Vibration-based Damage Identification Techniques Research Articles

Frequency response function-based closed-form expression for multi-damage quantification and its application on shear buildings

Vibration-based damage identification techniques have gained popularity immensely in the field of structural health monitoring (SHM). Frequency response function (FRF)-based damage quantification is mainly performed based on iterative model updating techniques. Most of these methods are time-consuming and erroneous in higher modes. Spectral element method (SEM) can overcome some of these limitations and can determine FRF expression directly for a broad class of civil structures. However, a closed-form expression for multiple damage severity is not proposed to date. In this study, an FRF-based formulation for quantifying damage has been proposed with the help of SEM in order to bypass the mode shape extraction for damage identification. To determine the effectiveness of the proposed formulation both numerical and experimental studies have been performed. A numerical simulation has been performed on a 14-storey shear building. Damage has been introduced by reducing the storey stiffness at intermediate and adjacent storeys. It has been perceived that damage severity at any storey can be estimated with only 3 sensors, one at the top storey and two others at the adjacent floors of the desired storey. To verify the effectiveness of the proposed expression, an experimental study has been carried out on a 9-storey miniature model. It has been observed that the first resonating peak amplitudes of the responses recorded simultaneously at desired locations of intact and damaged structures are sufficient to estimate the damage intensity. Thus, the proposed formulation is efficient as an output measurement-based approach. The novelty of this study lies in the proposed closed-form FRF-based multi-damage severity expression involving minimum number of sensors and without any information on the input excitation. The results obtained from both numerical and experimental study showcase the robustness, simplicity and applicability of the proposed formulation.

Reference-Free Vibration-Based Damage Identification Techniques for Bridge Structural Health Monitoring—A Critical Review and Perspective

Reference-Free Vibration-Based Damage Identification Techniques for Bridge Structural Health Monitoring—A Critical Review and Perspective

Vibration-Based Damage Identification in Steel Girder Bridges Using Artificial Neural Network Under Noisy Conditions

The vibration-based damage identification techniques use changes in modal properties of structures to detect damages. However, the results of these methods are not reliable under noise. Therefore, it is essential to clarify which method performs vigorous under noisy conditions. In this study, three damage detection methods, called modal strain energy-based damage index, modal flexibility, and modal curvature, are considered to detect damage with and without the presence of noise. The feasibility of these methods is demonstrated by applying a range of damage scenarios in the validated FE model of the I-40 Bridge. The info of the only first three bending mode shapes of the bridge is used to calculate damage indices. The outcome showed while all three methods were capable of detecting damage in the absence of noise, only the modal flexibility method could locate damages in the presence of noise. Thus, an approach is proposed to eliminate noise and quantify damage magnitude using an artificial neural network (ANN) and modal flexibility method. The modal flexibility damage index of different damage severities was contaminated with various noise levels used as input parameters to train the ANN. Results indicate the adequate performance of the trained ANN in noise-canceling and damage magnitude estimation.

RETRACTED: Multiple damage detections in plate-like structures using curvature mode shapes and gapped smoothing method

The engineering communities are using vibration-based damage identification techniques for structural damage detection since many years. Whenever a damage or crack occurs in the structure, then it ...

Experimental evaluation of vibration based damage identification techniques on a pedestrian bridge

Failures of civil structures, such as bridges, due to natural events or anthropic loads can generate significant social and economic impacts. As an alternative for the identification of damage in these structures, dynamic structural health monitoring has been proposed. This paper presents the experimental evaluation of three damage identification techniques on a full-scale footbridge. One of the evaluated techniques is based on damage localization vectors; a second technique is based on changes in the curvature of the modal shapes, while the third technique uses a numerical model and artificial neural networks for locating the damaged section. Five scenarios of controlled damage were induced in the footbridge. Output-only ambient vibration tests were performed at each damage state and the results of the identification techniques were analyzed. The three implemented techniques showed promising results for the numerical simulations, and two of these techniques produced satisfactory results in the experimental evaluation.

