scholarly journals Nondestructive Damage Detection Based on Modal Analysis

10.14311/644 ◽  
2004 ◽  
Vol 44 (5-6) ◽  
Author(s):  
T. Plachý ◽  
M. Polák
Keyword(s):  
Experimental Investigation ◽  
Damage Detection ◽  
Modal Analysis ◽  
Damage Identification ◽  
Rc Beams ◽  
Structural Elements ◽  
Composite Bridge ◽  
Rc Slabs ◽  
Concrete Deck

Three studies of damage identification and localization based on methods using experimentally estimated modal characteristics are presented. The results of an experimental investigation of simple structural elements (three RC-beams and three RC-slabs) obtained in the laboratory are compared with the results obtained on a real structure (a composite bridge – a concrete deck supported by steel girders) in situ. 

Monitoring of Deformation of Steel Structure-Roof of Football Stadium Slavia Prague

2012 ◽  
Vol 239-240 ◽  
pp. 622-630 ◽  
Author(s):  
Jiri Litos ◽  
Eva Vejmelková ◽  
Petr Konvalinka
Keyword(s):  
Experimental Investigation ◽  
Numerical Analysis ◽  
Large Scale ◽  
Steel Structure ◽  
Horizontal Direction ◽  
Structural Elements ◽  
Stress Levels ◽  
The Individual ◽  
Football Stadium

Monitoring of deformation of structure in large scale in situ is introduced. The steel roof of football stadium Slavia in Prague is a new progressive structure. Realization of the stadium roof was changed over the project, so it was necessary to verify the rigidity of the steel structure in horizontal direction. The experimental investigation was repeatedly conducted in three different stress levels and than monitoring of behaviour of the individual structural elements of the steel structure was compared with the numerical analysis.

scholarly journals Vibration Response-Based Damage Detection

2021 ◽  
pp. 133-173
Author(s):  
Maria Pina Limongelli ◽  
Emil Manoach ◽  
Said Quqa ◽  
Pier Francesco Giordano ◽  
Basuraj Bhowmik ◽  
...  
Keyword(s):  
Damage Detection ◽  
Health Monitoring ◽  
Material Properties ◽  
Damage Identification ◽  
Dynamic Properties ◽  
Health State ◽  
Structural Elements ◽  
Global Level ◽  
Damage Location

AbstractThis chapter aimed to present different data driven Vibration-Based Methods (VBMs) for Structural Health Monitoring (SHM). This family of methods, widely used for engineering applications, present several advantages for damage identification applications. First, VBMs provide continuous information on the health state of the structure at a global level without the need to access the damaged elements and to know their location. Furthermore, damage can be identified using the dynamic response of the structure measured by sensors non-necessarily located in the proximity of damage and without any prior knowledge about the damage location. By principle, VBMs can identify damage related to changes in the dynamic properties of structures, such as stiffness variations due to modifications in the connections between structural elements, or changes in geometric and material properties. A classification of different VBMs was presented in this chapter. Furthermore, several case studies were presented to demonstrate the potential of these methods.

scholarly journals A New Flexibility Based Damage Index for Damage Detection of Truss Structures

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
M. Montazer ◽  
S. M. Seyedpoor
Keyword(s):  
Damage Detection ◽  
Modal Analysis ◽  
Structural Damage ◽  
Damage Index ◽  
Truss Structures ◽  
Structural Elements ◽  
Reliable Tool ◽  
Flexibility Matrix ◽  
Strain Change ◽  
Flexibility Index

A new damage index, called strain change based on flexibility index (SCBFI), is introduced to locate damaged elements of truss systems. The principle of SCBFI is based on considering strain changes in structural elements, between undamaged and damaged states. The strain of an element is evaluated using the columnar coefficients of the flexibility matrix estimated via modal analysis information. Two illustrative test examples are considered to assess the performance of the proposed method. Numerical results indicate that the method can provide a reliable tool to accurately identify the multiple-structural damage for truss structures.

scholarly journals Bearing Damage Detection of a Reinforced Concrete Plate Based on Sensitivity Analysis and Chaotic Moth-Flame-Invasive Weed Optimization

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5488
Author(s):  
Minshui Huang ◽  
Yongzhi Lei
Keyword(s):  
Sensitivity Analysis ◽  
Reinforced Concrete ◽  
Damage Detection ◽  
Damage Identification ◽  
Structural Elements ◽  
Invasive Weed Optimization ◽  
Invasive Weed ◽  
Modal Strain Energy ◽  
Numerical Example ◽  
Concrete Plate

