Damage Identification Parameters Research Articles

Comparative study of dynamic parameters for damage identification of carbon fiber reinforced polymer tube

AbstractThe primary objective of the paper is the numerical and experimental investigation related to the damage recognition effects for CFRP tubes of four dynamic parameters. Four damage identification indexes consisting of natural frequency‐based index, Mode Shape‐based index (MS), Mode Shape Curvature‐based index (MSC), and Modal Flexibility Curvature‐based index (MFC) are established by analyzing the dynamic parameter data obtained before and after damage occurs. The performances of dynamic parameters are thoroughly discussed in the context of numerical simulations and experiment. The results indicate that the effect of natural frequency is not as significant as that of mode shape. MFC has the most notable effectiveness out of the four indexes. The simulation peak index pair is predicted to rise from 0.3 to 0.6 as the damage in the simulation model increases by 25% from 12.5%, indicating that MFC can feedback the damage degree. Moreover, the circumferential curvature index exhibits superior performance compared to the axial curvature index. To enhance the accuracy of the axial curvature index, it is proposed to increase the number of measuring sites along the tube's long direction.Highlights Damage identification indexes of four dynamic parameters are established. Discuss the identification ability of dynamic parameters by simulation and test. Two numerical models of CFRP tube with delamination damage are established. Impact and modal tests are executed to study the ability of four indexes.

Drive-by Bridge Damage Detection Using Continuous Wavelet Transform

Bridges serve as vital engineering structures crafted to facilitate secure and effective transportation networks. Throughout their life-cycle, they withstand various factors, including diverse environmental conditions, natural hazards, and substantial loads. Recent bridge failures underscore the significant risks posed to the structural integrity of bridges. Damage detection techniques, being core components of structural health monitoring, play a crucial role in objectively assessing bridge conditions. This article introduces a novel framework for identifying damage in bridges utilizing continuous wavelet analysis of accelerations recorded using two sensors mounted on a vehicle traversing the bridge. The proposed method leverages changes in the static response of the bridge, which has proven to be more sensitive to damage than its dynamic counterpart. By doing so, the method eliminates the reliance on modal parameters for damage identification, addressing a significant challenge in the field. The proposed framework also addresses key challenges encountered by drive-by monitoring methods. It mitigates the adverse effects of road roughness by utilizing residual accelerations and efficiently detects and locates damage even in the absence of corresponding data from an undamaged bridge. Numerical investigations demonstrate the robustness of the proposed method against various parameters, including damage location and extent, vehicle speeds, road roughness levels, different boundary conditions, and multi-damage scenarios.

Damage Detection Method of Simply Supported Beams Based on Difference of Nearby Difference Curvature Index

In order to improve the effectiveness and convenience of damage identification of two-span continuous beams, a new damage identification index <I>D</I>_i based on the deflection data of beam under concentrated load, which takes local flexural stiffness and shear stiffness as damage identification parameter, was proposed. The damage detection method based on <I>D</I>_i includes four main steps: arranging vertical deflection measurement points at equal intervals on the beam body and applying a concentrated load <I>F</I> at the mid span position of one of the spans. After measuring the <i>y</i>_i value at each measurement point, the differential deflection curvature value 1/<i>ρ</i>_ican be calculated; After obtaining specific values of <I>D</I>_iaccording to the definition, a graph with <I>D</I>_i as the vertical coordinate and the positions of each measuring point on the longitudinal axis of the beam as the horizontal coordinate can be drawn; The mutation position on the graph can indicate the location of the damage: if the mutation starts from point <i>j</i>, it indicates that the damage occurs in the area between measurement points <i>j</i>+1 and <i>j</i>+2; By selecting any two values from <I>D</I>_i-1, <I>D</I>_i, and <I>D</I>_i+1 and solving the corresponding definition equation simultaneously, the degree of beam damage characterized by the relative change in local stiffness can be determined. The results of numerical example validation indicate that this method has good damage identification performance.

