scholarly journals VIBRATION-BASED STRUCTURAL DAMAGE DETECTION TECHNIQUES: A REVIEW

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Akpabot Akpabot ◽  
Anthony Ede ◽  
Oluwarotimi Olofinnade ◽  
Abimbola Odetoyan
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Structural Integrity ◽  
Damage Identification ◽  
Practical Application ◽  
Engineering Structures ◽  
Detection Techniques ◽  
The Time Domain ◽  
Stiffness And Damping ◽  
Early Damage

Damage in infrastructure can be as a result of its degenerating state under service loads or after exposure to impact loads such as earthquakes. Early damage detection is essential to preventing failure and ensure the integrity and safety of structures. Damages lead to changes in the geometric and material properties like mass, stiffness, and damping, and influences the response behavior of the structure. It has been proven that vibration-based damage detection technique is an efficient means of damage identification and assessing structural integrity. This review article examines conventional vibration-based damage detection techniques. It highlights the importance of early damage detection as a means of ensuring infrastructural safety, reliability and maintenance. Damage detection techniques like the time domain methods, frequency domain and modal domain methods have been developed and constantly evolving to meet the existing challenge of identifying structural damages. The practical application is still minimal, hence more research works are necessary for damage detection in large civil engineering structures.

scholarly journals Crack Detection in Folded Plates With Back-Propagated Artificial Neural Network

2021 ◽  
Author(s):  
Can Gonenli ◽  
Oguzhan Das ◽  
Duygu Bagci Das
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Damage Detection ◽  
Crack Detection ◽  
Structural Integrity ◽  
Engineering Structures ◽  
Detection Techniques ◽  
Detection Model ◽  
Artificial Neural ◽  
Destructive Methods

Abstract Engineering structures may face various damages such as crack, delamination, and fatigue in several circumstances. Localizing such damages becomes essential to understand the health of the structures since they may not be able to operate anymore. Among the damage detection techniques, non-destructive methods are considerably more preferred than destructive methods since damage can be located without affecting the structural integrity. However, these methods have several drawbacks in terms of detecting abilities, time consumption, cost, and hardware or software requirements. Employing artificial intelligence techniques could overcome such issues and could provide a powerful damage detection model if the technique is utilized correctly. In this study, the crack localization in flat and folded plate structures has been conducted by employing a Back-propagated Artificial Neural Network (BPANN). For this purpose, cracks with 18 different dimensions have been modeled in flat and four different folded structures by utilizing the Finite Element Method. The dataset required to perform the crack localization procedure includes the first ten natural frequencies of all structures as input variables. As output variables, the dataset contains a total of 500 crack locations for five structures. It is concluded that the BPANN can localize all cracks with an average accuracy of 95.12%.

Structural Damage Detection Using Curvature Mode Difference Curve

2011 ◽  
Vol 250-253 ◽  
pp. 1248-1251 ◽  
Author(s):  
Hang Jing ◽  
Ling Ling Jia ◽  
Yi Zhao
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Numerical Differentiation ◽  
Engineering Structures ◽  
System Parameters ◽  
Numerical Studies ◽  
Damage Indicator ◽  
Structural Damage Identification ◽  
Changing Rate

Damage detection in civil engineering structures using the dynamic system parameters has become an important area of research. The sensitivity of damage indicator is of great value to structural damage identification. The curvature mode is an excellent parameter in damage detection of structures, while in case that certain curvature mode curve can’t show existence of damage. In this paper, numerical studies are conducted to demonstrate the deficiency of curvature mode to damage detection. Then a new damage indicator called “curvature mode changing rate” (CMCR) is introduced which is processed by numerical differentiation of curvature mode curve. The simulation results show that the new index is superior to curvature mode for structural damage identification, and it is still sensitive to the damaged location in the mode node.

scholarly journals Use of Bispectrum Analysis to Inspect the Non-Linear Dynamic Characteristics of Beam-Type Structures Containing a Breathing Crack

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1177
Author(s):  
Li Cui ◽  
Hao Xu ◽  
Jing Ge ◽  
Maosen Cao ◽  
Yangmin Xu ◽  
...  
Keyword(s):  
Damage Detection ◽  
Dynamic Characteristics ◽  
Structural Damage ◽  
Damage Identification ◽  
Crack Depth ◽  
Excitation Frequency ◽  
Breathing Crack ◽  
Engineering Structures ◽  
Linear Dynamic ◽  
Non Linear

