Damage Identification Procedure Research Articles

Multi-objective sensor placement optimization in SHM systems with Kriging-based mode shape interpolation

Sensor location optimization plays a key role in the application and development of structural integrity monitoring methodologies, especially in large mechanical structures. Given the existence of an effective damage detection and identification procedure, the question of how many and where to place the acquisition points (sensors) so that the monitoring system operates at peak efficiency arises. In this study, an innovative methodology is proposed in order to maximize the quality of modal information and minimize the number of sensors in the SHM system. To maximize the quality of modal information, it considered the reconstruction of mode shapes using Kriging interpolation. The study was carried out on plate-type composite material structures for initial validation and later applied and validated on a main rotor blade of the AS-350 helicopter. The initial modal information (modal deformation) was obtained through the finite element method, and the multi-objective Lichtenberg algorithm was used in the complex optimization process. The proposed method presented in this work allows for the best possible distribution of a minimum and sufficient number of acquisition points in a structure in order to obtain more modal information for a better modal reconstruction from kriging interpolation of these minimum points. Numerical examples and test results show that the proposed method is robust and effective for distributing a reduced number of sensors in a structure and at the same time guaranteeing the quality of the information obtained, even in noisy situations. Numerical results considering both the simple and complex geometric cases show that the proposed combined FS-kriging method is effective in distributing a finite number of sensors on the structures and at the same time guaranteeing the quality of the modal information obtained. The results also indicate that the layout of sensors obtained by multi-objective optimization does not become trivial and symmetrical when a set of modes is considered in the objective function formulation. The proposed strategy is an advantage in modal testing as it is only necessary to acquire signals at a limited number of points, saving time and operating costs in vibration-based processes.

Template mass and stiffness for vibration analysis and damage detection of plane structures

This paper investigates he vibration properties of template plane elements in both themes of optimum mass matrix formulation and damage identification. To find the optimum mass matrices for the elements, the classical and unconventional mass formulations for the plane problems are explored. The optimum mass is obtained by the template approach, along with an optimization procedure, based on the perturbation theory and sensitivity analysis. The efficiencies of the proposed optimum mass are investigated through numerical examples for some plane structures. Those pairs of the optimum mass and stiffness, which yield more accurate results in the vibration analysis, are utilized for damage identification. A novel damage localization index based on the in-plane transverse vibrations is proposed and applied successfully in a new two-stage damage identification procedure for planar structures. By using Test Analysis-Model correlation (TAM) and the element damage equations; authors' algorithm overcomes the challenges of limitations in measuring all the degrees of freedoms. Furthermore, the proposed algorithm has the potential to diagnose the false alarms and prevents the ill-condition problem in damage identification. The abilities of the suggested method are demonstrated through 11 different damage scenarios and the presence of noise.

Structural Health Evaluation of Arch Bridge by Field Test and Optimized BPNN Algorithm

Arch bridges play an important role in rural roads in China. Due to insufficient funds and a lack of management techniques, many rural arch bridges are in a state of disrepair, unable to meet the increasing transportation needs. Thus, it is of great significance to develop a set of rapid and economic damage identification procedures for the management and maintenance of old arch bridges. Sanliushui Bridge, located in Chenggu County, Hanzhong, is selected as a model case. Field tests and numerical simulations were carried out to identify the damage states of Sanliushui Bridge. The sum square of wavelet packet energy change rate, a damage identification index based on wavelet packet analysis method was implemented to process the measured data of the load test and the simulated data of the numerical calculation model with assumed damage. BPNN, GA-BPNN, PSO-BPNN and test data analysis are adopted to compare the measured data with the simulated data to quantitatively identify the damage degree of the selected bridge. By comparing the results of the two methods mentioned above, it is found that the proposed damage identification approach realized a precise damage identification of the selected arch bridges.

