scholarly journals Damage Detection of 2D Frame Structures using Incomplete Measurements by Optimization Procedure and Model Reduction

2018 ◽  
Vol 2 (3) ◽  
pp. 164 ◽  
Author(s):  
Du Dinh-Cong ◽  
Sang Pham-Duy ◽  
Trung Nguyen-Thoi
Keyword(s):  
Damage Detection ◽  
Objective Function ◽  
Model Reduction ◽  
Structural Damage ◽  
Optimization Procedure ◽  
Element Model ◽  
Frame Structure ◽  
Frame Structures ◽  
Damage Scenarios ◽  
Modal Data

The article presents an effective method for damage assessment of 2D frame structures using incomplete modal data by optimization procedure and model reduction technique. In this proposed method, the structural damage detection problem is defined as an optimization problem, in which a hybrid objective function and the damage severity of all elements are considered as the objective function and the continuous design variables, respectively. The teaching-learning-based optimization (TLBO) algorithm is applied as a powerful optimization tool to solve the problem. In addition, owing to the use of incomplete measurements, an improved reduction system (IRS) technique is adopted to reduce the mass and stiffness matrices of structural finite element model. The efficiency and robustness of the proposed method are validated with a 4-storey (3 bay) steel plane frame involving several damage scenarios without and with measurement noise. The obtained results clearly demonstrate that even the incompleteness and noisy environment of measured modal data, the present method can work properly in locating and estimating damage of the frame structure by utilizing only the first five incomplete modes' data.  This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Flexibility-Based Objective Functions for Constrained Optimization Problems on Structural Damage Detection

2011 ◽  
Vol 186 ◽  
pp. 383-387 ◽  
Author(s):  
Xi Chen ◽  
Ling Yu
Keyword(s):  
Damage Detection ◽  
Constrained Optimization ◽  
Objective Function ◽  
Structural Damage ◽  
Optimization Problems ◽  
Objective Functions ◽  
Structural Damage Detection ◽  
Constrained Optimization Problems ◽  
Modal Assurance Criterion ◽  
Damage Scenarios

Based on concepts of structural modal flexibility and modal assurance criterion (MAC), a new objective function is defined and studied for constrained optimization problems (COP) on structural damage detection (SDD) in this paper. Compared with traditionally objective function, which is defined based on natural frequencies and MAC, effect of objective functions on robustness of SDD calculation is evaluated through numerical simulation of a 2-storey rigid frame. Structural damages are identified by solving the COP on SDD based on an improved particle swarm optimization (IPSO) algorithm. Weak and multiple damage scenarios are mainly considered in various noise conditions. Some illustrated results show that the newly defined objective function is better than the traditional ones. It can be used to identify the damage locations but also to quantify the severity of weak and multiple damages in measurement noise conditions.

scholarly journals Charged System Search Algorithm Utilized for Structural Damage Detection

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Zahra Tabrizian ◽  
Gholamreza Ghodrati Amiri ◽  
Morteza Hossein Ali Beigy
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Mechanics ◽  
Search Algorithm ◽  
Element Model ◽  
Reduction Factor ◽  
Computational Time ◽  
Damage Scenarios ◽  
Charged System Search ◽  
Charged System

This paper presents damage detection and assessment methodology based on the changes in dynamic parameters of a structural system. The method is applied at an element level using a finite element model. According to continuum damage mechanics, damage is represented by a reduction factor of the element stiffness. A recently developed metaheuristic optimization algorithm known as the charged system search (CSS) is utilized for locating and quantifying the damaged areas of the structure. In order to demonstrate the abilities of this method, three examples are included comprising of a 10-elements cantilever beam, a Bowstring plane truss, and a 39-element three-story three-bay plane frame. The possible damage types in structures by considering several damage scenarios and using incomplete modal data are modeled. Finally, results are obtained from the CSS algorithm by detecting damage in these structures and compared to the results of the PSOPC algorithm. In addition, the effect of noise is shown in the results of the CSS algorithm by suitable diagrams. As is illustrated, this method has acceptable results in the structural detection damage with low computational time.

scholarly journals A New Damage Detection Method: Big Bang-Big Crunch (BB-BC) Algorithm

2013 ◽  
Vol 20 (4) ◽  
pp. 633-648 ◽  
Author(s):  
Zahra Tabrizian ◽  
Ehsan Afshari ◽  
Gholamreza Ghodrati Amiri ◽  
Morteza Hossein Ali Beigy ◽  
Seyed Mohammad Pourhoseini Nejad
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Element Model ◽  
Optimization Method ◽  
Big Bang ◽  
Continuous Variable ◽  
Particle Swarm Optimizer ◽  
Damage Scenarios ◽  
Damage Location ◽  
Big Crunch

The present paper aims to explore damage assessment methodology based on the changes in dynamic parameters properties of vibration of a structural system. The finite-element model is used to apply at an element level. Reduction of the element stiffness is considered for structural damage. A procedure for locating and quantifying damaged areas of the structure based on the innovative Big Bang-Big Crunch (BB-BC) optimization method is developed for continuous variable optimization. For verifying the method a number of damage scenarios for simulated structures have been considered. For the purpose of damage location and severity assessment the approach is applied in three examples by using complete and incomplete modal data. The effect of noise on the accuracy of the results is investigated in some cases. A great unbraced frame with a lot of damaged element is considered to prove the ability of proposed method. More over BB-BC optimization method in damage detection is compared with particle swarm optimizer with passive congregation (PSOPC) algorithm. This work shows that BB-BC optimization method is a feasible methodology to detect damage location and severity while introducing numerous advantages compared to referred method.

