Damage Identification in a Plate Structure Based on Strain Statistical Moment

2014 ◽  
Vol 17 (11) ◽  
pp. 1639-1655 ◽  
Author(s):  
Wei Xiang ◽  
Dansheng Wang ◽  
Hongping Zhu
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Model Updating ◽  
Numerical Study ◽  
Statistical Moment ◽  
Least Square ◽  
Measurement Noise ◽  
Good Prediction ◽  
Plate Structure ◽  
The Difference

The fourth strain statistical moment (FSSM) based damage detection method has been recently proposed by the authors and the results of numerical study demonstrated the proposed method is sensitive to local structural damage but insensitive to measurement noise for beam-type structure. In this paper, the method is extended to a plate structure. The method consists of two steps: damage localization and damage quantification. First, the damage is located by using the difference curved surfaces of FSSMs in one direction of a plate subjected to Gauss White Noise (GWN) excitation before and after damage. Then the model updating method based on least square algorithm is used to estimate the damage severities. Also, the numerical (finite element) simulations are carried out for a simply supported plate. The results demonstrate the proposed method can provide good prediction of both location and severity of damage at one or more sites, even under low damage severities and high measurement noise conditions.

Application of Bayesian statistical method in sensitivity-based seismic damage identification of structures: Numerical and experimental validation

2018 ◽  
Vol 17 (5) ◽  
pp. 1255-1276 ◽  
Author(s):  
Maryam Vahedi ◽  
Faramarz Khoshnoudian ◽  
Ting Yu Hsu
Keyword(s):  
Statistical Method ◽  
Structural Damage ◽  
Damage Identification ◽  
Model Updating ◽  
Least Square Method ◽  
Element Model ◽  
Least Square ◽  
Detection Methods ◽  
Sensitivity Equation ◽  
Stiffness Reduction

Most of the developed sensitivity-based damage detection methods are based on the application of external excitations which could be prohibitive due to infeasible excitation of all structural degrees of freedom. In this regard, identification of damage properties using seismic structural response would be advantageous. In this research, sensitivity-based finite element model updating method is proposed to identify structural damage by earthquake response in the frequency domain and the transfer function of the structure due to ground excitation. The obtained sensitivity equation is solved by linear least square method through defining constraints on the design variables. Since the attainable measured data are restricted by limits on the instrumentations and preciseness of the measurements and due to the fact that only a few of the lower modes of a structure can generally be determined with confidence, a Bayesian statistical method is utilized to enhance the reliability of the predicted damage properties. The proposed technique is applied to a numerical frame model and an experimental six-story steel structure with various scenarios of story stiffness reduction. The results are indicative of the capability of the proposed method for identification of damage location and severity.

Experimental investigation of damage identification in beam structures based on the strain statistical moment

2016 ◽  
Vol 20 (5) ◽  
pp. 747-758 ◽  
Author(s):  
Dansheng Wang ◽  
Zhen Chen ◽  
Wei Xiang ◽  
Hongping Zhu
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Gaussian White Noise ◽  
Statistical Moment ◽  
Least Square ◽  
Detection Technique ◽  
Before And After ◽  
Beam Type ◽  
Strain Responses

A new two-step damage detection technique based on the fourth strain statistical moment was recently proposed by the authors, and its sensitivity to local structural damage has been numerically demonstrated for beam-type structures. In this article, the proposed method is extended to an experimental beam to assess its feasibility and practicality. A simply supported steel beam was manufactured and subjected to Gaussian white-noise excitation before and after damage. The strain responses of each measurement point were recorded based on which fourth strain statistical moments were calculated. The proposed two-step technique was implemented to locate the damaged elements of the experimental beam, for which the damage sizes were identified based on the least-square updating algorithm. The experimental results show that the proposed fourth strain statistical moment index and the two-step damage detection technique are effective and feasible for beam-type structures.

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.

scholarly journals Detection of Sparse Damages in Structures

2019 ◽  
Author(s):  
Natalia Sabourova ◽  
Niklas Grip ◽  
Ulf Ohlsson ◽  
Lennart Elfgren ◽  
Yongming Tu ◽  
...  
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Model Updating ◽  
Element Model ◽  
Total Variation Regularization ◽  
Regularization Technique ◽  
Spatial Properties ◽  
Ill Posed ◽  
Pros And Cons ◽  
Kirchhoff Plate Model