A breathing crack is a typical form of structural damage attributed to long-term dynamic loads acting on engineering structures. Traditional linear damage identification methods suffer from the loss of valuable information when structural responses are essentially non-linear. To deal with this issue, bispectrum analysis is employed to study the non-linear dynamic characteristics of a beam structure containing a breathing crack, from the perspective of numerical simulation and experimental validation. A finite element model of a cantilever beam is built with contact elements to simulate a breathing crack. The effects of crack depth and location, excitation frequency and magnitude, and measurement noise on the non-linear behavior of the beam are studied systematically. The result demonstrates that bispectral analysis can effectively identify non-linear damage in different states with strong noise immunity. Compared with existing methods, the bispectral non-linear analysis can efficiently extract non-linear features of a breathing crack, and it can overcome the limitations of existing linear damage detection methods used for non-linear damage detection. This study’s outcome provides a theoretical basis and a paradigm for damage identification in cracked structures.

A State-of-the-Art Review on FRF-Based Structural Damage Detection: Development in Last Two Decades and Way Forward

2021 ◽  
Author(s):  
Saranika Das ◽  
Koushik Roy
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Excitation Frequency ◽  
Mode Shapes ◽  
Computational Time ◽  
Structural Damage Detection ◽  
Monitoring Methods ◽  
Detection Techniques ◽  
Noise Contamination

Vibration-based damage detection techniques receive wide attention of the research community in recent years to overcome the limitations of conventional structural health monitoring methods. The modal parameters, namely, natural frequencies, mode shapes, transmissibility, frequency response function (FRF), and other damage sensitive features are usually employed to identify damage in a structure. The main objective of this review is to generate a detailed understanding of FRF-based techniques and to study their performance in terms of advantage, accuracy, and limitations in structural damage detection. This paper also reviews various approaches to develop methodologies in terms of efficiency and computational time. The study observed that excitation frequency, location of application of excitation, type of sensor, number of measurement locations, noise contamination in FRF data, selection of frequency range for simulation, weighting and numerical techniques to solve the over-determined set of equations influence the effectiveness of damage identification procedure. Limitations and future prospects have also been addressed in this paper. The content of this paper aims to guide researchers in developing formulations, updating models, and improving results in the field of FRF-based damage identification.

Sparse damage detection via the elastic net method using modal data

2021 ◽  
pp. 147592172110219
Author(s):  
Rongrong Hou ◽  
Xiaoyou Wang ◽  
Yong Xia
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Measurement Data ◽  
Elastic Net ◽  
Sensitivity Matrix ◽  
Regularization Technique ◽  
Modal Data ◽  
Regularization Techniques ◽  
Net Method

The l1 regularization technique has been developed for damage detection by utilizing the sparsity feature of structural damage. However, the sensitivity matrix in the damage identification exhibits a strong correlation structure, which does not suffice the independency criteria of the l1 regularization technique. This study employs the elastic net method to solve the problem by combining the l1 and l2 regularization techniques. Moreover, the proposed method enables the grouped structural damage being identified simultaneously, whereas the l1 regularization cannot. A numerical cantilever beam and an experimental three-story frame are utilized to demonstrate the effectiveness of the proposed method. The results showed that the proposed method is able to accurately locate and quantify the single and multiple damages, even when the number of measurement data is much less than the number of elements. In particular, the present elastic net technique can detect the grouped damaged elements accurately, whilst the l1 regularization method cannot.

Structural Damage Assessment Using Output-Only Measurement: Localization and Quantification

2013 ◽  
Author(s):  
Chin-Hsiung Loh ◽  
Min-Hsuan Tseng ◽  
Shu-Hsien Chao
Keyword(s):  
Damage Detection ◽  
Damage Assessment ◽  
Structural Damage ◽  
Damage Identification ◽  
Model Updating ◽  
Null Space ◽  
Singular Spectrum Analysis ◽  
Damage Index ◽  
Computation Efficiency ◽  
Output Only