Vibration-based damage identification of an unreinforced masonry house model

Non-destructive vibration-based damage identification techniques are especially attractive for assessing damage in structures of high historical and architectural value. So far, most studies have focused on slender structures built using relatively homogeneous materials. In this study, global damage identification methods based on vibration response parameters were applied for identifying damage in an unreinforced masonry full-scale house model (non-homogeneous material and non-slender structure). The house model was dynamically loaded using an eccentric-mass shaker. Structural damage to the walls was initiated by increasing the amplitude of the applied load. At each damage state, a modal test was performed by impacting the walls with a calibrated hammer. Statistically significant variations of modal frequencies and the modal assurance criteria were considered as suitable parameters to identify damage. It was concluded that different sets of modes can be found for different states of damage because of material degradation, change in the support and connectivity conditions, and breaks in the members continuity generated by damage. All these changes are reflected in variations of modal frequencies and modal assurance criteria. It was also established that prior to identifying the damage distribution on the entire building, it was necessary to determine how the modal frequencies were related to each wall.

Assessment of vibration-based damage identification techniques using localized excitation source

The Bridge Engineering Laboratory in Kitami Institute of Technology, Japan has introduced a number of different damage identification techniques to detect structural damage and identify its location utilizing piezoelectric actuators as a localized excitation source. Several spectral functions, such as cross spectral density, power spectral density, phase angle and transfer function estimate, were used to estimate the dynamic response of the structure. Each function’s magnitude, measured in a specified frequency range, is used in the damage identification methods. The change of the spectral function magnitude between the baseline state and the current state is then used to identify the location of possible damage in the structure. It is then necessary to determine which spectral function is best able to estimate the dynamic response and which algorithm is best able to identify the damage. The first part of this paper compares the performance of different spectral functions when their magnitude is used in one damage identification algorithm using experimental data from a railway steel bridge. The second part of this paper compares the performance of different damage identification algorithms using the same data.

Model-Based Damage Identification in a Continuous Bridge Using Vibration Data

Damage often causes changes in the dynamic characteristics of a structure such as frequencies and mode shapes. Vibration-based damage identification techniques utilize the changes in the dynamic characteristics of a structure to determine the location and extent of damage in the structure. Such techniques are applied in this study to the Crowchild Bridge, a steel-free deck continuous bridge located in western Canada. While the numerical models of the bridge are correlated with the measured dynamic characteristics, computer simulation is used to study the identification of a number of different damage patterns, and the effects of measurement errors and incomplete mode shapes on the quality of results are evaluated. The effectiveness of some selected damage identification techniques is examined; the potential difficulties in identifying the damage are outlined; and areas of further research are suggested. A three-dimensional finite-element model and a simple two-dimensional girder model of the bridge have been constructed to study the usefulness of the selected damage identification methods. Another promising damage detection method proposed here is based on the application of neural networks that combines a vibration-based method.

Damage analysis of a steel–concrete composite frame by finite element model updating

In the last two decades, many studies have reported the effectiveness of Experimental Modal Analysis and Finite Element Model Updating in mechanical and aerospace engineering, where they represent useful tools for Structural Health recognition and can provide an information base for detection, assessment and quantification of structural damage due to exercise actions and exceptional events. The applications of Damage Detection techniques to civil constructions left some still not well clarified points, due to the great variety of structural typologies, material properties, boundary conditions and possible damage patterns, as in the case of seismic damage. In order to design post-earthquake rehabilitation interventions, in fact a careful knowledge of the damage distribution and residual structural capacity is obviously needed and this can be very expensive and time consuming. However, the application of vibration based damage identification techniques to high ductile structures designed according to seismic capacity approach can improve the feasibility, reliability and efficiency of these methods. In the present study, Finite Element Model Updating procedures based on vibration measurements were used to detect, assess and quantify the structural damage of a high ductile steel–concrete composite frame subjected to increasing seismic damage by means of pseudo dynamic and cyclic test at the Joint Research Centre (Ispra, Italy). The updating process, repeated for three damage levels, has been applied to different finite element structural models (addressing different modelling strategies), allowing a comprehensive description and quantification of the progressive degradation of beam-to-column joints, devoted to dissipate the seismic energy by design.

