Frequency-based Damage Detection Research Articles

The natural frequency estimation for a system composed of a beam and a spring-mass system

This study presents an approximate method for determining the natural frequency of a system composed of a beam and a two-degree-of-freedom spring-mass system. The expression for estimating the natural frequency is derived following the standard procedures of the forced vibration analysis of a beam. The results obtained using the current method are in good agreement with those obtained through the dynamic stiffness method, especially when the spring stiffness is large. The innovativeness of the current method is that it reveals the relevance between the natural frequency of the system, the natural frequency of the beam, and the mode shape data at the positions where the spring-mass system is attached to the beam. The method is potentially useful in the dynamic wheel-track interaction analysis because the train wheel is normally simplified as a spring-mass system with high spring stiffness. It may also be applied to natural frequency-based damage detection where an auxiliary spring-mass system is used. When the spring-mass system roves on the beam, the curve of natural frequency versus spring-mass system location would be relevant to the mode shape square which is sensitive to local damage.

Building information modeling integrated with damage detection algorithm for structural health monitoring of bridge

In this paper, a method for damage monitoring of bridges using modal parameters is presented. At first, fundamentals of frequency-based damage occurrence alarming are introduced. Second, building information modeling (BIM) software is used to construct a 3D geometric model of a bridge. A custom tool add-in based on Microsoft Excel is linked and analyzed related data for damage detection of the bridge using modal parameters. A finite element model of a bridge girder is established to investigate vibration characteristics under prestressing loss and structural damage. Frequency-based damage detection is implemented to alarm the damage occurrence of an inspected bridge girder. Last, the structural information of the bridge is updated to the BIM model to provide the structural performance of the inspected structure. The result reveals that BIM integrated with the damage detection algorithm can efficiently facilitate structural health bridges.

Eigenfrequency-Based Bayesian Approach for Damage Identification in Catenary Poles

This study proposes an efficient Bayesian, frequency-based damage identification approach to identify damages in cantilever structures with an acceptable error rate, even at high noise levels. The catenary poles of electric high-speed train systems were selected as a realistic case study to cover the objectives of this study. Compared to other frequency-based damage detection approaches described in the literature, the proposed approach is efficiently able to detect damages in cantilever structures to higher levels of damage detection, namely identifying both the damage location and severity using a low-cost structural health monitoring (SHM) system with a limited number of sensors; for example, accelerometers. The integration of Bayesian inference, as a stochastic framework, in the proposed approach, makes it possible to utilize the benefit of data fusion in merging the informative data from multiple damage features, which increases the quality and accuracy of the results. The findings provide the decision-maker with the information required to manage the maintenance, repair, or replacement procedures.

Frequency-based damage detection method for excitation signals above work frequencies: theoretical aspects and experimental results

This work presents a cost-effective methodology to determine small damages using frequency response functions (FRFs) in the high-frequency range. The main objective is to determine a failure in its initial stage, allowing it to be analyzed and tracked. A theoretical analysis is performed, relating changes in the structural frequency response to small damages. In the analytic study, the strain modal energy change is estimated when the modal wavelength is similar to the damage rift dimension. The frequency change magnitude and its observability are analyzed based on practical FRF parameters. To demonstrate that a small damage can be noticeable in a high-frequency spectrum, an experimental procedure is performed to confirm it. Using a robust singular value decomposition algorithm a failure identification at approximately 0.16% and 0.34% of structural mass change is achieved. Employing measurement datasets composed of reference and damage sets obtained from a single measurement point, these results show the effectiveness and possibilities of the presented method.