One of the important issues to conduct the damage detection of a structure using vibration-based damage detection (VBDD) is not only to detect the damage but also to locate and quantify the damage. In this paper a systematic way of damage assessment, including identification of damage location and damage quantification, is proposed by using output-only measurement. Four level of damage identification algorithms are proposed. First, to identify the damage occurrence, null-space and subspace damage index are used. The eigenvalue difference ratio is also discussed for detecting the damage. Second, to locate the damage, the change of mode shape slope ratio and the prediction error from response using singular spectrum analysis are used. Finally, to quantify the damage the RSSI-COV algorithm is used to identify the change of dynamic characteristics together with the model updating technique, the loss of stiffness can be identified. Experimental data collected from the bridge foundation scouring in hydraulic lab was used to demonstrate the applicability of the proposed methods. The computation efficiency of each method is also discussed so as to accommodate the online damage detection.

scholarly journals Use of Time- and Frequency-Domain Approaches for Damage Detection in Civil Engineering Structures

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
V. H. Nguyen ◽  
J. Mahowald ◽  
S. Maas ◽  
J.-C. Golinval
Keyword(s):  
Damage Detection ◽  
Frequency Domain ◽  
Prestressed Concrete ◽  
Civil Engineering ◽  
Damage Identification ◽  
Real Life ◽  
Hankel Matrix ◽  
Principal Component ◽  
Engineering Structures ◽  
Civil Engineering Structures

The aim of this paper is to apply both time- and frequency-domain-based approaches on real-life civil engineering structures and to assess their capability for damage detection. The methodology is based on Principal Component Analysis of the Hankel matrix built from output-only measurements and of Frequency Response Functions. Damage detection is performed using the concept of subspace angles between a current (possibly damaged state) and a reference (undamaged) state. The first structure is the Champangshiehl Bridge located in Luxembourg. Several damage levels were intentionally created by cutting a growing number of prestressed tendons and vibration data were acquired by the University of Luxembourg for each damaged state. The second example consists in reinforced and prestressed concrete panels. Successive damages were introduced in the panels by loading heavy weights and by cutting steel wires. The illustrations show different consequences in damage identification by the considered techniques.

Review on Damage Identification and Diagnosis Research of Civil Engineering Structure

2014 ◽  
Vol 1006-1007 ◽  
pp. 34-37 ◽  
Author(s):  
Hong Ni ◽  
Ming Hui Li ◽  
Xi Zuo
Keyword(s):  
Structural Damage ◽  
Civil Engineering ◽  
Damage Identification ◽  
Engineering Structures ◽  
Engineering Structure ◽  
Civil Engineering Structure ◽  
Structure Damage ◽  
Development Direction ◽  
Structural Damage Identification ◽  
Civil Engineering Structures

This paper first describes the importance of structural damage identification and diagnosis in civil engineering, and introduces domestic and foreign status of damage identification and diagnosis methods, and on the basis of this, it also introduces all kinds of methods for damage identification and diagnosis of civil engineering structures, and finally puts forward the development direction of civil engineering structure damage identification and diagnosis.

A Vibration-Based Structural Damage Detection Method and its Applications to Engineering Structures

2011 ◽  
Author(s):  
K. He ◽  
W. D. Zhu
Keyword(s):  
Damage Detection ◽  
Iterative Algorithm ◽  
Structural Damage ◽  
Detection Method ◽  
New Physics ◽  
Logistic Function ◽  
Frame Structure ◽  
Engineering Structures ◽  
System Equations ◽  
Extent Of Damage

Two major challenges associated with a vibration-based damage detection method using changes in natural frequencies are addressed: accurate modeling of structures and the development of a robust inverse algorithm to detect damage, which are defined as the forward and inverse problems, respectively. To resolve the forward problem, new physics-based finite element modeling techniques are developed for fillets in thin-walled beams and for bolted joints, so that complex structures can be accurately modeled with a reasonable model size. To resolve the inverse problem, a logistic function transformation is introduced to convert the constrained optimization problem to an unconstrained one, and a robust iterative algorithm using the Levenberg-Marquardt method is developed to accurately detect the locations and extent of damage. The new methodology can ensure global convergence of the iterative algorithm in solving under-determined system equations and deal with damage detection problems with relatively large modeling error and measurement noise. It is applied to various engineering structures including lightning masts, a space frame structure and one of its components, and a pipeline. The exact locations and extent of damage can be detected in the numerical simulation, and the locations and extent of damage can be successfully detected in experimental damage detection.

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