Bridge Condition Evaluation by In Situ Dynamic Data

The performance of vibration-based damage identification techniques for current condition evaluation of exist- ing bridges is studied through their application to dynamic response of an existing concrete bridge. First, in situ dynamic tests were performed and modal parameters (mode shapes and frequencies) were identified. As previous sets of in situ dy- namic parameters were not available, the reference dynamic parameters were obtained from a finite element model of the bridge. Comparing modal parameters of the finite element bridge model and the in situ experimental results through dam- age identification techniques, the bridge current condition was examined. That evaluation results showed that techniques like strain energy and flexibility curvature present promising results for current condition evaluation of existing bridges.

Damage localisation and severity evaluation of a beam-like timber structure based on modal strain energy and flexibility approaches

Timber bridges are often exposed to harsh environmental conditions, which, over time, can lead to deterioration resulting from decay, insect attack, weathering, and mechanical damage. In turn, this deterioration may lead to a loss of structural integrity that is detrimental to the structure and its users. Non-destructive evaluation (NDE) techniques provide effective means for assessment of current structural integrity status of given structures. As a global NDE technique, vibration-based damage identification techniques have received increasing attention for structural damage evaluation. Among them, there is a popular and promising damage identification method called the damage index method based on calculating the change of modal strain energy before and after damage. Despite its popularity, however, a systematic investigation on its capability and limitations in locating and quantifying damage is yet to be reported, especially for structures suffering multiple damage. In this paper, after reviewing the current NDE methods, the focus was set on the vibration-based NDE methods, in particular the damage index method. The investigation was based on finite element analysis (FEA) results of a timber beam by which the capability and limitation of the damage index was fully explored. As a result of the investigation, a new hybrid algorithm combining modified damage index (MDI) and change in flexibility algorithms is proposed for damage localisation and severity evaluation. The numerical results indicate that the proposed hybrid algorithms based on MDI method and flexibility have clear advantages in detecting damage locations and evaluating damage severities, especially for multiple damage cases.

Statistical damage identification for bridges using ambient vibration data

The inherent uncertainties in experimental data have been recognized as one of the main barriers against the application of vibration-based damage identification techniques on real-life bridges. A statistical damage identification procedure for bridge health monitoring is presented in this paper. It is assumed that the structure, in both healthy and unknown conditions, is monitored and the dynamic responses under ambient excitations are available. The damage identification procedure runs following a 4-step scheme including (1) data sample formation, (2) data normalization, (3) damage feature extraction, and (4) statistical damage evaluation. A hierarchical sequence matching scheme is suggested for data normalization to account for the effects of various environmental and operational conditions on the structural dynamics. The damage feature extraction technique based on time series analysis combining auto-regressive and auto-regressive with eXogenous inputs prediction models is adopted. A statistical index based on the damage features that are derived from a large number of data samples is proposed for novelty detection and damage localization. The effectiveness and robustness of the proposed procedure is demonstrated by numerical simulations performed on a three-span continuous girder bridge with reasonable damage severity.

Assessment of vibration-based damage identification techniques

In this paper some usual vibration-based damage identification techniques (VBDIT) will be reviewed and used for structural damage evaluation. With the help of a simple supported beam with different damage levels the reliability of these techniques will be investigated. The techniques reviewed herein are based on measured modal parameters which use only few mode shapes and/or modal frequencies of the structure that can be easily obtained by dynamic tests. In other words, by realizing two sets of dynamic measurements, corresponding to two moments of the structure lifetime, the dynamic modal parameters can be obtained. In order to assess properly the performance of these techniques different noise levels are randomly introduced to the response signals of a simulated beam which is exited by a random force. For different levels of damage and noise, the probabilities of damage detection and the probabilities of false alarm for the total number of simulations is evaluated. It can be concluded that among the evaluated techniques the strain energy method presents the best stability regarding noisy signals; however, the detection judgement depends on a threshold level which is discussed in this paper. The change in mode shape curvature, change in flexibility and change in flexibility curvature methods are also capable to detect and localise damaged elements but in the case of complex and simultaneous damages these techniques show less efficiency.