Multiple Damage Locations Research Articles

Damage detection of a thin plate using pseudo local flexibility method

The virtual forces of the original local flexibility method are restricted to inducing stress on the local parts of a structure. To circumvent this restriction, we developed a pseudo local flexibility (PLFM) method that can successfully detect damage to hyperstatic beam structures using fewer modes. For this study, we further developed the PLFM so that it could detect damage in plate structures. We also devised the theoretical background for the PLFM with non-local virtual forces for plate structures, and both the lateral and rotary degree of freedom (DOF) measurements were considered separately. This study investigates the effects of the number of modes, the actual location that sustained damage, multiple damage locations, and noise in modal parameters for the damage detection results obtained from damaged numerical plates. The results revealed that the PLFM can be used for damage detection, localization, and quantification for plate structures, regardless of the use of the lateral DOF and/or rotary DOF.

Damage assessment in plate-like structures using a two-stage method based on modal strain energy change and Jaya algorithm

ABSTRACTThe paper presents an effective two-stage approach based on modal strain energy change and Jaya algorithm for damage assessment in plate-like structures. In the first stage, a newly developed damage indicator, named as normalized modal strain energy-based damage index (nMSEBI), is proposed to help locate potential damage elements more effectively. After eliminating most of the healthy elements, the actual damaged sites and its extent in plate structure are determined in the second stage by minimizing an objective function, which is solved using Jaya algorithm. For finding a suitable objective function used in optimization process, two different objective functions are considered to examine their effects on the performance of the utilized optimization algorithm. The efficiency and accuracy of the proposed two-stage damage detection method are investigated by two numerical examples comprising a concrete plate and a four-layer (0°/90°/90°/0°) laminated composite plate with multiple damage locations. All of the obtained results indicate that even under measurement noise, the proposed method can identify the actual damage sites and estimate the extent of damage with high precision. In addition, the numerical results also show that the computational cost of the optimization process using the objective function based on modal flexibility change is much lower than that using the objective function based on mode shapes change.

An improved EMD method for modal identification and a combined static-dynamic method for damage detection

Empirical mode decomposition (EMD) is a highly adaptable signal processing method. However, the EMD approach has certain drawbacks, including distortions from end effects and mode mixing. In the present study, these two problems are addressed using an end extension method based on the support vector regression machine (SVRM) and a modal decomposition method based on the characteristics of the Hilbert transform. The algorithm includes two steps: using the SVRM, the time series data are extended at both endpoints to reduce the end effects, and then, a modified EMD method using the characteristics of the Hilbert transform is performed on the resulting signal to reduce mode mixing. A new combined static-dynamic method for identifying structural damage is presented. This method combines the static and dynamic information in an equilibrium equation that can be solved using the Moore-Penrose generalized matrix inverse. The combination method uses the differences in displacements of the structure with and without damage and variations in the modal force vector. Tests on a four-story, steel-frame structure were conducted to obtain static and dynamic responses of the structure. The modal parameters are identified using data from the dynamic tests and improved EMD method. The new method is shown to be more accurate and effective than the traditional EMD method. Through tests with a shear-type test frame, the higher performance of the proposed static-dynamic damage detection approach, which can detect both single and multiple damage locations and the degree of the damage, is demonstrated. For structures with multiple damage, the combined approach is more effective than either the static or dynamic method. The proposed EMD method and static-dynamic damage detection method offer improved modal identification and damage detection, respectively, in structures.

Numerical and experimental investigation of modal-energy-based damage localization for offshore wind turbine structures

Offshore wind turbine structures are prone to deterioration and damage during their service life in harsh marine environment. To explore highly efficient and robust damage detection methods for offshore wind turbine structures, three well-known modal strain energy indices are reviewed first and then a new index named total modal energy method is proposed. The innovation of the new index is the simultaneous use of modal strain energy and modal kinetic energy. To investigate the feasibility and robustness of the four modal-energy-based methods, numerical and experimental studies are conducted on a tripod-type offshore wind turbine structure with simulated and measured data. It is indicated that all the four modal-energy-based methods work well with limited incomplete modal data, especially for the single-damage cases. While for the cases of multiple damage locations, the new total modal energy index significantly outperforms the traditional modal strain energy indices. Moreover, high robustness is shown for the indices, when the measured mode shapes of undamaged and damaged structures are polluted with the same noise level. However, when their noise levels have some difference, two of the modal strain energy indices turn invalid, but the new total modal energy index still shows stronger robustness. As frequencies are also used in the total modal energy index, its robustness to the noise in modal frequencies is also studied. It is shown that the results are slightly affected by the measurement noise in modal frequencies. Besides, the influence of finite element modeling errors is also investigated with both simulated and experimental data. Results show that all the four modal-energy-based methods are all very stable and insensitive to certain modeling errors. So, finite element model updating is not necessary in the test structure herein.

