Damage detection at web/flange junction of welded I-section steel beam based on impact-optic technique

2018 ◽  
Author(s):  
Li Niu ◽  
Hongguang Zu ◽  
Ying Xu
Keyword(s):  
Damage Detection ◽  
Steel Beam

Internal longitudinal damage detection in a steel beam using Lamb waves: Simulation and test study

2017 ◽  
Vol 29 (3) ◽  
pp. 411-422 ◽  
Author(s):  
Chan Yik Park ◽  
Anthony N Palazotto ◽  
Chad S Hale ◽  
Hwee Kwon Jung
Keyword(s):  
Damage Detection ◽  
Lamb Waves ◽  
Steel Beam ◽  
Test Study

Localized Damage Detection Algorithm and Implementation on a Large-Scale Steel Beam-to-Column Moment Connection

2015 ◽  
Vol 31 (3) ◽  
pp. 1543-1566 ◽  
Author(s):  
Siavash Dorvash ◽  
Shamim N. Pakzad ◽  
Elizabeth L. LaCrosse ◽  
James M. Ricles ◽  
Ian C. Hodgson
Keyword(s):  
Damage Detection ◽  
Large Scale ◽  
Structural Changes ◽  
Structural Model ◽  
Detection Algorithm ◽  
Steel Beam ◽  
Extreme Loads ◽  
Moment Connection ◽  
Significant Research ◽  
Increasing Cyclic Loading

Civil structures experience loading scenarios ranging from typical ambient excitations to extreme loads induced by natural events that, depending on their intensity, cause damage. It is important to detect damage before it propagates to become detrimental to integrity and functionality of the structure. Significant research efforts are focused on developing damage detection algorithms to diagnose damage from performance and response of the structure. A major challenge in many existing algorithms is in their validation and absence of real-scale implementation. This paper presents implementation of influence-based damage detection algorithm by implementation on a large-scale structural model (steel beam-to-column moment connection) which experiences progressive damage towards collapse of the system through increasing cyclic loading. IDDA utilizes statistical analysis of correlation functions between the structural responses at different locations. It is shown through this implementation that IDDA, accompanied by a statistical framework, can accurately identify structural changes and indicate the intensity of the damage.

scholarly journals Damage Detection Technique for Cold-Formed Steel Beam Structure Based on NSGA-II

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Byung Kwan Oh ◽  
Se Woon Choi ◽  
Hyo Seon Park
Keyword(s):  
Damage Detection ◽  
Failure Mode ◽  
Optimization Technique ◽  
Local Buckling ◽  
Detection Technique ◽  
Steel Beam ◽  
Beam Structure ◽  
Nsga Ii ◽  
Error Functions ◽  
Cold Formed Steel

Cold-formed steel is uniform in quality, suitable for mass production, and light in weight. It is widely used for both structural and nonstructural members in buildings. When it is used in a bending structural member, damage such as local buckling is considered to be more important than general steel members in terms of failure mode. However, preceding studies on damage detection did not consider the failure characteristics of cold-formed beam members. Hence, this paper proposes a damage detection technique that considers the failure mode of local buckling for a cold-formed beam member. The differences between the dynamic characteristics from vibration-based measurements and those from finite element model are set to error functions. The error functions are minimized by the optimization technique NSGA-II. In the damage detection, the location of local damage and the severity of damage are considered variables. The proposed technique was validated through a simulation of damage detection for a cold-formed steel beam structure example.

Use of fiber Bragg grating array and random decrement for damage detection in steel beam

2016 ◽  
Vol 106 ◽  
pp. 348-354 ◽  
Author(s):  
A. Elshafey ◽  
H. Marzouk ◽  
X. Gu ◽  
M. Haddara ◽  
R. Morsy
Keyword(s):  
Damage Detection ◽  
Fiber Bragg Grating ◽  
Bragg Grating ◽  
Steel Beam ◽  
Random Decrement ◽  
Grating Array

scholarly journals Damage Detection in a Steel Beam Based on an Impact-Acoustics Approach

2018 ◽  
Vol 23 (No 3, September 2018) ◽  
pp. 327-331
Keyword(s):  
Damage Detection ◽  
Damage Identification ◽  
Impact Force ◽  
Detection System ◽  
Steel Beam ◽  
Acoustic Detection ◽  
Beam Structure ◽  
Acoustic Signatures ◽  
The Impact ◽  
Non Destructive

Vibration and acoustics travel through a structure under the action of an impact force at a position on that structure. The acoustic detection system comprises either an accelerometer or a microphone to capture the acoustic signatures of the vibrations. Both signatures can be simultaneously collected by an impact hammer test and are analysed by this non-destructive test to obtain more reliable results than those of a single signature. This work investigates the damage identification of the beam structure based on the experimental data collected from the impact hammer test using an accelerometer and a microphone. The damage detection experiment on a steel beam illustrates the reliability of the defect detection using the simultaneous measurements by two sensors.

Antioptimization for comparison of alternative structural models and damage detection

AIAA Journal ◽  
1999 ◽  
Vol 37 ◽  
pp. 857-864
Author(s):  
S. N. Gangadharan ◽  
E. Nikolaidis ◽  
K. Lee ◽  
R. T. Haftka ◽  
R. Burdisso
Keyword(s):  
Damage Detection ◽  
Structural Models
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