Application of a Model Updating Technique for Health Condition Monitoring and Damage Detection of Flexible Structures

1995 ◽  
Author(s):  
Joao A. Pereira ◽  
Ward Heylen ◽  
Stefan Lammens ◽  
Paul Sas
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Model Updating ◽  
Flexible Structures ◽  
Mesh Size ◽  
Health Condition ◽  
Frame Structure ◽  
Damage Area ◽  
Updating Procedure ◽  
Real Experimental Data

Abstract This paper discusses the application of a damage detection methodology to monitor the location and extent of partial structural damage. The methodology combines, in an iterative way, the model updating technique based on frequency response functions (FRF) with monitoring data aiming at identifying the damage area of the structure. After the updating procedure reaches a good correlation between the models, it compares the parameters of the damage structure with those of the undamaged one to find the deteriorated area. The influence of the FEM mesh size on the evaluation of the extent of the damage has also been discussed. The methodology is applied using real experimental data from a spatial frame structure.

scholarly journals An Improved Time-Domain Damage Detection Method for Railway Bridges Subjected to Unknown Moving Loads

2020 ◽  
Author(s):  
Mahdi Shahbaznia ◽  
Morteza Raissi Dehkordi ◽  
Akbar Mirzaee
Keyword(s):  
Damage Detection ◽  
Health Monitoring ◽  
Time Domain ◽  
Structural Damage ◽  
Model Updating ◽  
Numerical Models ◽  
Critical Parameters ◽  
Moving Loads ◽  
Railway Bridges ◽  
Updating Procedure

There is considerable interest in structural health monitoring (SHM) and damage detection of bridges and considerable progress has been made in this field in recent years. However, several challenges such as sensitivity to low levels of damage and identification without the knowledge of the moving load remain and need to be precisely investigated by researchers. The current work addresses such challenges and proposes an efficient response sensitivity-based model updating procedure in time-domain for damage identification of railway bridges subjected to unknown moving loads. The bridge is modelled as an Euler-Bernoulli beam and the train is modelled as a set of sprung masses passing over the beam. Structural damage is considered as a reduction in the modulus of elasticity of the elements. Sensitivity analysis and Tikhonov regularization methods are adopted and used to solve the inverse problem of the model updating. To verify the efficiency of the model, two numerical models with multiple damage scenarios subjected to unknown moving loads are analyzed. In addition, the efficiency of the proposed method in the presence of measurement noise is also verified. Numerical results reveal that the proposed model-updating procedure simultaneously identifies structural damages as well as the unknown moving loads with an acceptable accuracy. The effect of critical parameters such as mass and speed of the moving vehicle on the accuracy of identification results is investigated as well. Based on the findings of this research, the proposed method can be adopted and applied to online and long-term health monitoring of real bridge structures.

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.

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.

VIBRATION-BASED STRUCTURAL DAMAGE DETECTION UNDER VARYING TEMPERATURE CONDITIONS

2013 ◽  
Vol 13 (05) ◽  
pp. 1250082 ◽  
Author(s):  
XIAO-QING ZHOU ◽  
WEN HUANG
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Natural Frequencies ◽  
Environmental Changes ◽  
Model Updating ◽  
Modal Testing ◽  
Structural Damage Detection ◽  
Vibration Data ◽  
Temperature Conditions ◽  
Vibration Properties

In vibration-based structural damage detection, it is necessary to discriminate the variation of structural properties due to environmental changes from those caused by structural damages. The present paper aims to investigate the temperature effect on vibration-based structural damage detection in which the vibration data are measured under varying temperature conditions. A simply-supported slab was tested in laboratory to extract the vibration properties with modal testing. The slab was then damaged and the modal testing was conducted again, in which the temperature varied. The modal data measured under different temperature conditions were used to detect the damage with a two-stage model updating technique. Some damage was falsely detected if the temperature variation was not considered. Natural frequencies were then corrected to those under the same temperature conditions according to the relation between the temperature and material modulus. It is shown that all of the damaged elements can be accurately identified.

