Approach For Structural Damage Identification Research Articles

A two-step method for damage identification in beam structures based on influence line difference and acceleration data

This article presents a two-step approach for structural damage identification in beam structure. Damages are located using the influence line difference before and after damage, the calculation of damage severity is accomplished by acceleration data and bird mating optimizer algorithm. Local damages are simulated as the reduction of both the elemental Young’s modulus and mass of the beam. The technique for damage localization based on displacement influence line difference and its derivatives for beam structure has been outlined. An objective function that comprises dynamic acceleration is utilized in bird mating optimizer. All data are originated from only a few measurement points. Two numerical examples, namely, a simply supported beam and a four-span continuous beam, are investigated in this article. Identification results from different objective functions are compared with results from objective function conventional modal assurance criterion, which shows the superiority of the proposed function. In addition, results of dynamic responses under different types of excitation are presented. The effect of measurement noise level on damage identification results is studied. Studies in the article indicate that the proposed method is efficient and robust for identifying damages in beam structures.

Identification of Minor Structural Damage Based on Electromechanical Impedance Sensitivity and Sparse Regularization

AbstractThis paper proposes a structural damage identification approach based on model updating with electromechanical impedance sensitivity and the sparse regularization technique to identify the ...

Structural damage detection based on cloud model and Dempster-Shafer evidence theory

Cloud model and D-S theory have been widely used in uncertainty reasoning. Meanwhile, modal strain energy and Inner Product Vector are also utilized as damage-sensitive features to detect structural damage. In this paper, a new structural damage identification approach is proposed based on Dempster-Shafer theory and cloud model. Cloud models were created to make uncertainty reasoning in damage structures by modal strain energy and the Inner Product Vector of acceleration. Then the results of the two methods were combined by using the Dempster-Shafer theory. Due to the classical D-S theory involves counter – intuitive behavious when the high conflicting evidences exists, the distance function was introduced to correct the conflict factor K and combine the evidences. Moreover, a model of simple beam was created to verify the feasibility and accuracy for the single-damage and the multiple-damage. The effects of noise on damage detection were investigated simultaneously. The results show that the method has strong anti-noise ability and high accuracy.

A two-step approach for damage detection in beam based on influence line and bird mating optimizer

This paper presents a two-step approach for structural damage identification in beam structure using the influence line and bird mating optimizer (BMO). Local damage is simulated as the reduction of the elemental Young’s modulus and mass of beam element. The technique for damage localization based on influence line and its derivatives before and after damage for beam structure was outlined. An objective function comprised of dynamic acceleration is utilized for BMO algorithm. The dynamic response data under external force is calculated by Newmark integration method. Numerical examples of a simply supported beam was investigated. Effect of measurement noise is studied. Studies in the paper indicate that the proposed method is efficient and robust for identifying damages in beam structures.

Guided Modal Strain Energy-Based Approach for Structural Damage Identification Using Tug-of-War Optimization Algorithm

AbstractIn this paper a new guided structural damage identification approach is presented in order to localize and quantify multiple damage cases in different structural systems. The change in the ...

An enhanced response sensitivity approach for structural damage identification: convergence and performance

SummaryThis paper develops an enhanced response sensitivity approach for structural damage identification. The whole work is mainly two‐fold. Firstly, the general response sensitivity approach has been shown to perform well for small damage, but may not work for moderate or large damage. Therefore, to overcome this drawback, the trust‐region restriction is additionally enforced to enhance the general response sensitivity approach. In doing so, the Tikhonov regularization is invoked which is simple for practical manipulation and is shown equivalent to trust‐region considerations. Secondly, concrete convergence analysis is presented to guarantee the performance of the enhanced response sensitivity approach. Numerical examples are studied to verify the proposed approach. Copyright © 2016 John Wiley & Sons, Ltd.

Structural damage identification based on modified Cuckoo Search algorithm

The Cuckoo search (CS) algorithm is a simple and efficient global optimization algorithm and it has been applied to figure out large range of real-world optimization problem. In this paper, a new formula is introduced to the discovering probability process to improve the convergence rate and the Tournament Selection Strategy is adopted to enhance global search ability of the certain algorithm. Then an approach for structural damage identification based on modified Cuckoo search (MCS) is presented. Meanwhile, we take frequency residual error and the modal assurance criterion (MAC) as indexes of damage detection in view of the crack damage, and the MCS algorithm is utilized to identifying the structural damage. A simply supported beam and a 31-bar truss are studied as numerical example to illustrate the correctness and efficiency of the propose method. Besides, a laboratory work is also conducted to further verification. Studies show that, the proposed method can judge the damage location and degree of structures more accurately than its counterpart even under measurement noise, which demonstrates the MCS algorithm has a higher damage diagnosis precision.