Application of two dimensional Morlet wavelet transform in damage detection for composite laminates

Wavelet transform as a novel signal processing method for singularity detection has been introduced into vibration-based nondestructive testing (NDT) methods. However, for plate-like structures, the mode-shape-based NDT methods depend on the powerful two-dimensional (2D) singularity detection method. The 2D continuous wavelet transform (CWT) based on 2D Morlet wavelet function has high sensitivity to singularity in certain direction, but its anisotropic behavior strongly limits its application in damage detection for plate-like structures. In this paper, a modified 2D Morlet wavelet function is proposed to make the 2D CWT behave like a quasi-isotropic transform and show high sensitivity to damage in all directions. After a series of numerical simulations are conducted to investigate the performance of the modified 2D Morlet wavelet function and verify its effectivity in damage detection, a damage identification procedure for composite laminates is experimentally conducted and damage index (DI) is also determined by the modified wavelet coefficient. Results indicate that the 2D CWT based on the modified 2D Morlet wavelet can provide a baseline-free NDT method based on MS, and its effectivity and robustness are experimentally confirmed.

User-defined high impulsive frequency acquisition model for mechanical damage identification

In the past few decades, time–frequency (TF) methods have become increasingly popular in the field of modal identification and structural health monitoring. The general and significant shortfalls of the TF models are the distributed and vague frequency components as an output. To overcome the cons of the initial TF technique, segregation of the modes incorporated within the affected vibration signatures evolved eventually. The most utilized and preferred technique can be named empirical mode decomposition (EMD) and its variants. However, these variants, along with the basic framework, possess the multi-mode tendency, which further compels the extension of the whole damage identification procedure. This work presents the development of a temporally evolved, generalized and high impulsive frequency acquisition model for structural damage identification. To meet the said outcome, variational mode decomposition (VMD) is considered an optimization-based signal decomposition tool that utilizes the contents of the generated modal responses. This work also aims to investigate the applicability of VMD for the purpose of structural damage identification for the following situations: the old ADA steel bridge under vehicle-induced vibration for various damage scenarios; a three-story shear frame building model. Along with the said validation of the proposed condition monitoring model, this paper addresses the need of stable and reliable novel damage indicator (DI) as a statistical alteration of the extracted instantaneous outputs. The proposed DI as the mean of the ratio of the instantaneous outputs collectively indicates the relative capacity of the structure to produce a stable response. The selected outputs are instantaneous frequency, phase and energy, taken into consideration to depict the physical alterations in the measured response. The proposed DI evidently explains the physical relation of the involved factors with the degradation causes in the considered structure. The DI also reflects the remaining usefulness of the system and provides the measurements in safety aspects to the operators. The results so obtained are well competent for real bridge structures under the influence of dynamic loading conditions induced by vehicle movements.

An improved fracture approach to investigate the degradation of vibration characteristics for reinforced concrete beams under progressive damage

This work presents a cohesive fracture modeling approach to investigate the damage effects on the mechanical response of reinforced concrete beams in terms of degradation of vibration characteristics. The proposed model can simulate the diffuse cracking behavior of reinforced concrete beams together with the steel–concrete interaction providing also the static and dynamic response at increasing damage levels including the effects of concrete cyclic behavior. The numerical outcomes were validated through comparisons with experimental results reported in the literature, demonstrating the consistency and the applicability of the proposed numerical model in the framework of “model-based” damage identification procedures.

A novel approach for deterioration and damage identification in building structures based on Stockwell-Transform and deep convolutional neural network

ABSTRACT In this paper, a novel deterioration and damage identification procedure (DIP) is presented and applied to building models. The challenge associated with applications on these types of structures is related to the strong correlation of responses, an issue that gets further complicated when coping with real ambient vibrations with high levels of noise. Thus, a DIP is designed utilizing low-cost ambient vibrations to analyze the acceleration responses using the Stockwell transform (ST) to generate spectrograms. Subsequently, the ST outputs become the input of two series of Convolutional Neural Networks (CNNs) established for identifying deterioration and damage on the building models. To the best of our knowledge, this is the first time that both damage and deterioration are evaluated on building models through a combination of ST and CNN with high accuracy.