L1 Regularized Model Updating for Structural Damage Detection

2018 ◽  
Vol 18 (12) ◽  
pp. 1850157 ◽  
Author(s):  
Yu-Han Wu ◽  
Xiao-Qing Zhou
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Model Updating ◽  
Regularization Parameter ◽  
Structural Vibration ◽  
Mode Shapes ◽  
Modal Data ◽  
Vibration Data ◽  
Stiffness Reduction ◽  
Regularized Model

Model updating methods based on structural vibration data have been developed and applied to detecting structural damages in civil engineering. Compared with the large number of elements in the entire structure of interest, the number of damaged elements which are represented by the stiffness reduction is usually small. However, the widely used [Formula: see text] regularized model updating is unable to detect the sparse feature of the damage in a structure. In this paper, the [Formula: see text] regularized model updating based on the sparse recovery theory is developed to detect structural damage. Two different criteria are considered, namely, the frequencies and the combination of frequencies and mode shapes. In addition, a one-step model updating approach is used in which the measured modal data before and after the occurrence of damage will be compared directly and an accurate analytical model is not needed. A selection method for the [Formula: see text] regularization parameter is also developed. An experimental cantilever beam is used to demonstrate the effectiveness of the proposed method. The results show that the [Formula: see text] regularization approach can be successfully used to detect the sparse damaged elements using the first six modal data, whereas the [Formula: see text] counterpart cannot. The influence of the measurement quantity on the damage detection results is also studied.

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.

Research for Structural Damage Identification Method Based on Stable Time Series and Principal Component Analysis

2014 ◽  
Vol 578-579 ◽  
pp. 1020-1023
Author(s):  
Jing Zhou Lu ◽  
Jia Chen Wang ◽  
Xu Zhu
Keyword(s):  
Principal Component Analysis ◽  
Time Series ◽  
Damage Detection ◽  
Structural Damage ◽  
Computing Time ◽  
Principal Component ◽  
Component Analysis ◽  
Identification Accuracy ◽  
Frame Structure ◽  
Ar Model

In this paper, we introduce a set of techniques for time series analysis based on principal component analysis (PCA). Firstly, the autoregressive (AR) model is established using acceleration response data, and the root mean squared error (RMSE) of AR model is calculated based on PCA. Then a new damage sensitive feature (DSF) based on the AR coefficients is presented. To test the efficacy of the damage detection and localization methodologies, the algorithm has been tested on the analytical and experimental results of a three-story frame structure model of the Los Alamos National Laboratory. The result of the damage detection indicates that the algorithm is able to identify and localize minor to severe damage as defined for the structure. It shows that the suggested method can lead to less amount of computing time, high suitability and identification accuracy.

A Multi-State Strategy for Structural Damage Detection Using Sensitivity of Weighted Transmissibility Function

2021 ◽  
pp. 2150144
Author(s):  
Ziwei Luo ◽  
Huanlin Liu ◽  
Ling Yu
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Model Updating ◽  
Structural Parameters ◽  
Experimental Studies ◽  
Fe Model ◽  
Limited Information ◽  
Structural Damage Detection ◽  
State Strategy ◽  
Output Only

In practice, a model-based structural damage detection (SDD) method is helpful for locating and quantifying damages with the aid of reasonable finite element (FE) model. However, only limited information in single or two structural states is often used for model updating in existing studies, which is not reasonable enough to represent real structures. Meanwhile, as an output-only damage indicator, transmissibility function (TF) is proven to be effective for SDD, but it is not sensitive enough to change in structural parameters. Therefore, a multi-state strategy based on weighted TF (WTF) is proposed to improve sensitivity of TF to change in parameters and in order to further obtain a more reasonable FE model for SDD in this study. First, WTF is defined by TF weighted with element stiffness matrix, and relationships between WTFs and change in structural parameters are established based on sensitivity analysis. Then, a multi-state strategy is proposed to obtain multiple structural states, which is used to reasonably update the FE model and detect structural damages. Meanwhile, due to fabrication errors, a two-stage scheme is adopted to reduce the global and local discrepancy between the real structure and the FE model. Further, the [Formula: see text]-norm and the [Formula: see text]-norm regularization techniques are, respectively, introduced for both model updating and SDD problems by considering the characteristics of problems. Finally, the effectiveness of the proposed method is verified by a simply supported beam in numerical simulations and a six-storey frame in laboratory. From the simulation results, it can be seen that the sensitivity to structural damages can be improved by the definition of WTF. For the experimental studies, compared with the FE model updated from the single structural state, the FE model obtained by the multi-state strategy has an ability to more reasonably describe the change of states in the frame. Moreover, for the given structural damages, the proposed method can detect damage locations and degrees accurately, which shows the validity of the proposed method and the reliability of the updated FE model.

Sign in / Sign up

Export Citation Format

Share Document