Damage Identification Analyses of a Historic Masonry Structure in T-F Domain

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Beyen K.

Teknik Dergi, cilt.32, sa.2, 2021 (SCI Expanded İndekslerine Giren Dergi)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 32 Konu: 2
  • Basım Tarihi: 2021
  • Doi Numarası: 10.18400/tekderg.2019.426728
  • Dergi Adı: Teknik Dergi


Fatih mosque, a landmark structure in Istanbul, has suffered structural damage during 1999
Kocaeli earthquake. Using spectral, time-domain (OKID/ERA for SISO and MIMO models)
and T-F domain (WT, HHT) techniques on ambient vibrations, damage identification has
been performed. Results of parametric and spectral analyses indicate close global peaks.
Northwest arch (O3) that was expected to move in harmony with other arches cannot display
such a consistent behavior and produces additional local frequency at 24Hz due to damage.
Southeast arch (O1) also has comparable damage producing another locality at 38Hz.
Extending linear approaches into nonlinear-nonstationary methods, decompositions in WT
and HHT improved the results in the temporal-frequency energy distribution. Estimated
individual and global structural behavior are consistent with visually inspected damage states
for O3 and O1. On a global scale, damage additionally generates significant nonstationarity
on the neighbors in touch. Northeast arch (O2) is affected strongly by the anomalies appeared
at stations O3 and O1. Especially neighbor stations O6 andO7 located at the springing points
of the arch (O3) and others O5 and O6 located at the springing points of the arch (O2) are
strongly affected due to tension rod failure causing the dome base to open outwards. T-F
analysis detects and localizes any anomalous system behavior and can adequately capture the
system dynamics of any instrumented part of the structure at any particular time epoch. For
historical masonry structures with vulnerable components like large central dome and arches
that have low redundancy, there is a need to develop automatic signal/image processing
through, machine vision, and pattern recognition for early diagnosis and warning of gradual