A Multi-Objective DIRECT Algorithm Toward Structural Damage Identification With Limited Dynamic Response Information

A major challenge in structural health monitoring (SHM) is to accurately identify both the location and severity of damage using the dynamic response information acquired. While in theory the vibration-based and impedance-based methods may facilitate damage identification with the assistance of a credible baseline finite element model, the response information is generally limited, and the measurements may be heterogeneous, making an inverse analysis using sensitivity matrix difficult. Aiming at fundamental advancement, in this research we cast the damage identification problem into an optimization problem where possible changes of finite element properties due to damage occurrence are treated as unknowns. We employ the multiple damage location assurance criterion (MDLAC), which characterizes the relation between measurements and predictions (under sampled elemental property changes), as the vector-form objective function. We then develop an enhanced, multi-objective version of the dividing rectangles (DIRECT) approach to solve the optimization problem. The underlying idea of the multi-objective DIRECT approach is to branch and bound the unknown parametric space to converge to a set of optimal solutions. A new sampling scheme is established, which significantly increases the efficiency in minimizing the error between measurements and predictions. The enhanced DIRECT algorithm is particularly suited to solving for unknowns that are sparse, as in practical situations structural damage affects only a small region. A number of test cases using vibration response information are executed to demonstrate the effectiveness of the new approach.

Enhanced optimization-based structural damage detection method using modal strain energy and modal frequencies

To identify the location and severity of structural damages precisely, a two-stage damage detection method is proposed here. In the first stage, the most probable elements that maybe damaged are determined using the modal strain energy concept of structure. For such purpose, an efficient modal strain energy conversion-based index is proposed. In the second stage, the structural damage identification problem is defined as an optimization problem that to be solved by a modified genetic algorithm. In the optimization problem, the damage extents of structure’s elements which are determined in the previous stage are considered as the variables. An efficient objective function considering the first few modal frequencies of the structure, before and after damage occurrence, is utilized for optimization. The robustness of the proposed method is assessed by several benchmark examples. The numerical results exhibit the effectiveness of the proposed method for precisely determining the location and severity of multiple structural damages.

Efficiency of Jaya algorithm for solving the optimization-based structural damage identification problem based on a hybrid objective function

ABSTRACTA Jaya algorithm was recently proposed for solving effectively both constrained and unconstrained optimization problems. In this article, the Jaya algorithm is further extended for solving the optimization-based damage identification problem. In the current optimization problem, the vector of design variables represents the damage extent of elements discretized by the finite element model, and a hybrid objective function is proposed by combining two different objective functions to determine the sites and extent of damage. The first one is based on the multiple damage location assurance criterion and the second one is based on modal flexibility change. The robustness and efficiency of the proposed damage detection method are verified through three specific structures. The obtained results indicate that even under relatively high noise level, the proposed method not only successfully detects and quantifies damage in engineering structures, but also shows better efficiency in terms of computational cost.

A two-stage assessment method using damage locating vector method and differential evolution algorithm for damage identification of cross-ply laminated composite beams

This article proposes a two-stage damage identification method to identify the location and extent of multiple damages at individual layers in laminated composite beams. In the first stage, the dam...

Locating small structural damages in pipes using space-frequency DORT processing

A new imaging algorithm is introduced and applied for inspection of damages in pipes employing ultrasonic guided waves. The algorithm is based on the decomposition of the time-reversal operator (DORT, in its French acronym) and is demonstrated using both simulations and experiments. Its performance is compared against more traditional time-reversal imaging algorithms. The proposed algorithm is shown to be effective to determine the number and relative location of multiple small damages in pipes with good resolution.

Multi-stage method to identify structural damage using multiple damage location assurance criterion and an improved differential evolution algorithm

For the damage identification technique of civil structures, the reduction of the computational cost for methods based on the optimization algorithms is the most crucial step. In this study, a fast multi-stage method is developed that uses the multiple damage location assurance criterion and an improved differential evolution algorithm. In the new method, the suitable damage range is selected in different stages to reduce the computational cost of structural analysis. Five mutation operators are analysized not only in the basic differential evolution algorithm but also in the improved one. A new adaptive scaling factor with a segmented function is proposed which can operate the decay rate to avoid the premature phenomenon. The results of the study show that the precise locations and extents of structural damage are successfully realized. It is also shown that the multi-stage method using the improved differential evolution algorithm is substantially faster as compared to the basic one and can be used as an efficient and powerful measure of structural damage identification.