Influence of vehicle traffic on modal-based bridge monitoring

In recent years, there has been a surge of interest in modal-based monitoring systems, especially for bridge structures, to detect damage at an early stage and to extend the life of existing bridges as well as to minimize maintenance costs. The modal parameters, natural frequencies and mode shapes, depend on stiffness and mass of a structure. For an economic application of a modal-based monitoring system, the estimation of the modal parameters based on the Operational Modal Analysis needs to be estimated. The Operational Modal Analysis uses the naturally existing vibration sources, such as wind and traffic, to estimate the modal parameters. A significant advantage is therefore that the bridges do not have to be closed to traffic. In this context, the modal parameters are influenced by the vehicle traffic due to the associated temporally and spatially variable mass, stiffness and damping properties of the overall system. In this paper, the influence of those operational loads and road roughness on the modal parameter estimation is numerically investigated. The vehicles are modeled as half-vehicle models. In addition, the influence of vehicle traffic is shown using in situ measurements on an existing bridge. A high sensitivity of the natural frequencies to operational loads can be shown, so that they are not reliable damage identification parameters. In contrast, the mode shapes exhibit small amplitude scatter due to the operating loads if the excitation frequency is not in the range of the natural frequency of the bridge. This is very unlikely, especially for bridges under vehicle traffic, due to the variety of vehicle designs and thus the broadband excitation.

Conventional Bridge Damage Identification Based on BP Neural Network

Aiming at the problem of insensitivity of damage identification in conventional bridges, the application of BP neural network in long-span bridges is studied, and it is extended to the field of damage identification of conventional bridges. The finite element models of three-span continuous variable cross-section box girders under intact and damaged conditions are established by Midas civil, and the eigenvalues of bridges under different conditions are analyzed. It is found that in conventional bridges, the sensitivity to structural damage is: mode > vertical displacement > natural frequency. The parameterized natural frequencies and modes of structures are used as input of BP neural network, and the damage location and degree are used as output to train the neural network. Then, the damage location and degree are identified under different working conditions, and the results show that the recognition effect is not satisfactory. Analyzing the reason, the natural frequency and modal shape of the structure will change when the conventional bridge is damaged, but the deformation value is very small. When training the BP neural network, it is easy to appear over-fitting, which results in poor recognition effect. Therefore, it is difficult to identify structural damage by using BP neural network through acquiring the characteristics of conventional bridges. It is still necessary to study appropriate damage identification parameters and methods that can be applied to conventional bridges.

Study of multiple-site structural damage detection application using vibration response

The identification effects of different modal parameters (displacement mode, rotation mode, and curvature mode) of the beam structure on structural damage during crack initiation are studied in this paper. Firstly, the displacement mode, the rotation mode and the curvature mode of the two-span simply supported beam are calculated using the vibration response. Secondly, combining the multi-resolution and singularity analysis characteristics of continuous wavelet transform, the wavelet transform coefficients of three modal parameters are calculated to identify the singularity of structural modal parameters. Thirdly, the recognition effects of each method on structural damage are compared by adding different degrees of random noise to the simulation data. The results show that the damage identification methods based on three different modal parameters can locate small-scale structural damage, but the anti-noise performance of each method is different, the anti-noise performance of the rotation mode is the best, the displacement mode is second and the curvature mode is poor. Finally, the experimental data is used to verify the recognition effect of each damage identification method based on different modal parameters on the actual structural damage. The experimental results show that the damage recognition effect of the rotation mode parameters is better, while the displacement mode and the curvature mode parameters are similar, but the curvature mode method is more likely to be interfered at the smaller damage. These analysis results provide a reference for the selection of different damage identification parameters according to the environment and response characteristics in engineering practice.