Experimental investigation on multi-objective multi-type sensor optimal placement for structural damage detection

2018 ◽  
Vol 18 (3) ◽  
pp. 882-901 ◽  
Author(s):  
Jian-Fu Lin ◽  
You-Lin Xu ◽  
Sheng Zhan
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Structural Damage ◽  
Sensor Placement ◽  
Element Model ◽  
Frame Structure ◽  
Optimal Placement ◽  
Optimal Sensor Placement ◽  
Damage Scenarios ◽  
The Finite Element Model

An optimal sensor placement with multiple types of sensors could provide informative data of a structure to facilitate its structural damage detection. A response covariance-based multi-objective multi-type sensor optimal placement method has been thus developed. To validate this method, an experimental investigation was designed and performed in terms of a nine-bay three-dimensional frame structure, and the experimental details and results are presented in this article. The frame structure was first built, and a finite element model of the frame structure was constructed and updated. The proposed method was then applied to the finite element model to find the optimal sensor placement configuration. The multi-type sensors were then installed on the frame structure according to the determined optimal sensor numbers and positions. Different damage scenarios were then generated on the frame structure. These damage scenarios covered single and multiple damage cases occurring at different locations with different damage severities. A series of experiments, including the optimal and non-optimal sensor placements, were finally carried out, and the measurement data were used together with the finite element model to identify damage quantitatively. The identification results show that the optimal multi-type sensor placement determined by the proposed method could provide accurate damage localization and satisfactory damage quantitation and that the optimal sensor placement yielded better damage identification than the non-optimal sensor placement.

Damage Identification in Frame Structures Based on FE Model Updating

2010 ◽  
Vol 132 (5) ◽  
Author(s):  
Ling Yu ◽  
Tao Yin
Keyword(s):  
Objective Function ◽  
Model Updating ◽  
Trust Region ◽  
Nonlinear Least Squares ◽  
Element Model ◽  
Frame Structure ◽  
Mode Shapes ◽  
Frame Structures ◽  
Fe Model ◽  
Bound Constraints

This paper proposed a practical damage detection method for frame structures based on finite element model-updating techniques. An objective function is defined as minimizing the discrepancies between the experimental and analytical modal parameters (namely, natural frequencies and mode shapes), which is set as a nonlinear least-squares problem with bound constraints. Unlike the commonly used line-search methods, the trust-region approach, a simple yet very powerful concept for minimization, is employed in order to make the optimization process more robust and reliable. Noting the objective function may sometimes be underdetermined for complex structures due to a relatively larger number of potential damaged elements, this paper attempts to propose a simple and convenient solution by expanding the original objective function. Moreover, the relative weighting scheme between different parts in the objective function is also investigated. One numerical two-story portal frame structure and two laboratory-tested frame structures, including a simple three-story steel frame structure and a more complex frame structure with bolted joints, are all adopted to evaluate the efficiency of the proposed technique. Some important issues about the application of the proposed method are also discussed in this paper.

scholarly journals A Combined Modal Correlation Criterion for Structural Damage Identification with Noisy Modal Data

2018 ◽  
Vol 2018 ◽  
pp. 1-20 ◽  
Author(s):  
Manolis Georgioudakis ◽  
Vagelis Plevris
Keyword(s):  
Structural Damage ◽  
High Efficiency ◽  
Damage Identification ◽  
Model Updating ◽  
Search Algorithm ◽  
Element Model ◽  
Identification Problem ◽  
Damage Scenarios ◽  
Modal Data ◽  
Structural Damage Identification

Structural damage identification is a scientific field that has attracted a lot of interest in the scientific community during the recent years. There have been many studies intending to find a reliable method to identify damage in structural elements both in location and extent. Most damage identification methods are based on the changes of dynamic characteristics and static responses, but the incompleteness of the test data is a great obstacle for both. In this paper, a structural damage identification method based on the finite element model updating is proposed, in order to provide the location and the extent of structural damage using incomplete modal data of a damaged structure. The structural damage identification problem is treated as an unconstrained optimization problem which is solved using the differential evolution search algorithm. The objective function used in the optimization process is based on a combination of two modal correlation criteria, providing a measure of consistency and correlation between estimations of mode shape vectors. The performance and robustness of the proposed approach are evaluated with two numerical examples: a simply supported concrete beam and a concrete frame under several damage scenarios. The obtained results exhibit high efficiency of the proposed approach for accurately identifying the location and extent of structural damage.

