Techno Press
Techno Press

Smart Structures and Systems
  Volume 23, Number 2, February 2019 , pages 123-139
DOI: https://doi.org/10.12989/sss.2019.23.2.123
 

Impact force localization for civil infrastructure using augmented Kalman Filter optimization
Muhammad M. Saleem and Hongki Jo

 
Abstract
    Impact forces induced by external object collisions can cause serious damages to civil engineering structures. While accurate and prompt identification of such impact forces is a critical task in structural health monitoring, it is not readily feasible for civil structures because the force measurement is extremely challenging and the force location is unpredictable for full-scale field structures. This study proposes a novel approach for identification of impact force including its location and time history using a small number of multi-metric observations. The method combines an augmented Kalman filter (AKF) and Genetic algorithm for accurate identification of impact force. The location of impact force is statistically determined in the way to minimize the AKF response estimate error at measured locations and then time history of the impact force is accurately constructed by optimizing the error co-variances of AKF using Genetic algorithm. The efficacy of proposed approach is numerically demonstrated using a truss and a plate model considering the presence of modelling error and measurement noises.
 
Key Words
    augmented Kalman filter; genetic algorithm; strain gauges; accelerometers; impact force
 
Address
Muhammad M. Saleem: Department of Civil Engineering and Engineering Mechanics, The University of Arizona,
1209 E 2nd street Tucson, AZ 85719, USA;
Department of Civil Engineering, University of Engineering and Technology Lahore, G.T. Road Lahore, 54890, Pakistan
Hongki Jo: Department of Civil Engineering and Engineering Mechanics, The University of Arizona,
1209 E 2nd street Tucson, AZ 85719, USA
 
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