Damage integrity assessment for beams using structural health monitoring technique

Structural health assessment of critical structure is one of the essential safety requirements. Three levels of structural health assessment are performed in this paper, i.e., damage identification, localisation and quantification. Among all the computational tools available in civil engineering for damage detection, artificial neural network (ANN) and support vector machine (SVM) are aimed to detect damage in beams. Cantilever I and hollow beams are modelled using finite element software and modal parameters are extracted. An attempt is made to demonstrate that parameters such as mode shapes and frequency are adequate for detection of structural damage using three classical techniques namely frequency-based damage detection method (FBDD), mode shape-based damage detection method (MBDD), mode shape curvature square (MSCS) damage detection techniques. Damage scenarios are created in the beam with various severities and locations along the beam. The modal parameters thus extracted from ANSYS for damaged beams are used as input for ANN and SVM algorithms for damage assessment. Thus, the results show that both algorithms are accurate for detecting damage in cantilever beams but ANN performed better than SVM.

Frequency Based Damage Detection and Localization of Propeller Shaft of a Ship Using Experimental Modal Analysis

: The whole ship is dependent on the propeller shaft for its movement, the vibrations produced from the shaft destabilizes the whole ship and may lead to accidents. With this objective in mind, in this paper, we describe a methodology to detect and locate the crack present in the intermediate simply supported shaft using experimental modal analysis. In the present work, 304 stainless steel material shaft is taken as the specimen as it is one of the most versatile and widely used steels in the world for making different shafts used in any machinery equipment like ships propeller shaft, engine shafts, motor shafts. Initially, analytical analysis is done on the simply supported shaft then numerical modal analysis using ANSYS 2019 R3 software. Results obtained from the numerical modal analysis are compared with the experimental modal analysis which is done using FFT analyzer. Finally, the first three natural frequencies are used as a tool to detect damage detection and location in the propeller intermediate shaft

Frequency-based damage detection in cantilever beam using vision-based monitoring system with motion magnification technique

This article proposes a method for damage detection using vision-based monitoring with motion magnification technique. The methods based on the vibration characteristics of structures such as natural frequency, mode shapes, and modal damping have been applied to structural damage detection. However, the conventional methods have limitations for practical applications. Vision-based monitoring system can be employed as a new structural monitoring system because of its simplicity, potentially low cost, and unique capability of collecting high-resolution data. A methodology called video motion magnification has been developed to amplify non-visible small motions in a video to reveal the dynamic response. The video motion magnification method can be applied to measure small displacements to calculate the natural frequencies and the operational deflection shapes of the structures. Unlike conventional optimization methods, a genetic algorithm explores the entire solution space and can obtain the global optimum. In this article, identification of the location and magnitude of damage in a cantilever beam is formulated as an optimization problem using a real-value genetic algorithm by minimizing the objective function, which directly compares the first three natural frequencies changes from the phase-based motion magnification measurement and from the analytical model of a damaged cantilever beam.

A novel method of vibration modes selection for improving accuracy of frequency-based damage detection

Frequency-based damage detection techniques have been widely applied to structural health monitoring. By analysing the changes (shifts) in natural frequencies in a structure with and without damage, these techniques solve the inverse problem of determining size and location of damage. In the existing literature, the first few or random modes of frequency shifts are given to the inverse algorithms as inputs in order to predict the damage parameters. These frequency shifts can be either numerical or measured. While the accuracy of prediction in the former (numerical) case has been found to be satisfactory, the use of measured frequencies has often shown large errors. This can be attributed to unavoidable noise in frequencies, including the mismatch between FEM model and real structure, as well as the noise in the measurement itself. Previous research has shown that the noise in frequency will actually be magnified in the discrepancy of frequency shifts, and thus affect the damage prediction accuracy. And moreover, the same noise added to different modes of frequency of a damaged case will lead to the different levels of deviation in different modes of frequency shifts. This observation indicates that potentially some modes of frequency shifts are less affected by the noise than others for a given case. However, so far, there has been no studies that attempt to identify particular vibration modes of frequency shifts that are (a) less affected by the noise for all damage cases and (b) result in a more accurate prediction of damage. In this study, a novel concept of Noise Response Rate (NRR) is proposed to evaluate the sensitivity of each mode of the frequency shift to noise. Further, it is shown that selecting the vibration modes with low NRR values improves the prediction accuracy of frequency-based damage detection. The efficacy of NRR is demonstrated through a case study on a composite curved plate compared with the conventional method for damage detection.

