INFLUENCE OF OBJECTIVE FUNCTIONS IN STRUCTURAL DAMAGE IDENTIFICATION USING REFINED AND SIMPLE MODELS

2009 ◽  
Vol 09 (04) ◽  
pp. 607-625 ◽  
Author(s):  
RICARDO PERERA ◽  
SHENG-EN FANG
Keyword(s):  
Dynamic Response ◽  
Objective Function ◽  
Structural Damage ◽  
Damage Identification ◽  
Computational Cost ◽  
Computational Time ◽  
Fe Model ◽  
Beam Model ◽  
Objective Functions ◽  
Multi Objective

The most usual approach for solving damage identification problems is the use of the finite element (FE) model updating method. To apply the method, a minimization of an objective function measuring the fit between measured and model predicted data is performed. Then, the success of the procedure depends strongly on the accuracy of the FE model and the choice of a suitable objective function. Although detailed FE models provide an accurate means for calculating the dynamic response of the structure, their size and complexity involve a large number of parameters to be updated and a high computational cost. In order to shorten the computational time, more simplified and practical models able to model the global dynamic response of the structure accurately would be desirable. Furthermore, working with several objective functions instead of only one would increase the robustness and performance of the procedure. In this paper, a multi-objective simple beam model is proposed and compared with a more refined model based on plane elements. Furthermore, in the multi-objective framework, different combinations of objective functions are studied. The reliability and effectiveness of the proposed model has been evaluated in a damage detection problem of a reinforced concrete frame experimentally tested under different levels of damage.

Local Mass Addition and Data Fusion for Structural Damage Identification Using Approximate Models

2020 ◽  
Vol 20 (11) ◽  
pp. 2050124
Author(s):  
Jilin Hou ◽  
Zhenkun Li ◽  
Qingxia Zhang ◽  
Łukasz Jankowski ◽  
Haibin Zhang
Keyword(s):  
Data Fusion ◽  
Objective Function ◽  
Structural Damage ◽  
Damage Identification ◽  
Structural Parameters ◽  
Identification Accuracy ◽  
Fe Model ◽  
Local Damage ◽  
Approximate Models ◽  
Structural Damage Identification

In practical civil engineering, structural damage identification is difficult to implement due to the shortage of measured modal information and the influence of noise. Furthermore, typical damage identification methods generally rely on a precise Finite Element (FE) model of the monitored structure. Pointwise mass alterations of the structure can effectively improve the quantity and sensitivity of the measured data, while the data fusion methods can adequately utilize various kinds of data and identification results. This paper proposes a damage identification method that requires only approximate FE models and combines the advantages of pointwise mass additions and data fusion. First, an additional mass is placed at different positions throughout the structure to collect the dynamic response and obtain the corresponding modal information. The resulting relation between natural frequencies and the position of the added mass is sensitive to local damage, and it is thus utilized to form a new objective function based on the modal assurance criterion (MAC) and [Formula: see text]-based sparsity promotion. The proposed objective function is mostly insensitive to global structural parameters, but remains sensitive to local damage. Several approximate FE models are then established and separately used to identify the damage of the structure, and then the Dempster–Shafer method of data fusion is applied to fuse the results from all the approximate models. Finally, fractional data fusion is proposed to combine the results according to the parametric probability distribution of the approximate FE models, which allows the natural weight of each approximate model to be determined for the fusion process. Such an approach circumvents the need for a precise FE model, which is usually not easy to obtain in real application, and thus enhances the practical applicability of the proposed method, while maintaining the damage identification accuracy. The proposed approach is verified numerically and experimentally. Numerical simulations of a simply supported beam and a long-span bridge confirm that it can be used for damage identification, including a single damage and multiple damages, with a high accuracy. Finally, an experiment of a cantilever beam is successfully performed.

scholarly journals A Multi-Objective DIRECT Algorithm Toward Structural Damage Identification With Limited Dynamic Response Information

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Pei Cao ◽  
Qi Shuai ◽  
Jiong Tang
Keyword(s):  
Finite Element ◽  
Dynamic Response ◽  
Structural Damage ◽  
Optimization Problem ◽  
Damage Identification ◽  
Direct Approach ◽  
Direct Algorithm ◽  
Sensitivity Matrix ◽  
Multi Objective ◽  
Response Information

A major challenge in structural health monitoring (SHM) is to accurately identify both the location and severity of damage using the dynamic response information acquired. While in theory the vibration-based and impedance-based methods may facilitate damage identification with the assistance of a credible baseline finite element model, the response information is generally limited, and the measurements may be heterogeneous, making an inverse analysis using sensitivity matrix difficult. Aiming at fundamental advancement, in this research we cast the damage identification problem into an optimization problem where possible changes of finite element properties due to damage occurrence are treated as unknowns. We employ the multiple damage location assurance criterion (MDLAC), which characterizes the relation between measurements and predictions (under sampled elemental property changes), as the vector-form objective function. We then develop an enhanced, multi-objective version of the dividing rectangles (DIRECT) approach to solve the optimization problem. The underlying idea of the multi-objective DIRECT approach is to branch and bound the unknown parametric space to converge to a set of optimal solutions. A new sampling scheme is established, which significantly increases the efficiency in minimizing the error between measurements and predictions. The enhanced DIRECT algorithm is particularly suited to solving for unknowns that are sparse, as in practical situations structural damage affects only a small region. A number of test cases using vibration response information are executed to demonstrate the effectiveness of the new approach.