Damage detection of plate-like structures using intelligent surrogate model

Cracks in plate-like structures are some of the main reasons for destruction of the entire structure. In this study, a novel two-stage methodology is proposed for damage detection of flexural plates using an optimized artificial neural network. In the first stage, location of damages in plates is investigated using curvature-moment and curvature-moment derivative concepts. After detecting the damaged areas, the equations for damage severity detection are solved via Bat Algorithm (BA). In the second stage, in order to efficiently reduce the computational cost of model updating during the optimization process of damage severity detection, multiple damage location assurance criterion index based on the frequency change vector of structures are evaluated using properly trained cascade feed-forward neural network (CFNN) as a surrogate model. In order to achieve the most generalized neural network as a surrogate model, its structure is optimized using binary version of BA. To validate this proposed solution method, two examples are presented. The results indicate that after determining the damage location based on curvature-moment derivative concept, the proposed solution method for damage severity detection leads to significant reduction of computational time compared with direct finite element method. Furthermore, integrating BA with the efficient approximation mechanism of finite element model, maintains the acceptable accuracy of damage severity detection.

A wavelet-based Bayesian damage identification technique using an evolutionary algorithm

Structural damage identification is a challenging task, especially when response measurements have local discontinuities and display non-stationarity. This paper presents a one-stage model-based damage identification technique using wavelet power spectra to address this problem. To detect, locate and estimate the severity of damage, the finite element model is updated using a Bayesian probabilistic approach and a covariance matrix adaptation evolution strategy, taking into account the uncertainty caused by measurement noise and modelling error. A range of numerical simulations are used to evaluate the efficacy of the model under different damage scenarios, including: both single and multiple damage locations; varying damage severity; the introduction of noise and modelling errors and incompleteness in the number of captured modes and measurement response data applied to a beam structure. The results obtained across the damage scenarios are observed to be robust. A comparison against existing power spectral density-based methods, which are only applicable in the case of stationary data, indicates that the proposed approach outperforms in almost all damage conditions.

Identifiability Analysis of Finite Element Models for Vibration Response-Based Structural Damage Detection in Elastic Beams

Abstract Finite element model (FEM) is a broadly used numerical tool in structural damage detection. In such applications, damage parameters in FEM are estimated by minimizing the differences between experimental modal analysis data and the corresponding FEM model prediction. Very limited works exist on analyzing the identifiability of the FEM used in such applications. In this paper, the identifiability of FEM-based structural damage detection is investigated for undamped elastic beams. We theoretically proved that damage severity at a given location in a uniform beam is identifiable by reformulating the FEM into a linear time invariant (LTI) system. A numerical algorithm is also proposed for checking the identifiability issue of multiple damage locations. Numerical case studies are provided to validate the effectiveness and usefulness of the proposed framework.

A multi-stage approach for damage detection in structural systems based on flexibility

The paper proposes a fusion approach for damage detection in structural applications in the case of multiple damage locations and three-dimensional systems. Based on the Dempster–Shafer evidence theory, a multi-stage approach is proposed with the mode shapes assumed as primary sources and local decisions based on a flexibility method. The proposed approach has been applied to two case studies, a a fixed end beam analyzed in other papers and a three dimensional structures codified in a Benchmark problem. Both the case studies have shown the ability and the efficiency of the proposed approach to detect damage also in the case of multiple damage, limited number of identified parameters and noise measurements.

Resolving Individual Damage Sites in DNA with AFM using Reengineered Repair Proteins

UV irradiation can produce widespread and chemically heterogeneous damage that can accumulate to cause diseases, most notably melanoma and other types of cancers. The ability to identify, map and discriminate discrete damage sites on single DNA molecules can provide new diagnostics or insights into the progression and onset of precancerous conditions and melanoma. Atomic Force Microscopy (AFM) provides an ideal method to map individual damage locations because it produces real space images of single DNA molecules. However, UV-induced damage and many damage-binding proteins that could be used to label these sites are not directly resolvable by AFM. Here we have reengineered DNA damage proteins at the genetic level to be observable by AFM imaging when bound to damaged DNA. Using T4 Endonuclease V, a pyrimidine dimer-specific base excision repair protein too small to imaged by AFM, as a model UV damage repair protein we introduced a number of discrete I27 domains at the C-terminus, which sufficiently increases its size without interfering with native activity. Using these novel “structural labels”, we are currently trying to visualize multiple damage locations simultaneously in both linear and genomic DNA via single molecule AFM imaging. These structural labels which can be adapted to a number of damage-binding proteins to target a variety of damage sites provide a potential methodology for single molecule diagnostics.

A Bayesian Damage Identification Technique Using Evolutionary Algorithms - a Comparative Study

In this paper, a one-stage model-based damage identification technique based on the response power spectral density of a structure is investigated. The technique uses a finite element updating method with a Bayesian probabilistic framework that considers the uncertainty caused by measurement noise and modelling errors. The efficacy of two different evolutionary algorithms – a genetic algorithm and a covariance matrix adaptation evolution strategy – is examined via numerical simulation of time-history response data for a beam structure. A range of different damage scenarios have been considered including: both single and multiple damage locations; varying damage severity; the introduction of noise and modelling errors and incompleteness in the number of captured modes and measurement response data. The results clearly show that both evolutionary algorithms implemented are effective and their overall performance, measured in terms of accuracy, is very similar. However, the covariance matrix strategy is found to be significantly superior in terms of its convergence rate and the number of function evaluations required to find the solution for both noisy and noise-free response data.

