroborated assumptions made in their development. This applies to spatio- temporal characteristics of pedestrian loading and the nature of multi-object interactions. To alleviate this problem, a framework for the determination of localised pedestrian forces on full-scale structures is presented using a wireless attitude and heading reference systems (AHRS). An AHRS comprises a triad of tri-axial accelerometers, gyroscopes and magnetometers managed by a dedicated data processing unit, allowing motion in three-dimensional space to be reconstructed. A pedestrian loading model based on a single point inertial measurement from an AHRS is derived and shown to perform well against benchmark data collected on an instrumented treadmill. Unlike other models, the current model does not take any predefined form nor does it require any extrapolations as to the timing and amplitude of pedestrian loading. In order to assess correctly the influence of the moving pedestrian on behaviour of a structure, an algorithm for tracking the point of application of pedestrian force is developed based on data from a single AHRS attached to a foot. A set of controlled walking tests with a single pedestrian is conducted on a real footbridge for validation purposes. A remarkably good match between the measured and simulated bridge response is found, indeed confirming applicability of the proposed framework.
The research presented here was funded by EPSRC (grant EP/I029567/2). Authors thank Devon County Council for permitting the experimental campaign to be conducted on Baker Bridge in Exeter, UK, and Dr Erfan Shahabpour (supported by EPSRC grant EP/K03877X/1) for providing access to and assisting with measurements on the ADAL-3D treadmill at the University of Sheffield (funded by EPSRC grant EP/E018734/1).
This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.
Available online 16 May 2016