Uncertainties of Parameters Quantification in SHM

Mohammad Shamim Miah*, Werner Lienhart

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


The uncertainties of parameters quantification due to various known and unknown conditions are crucial to understand structural health monitoring (SHM) systems. For instance, the amplitudes and the variation of loading conditions play a vital rule how the structural parameters are going to be changed. Hence, the aforementioned issue leads to an additional challenge in the area of SHM that requires attention. This study observed the behaviour of a steel bridge experimentally by employing multi-sensors scenarios e.g. accelerometers and laser triangulation sensor. The dynamical properties such as the peak (e.g. maximum-minimum) accelerations and displacements are evaluated. Additionally, the frequencies and damping ratio from the measured data of the tested bridge has been estimated by utilizing the fast Fourier transform (FFT) estimation. The outcome shows that the variation of input excitations (i.e., random, free-decay, extra-loading) effects the investigated properties as well as on their magnitudes considerably. Therefore, the findings suggest that before making a final judgement based on the identified/estimated properties from measured data, the underlying uncertainties need to be considered to avoid sub-optimal assessment strategy.
Original languageEnglish
Title of host publicationECCOMAS 2022 : Proceedings of 8th European Congress on Computational Methods in Applied Sciences and Engineering
Number of pages13
Publication statusPublished - 2022
Event8th European Congress on Computational Methods in Applied Sciences and Engineering: ECCOMAS CONGRESS 2022 - Oslo, Oslo, Norway
Duration: 5 Jun 20229 Jun 2022


Conference8th European Congress on Computational Methods in Applied Sciences and Engineering
Abbreviated titleECCOMAS CONGRESS 2022
Internet address

Fields of Expertise

  • Sustainable Systems
  • Information, Communication & Computing

Treatment code (Nähere Zuordnung)

  • Experimental


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