New structural damage-identification method using modal updating and model reduction

2014 ◽  
Vol 229 (6) ◽  
pp. 1041-1059 ◽  
Author(s):  
Mir M Ettefagh ◽  
Hossein Akbari ◽  
Keivan Asadi ◽  
Farshid Abbasi
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Damage Detection ◽  
Model Reduction ◽  
Traditional Method ◽  
Structural Damage ◽  
Model Updating ◽  
Element Model ◽  
Detection Algorithm ◽  
Detection Methods

Early prediction of damages using vibration signal is essential in avoiding the failure in structures. Among different damage-detection approaches, the finite-element model updating and modal analysis-based methods are of most importance due to their applicability and feasibility. Owing to some restrictions in nodal measurements in experimental cases, finite-element model reduction is an indispensable part of fault-detection methods. Even though model reduction of dynamic systems leads to the less complicated models, an improved convergence rate and acceptable accuracy are highly required for a successful structural health monitoring of the real complex systems. In this paper, the aim is to design a damage-detection algorithm based on a new model updating method, which has a faster rate of convergence and higher accuracy. Then the proposed method is applied on a simulated damaged beam considering different noise levels to see how capable the method is in dealing with noise-corrupted data. Finally, the experimentally extracted data from a cracked beam in a real noisy condition are used to evaluate the efficiency of the proposed method in identifying the damages in a beam-like structure. It is concluded that the identification of the damages by the proposed method is encouraging and robust to the noise compared with the traditional method. Also, the proposed method converges faster and is more accurate in identifying damage than the traditional method.

A DE-Based Algorithm for Structural Damage Detection

2014 ◽  
Vol 919-921 ◽  
pp. 303-307 ◽  
Author(s):  
Yong Ming Fu ◽  
Ling Yu
Keyword(s):  
Damage Detection ◽  
Objective Function ◽  
Structural Damage ◽  
Model Updating ◽  
Heuristic Method ◽  
Identification Accuracy ◽  
Frame Structure ◽  
Mode Shapes ◽  
Fe Model ◽  
Structural Damage Detection

The development of a methodology for the accurate and reliable assessment of structural damages, as one crucial step in the structural health monitoring (SHM) field, is very important to ensure the safety, integrity and stability of structures. An improved adaptive differential evolution (IADE) algorithm is proposed for structural damage detection (SDD) based on DE algorithm and FE model-updating techniques. An objective function is defined as minimizing the discrepancies between the experimental and analytical modal parameters (namely, natural frequencies and mode shapes). It is set as a nonlinear least-squares problem with bound constraints. Unlike the commonly used line-search methods, the IADE approach, a heuristic method for the direct search of the optimal point of the given objective function, is employed to make the optimization process more robust and reliable. Some numerical simulations for single and multiple damage cases of a 25-bar space truss frame structure have been conducted for evaluation on the reliability and robustness of the proposed method. The illustrated results show that the IADE algorithm is very effective for SDD. It can not only locate the structural damages but also quantify the severity of damages. Regardless of slight damage or multiple damages, the identification accuracy is very high and noise immunity is better, which shows that the IADE algorithm is feasible and effective for SDD.

Optimal Sensor Placement Algorithm for Structural Damage Identification

2020 ◽  
Vol 14 (1) ◽  
pp. 69-81
Author(s):  
C.H. Li ◽  
Q.W. Yang
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Sensor Placement ◽  
Optimization Procedure ◽  
Frame Structure ◽  
Truss Structures ◽  
Optimal Sensor Placement ◽  
Structural Damage Identification ◽  
Placement Algorithm ◽  
Sensor Locations

Background: Structural damage identification is a very important subject in the field of civil, mechanical and aerospace engineering according to recent patents. Optimal sensor placement is one of the key problems to be solved in structural damage identification. Methods: This paper presents a simple and convenient algorithm for optimizing sensor locations for structural damage identification. Unlike other algorithms found in the published papers, the optimization procedure of sensor placement is divided into two stages. The first stage is to determine the key parts in the whole structure by their contribution to the global flexibility perturbation. The second stage is to place sensors on the nodes associated with those key parts for monitoring possible damage more efficiently. With the sensor locations determined by the proposed optimization process, structural damage can be readily identified by using the incomplete modes yielded from these optimized sensor measurements. In addition, an Improved Ridge Estimate (IRE) technique is proposed in this study to effectively resist the data errors due to modal truncation and measurement noise. Two truss structures and a frame structure are used as examples to demonstrate the feasibility and efficiency of the presented algorithm. Results: From the numerical results, structural damages can be successfully detected by the proposed method using the partial modes yielded by the optimal measurement with 5% noise level. Conclusion: It has been shown that the proposed method is simple to implement and effective for structural damage identification.

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