The Differential Evolution method applied to continuum damage identification via flexibility matrix

In the present work, a structural damage identification approach, built on the flexibility matrix, is proposed. Here, the damage state of the structure is continuously described by a cohesion parameter, which, in turn, is spatially discretized by the finite element method. Then, the inverse problem of damage identification is defined as an optimization one, where the objective is to minimize, with respect to the nodal cohesion parameters, a functional based on the difference between the experimentally obtained flexibility matrix and the corresponding one predicted by a finite element model of the structure. The Differential Evolution stochastic optimization method was considered for solving the resulting damage identification problem. The assessment of the proposed approach has been performed by means of numerical simulations on a simply supported Euler–Bernoulli beam. A brief analysis of the influence of different damage positions and severities on the undamped natural frequencies and on the flexibility matrix of the structure is presented. Then, the influence of damage and different levels of noise on the mode shapes of the structure is also considered. In the damage identification problem, different damage scenarios and noise levels were addressed. For comparison purposes, other stochastic optimization methods, namely, Particle Swarm Optimization, Luus–Jaakola and Simulated Annealing, were also considered for the identification of one damage scenario in the presence of noise corrupted data.

Structural damage identification with power spectral density transmissibility: numerical and experimental studies

This paper proposes a structural damage identification approach based on the power spectral density transmissibility (PSDT), which is developed to formulate the relationship between two sets of auto-spectral density functions of output responses. The accuracy of response reconstruction with PSDT is investigated and the damage identification in structures is conducted with measured acceleration responses from the damaged state. Numerical studies on a seven-storey plane frame structure are conducted to investigate the performance of the proposed damage identification approach. The initial finite element model of the structure and measured acceleration measurements from the damaged structure are used for the identification with a dynamic response sensitivity-based model updating method. The simulated damages can be identified accurately without and with a 5% noise effect included in the simulated responses. Experimental studies on a steel plane frame structure in the laboratory are performed to further verify the accuracy of response reconstruction with PSDT and validate the proposed damage identification approach. The locations of the introduced damage are detected accurately and the stiffness reductions in the damaged elements are identified close to the true values. The identification results demonstrated the accuracy of response reconstruction as well as the correctness and efficiency of the proposed damage identification approach.

Structural Damage Identification with Extracted Impulse Response Functions and Optimal Sensor Locations

This paper presents a structural damage identification approach based on the time domain impulse response functions, which are extracted from the measured dynamic responses with the input available. The theoretical sensitivity of the impulse response function with respect to the system stiffness parameters considering the damping model is derived. The first-order sensitivity based model updating technique is performed for the iterative model updating. The initial structural finite element model and acceleration measurements from the damaged structure are required. Local damage is identified as a reduction in the elemental stiffness factors. The impulse response function sensitivity based optimal sensor placement strategy is employed to investigate the best sensor locations for identification. Numerical studies on a beam model are conducted to validate the proposed approach for the extraction of time domain impulse response functions and subsequent damage identification. The simulated damage can be identified effectively and accurately.

A “Pseudo-excitation” approach for structural damage identification: From “Strong” to “Weak” modality

A damage characterization framework based on the “pseudo-excitation” (PE) approach has recently been established, aimed at quantitatively identifying damage in beam-, plate-, and shell-like structural components. However, it is envisaged that the effectiveness of the PE approach can be restricted in practical implementation, due to the involvement of high-order derivatives of structural dynamic deflections, in which measurement noise and uncertainties can overwhelm the damage-associated signal features upon mathematical differentiation. In this study, the PE approach was revamped by introducing the weighted integration, whereby the prerequisite of satisfying the local equilibrium conditions was relaxed from “point-by-point” to “region-by-region”. The revamped modality was thus colloquially referred to as “weak formulation” of the PE approach, as opposed to its original version which is contrastively termed as “strong formulation”. By properly configuring a weight function, noise immunity of the PE approach was enhanced, giving rise to improved detection accuracy and precision even under noisy measurement conditions. Furthermore, the ‘weak formulation’ was extended to a series of coherent variants through partial integration, rendering a multitude of detection strategies by selecting measurement parameters and configurations. This endowed the PE approach with flexibility in experimental manipulability, so as to accommodate various detection requirements. As an application of the “weak formulation”, a continuous gauss smoothing (CGS)-based detection scheme was developed, and validated by localizing multiple cracks in a beam structure, showing fairly improved noise tolerance.