Structural Damage Identification Based on Model Updating

2006 ◽  
Author(s):  
T. Yin ◽  
L. Yu ◽  
H. P. Zhu
Keyword(s):  
Objective Function ◽  
Structural Damage ◽  
Damage Identification ◽  
Model Updating ◽  
Frame Structure ◽  
Mode Shapes ◽  
Fe Model ◽  
Portal Frame ◽  
Structural Damage Identification ◽  
Portal Frame Structure

This paper presents a new method for structural damage identification based on the finite element (FE) model updating techniques. First, an objective function is defined as minimizing the sum of differences between the experimental and analytical modal data (natural frequencies and mode shapes), which is set as a nonlinear least-squares problem with bound-constrains. The trust-region approach is then used to solve the minimization problem in order to make this optimization process more robust and reliable. In addition, the expansion and weighting of the original objective function are investigated so that the presented method can be well applied into the damage identification of more real structures. Finally, a numerical simulation model of two-story portal frame structure is adopted to evaluate the efficiency of the proposed technique when both the single and multiple damage cases are set up in the model. Some important issues are also discussed in this paper. The illustrated results show that the single and multiple damages on the two-story portal frame structure can be well identified by the proposed method.

scholarly journals An Improved Objective Function for Modal-Based Damage Identification Using Substructural Virtual Distortion Method

2019 ◽  
Vol 9 (5) ◽  
pp. 971 ◽  
Author(s):  
Jilin Hou ◽  
Sijie Wang ◽  
Qingxia Zhang ◽  
Łukasz Jankowski
Keyword(s):  
Objective Function ◽  
Frequency Response ◽  
Large Scale ◽  
Damage Identification ◽  
Frame Structure ◽  
Modal Parameters ◽  
Fe Model ◽  
Objective Functions ◽  
Important Approach ◽  
Optimization Efficiency

Damage identification based on modal parameters is an important approach in structural health monitoring (SHM). Generally, traditional objective functions used for damage identification minimize the mismatch between measured modal parameters and the parameters obtained from the finite element (FE) model. However, during the optimization process, the repetitive calculation of structural modes is usually time-consuming and inefficient, especially for large-scale structures. In this paper, an improved objective function is proposed based on certain characteristics of the peaks of the frequency response function (FRF). Traditional objective functions contain terms that quantify modal shapes and/or natural frequencies. Here, it is proposed to replace them by the FRF of the FE model, which allows the repeated full modal analysis to be avoided and thus increases the computational efficiency. Moreover, the efficiency is further enhanced by employing the substructural virtual distortion method (SVDM), which allows the frequency response of the FE model of the damaged structure to be quickly computed without the costly re-analysis of the entire damaged structure. Finally, the effectiveness of the proposed method is verified using an eight-story frame structure model under several damage cases. The damage location and extent of each substructure can be identified accurately with 5% white Gaussian noise, and the optimization efficiency is greatly improved compared with the method using a traditional objective function.

Two-Stage Structural Damage Assessment by Combining Modal Kinetic Energy Change with Symbiotic Organisms Search

2019 ◽  
Vol 19 (10) ◽  
pp. 1950120 ◽  
Author(s):  
D. Dinh-Cong ◽  
T. Nguyen-Thoi ◽  
M. Vinyas ◽  
Duc T. Nguyen
Keyword(s):  
Kinetic Energy ◽  
Damage Assessment ◽  
Structural Damage ◽  
Heuristic Algorithms ◽  
Computational Cost ◽  
Energy Change ◽  
Fe Model ◽  
Two Stage ◽  
Symbiotic Organisms Search ◽  
Symbiotic Organisms

In the literature, modal kinetic energy (MKE) has been commonly utilized for optimal sensor placement strategies. However, there have been very few studies on its application to structural damage detection. This paper introduces a new two-stage structural damage assessment method by combining the modal kinetic energy change ratio (MKECR) and symbiotic organisms search (SOS) algorithm. In the first stage, an efficient damage indicator, named MKECR, is used to locate the potential damaged sites. Meanwhile, for the purpose of comparison with MKECR, three other indices are also used. In the second stage, an SOS-based finite element (FE) model updating strategy is adopted to estimate the damage magnitude of identified sites, while excluding false warnings (if any), where an objective function is proposed using a combination of the flexibility matrix and modal assurance criterion (MAC). The performance of the SOS algorithm is also verified by comparing with four other meta-heuristic algorithms. Finally, three numerical examples of 2D truss and frame structures with various hypothetical damage scenarios are carried out to investigate the capability of the proposed method. The numerical results indicate that the proposed method not only can accurately locate and quantify single- and multi-damage in the structures, but also shows a great saving in computational cost.

