Performance Assessment of Vibration Parameters as Damage Indicators for Bridge Structures under Ambient Excitation

An automatic bridge damage diagnostics method using empirical mode decomposition based health indicators and neuro‐fuzzy classification

“…Indeed, the sensors can provide thousands of values of the bridge acceleration at each time second, whereas features can extract relevant information regarding the bridge health state, by merging the thousands sensor values into a lumped assessment. Statistical features (such as mean value, standard deviation, kurtosis and root mean square), frequency‐domain features (such as peaks and amplitudes of the bridge frequencies that are obtained by using the fast Fourier transform [FFT]) and vibration parameters (such as peak ground acceleration, Arias intensity and cumulative absolute velocity) are assessed at each τ time step in order to extract information from the free‐vibration behaviour of the bridge 28,41,49 . The assessment of reliable features can be susceptible to the non‐stationarity of the bridge vibrations.…”

“…In this way, statistical, frequency‐based and vibration parameters of the bridge are evaluated in order to assess the health state of the bridge. In fact, changes in statistical and vibration features of the bridge behaviour can identify a damage of the bridge structure: An increase of the bridge vibration behaviour can be caused by a reduction of bridge stiffness, which leads to a lower structural ability in resisting to external excitation in a static and stable manner 28 . Similarly, a change in the frequency‐based feature, which estimates modal and vibration characteristics of the bridge, can represent changes in bridge physical characteristics, such as stiffness and mass 33,37,40 .…”

A State of the Art Review of Modal-Based Damage Detection in Bridges: Development, Challenges, and Solutions

“…Moughty & Casas [138] assessed the damage sensitivity of a number of vibration parameters extracted from a progressive damage test on the S101 Bridge in Austria subjected to ambient excitation [139]. The parameters assessed were: Max Peak-to-Peak Acceleration; Sustained Maximum Acceleration [140]; Mean Period [141]; Mean Frequency; Cumulative Absolute Velocity [142]; Arias Intensity [143]; Destructive Potential Factor [144]; and Vibration Intensity (in Vibrars) [145].…”

“…In this regard, Moughty & Casas [138] assessed numerous vibration-based DSFs on the S101 Bridge in Austria and discovered that DSFs that incorporated a vibration energy variable with an empirical frequency denominator exhibited significant damage sensitivity and resolution. Vibration-based DSFs were also shown to be suitable for use in real-time condition assessments by Santos et al [149] through the use of robust online clustering on the Samora Machel Bridge.…”

Structural Health Monitoring (SHM) of Civil Structures

“…Finally, for the advancement of SHM in bridges, this paper emphasized the necessity to explore and investigate alternative options to modal-based DSFs. In this regard, Moughty & Casas [138] assessed numerous vibration-based DSFs on the S101 Bridge in Austria and discovered that DSFs that incorporated a vibration energy variable with an empirical frequency denominator exhibited significant damage sensitivity and resolution. Vibration-based DSFs were also shown to be suitable for use in real-time condition assessments by Santos et al [149] through the use of robust online clustering on the Samora Machel Bridge.…”