This article proposes a novel damage detection method based on the sensitivity analysis and chaotic moth-flame-invasive weed optimization (CMF-IWO), which is utilized to simultaneously identify the damage of structural elements and bearings. First, the sensitivity coefficients of eigenvalues to the damage factors of structural elements and bearings are deduced, the regularization technology is used to solve the problem of equation undetermined, meanwhile, the modal strain energy-based index is utilized to detect the damage locations, and the regularization objective function is constructed to quantify the damage severity. Then, for the subsequent procedure of damage detection, CMF-IWO is proposed based on moth-flame optimization and invasive weed optimization as well as chaos theory, reverse learning, and evolutional strategy. The optimization effectiveness of the hybrid algorithm is verified by five benchmark functions and a damage identification numerical example of a simply supported beam; the results demonstrate it is of great global search ability and higher convergence efficiency. After that, a numerical example of an 8-span continuous beam and an experimental reinforced concrete plate are both adopted to evaluate the proposed damage identification method. The results of the numerical example indicate that the proposed method can locate and quantify the damage of structural elements and bearings with high accuracy. Furthermore, the outcomes of the experimental example show that despite the existence of some errors and uncertain factors, the method still obtains an acceptable result. Generally speaking, the proposed method is proved that it is of good feasibility.

scholarly journals Clustering Elements of Truss Structures for Damage Identification by CBO

2020 ◽  
Author(s):  
Mohammad Hosein Talebpour ◽  
Younes Goudarzi ◽  
Mehrdad Sharifnezhad
Keyword(s):  
Damage Detection ◽  
Damage Identification ◽  
Dynamic Properties ◽  
Heuristic Method ◽  
Search Space ◽  
Truss Structures ◽  
Local Optimum ◽  
Structural Elements ◽  
Modal Strain Energy ◽  
Damage Location

The number of structural elements plays a significant role in detecting damage location and severity; such methods have sometimes failed to provide correct solutions due to the entrapment of damage detection algorithms in the local optimum. To resolve this problem, this study proposed the simultaneous use of mathematical and statistical methods to narrow down the search space. To this end, a two-step damage detection method was proposed. In the first step, the structural elements were initially divided into different clusters using the k-means method. Subsequently, the possibly damaged elements of each cluster were identified. In the second step, the elements selected in the first step were placed in a new set, and a process was applied to identify their respective damage location and severity. Thus, the proposed method reduced the search space as well as the possibility of entrapment in the local optimum. Other advantages of the proposed method include the use of fewer dynamic properties. Accordingly, by narrowing down the search space and the dimensions of the system for governing equations, the proposed method could significantly increase the chance of obtaining favorable results in structures with many elements and those with few vibration modes. A meta-heuristic method, called the colliding bodies optimization (CBO), was used in the proposed damage detection optimization algorithm. The optimization problem was based on the modal strain energy equations. According to the results, the proposed method was able to detect the location and severity of damage, even at its slightest percentage.

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.

scholarly journals Development of a Novel Damage Detection Framework for Truss Railway Bridges Using Operational Acceleration and Strain Response

Vibration ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 422-445
Author(s):  
Md Riasat Azim ◽  
Mustafa Gül
Keyword(s):  
Damage Detection ◽  
Damage Identification ◽  
Numerical Study ◽  
Damage Index ◽  
Strain Analysis ◽  
Time History ◽  
Principal Component ◽  
Element Model ◽  
Railway Bridges ◽  
Truss Bridge

Railway bridges are an integral part of any railway communication network. As more and more railway bridges are showing signs of deterioration due to various natural and artificial causes, it is becoming increasingly imperative to develop effective health monitoring strategies specifically tailored to railway bridges. This paper presents a new damage detection framework for element level damage identification, for railway truss bridges, that combines the analysis of acceleration and strain responses. For this research, operational acceleration and strain time-history responses are obtained in response to the passage of trains. The acceleration response is analyzed through a sensor-clustering-based time-series analysis method and damage features are investigated in terms of structural nodes from the truss bridge. The strain data is analyzed through principal component analysis and provides information on damage from instrumented truss elements. A new damage index is developed by formulating a strategy to combine the damage features obtained individually from both acceleration and strain analysis. The proposed method is validated through a numerical study by utilizing a finite element model of a railway truss bridge. It is shown that while both methods individually can provide information on damage location, and severity, the new framework helps to provide substantially improved damage localization and can overcome the limitations of individual analysis.

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