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.

scholarly journals Damage Identification by the Data Expansion and Substructuring Methods

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Eun-Taik Lee ◽  
Hee-Chang Eun
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Expansion Method ◽  
External Noise ◽  
Detection Methods ◽  
Damage Indices ◽  
Before And After ◽  
Stiffness Variation ◽  
Data Expansion

Structural damage can be detected by comparing the responses before and after the damage. The responses are transformed into curvature, strain, and stress, among others, which characterize the mechanical behavior of the structural members, and can be utilized as damage indices for damage detection. The damage of a truss structure can rarely be detected by the displacements only at nodes. This work investigates damage detection methods using the stress or stiffness variation rate of the truss element before and after the damage. This paper considers three different cases according to the number of measurement locations. If the complete responses at a full set of degrees of freedom are measured, the stiffness variation rates of the elements are calculated accurately, and the damage can be explicitly detected despite external noise. If the number of measured data points is fewer than the system order, the displacements are estimated by the data expansion method, and the damage-expected regions are predicted by the stiffness variation rates. Apart from the explicitly damaged elements, the substructuring approach is adopted for closer damage detection with several measurement sensors despite external noise. It is illustrated by the examples that three cases are compared numerically. The numerical examples compare and analyze the numerical results of the three cases.

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.

Sparse damage detection via the elastic net method using modal data

2021 ◽  
pp. 147592172110219
Author(s):  
Rongrong Hou ◽  
Xiaoyou Wang ◽  
Yong Xia
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Measurement Data ◽  
Elastic Net ◽  
Sensitivity Matrix ◽  
Regularization Technique ◽  
Modal Data ◽  
Regularization Techniques ◽  
Net Method

The l1 regularization technique has been developed for damage detection by utilizing the sparsity feature of structural damage. However, the sensitivity matrix in the damage identification exhibits a strong correlation structure, which does not suffice the independency criteria of the l1 regularization technique. This study employs the elastic net method to solve the problem by combining the l1 and l2 regularization techniques. Moreover, the proposed method enables the grouped structural damage being identified simultaneously, whereas the l1 regularization cannot. A numerical cantilever beam and an experimental three-story frame are utilized to demonstrate the effectiveness of the proposed method. The results showed that the proposed method is able to accurately locate and quantify the single and multiple damages, even when the number of measurement data is much less than the number of elements. In particular, the present elastic net technique can detect the grouped damaged elements accurately, whilst the l1 regularization method cannot.

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.

Nonlinear Structural Damage Detection Based on Adaptive Volterra Filter Model

2018 ◽  
Vol 18 (02) ◽  
pp. 1871003 ◽  
Author(s):  
J. Prawin ◽  
A. Rama Mohan Rao
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Linear Models ◽  
Time History ◽  
Diagnostic Techniques ◽  
Filter Model ◽  
Volterra Filter ◽  
Damage Indices ◽  
Before And After ◽  
Nonlinear Time History

The majority of the existing damage diagnostic techniques are based on linear models. Changes in the state of the dynamics of these models, before and after damage in the structure based on the vibration measurements, are popularly used as damage indicators. However, the system may initially behave linearly and subsequently exhibit nonlinearity due to the incipience of damage. Breathing cracks that exhibit bilinear behavior are one such example of the damage induced due to nonlinearity. Further many real world structures even in their undamaged state are nonlinear. Hence, in this paper, we present a nonlinear damage detection technique based on the adaptive Volterra filter using the nonlinear time history response. Three damage indices based on the adaptive Volterra filter are proposed and their sensitiveness to damage and noise is assessed through two numerically simulated examples. Numerical investigations demonstrate the effectiveness of the adaptive Volterra filter model to detect damage in nonlinear structures even with measurement noise.

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.

scholarly journals Structural Damage Identification Based on the Minimum System Realization and Sensitivity Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
W. R. Li ◽  
Y. F. Du ◽  
S. Y. Tang ◽  
L. J. Zhao
Keyword(s):  
Sensitivity Analysis ◽  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Structural Information ◽  
Structural Response ◽  
Frame Structure ◽  
Structural Damage Detection ◽  
System Realization ◽  
Minimum System

On the basis of the thought that the minimum system realization plays the role as a coagulator of structural information and contains abundant information on the structure, this paper proposes a new method, which combines minimum system realization and sensitivity analysis, for structural damage detection. The structural damage detection procedure consists of three steps: (1) identifying the minimum system realization matrixes A, B, and R using the structural response data; (2) defining the mode vector, which is based on minimum system realization matrix, by introducing the concept of the measurement; (3) identifying the location and severity of the damage step by step by continuously rotating the mode vector. The proposed method was verified through a five-floor frame model. As demonstrated by numerical simulation, the proposed method based on the combination of the minimum realization system and sensitivity analysis is effective for the damage detection of frame structure. This method not only can detect the damage and quantify the damage severity, but also is not sensitive to the noise.

Structural Multi-Damage Identification Based on Modal Strain Energy Equivalence Index Method

2014 ◽  
Vol 14 (07) ◽  
pp. 1450028 ◽  
Author(s):  
Hui Yong Guo ◽  
Zheng Liang Li
Keyword(s):  
Energy Dissipation ◽  
Structural Damage ◽  
Strain Energy ◽  
Damage Identification ◽  
Index Method ◽  
Modal Strain Energy ◽  
Energy Equivalence ◽  
Before And After ◽  
Accurate Expression ◽  
Equivalence Theory

In order to solve structural multi-damage identification problems, a damage detection method based on modal strain energy equivalence index (MSEEI) is presented. First, an accurate expression of modal strain energy (MSE) before and after damage occurs is given. Then, according to the energy equivalence theory that the change in MSE caused by the damage should be equivalent to the energy dissipation caused by the same damage, an energy equivalence equation is deduced. Finally, four roots of the energy equivalence equation are found and a MSEEI is obtained from the four roots. Simulation results demonstrate that the proposed MSEEI method can identify structural damage locations and extent with good accuracy. Identification precision of the proposed method is clearly better than that of the modal strain energy dissipation ratio index (MSEDRI) method.

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