A Cohesive fracture approach for the nonlinear analysis of load-induced degradation of vibration characteristics in RC beams

In this work, the effects of damage on the mechanical and vibrational response of reinforced concrete structures is investigated. The proposed model is based on a cohesive interface approach able to simulate the diffuse cracking behavior typical of reinforced concrete structures, in conjunction with an embedded truss model, able to simulate interaction phenomena between steel reinforcement and surrounding concrete. The mathematical model is developed to describe in a realistic way the crack pattern and its evolution and to determine the main factors that can influence the static and dynamic response of damaged reinforced concrete structures. Their static and dynamic properties were evaluated for increasing levels of damage after the removal of the load, starting from the load level at the first crack nucleation to the load level of incipient collapse. In order to verify the accuracy and reliability of the proposed computational model, the numerical results, obtained in terms of variations of the vibrational characteristics of the system will also be compared with experimental data reported in literature. Results show the applicability and reliability of damage identification procedures based on both mathematical models and experimental data for structural systems such as reinforced concrete beams common in girder bridges.

A State-of-the-Art Review on FRF-Based Structural Damage Detection: Development in Last Two Decades and Way Forward

Vibration-based damage detection techniques receive wide attention of the research community in recent years to overcome the limitations of conventional structural health monitoring methods. The modal parameters, namely, natural frequencies, mode shapes, transmissibility, frequency response function (FRF), and other damage sensitive features are usually employed to identify damage in a structure. The main objective of this review is to generate a detailed understanding of FRF-based techniques and to study their performance in terms of advantage, accuracy, and limitations in structural damage detection. This paper also reviews various approaches to develop methodologies in terms of efficiency and computational time. The study observed that excitation frequency, location of application of excitation, type of sensor, number of measurement locations, noise contamination in FRF data, selection of frequency range for simulation, weighting and numerical techniques to solve the over-determined set of equations influence the effectiveness of damage identification procedure. Limitations and future prospects have also been addressed in this paper. The content of this paper aims to guide researchers in developing formulations, updating models, and improving results in the field of FRF-based damage identification.

An effective damage identification procedure using model updating technique and multi-objective optimization algorithm for structures made of functionally graded materials

An effective damage identification procedure using model updating technique and multi-objective optimization algorithm for structures made of functionally graded materials

Structural damage identification through sensitivity-based finite element model updating and wavelet packet transform component energy

Civil infrastructures deteriorate due to aging, adverse environmental conditions, and inadequate maintenance. Thus, to ensure both safety and serviceability of the structures as well as to mitigate economic losses, it is essential to employ a comprehensive structural health monitoring (SHM) system and appropriate damage identification procedure. Finite element (FE) model updating is one of the most common approaches of damage detection in civil engineering. The most widely used techniques for FE model updating have been developed based on data in the time, time–frequency, and modal domains. In this study, a novel damage identification technique is proposed based on wavelet packet transform component energy (WPTCE). The discrepancy between WPTCE of intact and damaged states of the structure was considered as a residual in the sensitivity-based FE model updating procedure. Two numerical examples, namely a two-dimensional truss bridge and a double layer diamatic dome was used to illustrate the efficiency and applicability of the proposed method in structural damage identification. Sensitivity analysis showed that the WPTCE is a highly sensitive response to structural damages. Further, the results revealed that the proposed method leads to accurate detection of damage, though the measured signals are contaminated by noise.

Dynamic damage identification for a full-scale parabolic tuff barrel vault under differential settlements of the supports

The vibration response of a full-scale polycentric near parabolic tuff barrel vault under differential settlements of the abutments are experimentally analyzed. During the experimental tests, the static and dynamic responses of the vault have been continuously monitored through a large number of sensors of different kinds placed in suitable points of the structure and supports.The data acquired by the accelerometric sensors are used for detection, localization, and quantitative assessment of the damage by means of a dynamic damage identification (DDI) procedure specifically developed for arches. Numerical models calibrated from experimental results are employed to evaluate the effectiveness of the proposed DDI approach. The position of the crack hinges related to the experimental and theoretical collapse mechanism of the vault, along with their actual depth, turn out to be effectively identified through the proposed DDI procedure, showing the capabilities of such an approach for assessing damage even in existing full-scale masonry constructions.