Vibration-based Structural Health Assessment of a Wind Turbine Tower Using a Wind Turbine Model

Wind turbine towers play an important role in supporting the energy-generating components such as blades, hubs, and nacelles and in resisting wind loads generated by the blades. Therefore, it is essential to secure the structural safety and stability of wind turbine towers, which may be damaged by unforeseen strong winds, through structural health monitoring. In this study, the dynamic characteristics of a wind turbine tower model with and without damage at various locations were investigated though indoor experiments for the purpose of damage assessment and structural health monitoring. These results were compared with those obtained using a finite element model. To propose an appropriate damage detection technique for a wind turbine tower, frequency-based damage detection techniques were applied, and the results were verified by using the numerical model of a 3 MW wind turbine tower operating in Jeju Island, Korea.

A comparative assessment of different frequency based damage detection in unidirectional composite plates using MFC sensors

The basic concept of the vibration based damage identification methods is that the dynamic behaviour of a structure can change if damage occurs. Damage in a structure can alter the structural integrity, and therefore, the physical properties like stiffness, mass and/or damping may change. The dynamic behaviour of a structure is a function of these physical properties and will, therefore, directly be affected by the damage. The dynamic behaviour can be described in terms of time, frequency and modal domain parameters. The changes in these parameters (or properties derived from these parameters) are used as indicators of damage. Hence, this work has two main objectives. The first one is to provide an overview of the structural vibration based damage identification methods. For this purpose, a fundamental description of the structural vibration based damage identification problem is given, followed by a short literature overview of the damage features, which are commonly addressed. The second objective is to create a damage identification method for detection of the damage in composite structures. To aid in this process, two basic principles are discussed, namely the effect of the potential damage case on the dynamic behaviour, and the consequences involved with the information reduction in the signal processing. Modal properties from the structural dynamic output response are obtained. In addition, experimental and computational results are presented for the application of modal analysis techniques applied to composite specimens with and without damage. The excitation of the structures is performed using an impact hammer and, for measuring the output data, accelerometers as well as piezoelectric sensors. Finite element models are developed by shell elements, and numerical results are compared to experimental data, showing good correlation for the response of the specimens in some specific frequency range. Finally, FRFs are analysed using suitable metrics, including a new one, which are compared in terms of their capability for damage identification. The experimental and numerical results show that the vibration-based damage methods combined to the metrics can be used in Structural Health Monitoring (SHM) systems to identify the damage in the structure.

Damage detection using modal frequency curve and squared residual wavelet coefficients-based damage indicator

A theoretical and experimental study of the frequency-based damage detection method has been presented in this paper. Based on the eigenvalue problem and perturbation assumption of defect in modal response, the theoretical basis of the modal frequency curve method is established. The extraction of defect characteristics from the modal frequency curve via discrete wavelet transform is illustrated. The above background leads to the development of a new multiple-mode damage indicator for damage localisation and a damage estimator for size prediction. Then, the proposed method has been applied to aluminium samples with pre-defined damage sections. Finite element modelling and experimental testing results are presented to demonstrate the performance of the method. Additionally, detectability with respect to the various mass ratios is investigated to support the ability of the method in real applications. The numerical and experimental results suggest that the use of the damage indicator provides a more robust and unambiguous damage identification than the sole use of the wavelet coefficients of the modes investigated. In addition, the damage estimator predicts the defect size to a satisfactory level.

Numerical evaluation for vibration-based damage detection in wind turbine tower structure

In this study, the feasibility of vibration-based damage detection methods for the wind turbine tower (WTT) structure is evaluated. First, a frequency-based damage detection (FBDD) is outlined. A damage-localization algorithm is visited to locate damage from changes in natural frequencies. Second, a mode-shape-based damage detection (MBDD) method is outlined. A damage index algorithm is utilized to localize damage from estimating changes in modal strain energies. Third, a finite element (FE) model based on a real WTT is established by using commercial software, Midas FEA. Several damage scenarios are numerically simulated in the FE model of the WTT. Finally, both FBDD and MBDD methods are employed to identify the damage scenarios simulated in the WTT. Damage regions are chosen close to the bolt connection of WTT segments; from there, the stiffness of damage elements are reduced.

