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Table 1 An overview of recent damage detection approaches

From: Railway bridge damage detection based on extraction of instantaneous frequency by Wavelet Synchrosqueezed Transform

Research study

Considered response 1

Damage Sensitive Feature 2

Applied technique 3

Moving object

Validation

Huseynov et al. (2020)

\(\ddot {x}\)

rotation

rotation influence line

series of constant forces

Numerically experimentally

Zhang et al. (2017)

x, \(\dot {x}, \ddot {x}\)

phase trajectory

low-pass filter & moving average

constant force & mass

Numerically experimentally

He and Zhu (2016)

x

moving frequency

DWT

constant force & vehicle

Numerically

Aied et al. (2016)

\(\ddot {x}\)

discontinuity in IMF

EEMD

a constant force

Numerically

Yu et al. (2016)

x

Wavelet coefficient

CWT

a constant force

Numerically experimentally

Nguyen (2013)

x

instantaneous frequency

CWT

a half-vehicle

Numerically

Gonzales and Hester (2013)

\(\ddot {x}\)

mid-span ‘static’ deflection and acceleration

MAF

a constant force & a vehicle

Numerically

Khorram et al. (2013)

x

Wavelet coefficients

CWT & Factorial Design

a constant force

Numerically

Zhang et al. (2013)

\(\dot {x}\)

wavelet coefficient

CWT

a constant force

Numerically

Hester and Gonzalez (2012)

\(\ddot {x}\)

wavelet coefficient

CWT

a constant force

Numerically

Meredith et al. (2012)

\(\ddot {x}\)

high peaks in IMFs

MAF followed by EMD

a constant force

Numerically

Roveri and Carcaterra (2012)

x

instantaneous frequency

HHT

constant force

Numerically

Pakrashi et al. (2009)

ε

Wavelet coefficient & Wavelet phase

CWT

vehicle

Numerically experimentally

Zhu and Law (2006)

x

Wavelet coefficient

CWT

constant force

Numerically

  1. 1\(x, \dot {x}, \ddot {x}\) and ε represent the bridge displacement, velocity, acceleration and strain response.
  2. 2IMF: Intrinsic Mode Function.
  3. 3DWT: Descrete Wavelet Transform, CWT: Continouse Wavelet Transform, EMD: Empirical Mode Decomposition, EEMD: Ensemble Empirical Mode Decomposition, MAF: Moving Average Filter, HHT: Hilbert Huang Transform