Damage identification parameters of dual-phase 600–800 steels based on experimental void analysis and finite element simulations

In this work, the damage behavior of cold-rolled zinc-coated dual-phase steel sheets 600 and 800 grades was evaluated by means of standard uniaxial tensile testing, microstructural characterization and finite element modeling. The void formation in both steels was investigated as a function of the plastic strain level from digital image processing of scanning electron micrographs to quantify the average void size and to determine the corresponding measures of void density, void area fraction and void aspect ratio. Based on the void analysis and the experimental uniaxial tensile test data, a four-step procedure is proposed to identify the parameters of the Gurson–Tvergaard–Needleman (GTN) damage model. Bearing in mind the non-uniqueness of the GTN model parameters, 3D finite element simulations using a single element and an 1/8 symmetry uniaxial tensile specimen model were performed in a systematic manner to investigate the role of both nucleation and failure parameters on the uniaxial behavior. At low straining levels, most of the void initiated by debonding of globular aluminum-oxide inclusions identified by EDS in both dual-phase steels. At higher straining levels, the void density evolution is found to be more pronounced in DP600 steel owing to the faster void nucleation rate at the ferrite grain boundaries. A good agreement between predictions and experimental load-elongation is achieved allowing for the identification of the full set of GTN damage model parameters of both DP600 and DP800 steels. The proposed damage calibration of dual-phase steels can be very helpful in simulations of practical sheet metal forming processes.

Bearing damage assessment using Jensen-Rényi Divergence based on EEMD

An Ensemble Empirical Mode Decomposition (EEMD) and Jensen Rényi divergence (JRD) based methodology is proposed for the degradation assessment of rolling element bearings using vibration data. The EEMD decomposes vibration signals into a set of intrinsic mode functions (IMFs). A systematic methodology to select IMFs that are sensitive and closely related to the fault is proposed in the paper. The change in probability distribution of the energies of the sensitive IMFs is measured through JRD which acts as a damage identification parameter. Evaluation of JRD with sensitive IMFs makes it largely unaffected by change/fluctuations in operating conditions. Further, an algorithm based on Chebyshev's inequality is applied to JRD to identify exact points of change in bearing health and remove outliers. The identified change points are investigated for fault classification as possible locations where specific defect initiation could have taken place. For fault classification, two new parameters are proposed: ‘α value’ and Probable Fault Index, which together classify the fault. To standardize the degradation process, a Confidence Value parameter is proposed to quantify the bearing degradation value in a range of zero to unity. A simulation study is first carried out to demonstrate the robustness of the proposed JRD parameter under variable operating conditions of load and speed. The proposed methodology is then validated on experimental data (seeded defect data and accelerated bearing life test data). The first validation on two different vibration datasets (inner/outer) obtained from seeded defect experiments demonstrate the effectiveness of JRD parameter in detecting a change in health state as the severity of fault changes. The second validation is on two accelerated life tests. The results demonstrate the proposed approach as a potential tool for bearing performance degradation assessment.

Bearing diagnosis based on Mahalanobis–Taguchi–Gram–Schmidt method

A methodology is developed for defect type identification in rolling element bearings using the integrated Mahalanobis–Taguchi–Gram–Schmidt (MTGS) method. Vibration data recorded from bearings with seeded defects on outer race, inner race and balls are processed in time, frequency, and time–frequency domains. Eleven damage identification parameters (RMS, Peak, Crest Factor, and Kurtosis in time domain, amplitude of outer race, inner race, and ball defect frequencies in FFT spectrum and HFRT spectrum in frequency domain and peak of HHT spectrum in time–frequency domain) are computed. Using MTGS, these damage identification parameters (DIPs) are fused into a single DIP, Mahalanobis distance (MD), and gain values for the presence of all DIPs are calculated. The gain value is used to identify the usefulness of DIP and the DIPs with positive gain are again fused into MD by using Gram–Schmidt Orthogonalization process (GSP) in order to calculate Gram–Schmidt Vectors (GSVs). Among the remaining DIPs, sign of GSVs of frequency domain DIPs is checked to classify the probable defect. The approach uses MTGS method for combining the damage parameters and in conjunction with the GSV classifies the defect.A Defect Occurrence Index (DOI) is proposed to rank the probability of existence of a type of bearing damage (ball defect/inner race defect/outer race defect/other anomalies). The methodology is successfully validated on vibration data from a different machine, bearing type and shape/configuration of the defect. The proposed methodology is also applied on the vibration data acquired from the accelerated life test on the bearings, which established the applicability of the method on naturally induced and naturally progressed defect. It is observed that the methodology successfully identifies the correct type of bearing defect. The proposed methodology is also useful in identifying the time of initiation of a defect and has potential for implementation in a real time environment.