<p>Structural damage is often a spatially sparse phenomenon, i.e. it occurs only in a small part of the structure. This property of damage has not been utilized in the field of structural damage identification until quite recently, when the sparsity-based regularization developed in compressed sensing problems found its application in this field.</p><p>In this paper we consider classical sensitivity-based finite element model updating combined with a regularization technique appropriate for the expected type of sparse damage. Traditionally, (I), &#119897;2- norm regularization was used to solve the ill-posed inverse problems, such as damage identification. However, using already well established, (II), &#119897;l-norm regularization or our proposed, (III), &#119897;l-norm total variation regularization and, (IV), general dictionary-based regularization allows us to find damages with special spatial properties quite precisely using much fewer measurement locations than the number of possibly damaged elements of the structure. The validity of the proposed methods is demonstrated using simulations on a Kirchhoff plate model. The pros and cons of these methods are discussed.</p>

scholarly journals A Super-Harmonic Feature Based Updating Method for Crack Identification in Rotors Using a Kriging Surrogate Model

2019 ◽  
Vol 9 (12) ◽  
pp. 2428 ◽  
Author(s):  
Zhiwen Lu ◽  
Yong Lv ◽  
Huajiang Ouyang
Keyword(s):  
Surrogate Model ◽  
Structural Damage ◽  
Damage Identification ◽  
Model Updating ◽  
Gaussian White Noise ◽  
Crack Identification ◽  
Breathing Crack ◽  
Kriging Surrogate Model ◽  
Nonlinear Characteristics ◽  
Practical Applications

Dynamic model updating based on finite element method (FEM) has been widely investigated for structural damage identification, especially for static structures. Despite the substantial advances in this method, the key issue still needs to be addressed to boost its efficiency in practical applications. This paper introduces the updating idea into crack identification for rotating rotors, which has been rarely addressed in the literature. To address the problem, a novel Kriging surrogate model-based FEM updating method is proposed for the breathing crack identification of rotors by using the super-harmonic nonlinear characteristics. In this method, the breathing crack induced nonlinear characteristics from two locations of the rotors are harnessed instead of the traditional linear damage features for more sensitive and accurate breathing crack identification. Moreover, a FEM of a two-disc rotor-bearing system with a response-dependent breathing crack is established, which is partly validated by experiments. In addition, the associated breathing crack induced nonlinear characteristics are investigated and used to construct the objective function of Kriging surrogate model. Finally, the feasibility and the effectiveness of the proposed method are verified by numerical experiments with Gaussian white noise contamination. Results demonstrate that the proposed method is effective, accurate, and robust for breathing crack identification in rotors and is promising for practical engineering applications.

A Flexibility-Based Method for Structural Damage Identification Using Ambient Modal Data

2009 ◽  
Vol 24 (3) ◽  
pp. 153-159 ◽  
Author(s):  
Q. W. Yang
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Simulated Data ◽  
Least Square ◽  
Ambient Vibration ◽  
Mode Shapes ◽  
Vibration Modes ◽  
Sensitivity Equation ◽  
Structural Damage Identification ◽  
Normalization Factors

Structural damage identification using ambient vibration modes has become a very important research area in recent years. The main issue surrounding the use of ambient vibration modes is the mass normalization of the measured mode shapes. This paper presents a promising approach that extends the flexibility sensitivity technique to tackle the ambient vibration case. By introducing the mass normalization factors, manipulating the flexibility sensitivity equation, the unknown damage parameters and mass normalization factors can be computed simultaneously by the least-square technique. The effectiveness of the proposed method is illustrated using simulated data with measurement noise on three examples. It has been shown that the proposed procedure is simple to implement and may be useful for structural damage identification under ambient vibration case.

Review and Prospect on Dynamic FE Model Updating Methods of Footbridge Structures Based on Ambient Excitation

2011 ◽  
Vol 291-294 ◽  
pp. 1572-1577
Author(s):  
Rui Zhao ◽  
Yi Gang Zhang
Keyword(s):  
Structural Damage ◽  
Optimization Design ◽  
Damage Identification ◽  
Model Updating ◽  
Target Function ◽  
Optimization Theory ◽  
Empirical Method ◽  
Fe Model ◽  
Fe Model Updating ◽  
Ambient Excitation

The discrete finite element (FE) model often cannot reflect structure characteristics accurately due to imply more idealistic assumptions and simplifications. Therefore, it is necessary to update FE model for structural damage identification, response calculation, safety evaluation, optimization design, and so on. This article will illustrate respectively three key steps of updating parameters selection, target function selection and optimization method in process of dynamic FE model updating of footbridge structures based on ambient excitation, and put forward a feasible updating method: combine empirical method with sensitivity analysis method to select updating parameters; joint natural frequencies, MAC and modal flexibility as target function; adopt optimization algorithm based on the optimization theory.

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