Structural health monitoring using adaptive LMS filters

  • Authors:

  • Mostafa Nayyerloo;J. Geoffrey Chase;Gregory A. MacRae;XiaoQi Chen;Christopher E. Hann

  • Affiliations:

  • Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand.;Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand.;Department of Civil and Natural Resources Engineering, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand.;Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand.;Department of Mechanical Engineering, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand

  • Venue:
  • International Journal of Computer Applications in Technology
  • Year:
  • 2010

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Abstract

A structure's level of damage is determined using a non-linear model-based method utilising a Bouc-Wen hysteretic model. It employs adaptive Least Mean Squares (LMS) filtering theory in real time to identify changes in stiffness due to modelling error damage, as well as plastic and permanent displacements, which are critical to determining ongoing safety and use. The Structural Health Monitoring (SHM) method is validated on a four-storey shear structure model undergoing seismic excitation. For the simulated structure, the algorithm identifies stiffness changes to within 10% of the true value in 0.20 s, and permanent deflection is identified to within 5% of the actual as-modelled value using noise-free simulation-derived structural responses.