An integrated approach for structural damage identification using wavelet neuro-fuzzy model

Structural damage can be identified by processing structural vibration response signals and excitation data, and thus the suitability of signal processing methods is essential to structural damage identification. To explore an intelligent signal processing method for structural damage identification, the paper integrated wavelet real-time filtering algorithm, Adaptive Neruo-Fuzzy Inference System (ANFIS) and interval modeling technique to process structural response signals and excitation data. With Wavelet Transform (WT) algorithm filtering random noise, ANFIS was found to model the structural behavior properly and interval modeling technique to quantify damage index accurately. The rapid identifications of several unknown damages and small damages indicate the efficiency of this integrated method. The comparison of these results and some other signal processing methods shows that, the proposed method can be used to identify both the time and the location when the structural damage occurs unexpectedly.

Multi-stage approach for structural damage identification using particle swarm optimization

An efficient methodology using static test data and changes in natural frequencies is proposed to identify the damages in structural systems. The methodology consists of two main stages. In the first stage, the Damage Signal Match (DSM) technique is employed to quickly identify the most potentially damaged elements so as to reduce the number of the solution space (solution parameters). In the second stage, a particle swarm optimization (PSO) approach is presented to accurately determine the actual damage extents using the first stage results. One numerical case study by using a planar truss and one experimental case study by using a full-scale steel truss structure are used to verify the proposed hybrid method. The identification results show that the proposed methodology can identify the location and severity of damage with a reasonable level of accuracy, even when practical considerations limit the number of measurements to only a few for a complex structure.

A Probabilistic Damage Identification Approach for Structures under Unknown Excitation and with Measurement Uncertainties

Recently, an innovative algorithm has been proposed by the authors for the identification of structural damage under unknown external excitations. However, identification accuracy of this proposed deterministic algorithm decreases under high level of measurement noise. A probabilistic approach is therefore proposed in this paper for damage identification considering measurement noise uncertainties. Based on the former deterministic algorithm, the statistical values of the identified structural parameters are estimated using the statistical theory and a damage index is defined. The probability of identified structural damage is further derived based on the reliability theory. The unknown external excitations to the structure are also identified by statistical evaluation. A numerical example of the identification of structural damage of a multistory shear-type building and its unknown excitation shows that the proposed probabilistic approach can accurately identify structural damage and the unknown excitations using only partial measurements of structural acceleration responses contaminated by intensive measurement noises.

A probabilistic damage identification approach for structures with uncertainties under unknown input

To avoid the false positives of damages in the deterministic identification method induced by uncertainties in measurement noise, a probabilistic method is proposed to identify damages of the structures with uncertainties under unknown input. The proposed probabilistic method is developed from a deterministic simultaneous identification method of structural physical parameters and input based on dynamic response sensitivity. The deterministic simultaneous identification method is first derived. The effect of uncertainties caused by measurement noise on the identified parameters is then investigated. The statistical parameters of the identified structural parameters are calculated. The damage index is derived from the statistical parameters of the physical parameters of intact and damaged structure. The probability of identified damage, defined as the probability of identified structural stiffness smaller than that of intact structure, is further derived using the probability method. A twelve-story building and a nine-bay three-dimensional frame structure are, respectively, analyzed numerically and experimentally using the proposed method. The research results indicate that the probabilistic simultaneous identification method for damage and input can decrease the false positives of damages in contrast with the deterministic method under intensive measurement noise, and it can also achieve an accurate identification for structural unknown input.

An acceleration residual generation approach for structural damage identification

A residual generation approach using time-domain acceleration signals is presented for the detection of occurrence and location of damage in a structural system. An explicit damage indicator is also incorporated in the acceleration-based residual generators for the estimation of the severity of damage in individual elements. The formulation of the acceleration residual generators for damage detection extends from a previous work in the literature where displacements and velocities were considered. The basic idea of the damage residual generation is to transform the state–space description of a dynamic system with structural (stiffness) changes in different elements into multi-failure events. Consequently, the damage detection becomes effectively a disturbances decoupling problem (DDP) in control terminology, so that a geometric technique can be employed to design residual generators for individual components of the structure. By analyzing the residual error signal with an error model, the damage severity of a component can be established. Numerical and experimental examples are given to illustrate the implementation and the effectiveness of the approach.

The strain field method for structural damage identification using Brillouin optical fibersensing

The theory of the strain field (SF) method using Brillouin optical fiber sensing(BOFS) is proposed for structural damage identification in this paper. Field testverification of this method was carried out by implementing a destructive loadingtest to an existing prestressed concrete bridge. A series of structural damagescenarios were thus produced for identification. A sub-matrix featuring the damagescenarios was first extracted from the space–time matrix to obtain the strain fielddistribution in space–time coordinates. Furthermore, other feature extractionoperations, including row vector extraction, column vector extraction and boundaryextraction, were performed to characterize the structural damage behavior anddamage evolution patterns. Finally, damage localization and quantification weresuccessfully implemented in both space and time domains in terms of a damageindex vector array. The investigation results demonstrated the SF method usingBOFS is a feasible and efficient approach for structural damage identification.