A Mahalanobis Distance Cumulant-Based Structural Damage Identification Method with IMFs and Fitting Residual of SHM Measurements

Data-driven damage identification based on measurements of the structural health monitoring (SHM) system is a hot issue. In this study, based on the intrinsic mode functions (IMFs) decomposed by the empirical mode decomposition (EMD) method and the trend term fitting residual of measured data, a structural damage identification method based on Mahalanobis distance cumulant (MDC) was proposed. The damage feature vector is composed of the squared MDC values and is calculated by the segmentation data set. It makes the changes of monitoring points caused by damage accumulate as “amplification effect,” so as to obtain more damage information. The calculation method of the damage feature vector and the damage identification procedure were given. A mass-spring system with four mass points and four springs was used to simulate the damage cases. The results showed that the damage feature vector MDC can effectively identify the occurrence and location of the damage. The dynamic measurements of a prestress concrete continuous box-girder bridge were used for decomposing into IMFs and the trend term by the EMD method and the recursive algorithm autoregressive-moving average with the exogenous inputs (RARMX) method, which were used for fitting the trend term and to obtain the fitting residual. By using the first n-order IMFs and the fitting residual as the clusters for damage identification, the effectiveness of the method is also shown.

A Novel Method to Estimate the Damage Severity Using Spatial Wavelets and Local Regularity Algorithm

In the process of structural damage detection using continuous wavelet transform (CWT), the perturbation or damage is located by identifying the defects locally in the input signal data. In this work the damage identification procedure using continuous wavelet transform is developed. This method is studied numerically using a simple beam model. The influence of reduced spatial sampling using fundamental mode shape is investigated in detail. The method is also investigated to ascertain the smallest level of damage identified using strain energy mode shape data.

Embankment responses to shield tunnelling considering soil-structure interaction: case studies in Hangzhou soft ground

As more and more under-river tunnels are constructed in urban areas, the deformations and potential damage of existing embankments due to tunnelling have become a major concern. This problem is complex because not only does tunnelling affect the existing embankments, but their presence also alters tunnelling-induced ground movements. An analytical method, which takes account of the effects of the embankment’s self-weight, the property of the soil-embankment interface, and the embankment’s bending and axial stiffness, is put forward to estimate the embankment’s deflections and horizontal strains due to tunnelling. Subsequently, a procedure is proposed to identify the embankment’s damage level based on its calculated maximum tensile strain. In the end, case studies of three embankments in Hangzhou soft ground are conducted to examine and validate the analytical method and the damage identification procedure. Further parametric studies show that the embankment’s bending stiffness has a significant effect on its deflections and damage level, while the influence of self-weight is mild.

Theory and numerical application of damage localization method state projection estimation error (SP2E)

In this article, the authors elaborate the theory and application of the state projection estimation error (SP2E) method. SP2E has been developed to efficiently localize structural damage. The authors begin by discussing some estimation techniques for damage identification. Because exact analytical mechanical parameters and structural excitations are often unknown for real large-scale structures, the parametrization of a mechanical system by stochastic subspace identification is considered. This leads to discrete-time state space parameters and is the basis for estimation, which allows to cope with unknown structural excitations. For damage localization, we applied SP2E and compared the result afterwards to a defined difference process. This led to the proposed damage identification procedure, which finally is applied in real laboratory experiments. Based on a discussion of different estimation techniques and their numerical application, the experimental results confirm the method SP2E.