The Monitoring Method for Crack Damage of Concrete Structures Based on Piezoceramics Transducers

A method for monitoring the crack damage of concrete structure based on piezoceramics transducers was introduced in the paper. The PZT patches were packaged as smart aggregates which buried into concrete structures in pair. One is as actuator to transmit monitoring signals, and the other is as sensor to receive the monitoring signals. Sine sweep frequency wave was used as monitoring signal type, and its energy value was used as damage identification parameter. At last, a test was conducted to prove the effectiveness of monitoring method. The crack damage of a reinforced concrete beam under the load was monitored during the whole test process. The develop trend of damage identification parameter could reflect the develop trend of damage. The method proposed in the paper is feasible for crack damage monitoring of concrete structure.

Study on Damage Identification of Simply Supported-Beam Based on Modal Strain Energy Method

In present study, ANSYS finite element method was utilized to analyze the modal of simply supported beam and then the study on damage identification was performed based on modal strain energy method. The comparative analysis of results obtained by modal strain energy changes rate method and modal strain energy index demonstrates that modal strain energy index is an effective damage identification parameter.

A novel methodology for online detection of bearing health status for naturally progressing defect

A methodology is proposed for the online detection of health status of rolling element bearing into various damage stages for naturally progressing defect. Various damage identification parameters are derived from processing vibration data in time domain, frequency domain and time–frequency domain. The parameters are fused into a single parameter, Mahalanobis distance, by application of Gram–Schmidt Orthogonalization process. Chebyshev׳s inequality is applied to the Mahalanobis distance for online monitoring and damage stage detection. A simulation study is first carried out to show working of the proposed methodology in presence of varying trends of damage identification parameters. The proposed methodology is then validated on experimental data. The first validation is on the vibration data acquired from a bearing having seeded defect. Later, two accelerated life tests are conducted on a specially designed test rig at different load and speed combinations on the bearings for ensuring naturally induced and progressed defects. The methodology is successfully verified on the vibration data acquired from the naturally induced and progressed defect experiments.

Damage identification of slab–girder structures: experimental studies

Slab–girder structures composed of steel girder and reinforced concrete slab are widely used in buildings and bridges in the world. Their advantages are largely based on the composite action through the shear connection between slab and girder. In order to assess the integrity of this kind of structures, numerous vibration-based damage identification methods have been proposed. In this study, a scaled composite slab–girder model was constructed in the laboratory. Some removable shear connectors were specially designed and fabricated to connect the girder and slab that were cast separately. Then, a two-stage experiment including both static and vibration tests was performed. In the first stage, vibration tests were conducted under different damage scenarios, where a certain number of shear connectors at certain locations were removed step by step. In the second stage, two sets of hydraulic loading equipment were used to apply four-point static loads in the test. The loads are increased gradually until concrete slab cracked. The loading histories as well as deflections at different points of the beam are recorded. Vibration test was carried out before and after concrete cracking. Experimental results show that the changes of mode shapes and relative displacement between slab and girder may be two promising parameters for damage identification of slab–girder structures.

Modal macro-strain flexibility methods for damage localization in flexural structures using long-gage FBG sensors

Modal flexibility is a robust and promising damage index for constructed facilities. However, the classical-flexibility methods are still unable to provide the required accuracy and reliability for damage localization due to their low sensitivity to small and multiple damages, and high sensitivity to measurement noise. In most cases, the modal parameters of the structures in the healthy state are required as baseline. On the other hand, the recent major advances in structural dynamics and mechanical vibration measurements have provided the opportunity to exploit more reliable modal parameters for damage identification. This paper presents modal macro-strain (MMS) flexibility methods to detect and locate multiple damages in elastic structures on the basis of dynamic distributed strain measurements from long-gage fiber Bragg grating sensors. Through analytical and experimental investigations, the MMS flexibility and its curvature have been validated as reliable indices to accurately localize less severe practical damages from few measurable modes with or without baseline information. The proposed damage indices are promising alternatives to the classical approach for civil structures where mode truncation and measurement errors are inevitable. Copyright © 2009 John Wiley & Sons, Ltd.