Towards Uniformly Distributed Compliance in Compliant Mechanisms: A Multi-Objective Approach

2006 ◽  
Author(s):  
Stephen L. Canfield ◽  
Daniel L. Chlarson ◽  
Alexander Shibakov ◽  
Patrick V. Hull
Keyword(s):  
Finite Element ◽  
Objective Function ◽  
Compliant Mechanisms ◽  
Optimality Criteria ◽  
Optimal Designs ◽  
Limiting Factors ◽  
Objective Functions ◽  
Multi Objective ◽  
Simple Addition ◽  
Current Formulation

Researchers in the field of optimal synthesis of compliant mechanisms have been working to develop tools that yield distributed compliant devices to perform specific tasks. However, it has been demonstrated in the literature that much of this work has resulted in mechanisms that localize compliance rather than distribute it as desired. In fact, Yin and Ananthasuresh (2003) [1] demonstrate that based on the current formulation of optimality criteria and analysis via the finite element (FE) technique, a lumped compliant device will always exist as the minimizing solution to the objective function. The addition of constraints on allowable strain simply moves the solution back from this objective. Therefore, modification to the standard optimality criteria needs to take place. Yin and Ananthasuresh [1] proposed and compared several approaches that include distributivity-based measures within the optimality criteria, and demonstrated the effectiveness of this approach. In this paper, the authors propose to build on this problem. In a similar manner, a general approach to the topology synthesis problem will be suggested to yield mechanisms in which the compliance is distributed throughout the device. This work will be based on the idea of including compliance distribution directly within the objective functions, while addressing some of the potential limiting factors in past approaches. The technique will be generalized to allow simple addition of criteria in the future, and to deliver optimal designs through to manufacture. This work will first revisit and propose several quantitative definitions for distributed compliant devices. Then, a multi-objective formulation based on a non-dominating sort and Pareto set method will be incorporated that will provide information on the nature of the problem and compatibility of employed objective functions.

Pseudo Strain Energy Density-Based Structural Damage Identification

2009 ◽  
Vol 413-414 ◽  
pp. 71-78
Author(s):  
Xiao Qiang Chen ◽  
Hong Ping Zhu ◽  
Dan Sheng Wang
Keyword(s):  
Energy Density ◽  
Strain Energy Density ◽  
Structural Damage ◽  
Strain Energy ◽  
Damage Identification ◽  
Wavelet Packet ◽  
Damage Index ◽  
Dynamic Strain ◽  
Beam Model ◽  
Measured Strain

In this paper, a new time-domain method for detecting structural local damage has been developed, which is based on the measured strain signals. The “pseudo strain energy density (PSED)” is defined and used to build two major damage indexes, the “average pseudo strain energy density” (APSED) and the “average pseudo strain energy density changing rate” (APSEDR). A probability and mathematical statistics technique is utilized to derive a standardized damage index. Afterwards, these indexes are used to establish the damage identification strategies for beam structures and plate structures respectively. Furthermore, the wavelet packet transform is used to pre-process the measured dynamic strain signals. Then, the effectivity of the new damage identification method is confirmed by numerical simulations. Finally, a laboratory beam model experiment is conducted to verify this method examine the feasibility and applicability of the new method.

A novel fuzzy based weighted aggregation based multi objective function for AVR optimization

2021 ◽  
pp. 1-24
Author(s):  
Amrit Kaur Bhullar ◽  
Ranjit Kaur ◽  
Swati Sondhi
Keyword(s):  
Objective Function ◽  
Weighting Factor ◽  
Superior Performance ◽  
Computational Time ◽  
Multi Objective ◽  
Space Efficiency ◽  
Point Tracking ◽  
Avr System ◽  
Optimum Solution ◽  
Time And Energy

Today optimization algorithms are widely used in every application to increase quality, quantity and efficiency of making products as well as to minimize the production cost. Most of the techniques applied on different applications try to satisfy more than one parameter of interest in the design problem. In doing so, an objective function based on weighted aggregation has been designed to fulfill multi-objective optimization (MOO). A lot of computational time and energy is wasted in tuning the value of weighting factor in terms of number of trials each having hundreds of iterations to achieve the optimum solution. To reduce such tedious practice of adjustment of weighting factor with multiple iterations, Fuzzy technique is proposed for auto-tuning of weighting factor in this paper that will benefit the researchers who are working upon optimization of their designed objectives using artificial intelligence techniques. This paper proposes MOO settlement method that does not require complex mathematical equations in order to simplify the weight finding problem of weighted aggregation objective function (WAOF). The results have been compared in terms of time and space efficiency to show the importance of Fuzzy-WAOF (F-WAOF). Further the results taken on Automatic Voltage Regulator (AVR) system for set point tracking, load disturbance, controller effort and modelling errors, prove the superior performance of the proposed method as compared to state of the art techniques.

Sign in / Sign up

Export Citation Format

Share Document