Statistical damage identification method based on dynamic response sensitivity

The traditional deterministic damage detection method is based on the assumption that the measured data and the finite element model are accurate. However, in real situation, there are many uncertainties in the damage identification procedure such as the errors of the finite element model and the measurement noise. Since the uncertainties inevitably exist in the finite element models and measured data, the statistic method which considers the uncertainty has wide practical application. This paper proposes a statistical damage identification method based on dynamic response sensitivity in state-space domain. Considering the noise of the finite element model and measured acceleration response, the statistical variations of the damaged finite element model are derived with perturbation method which is based on a Taylor series expansion of the response vector and verified by Monte Carlo technique. Afterward, the probability of damage existence for each structural element is estimated using the statistical characteristic of the identified structural parameters. A numerical simply supported beam under the moving load is applied to demonstrate the accuracy and efficiency of the proposed statistical method.

A multiobjective sensor placement optimization for SHM systems considering Fisher information matrix and mode shape interpolation

Sensor placement optimization plays a key role in structural health monitoring (SHM) of large mechanical structures. Given the existence of an effective damage identification procedure, the problem arises as to how the acquisition points should be placed for optimal efficiency of the detection system. The global multiobjective optimization of sensor locations for structural health monitoring systems is studied in this paper. First, a laminated composite plate is modelled using Finite Element Method (FEM) and put into modal analysis. Then, multiobjective genetic algorithms (GAs) are adopted to search for the optimal locations of sensors. Numerical issues arising in the selection of the optimal sensor configuration in structural dynamics are addressed. A method of multiobjective sensor locations optimization using the collected information by Fisher Information Matrix (FIM) and mode shape interpolation is presented in this paper. The sensor locations are prioritized according to their ability to localize structural damage based on the eigenvector sensitivity method. The proposed method presented in this paper allows to distribute the points of acquisition on a structure in the best possible way so as to obtain both data of greater modal information and data for better modal reconstruction from a minimum point interpolation. Numerical example and test results show that the proposed method is effective to distribute a reduced number of sensors on a structure and at the same time guarantee the quality of information obtained. The results still indicate that the modal configuration obtained by multiobjective optimization does not become trivial when a set of modes is used in the construction of the objective function. This strategy is an advantage in experimental modal analysis tests, since it is only necessary to acquire signals in a limited number of points, saving time and operational costs.

An enhanced energy vibration-based approach for damage detection and localization

This paper addresses the enhanced identification and localization of structural damage by means of the recorded response induced by ambient excitation. Damage detection is based purely on the vibration energy in structural acceleration records, deriving thereof the normalized cumulative power spectral density as the characteristic damage sensitive quantity. As key aspect of this contribution, a method for “correction” of the recorded response is proposed, to account for deviations from perfect stationary white noise excitation. Based on an overdetermined system of equations, recorded spectra are modified to better fit previously recorded spectra. This fitting affects broader frequency ranges, while the damage sensitive feature captures changes in narrow frequency bands. Thus, the proposed “correction” method does not mask or remove the effects of structural changes in the response. Subsequent damage localization in cantilever-like structures is based on the changes of the drift of the fundamental mode shape amplitudes. The efficiency of the proposed two-step damage identification procedure is tested on a small-scale shear frame model in various damaged conditions. It is shown that the defined normalized cumulative power spectral density damage index is suitable to indicate most of the imposed damages, in particular when the proposed response correction methodology is applied. The spots of damage are successfully identified by the utilized mode shape damage indicator.

Damage detection via closed-form sensitivity matrix of modal kinetic energy change ratio

In this paper, a new damage detection method based on a damage sensitive feature parameter named Modal Kinetic Energy Change Ratio has been proposed. The sensitivity matrix for the damage identification procedure is calculated by making use of the closed-form sensitivity of eigenvalues of the structure. Numerical simulations and experimental tests were carried out on a beam-like structure in order to examine the reliability and feasibility of the proposed method. System Equivalent Reduction Expansion Technique is employed to omit rotational degrees of freedom of the model. It is demonstrated that this method locates and quantifies structural damage(s) with acceptable accuracy. The best advantage of the proposed method comparing to the ones which are based on modal strain energy is that it is not sensitive to mode shape noise and yields favorable results under moderate noise in natural frequencies.