scholarly journals Damaged Flexibility Matrix Method for Damage Detection of Frame Buildings

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Luis S. Vaca Oyola ◽  
Mónica R. Jaime Fonseca ◽  
Ramsés Rodríguez Rocha
Keyword(s):  
Damage Detection ◽  
Matrix Method ◽  
Structural Damage ◽  
Numerical Models ◽  
Structural Elements ◽  
Structural Element ◽  
New Approach ◽  
Building Model ◽  
Flexibility Matrix ◽  
Frame Buildings

This study presents the damaged flexibility matrix method (DFM) to identify and determine the magnitude of damage in structural elements of plane frame buildings. Damage is expressed as the increment in flexibility along the damaged structural element. This method uses a new approach to assemble the flexibility matrix of the structure through an iterative process, and it adjusts the eigenvalues of the damaged flexibility matrices of each system element. The DFM was calibrated using numerical models of plane frames of buildings studied by other authors. The advantage of the DFM, with respect to other flexibility-based methods, is that DFM minimizes the adverse effect of modal truncation. The DFM demonstrated excellent accuracy with complete modal information, even when it was applied to a more realistic scenario, considering frequencies and modal shapes measured from the recorded accelerations of buildings stories. The DFM also presents a new approach to simulate the effects of noise by perturbing matrices of flexibilities. This approach can be useful for research on realistic damage detection. The combined effects of incomplete modal information and noise were studied in a ten-story four-bay building model taken from the literature. The ability of the DFM to assess structural damage was corroborated. Application of the proposed method to a ten-story four-bay building model demonstrates its efficiency to identify the flexibility increment in damaged structural elements.

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.

FEM Free Damage Detection of Beam Structures Using the Deflections Estimated by Modal Flexibility Matrix

2021 ◽  
pp. 2150128
Author(s):  
Wen-Yu He ◽  
Wei-Xin Ren ◽  
Lei Cao ◽  
Quan Wang
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Index ◽  
Element Model ◽  
Mode Shapes ◽  
Beam Structures ◽  
Flexibility Matrix ◽  
Damage Quantification ◽  
Modal Flexibility ◽  
The Cost

The deflection of the beam estimated from modal flexibility matrix (MFM) indirectly is used in structural damage detection due to the fact that deflection is less sensitive to experimental noise than the element in MFM. However, the requirement for mass-normalized mode shapes (MMSs) with a high spatial resolution and the difficulty in damage quantification restricts the practicability of MFM-based deflection damage detection. A damage detection method using the deflections estimated from MFM is proposed for beam structures. The MMSs of beams are identified by using a parked vehicle. The MFM is then formulated to estimate the positive-bending-inspection-load (PBIL) caused deflection. The change of deflection curvature (CDC) is defined as a damage index to localize damage. The relationship between the damage severity and the deflection curvatures is further investigated and a damage quantification approach is proposed accordingly. Numerical and experimental examples indicated that the presented approach can detect damages with adequate accuracy at the cost of limited number of sensors. No finite element model (FEM) is required during the whole detection process.

Damage Assessment of a Building Subjected to a Terrorist Attack

2014 ◽  
Vol 17 (11) ◽  
pp. 1693-1704 ◽  
Author(s):  
E.L. Eskew ◽  
S. Jang
Keyword(s):  
Damage Detection ◽  
Damage Assessment ◽  
Structural Damage ◽  
Numerical Models ◽  
Terrorist Attack ◽  
Structural Response ◽  
Structural Condition ◽  
Condition Assessment ◽  
Detection Methods ◽  
Specific Element

