Environmental Engineering Reference
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Furthermore, AMA was improved by combining PSO, which was expected to
be useful for civil infrastructures instrumented with large number of sensors. The
proposed AMA was verified through a trial involving different sensor placements
for characterizing the vibrational behavior of the Canton Tower (Shanghai, China).
Modal assurance criterion (MAC) was chosen to yield two types of objective
functions, and for comparison with AMS, a conventional monkey algorithm (MA)
was used with a dual-structure coding method. Two simplified finite element (FE)
models of the Canton Tower were established with and without the antenna mast.
For all cases of objective functions and FE models, AMA exhibited the best
performance in optimizing sensor placement.
Data processing and transferring techniques have also been developed by
adopting biological concepts with the purposes of improving accuracy in data
detection and realizing real-time data processing for large-scale civil infrastruc-
tures (Lin et al.
2010
; Peckens and Lynch
2013
). A new damage extraction and
classification method for SHM based on the concept of a deoxyribonucleic acid
(DNA) array was implemented (Lin et al.
2010
). The purpose was to improve
damage detection accuracy. Damage characteristics were extracted using a double-
tier regression model to establish the autoregressive (AR)-autoregressive exoge-
neous (ARX) database, which was regarded as analogous to DNA of biological
creatures. Just as how DNA arrays are classified based on DNA patterns using
naïve Bayesian (NB) algorithm for detecting cancer cells, AR-ARX arrays could
also be classified using an NB algorithm and further improved through optimi-
zation using a likelihood selection method. The novel DNA-inspired SHM system
was verified through experiments involving a six-story building under ambient
vibration. It was shown that the optimized SHM system achieved 90-95 %
accuracy in terms of damage identification. To enable real-time data processing,
the auditory signal compression and transferring concepts were used (Peckens and
Lynch
2013
). Inspired by the cochlea, high signal compression ratio was achieved
with a reasonable reconstruction error as compared to two other conventional
compressive techniques, namely wavelet transforms and compressed sensing
(Fig.
11.2
) (Peckens and Lynch
2013
).
There have been other efforts in using bio-inspired concepts for improving
damage detection and SHM (Loh and Azhari
2012
; Salowitz et al.
2013
; Kirikera
et al.
2008
). Fatigue monitoring has been considered challenging, particularly due to
its long time-scales and high-frequency signals. Inspired by the concept of tree ring
data tracking, an intelligent fatigue monitoring system was developed (Bai et al.
2014
). Fatigue characteristics (i.e., the amplitude of strain, the number of cycles, and
the stress state) were acquired with a high degree of accuracy, which could be
transmitted in real-time via a wireless network. The wireless fatigue monitoring
system was validated using cantilever bending fatigue tests. Maximum strain of the
test specimen was tracked using either strain gage or polyvinylidene fluoride, and
the obtained digital signals were processed to extract the number of loading cycles,
among other fatigue characteristics. Feature extraction was performed using digital
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