scholarly journals A Comparative Study on Sensitivity-Based Damage Detection Methods in Bridges

2015 ◽  
Vol 2015 ◽  
pp. 1-19 ◽  
Author(s):  
Akbar Mirzaee ◽  
Reza Abbasnia ◽  
Mohsenali Shayanfar
Keyword(s):  
Finite Element ◽  
Comparative Study ◽  
Damage Detection ◽  
Model Updating ◽  
Moving Load ◽  
Element Model ◽  
Measurement Noise ◽  
Detection Methods ◽  
Sensitivity Matrix ◽  
Discrete Approach

This paper provides a comparative study on four different sensitivity-based damage detection methods for bridges. The methods investigated in this study are approximation approach, semianalytical discrete approach, and analytical discrete approach, which includes direct differential and adjoint variable methods. These sensitivity-based methods utilize finite element model updating procedure and allow a wide choice of physically meaningful parameters leading to vast range of applications in damage detection. The most important difficulty in these methods is calculation of sensitivity matrix. Calculation of this massive matrix is repeated in each iteration and has a significant effect on the efficiency of method. In this study, the acceleration measurements are simulated from the solution to the forward problem using finite element method under moving load with various speeds, along with the addition of artificially produced measurement noise. Various damaged structures with different damage patterns including single, multiple, and random damage are considered and efficiency of four sensitivity methods is compared. Moreover, various possible sources of error such as the effects of measurement noise as well as initial assumption error in stability of the methods are also discussed.

A Multi-Scale Wavelet Finite Element Model for Damage Detection of Beams Under a Moving Load

2018 ◽  
Vol 18 (06) ◽  
pp. 1850078 ◽  
Author(s):  
Wen-Yu He ◽  
Songye Zhu ◽  
Zhi-Wei Chen
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Dynamic Analysis ◽  
Damage Detection ◽  
Model Updating ◽  
Moving Load ◽  
Element Model ◽  
Multi Scale ◽  
Computation Efficiency ◽  
Wavelet Finite Element

The resolution of structural finite element model (FEM) determines the computation cost and accuracy in dynamic analysis. This study proposes a novel wavelet finite element model (WFEM), which facilitates adaptive mesh refinement, for the dynamic analysis and damage detection of beam structures subjected to a moving load (ML). The multi-scale equations of motion for the beam under the ML are derived using the second-generation cubic Hermite multi-wavelets as the shape functions. Then an adaptive-scale analysis strategy is established, in which the scales of the wavelet beam elements are dynamically changed according to the ML position. The performance of the multi-scale WFEM is examined in both dynamic analysis and damage detection problems. It is demonstrated that the multi-scale WFEM with a similar number of degrees of freedom can achieve much higher accuracy than the traditional FEM. In particular, the multi-scale WFEM enables the detection of sub-element damage with a progressive model updating process. The advantage in computation efficiency and accuracy makes the proposed method a promising tool for multi-scale dynamic analysis or damage detection of structures.

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.

Finite Element Model Updating of Large Structures by the Clustering of Parameter Sensitivities

2006 ◽  
Vol 5-6 ◽  
pp. 85-92 ◽  
Author(s):  
H. Shahverdi ◽  
Cristinel Mares ◽  
W. Wang ◽  
C.H. Greaves ◽  
John E. Mottershead
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Model Updating ◽  
Mass Density ◽  
Element Model ◽  
Finite Element Model Updating ◽  
Sensitivity Matrix ◽  
Large Structures ◽  
New Development ◽  
Bending Modes

Finite element model updating of a Westland Lynx XZ649 helicopter tail is presented. Eigenvalue sensitivities with respect to Young’s modulus and mass density are used. Large groups based on material input data were divided to form smaller subgroups so that those parts of the model responsible for errors in the predicted eigenvalues were located. A particular new development was the use of parameter clustering based on the similarity of different columns of the sensitivity matrix. Finally the finite element model was updated successfully with regard to the lower frequency tail-bending modes.

scholarly journals Clustering of Parameter Sensitivities: Examples from a Helicopter Airframe Model Updating Exercise

2009 ◽  
Vol 16 (1) ◽  
pp. 75-87 ◽  
Author(s):  
H. Shahverdi ◽  
C. Mares ◽  
W. Wang ◽  
J.E. Mottershead
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Large Scale ◽  
Structural Changes ◽  
Model Updating ◽  
Mass Density ◽  
Main Tool ◽  
Element Model ◽  
Sensitivity Matrix ◽  
Comparative Results

The need for high fidelity models in the aerospace industry has become ever more important as increasingly stringent requirements on noise and vibration levels, reliability, maintenance costs etc. come into effect. In this paper, the results of a finite element model updating exercise on a Westland Lynx XZ649 helicopter are presented. For large and complex structures, such as a helicopter airframe, the finite element model represents the main tool for obtaining accurate models which could predict the sensitivities of responses to structural changes and optimisation of the vibration levels. In this study, the eigenvalue sensitivities with respect to Young's modulus and mass density are used in a detailed parameterisation of the structure. A new methodology is developed using an unsupervised learning technique based on similarity clustering of the columns of the sensitivity matrix. An assessment of model updating strategies is given and comparative results for the correction of vibration modes are discussed in detail. The role of the clustering technique in updating large-scale models is emphasised.

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