Damage Detection of Functionally Graded Euler-Bernoulli Beam Based on Element Modal Strain Energy Equivalence Index

2018 ◽  
Vol 10 (7) ◽  
pp. 1036-1044 ◽  
Author(s):  
De-Lei Yang ◽  
Zhong-Ming Hu ◽  
Chun-Yan Kang ◽  
Jia Liang
Keyword(s):  
Damage Detection ◽  
Strain Energy ◽  
Functionally Graded ◽  
Bernoulli Beam ◽  
Modal Strain Energy ◽  
Energy Equivalence ◽  
Euler Bernoulli Beam

On the study of element modal strain energy sensitivity for damage detection of functionally graded beams

2019 ◽  
Vol 224 ◽  
pp. 110989 ◽  
Author(s):  
Delei Yang ◽  
Chunyan Kang ◽  
Zhongming Hu ◽  
Bailong Ye ◽  
Ping Xiang
Keyword(s):  
Damage Detection ◽  
Strain Energy ◽  
Functionally Graded ◽  
Modal Strain Energy

Employing Surface Roughness for Bridge-Vehicle Interaction Based Damage Detection

2011 ◽  
Author(s):  
Vesna Jaksic ◽  
Vikram Pakrashi ◽  
Alan O’Connor
Keyword(s):  
Surface Roughness ◽  
Damage Detection ◽  
Flexural Rigidity ◽  
Single Point ◽  
Point Load ◽  
Ride Quality ◽  
Breathing Crack ◽  
Bernoulli Beam ◽  
Statistical Parameters ◽  
Euler Bernoulli Beam

Damage detection and Structural Health Monitoring (SHM) for bridges employing bridge-vehicle interaction has created considerable interest in recent times. In this regard, a significant amount of work is present on the bridge-vehicle interaction models and on damage models. Surface roughness on bridges is typically used for detailing models and analyses are present relating surface roughness to the dynamic amplification of response of the bridge, the vehicle or to the ride quality. This paper presents the potential of using surface roughness for damage detection of bridge structures through bridge-vehicle interaction. The concept is introduced by considering a single point observation of the interaction of an Euler-Bernoulli beam with a breathing crack traversed by a point load. The breathing crack is treated as a nonlinear system with bilinear stiffness characteristics related to the opening and closing of crack. A uniform degradation of flexural rigidity of an Euler-Bernoulli beam traversed by a point load is also considered in this regard. The surface roughness of the beam is essentially a spatial representation of some spectral definition and is treated as a broadband white noise in this paper. The mean removed residuals of beam response are analyzed to estimate damage extent. Uniform velocity and acceleration conditions of the traversing load are investigated for the appropriateness of use. The detection and calibration of damage is investigated through cumulant based statistical parameters computed on stochastic, normalized responses of the damaged beam due to passages of the load. Possibilities of damage detection and calibration under benchmarked and non-benchmarked cases are discussed. Practicalities behind implementing this concept are also considered.

scholarly journals Damage Detection of a Continuous Bridge from Response of a Moving Vehicle

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Z. H. Li ◽  
F. T. K. Au
Keyword(s):  
Genetic Algorithm ◽  
Damage Detection ◽  
Strain Energy ◽  
Identification Problem ◽  
Modal Strain Energy ◽  
Moving Vehicle ◽  
Second Stage ◽  
Damage Location ◽  
Damage Indicator ◽  
Vertical Accelerations

This paper presents a multistage multipass method to identify the damage location of a continuous bridge from the response of a vehicle moving on the rough road surface of the bridge. The vehicle runs over the bridge several times at different velocities and the corresponding responses of the vehicle can be obtained. The vertical accelerations of the vehicle running on the intact and damaged bridges are used for identification. The multistage damage detection method is implemented by the modal strain energy based method and genetic algorithm. The modal strain energy based method estimates the damage location by calculating a damage indicator from the frequencies extracted from the vehicle responses of both the intact and damaged states of the bridge. At the second stage, the identification problem is transformed into a global optimization problem and is solved by genetic algorithm techniques. For each pass of the vehicle, the method can identify the location of the damage until it is determined with acceptable accuracy. A two-span continuous bridge is used to verify the method. The numerical results show that this method can identify the location of damage reasonably well.

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