On the use of numerical models for validation of high frequency based damage detection methodologies

This article identifies and addresses current limitations on the use of numerical models for validation and/or calibration of damage detection methodologies that are based on the analysis of the high frequency response of the structure to identify the occurrence of abrupt anomalies. Distributed-plasticity non-linear fiber-based models in combination with experimental data from a full-scale reinforced concrete column test are used to point out current modeling techniques limitations. It was found that the numerical model was capable of reproducing the global and local response of the structure at a wide range of inelastic demands, including the occurrences of rebar ruptures. However, when abrupt sudden damage occurs, like rebar fracture, a high frequency pulse is detected in the accelerations recorded in the structure that the numerical model is incapable of reproducing. Since the occurrence of such pulse is fundamental on the detection of damage, it is proposed to add this effect to the simulated response before it is used for validation purposes.

Experimental investigation of frequency-based multi-damage detection for beams using support vector regression

A frequency-based damage detection method in conjunction with the support vector regression is presented. The wavelet finite element method is used for numerical simulation to determinate the relationship database between multi-damage locations/depths and natural frequencies of a beam. Then, support vector regression is applied to extract the damage locations and depths from the database due to its ability in handling nonlinearity, finding global solutions, and processing high dimensional input vector. Finally, a large number of experiments have been carried out to further examine the performance of the proposed method.

Theoretical and experimental structural damage diagnosis method using natural frequencies through an improved sensitivity equation

In this study, a frequency-based technique is presented to detect any number of localized damages which induce stiffness reduction in a structure. The sensitivity of natural frequencies is characterized as a second order element level function of the stiffness reduction. To achieve accurate results, change in the mode shapes of the structure are expressed as a linear combination of the intact structure mode shapes and are considered to develop sensitivity equations. The overall formulation yields an indeterminate set of equations. An optimization criterion is used to solve these equations to obtain the change of the structural parameters. The method was applied to a truss using numerically simulated data and it was verified using experimentally measured data of a steel cantilever beam and a one-story one-bay frame. Results show the efficiency of the proposed method and the importance of including the changes of the mode shapes through a frequency-based damage detection algorithm and also approve that the method is able to detect damage without an exact model of the undamaged structure.

무선 가속도 센서노드를 이용한 강 거더 볼트연결 부재의 진동기반 손상 모니터링 체계

본 연구에서는 무선 가속도 센서노드를 이용한 강 거더 볼트연결 부재의 진동기반 손상 모니터링 체계를 제안하였다. 이 같은 연구목표를 위해, 다음과 같은 연구를 수행하였다. 먼저, 무선 가속도 센서노드의 하드웨어 구성 및 내장된 작동 소프트웨어를 제시하였다. 다음으로, 강 거더 볼트연결 부재의 진동기반 손상 모니터링 체계를 제시하였다. 손상 모니터링 체계는 가속도 응답특성 분석을 통해 전역적 손상발생 경보 및 손상위치 추정을 수행한다. 전역적 손상발생 경보는 파워스펙트럼밀도의 상관계수를 적용하였다. 손상위치 추정은 고유 진동수기반 손상검색 기법과 모드형상기반 손상검색 기법을 적용하였다. 마지막으로, 모형 강 거더의 볼트연결 부재 손상을 식별하기 위한 진동기반 손상 모니터링 체계의 적용성을 검증하였다. This study propose the vibration-based damage monitoring scheme for steel girder bolt-connection member by using wireless acceleration sensor node. In order to achieve the objective, the following approaches are implemented. Firstly, wireless acceleration sensor node is described on the design of hardware components and embedded operation software. Secondly, the vibration-based damage monitoring scheme of the steel girder bolt-connection member is described. The damage monitoring scheme performed global damage occurrence alarming and damage localization estimation by the acceleration response feature analysis. The global damage alarming is applied to the correlation coefficient of power spectral density. The damage localization estimation is applied to the frequency-based damage detection technique and the mode-shape-based damage detection technique. Finally, the performance of the vibration-based damage monitoring scheme is evaluated for detecting the bolt-connection member damage on a lab-scale steel girder.

