Multi-objective sensor placement optimization for structural response estimation under spatially varying dynamic loading of bridges

Muhammad Mazhar Saleem, Hongki Jo

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Although a lot of different types of sensors are available in the market only a limited number of sensors can be installed on a structure. Proper placement of these sensors plays a vital role in effectively achieving the objectives of a monitoring system. Sensor placement becomes especially critical in the case of bridges where the applied loading keeps on changing its location. A sensor layout that provides good quality structural response estimates for a given applied loading may not yield acceptable results for a different loading arrangement. Further, usually different types of sensors are installed on a structure e.g. strain gauges and accelerometers. These sensors measure different physical quantities having different units and orders of magnitude thus cannot be easily incorporated in a sensor placement optimization (SPO) process. So, this research work proposes a multi-objective sensor placement optimization approach that can effectively deal with different types of sensor measurements and spatially varying loading such as in the case of bridges. The proposed method employs an augmented Kalman filter (AKF) for structural response estimation and a multi-objective genetic algorithm for SPO. The AKF can effectively estimate structural response using a few heterogeneous noisy measurements while incorporating the modeling error. The effectiveness of the proposed method is demonstrated using a numerical example of a 3D truss bridge structure. The results show that the proposed multi-objective optimization method yields a sensor arrangement that remains effective against spatially varying dynamic loading.

Original languageEnglish (US)
Pages (from-to)2255-2266
Number of pages12
JournalAdvances in Structural Engineering
Issue number10
StatePublished - Jul 2021


  • multi-objective genetic algorithm
  • sensor placement optimization
  • structural response estimation

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction


Dive into the research topics of 'Multi-objective sensor placement optimization for structural response estimation under spatially varying dynamic loading of bridges'. Together they form a unique fingerprint.

Cite this