An increasing threat of global terrorism has led to concerns about bombings of buildings, which could cause minor to severe structural damage. After such an event, it is important to rapidly assess the damage to the building to ensure safe and efficient emergency response. Current methods of visual inspection and non-destructive testing are expensive, subjective, and time consuming for emergency responders' usage immediately after an attack. On the other hand, vibration-based damage detection methods with wireless smart sensors could provide rapid assessment of structural characteristics with low cost. For blast analysis, structural response is usually determined using a simplified SDOF version of the undamaged structure, such as used in a Pressure-Impulse (P-I) Diagram, or using more complex FEM (finite element method) models. However, the simplified models cannot take into account damage caused by blast focus at a specific location or on a specific element, which may induce local failure leading to potential progressive collapse, and the more complex FEM models take too long to derive applicable results to be effective for a rapid structural assessment. In this paper, a new method to incorporate vibration-based damage detection methods to calculate the multi degree of freedom structural stiffness for determining structural condition is provided to create a framework for the rapid structural condition assessment of buildings after a terrorist attack. The stiffness parameters are generated from the modal analysis of the measured vibration on the building, which are then used in a numerical simulation to determine its structural response from the blast. The calculated structural response is then compared to limit conditions that have been developed from ASCE blast design codes to determine the damage assessment. A laboratory-scale building frame has been employed to validate the developed use of experimentally determined stiffness by comparing the P-I diagram using the experimental stiffness with that from numerical models. The reasonable match between the P-I diagrams from the numerical models and the experiments shows the positive potential of the method. The framework and examples of how to develop a rapid condition assessment are presented.

A flexibility method for structural damage identification using continuous ant colony optimization

2015 ◽  
Vol 11 (2) ◽  
pp. 186-201 ◽  
Author(s):  
Maryam Daei ◽  
S. Hamid Mirmohammadi
Keyword(s):  
Experimental Data ◽  
Damage Detection ◽  
Ant Colony Optimization ◽  
Structural Damage ◽  
Optimization Problem ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Computational Time ◽  
Content Type ◽  
Flexibility Matrix

Purpose – The interest in the ability to detect damage at the earliest possible stage is pervasive throughout the civil engineering over the last two decades. In general, the experimental techniques for damage detection are expensive and require that the vicinity of the damage is known and readily accessible; therefore several methods intend to detect damage based on numerical model and by means of minimum experimental data about dynamic properties or response of damaged structures. The paper aims to discuss these issues. Design/methodology/approach – In this paper, the damage detection problem is formulated as an optimization problem such as to obtain the minimum difference between the numerical and experimental variables, and then a modified ant colony optimization (ACO) algorithm is proposed for solving this optimization problem. In the proposed algorithm, the structural damage is detected by using dynamically measured flexibility matrix, since the flexibility matrix of the structure can be estimated from only the first few modes. The continuous version of ACO is employed as a probabilistic technique for solving this computational problem. Findings – Compared to classical methods, one of the main strengths of this meta-heuristic method is the generally better robustness in achieving global optimum. The efficiency of the proposed algorithm is illustrated by numerical examples. The proposed method enables the deduction of the extent and location of structural damage, while using short computational time and resulting good accuracy. Originality/value – Finding accurate results by means of minimum experimental data, while using short computational time is the final goal of all researches in the structural damage detection methods. In this paper, it gains by applying flexibility matrix in the definition of objective function, and also via using continuous ant colony algorithm as a powerful meta-heuristic techniques in the constrained nonlinear optimization problem.

scholarly journals A Universal Fast Algorithm for Sensitivity-Based Structural Damage Detection

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Q. W. Yang ◽  
J. K. Liu ◽  
C.H. Li ◽  
C.F. Liang
Keyword(s):  
Damage Detection ◽  
Fast Algorithm ◽  
Structural Damage ◽  
Research Area ◽  
Detection Methods ◽  
Structural Damage Detection ◽  
Response Data ◽  
Flexibility Matrix ◽  
New Research ◽  
Measured Response

Structural damage detection using measured response data has emerged as a new research area in civil, mechanical, and aerospace engineering communities in recent years. In this paper, a universal fast algorithm is presented for sensitivity-based structural damage detection, which can quickly improve the calculation accuracy of the existing sensitivity-based technique without any high-order sensitivity analysis or multi-iterations. The key formula of the universal fast algorithm is derived from the stiffness and flexibility matrix spectral decomposition theory. With the introduction of the key formula, the proposed method is able to quickly achieve more accurate results than that obtained by the original sensitivity-based methods, regardless of whether the damage is small or large. Three examples are used to demonstrate the feasibility and superiority of the proposed method. It has been shown that the universal fast algorithm is simple to implement and quickly gains higher accuracy over the existing sensitivity-based damage detection methods.