Structural Damage Detection with Cross Correlation Function of Vibration Observations

A structural damage identification technique based on cross correlation function analysis of vibration measurements is proposed. An 8-storey steel shear building model has been chosen as the case verification. Structural acceleration responses from neighbouring test points are used to establish damage identification parameters. Experimental analysis shows that the method can achieve quite precise results.

Hypersensitivity of strain-based indicators for structural damage identification: A review

Because of the sensitive characteristic to local defects, strain has been widely utilized to identify the presence, location, and severity of damage in structures, and this paper reviews recent publications regarding strain-related techniques on structural damage identification. A brief description on the strain–displacement relationship at defective areas is first presented. Then, damage identification using various strain-related parameters, such as strain (curvature) mode shape, strain energy, strain frequency response function, etc., is explored and the hypersensitivity of corresponding damage indicators will be examined systematically. Finally, some generalized criteria on the selection of strain-based parameters for damage identification are concluded and suggestions for future work are discussed.

Vibration-based structural damage identification using wavelet transform

This paper presents a new damage identification technique based on the statistical moments of the energy density function of the vibration responses in the time–scale (or time–frequency) domain. The continuous wavelet transform is first conducted to decompose the vibration responses into discrete energy distributions as a joint function of time and scale. The principal structural response features are then extracted from the energy density functions using moments. Consequently, the zeroth-order moment (ZOM) known as the total energy of the joint density function is computed at each measurement grid point for the pre-damage and post-damage states and is then implemented for detection and localization of damage in a concrete plate model and in a steel plate girder of a bridge structure. The significant contribution is that the wavelet coefficients are transformed into a new damage identification parameter in the space domain which is considered to be a novel application of the wavelet analysis coefficients. The major advantage is that the time–frequency analysis conducted using the wavelet transform provides a powerful tool to characterize deterministic as well as random (stationary and non-stationary) responses and can be used to detect slight changes in the response characteristics and local variations. Finally, comparison of the results obtained from the proposed method and those obtained from existing non-model-based damage identification techniques shows that the proposed method is more sensitive to damage than these other methods.

Damage Identification Based on Dead Load Redistribution: Effect of Measurement Error

The effect of measurement error on the results of a new method for damage identification in large, massive civil structures is presented. The damage identification procedure is based on the redistribution of dead load in the structure that takes place when damage occurs. Damage is modeled in the flexural member by a section of reduced flexural rigidity. Static strain measurements are used as input to the procedure. The damage identification parameters are determined using a genetic algorithm. The effect of measurement error is investigated using Monte Carlo simulation. The measurement error is modeled as a Guassian, zero mean random variable. When the model element length is equal to the damage zone length, the results are in good agreement. The correct location and severity is determined even for significant levels of measurement error. The error-to-strain ratio is a convenient parameter for establishing when the error is too significant: results show that for error-to-strain ratios below about 40%, the procedure is able to determine the approximate location and severity of damage accurately. Damage is correctly identified, in an average sense, for the realistic case of when the model element length is not equal to the actual damage zone length. False-positive tests are conducted: the procedure is not prone to incorrectly identify damage when it does not exist, even in the presence of significant measurement error.

Damage detection of frames using the increment of lateral displacement change

The method proposed in this paper is based on the fact that the damage in different types of structural members has distinctive influence on the structural stiffness. The intrinsic mechanical property of the structure is tapped and fully utilized for damage detection. The simplified model of the flexibility of frames treats the individual storeys as springs in series and the frame as an equivalent column. It fully considers the main deformation of all beams and columns in the frame. The deformation property of the simplified model accorded well with that of the actual frame model. The obtained increment, of lateral displacement change (IOLDC) at the storey level was found to be very sensitive to the local damage in the frame. A damage detection method is proposed using the IOLDCs as the damage identification parameters. Numerical examples demonstrate the potential applicability of this method.