Damage Detection in Nonlinear Systems Using Optimal Feedback Auxiliary Signals and System Augmentations

An optimal sensitivity enhancing feedback control has been proposed recently. This method differs from previous sensitivity enhancing approaches because in addition to placing the closed-loop eigenvalues of the interrogated system, the eigenvectors are also optimally placed. This technique addresses two major limitations of frequency-based damage detection methods: the low sensitivity of the frequencies to damages and the limited range of damage scenarios identifiable from frequency-only measurement data. An unresolved challenge is enhancing sensitivity for nonlinear systems. This paper addresses this challenge by using optimal feedback auxiliary signals to enhance sensitivity for damage detection in nonlinear systems. The nonlinearity is accounted for by creating augmented linear models of higher order (in a higher dimensional state space). The methodology for constructing augmented linear systems with this property has been previously proposed by the authors (2008, “Multiple Augmentations of Nonlinear Systems and Generalized Minimum Rank Perturbations for Damage Detection,” J. Sound Vib., 316(1-5), pp. 101–121). Herein, the focus is on generalizing the previous work on sensitivity enhancing feedback and on system augmentation for enhancing sensitivity of damage detection in nonlinear systems. Results obtained by applying the optimal feedback auxiliary signals and optimal augmentation to a nonlinear mass-spring system are presented.

Detection of structural damage through changes in frequency

Among all the structural vibration characteristics, natural frequencies are relatively simple and accurate to measure, and provide the structural global damage information. In this paper, the feasibility of using only natural frequencies to identify structural damage is exploited by adopting two usual approaches, namely, sensitivity analysis and neural networks. Some aspects of damage detection such as the problem of incomplete modal test data and robustness of detection are considered. A laboratory tested 3-storey frame is used to demonstrate the possibility of frequency-based damage detection techniques. The numerical results show that the damaged element can be correctly localized and the content of damage can be identified with relatively high degree of accuracy by using the changes in frequencies.

Temperature effects on frequency-based damage detection in plate-girder bridges

In this paper the variability of modal properties caused by temperature effects is assessed in order to adjust modal data used for nondestructive damage detection in structures. First, an experiment to estimate temperature effects on modal properties is performed. Pre-damage and post-damage dynamic modal data from a model plate-girder bridge are described. The relationship between temperature and natural frequencies is analyzed and a set of empirical frequency-correction formulas are obtained for the test structure. Next, a frequency-based damage-detection method is utilized to locate and estimate severity of damage in the test structure for which a set of pre-damage and post-damage frequencies were measured at different temperature conditions. A theory of the frequency-based damage-detection algorithm that related to beam-type structures is outlined. The measured frequencies are adjusted by the frequency-correction formulas and fed into the damage-detection scheme that locates damage and estimates severity of damage in the test structure. Results of the analysis indicates that the temperature correction scheme works for the accurate damage localization and severity estimation in the test structure.

Damage identification in beam-type structures: frequency-based method vs mode-shape-based method

This paper presents a methodology to nondestructively locate and estimate the size of damage in structures for which a few natural frequencies or a few mode shapes are available. First, a frequency-based damage detection (FBDD) method is outlined. A damage-localization algorithm to locate damage from changes in natural frequencies and a damage-sizing algorithm to estimate crack-size from natural frequency perturbation are formulated. Next, a mode-shape-based damage detection (MBDD) method is outlined. A damage index algorithm to localize and estimate the severity of damage from monitoring changes in modal strain energy is formulated. The FBDD method and the MBDD method are evaluated for several damage scenarios by locating and sizing damage in numerically simulated prestressed concrete beams for which two natural frequencies and mode shapes are generated from finite element models. The result of the analyses indicates that the FBDD method and the MBDD method correctly localize the damage and accurately estimate the sizes of the cracks simulated in the test beam.