Damage Identification of Urban Overpass Based on Hybrid Neurogenetic Algorithm Using Static and Dynamic Properties

Urban overpass is an important component of transportation system. Health condition of overpass is essential to guarantee the safe operation of urban traffic. Therefore, damage identification of urban overpass possesses important practical significance. In this paper, finite element model of left auxiliary bridge of Qianjin Overpass is constructed and vulnerable sections of structure are chosen as objects for damage recognition. Considering the asymmetry of Qianjin bridge, change rate of modal frequency and strain ratio are selected as input parameters for hybrid neurogenetic algorithm, respectively. Identification effects of damage location and severity are investigated and discussed. The results reveal that the proposed method can successfully identify locations and severities with single and multiple damage locations; its interpolation ability is better than extrapolation ability. Comparative analysis with BP neural network is conducted and reveals that the damage identification accuracy of hybrid neurogenetic algorithm is superior to BP. The effectiveness between dynamic and static properties as input variable is also analyzed. It indicates that the identification effect of strain ratios is more satisfactory than frequency ratio.

Non-Destructive Evaluation Method Based On Dynamic Invariant Stress Resultants

Most of the vibration based damage detection methods are based on changes in frequencies, mode shapes, mode shape curvature, and flexibilities. These methods are limited and typically can only detect the presence and location of damage. Current methods seldom can identify the exact severity of damage to structures. This paper will present research in the development of a new non-destructive evaluation method to identify the existence, location, and severity of damage for structural systems. The method utilizes the concept of invariant stress resultants (ISR). The basic concept of ISR is that at any given cross section the resultant internal force distribution in a structural member is not affected by the inflicted damage. The method utilizes dynamic analysis of the structure to simulate direct measurements of acceleration, velocity and displacement simultaneously. The proposed dynamic ISR method is developed and utilized to detect the damage of corresponding changes in mass, damping and stiffness. The objectives of this research are to develop the basic theory of the dynamic ISR method, apply it to the specific types of structures, and verify the accuracy of the developed theory. Numerical results that demonstrate the application of the method will reflect the advanced sensitivity and accuracy in characterizing multiple damage locations.

Nonparametric statistical formulations for structural health monitoring

This paper presents a group of nonparametric statistical formulations for structural health monitoring (SHM). Vibration response data are first represented by the coefficients of a series of fitted autoregressive (AR) models in the time domain or by the averages of binned power spectral density (PSD) estimates in the frequency domain. Three types of statistical hypotheses are then formulated and tested by nonparametric techniques to monitor these characteristics. Specifically, two-sample Kolmogorov–Smirnov test, Mann–Whitney test, and Mood test are used in this study. For each type of hypothesis formulation, a function of the resulting P-values is used to define a damage indicator profile (DIP) whereby damage locations are identified. The highlight of these formulations is that, due to their nonparametric nature, they do not require a particular functional form for the probability distribution of the underlying population of an extracted vibration response data characteristic. Two numerically simulated case studies, i.e., a 20-degree-of-freedom system and a hyperbolic paraboloid roof shell, demonstrate the efficacy of the proposed nonparametric SHM formulations. Multiple damage locations are also considered in the case studies.

Reliability of Using Curvature TechniquesinStructural Damage Detection

A damage in a structure alters its dynamic characteristics; namely, natural frequencies, modal damping values, and mode shapes. Changes also occur in some of the structural parameters such as:the mass, dampingand stiffness matrices of the structure. Among different algorithms developed for structural damage identification, changes in eithermode shape curvature oruniform load surface (ULS) curvature, derived from measured modal properties,have shown promise for locating structural damage. However, to date there is not a study reported in the technical literature that directly compares these two promising methods. The numerical results in this paper attempt to fill this void in the study of damage detection methods. In this paper, a numerical study is investigated to compare the robustness of these two methodsin damage detection using the frequencies and mode shapes of the first few modes. Also, the application of a damage localization algorithm to these two methods in detecting and locating damage is demonstrated. The numerical results show that both of the two methods can accurately locate single damage with different damage characteristics (location and severity).However, thetwo methods have shownless sensitivity to specific types of damage when applied to multiple damage locations. Also, the results of the ULS curvature method contain less noise than that of the results of the mode shape curvature method.Finally, the mode shape curvature can pinpoint damage locations even with one of the lower mode shapes of the structure and it does not require the mode frequency.