scholarly journals Unsupervised Structural Damage Detection Technique Based on a Deep Convolutional Autoencoder

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zahra Rastin ◽  
Gholamreza Ghodrati Amiri ◽  
Ehsan Darvishan
Keyword(s):  
Deep Learning ◽  
Damage Detection ◽  
Structural Damage ◽  
Numerical Models ◽  
Health State ◽  
Training Phase ◽  
Structural Damage Detection ◽  
Healthy State ◽  
Convolutional Autoencoder ◽  
Unsupervised Deep Learning

Structural health monitoring (SHM) is a hot research topic with the main purpose of damage detection in a structure and assessing its health state. The major focus of SHM studies in recent years has been on developing vibration-based damage detection algorithms and using machine learning, especially deep learning-based approaches. Most of the deep learning-based methods proposed for damage detection in civil structures are based on supervised algorithms that require data from the healthy state and different damaged states of the structure in the training phase. As it is not usually possible to collect data from damaged states of a large civil structure, using such algorithms for these structures may be impractical. This paper proposes a new unsupervised deep learning-based method for structural damage detection based on convolutional autoencoders (CAEs). The main objective of the proposed method is to identify and quantify structural damage using a CAE network that employs raw vibration signals from the structure and is trained by the signals solely acquired from the healthy state of the structure. The CAE is chosen to take advantage of high feature extraction capability of convolution layers and at the same time use the advantages of an autoencoder as an unsupervised algorithm that does not need data from damaged states in the training phase. Applications on the two numerical models of IASC-ASCE benchmark structure and a grid structure located at the University of Central Florida, as well as the full-scale Tianjin Yonghe Bridge, prove the efficiency of the proposed algorithm in assessing the global health state of the structures and quantifying the damage.

A Coupled Sensitivity Method for Structural Damage Detection

2013 ◽  
Vol 681 ◽  
pp. 271-275
Author(s):  
Jing Li ◽  
Pei Jun Wei
Keyword(s):  
Damage Detection ◽  
Mode Shape ◽  
Structural Damage ◽  
Damage Identification ◽  
Perturbation Approach ◽  
Structural Damage Detection ◽  
Beam Structure ◽  
Flexibility Matrix ◽  
Eigenvalue Sensitivity ◽  
Sensitivity Method

Based on the vibration information, a mixed sensitivity method is presented to identify structural damage by combining the eigenvalue sensitivity with the generalized flexibility sensitivity. The sensitivity of structural generalized flexibility matrix is firstly derived by using the first frequency and the corresponding mode shape only and then the eigenvalue sensitivity together with the generalized flexibility sensitivity are combined to calculate the elemental damage parameters. The presented mixed perturbation approach is demonstrated by a numerical example concerning a simple supported beam structure. It has been shown that the proposed procedure is simple to implement and may be useful for structural damage identification.

scholarly journals Boundary Strategy for Optimization-based Structural Damage Detection Problem using Metaheuristic Algorithms

2020 ◽  
Author(s):  
Ali Kaveh ◽  
Seyed Milad Hosseini ◽  
Ataollah Zaerreza
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Optimization Method ◽  
Metaheuristic Algorithms ◽  
Structural Elements ◽  
Detection Problem ◽  
Vibration Data ◽  
New Strategy ◽  
Optimum Solution ◽  
Better Than

The present paper proposes a new strategy namely Boundary Strategy (BS) in the process of optimization-based damage detection using metaheuristic algorithms. This strategy gradually neutralizes the effects of structural elements that are healthy in the optimization process. BS causes the optimization method to find the optimum solution better than conventional methods that do not use the proposed BS. This technique improves both aspects of the accuracy and convergence speed of the algorithms in identifying and quantifying the damage. To evaluate the performance of the developed strategy, a new damage-sensitive cost function, which is defined based on vibration data of the structure, is optimized utilizing the Shuffled Shepherd Optimization Algorithm (SSOA). Different examples including truss, beam, and frame are investigated numerically in order to indicate the applicability of the proposed technique. The proposed approach is also applied to other well-known optimization algorithms including TLBO, GWO, and MFO. The obtained results illustrate that the proposed method improves the performance of the utilized algorithms in identifying and quantifying of the damaged elements, even for noise-contaminated data.

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