Damage Detection Strategy Research Articles

Locating Damage Using Integrated Global-Local Approach with Wireless Sensing System and Single-Chip Impedance Measurement Device

This study developed an integrated global-local approach for locating damage on building structures. A damage detection approach with a novel embedded frequency response function damage index (NEFDI) was proposed and embedded in the Imote2.NET-based wireless structural health monitoring (SHM) system to locate global damage. Local damage is then identified using an electromechanical impedance- (EMI-) based damage detection method. The electromechanical impedance was measured using a single-chip impedance measurement device which has the advantages of small size, low cost, and portability. The feasibility of the proposed damage detection scheme was studied with reference to a numerical example of a six-storey shear plane frame structure and a small-scale experimental steel frame. Numerical and experimental analysis using the integrated global-local SHM approach reveals that, after NEFDI indicates the approximate location of a damaged area, the EMI-based damage detection approach can then identify the detailed damage location in the structure of the building.

Detection of Cracks in Structures Using Two Crack Transfer Matrix

Abstract A novel damage detection scheme for multiple crack detection in a beam like structures is presented, based on a transfer matrix (TM) derived from the beam element with two cracks. Based on Linear Elastic Fracture Mechanics (LEFM) principles, a crack is modelled as a hinge which provides an additional flexibility to the element. Each element is assumed to have two open edge cracks and a new TM called Two Crack Transfer Matrix (TCTM) is developed using the Finite Element method. Using an inverse approach, the TCTM is used to predict cracks in a beam. The state vector at a node includes displacements, forces and moments at that node; when it is multiplied with the TM the state vector at the adjacent node can be obtained. The state vector formed at the starting node, known as initial state vector needs to be estimated, from which state vectors at adjacent nodes are predicted using the TM. Displacement responses are measured at a few adjacent nodes in the structure. The mean square error (MSE) between measured and predicted responses is minimized using a heuristic optimization algorithm, with crack depth and location in each element as the optimization variables. Two numerical examples, a cantilever and a sub-structure (SS) of a frame with nine members are solved with two cracks in each element. The damage detection method is also validated experimentally by local identification of a SS of a fixed beam where the initial state vector is measured using strain gauges and accelerometers. Using this method, maximum of two cracks per element were successfully identified. The TCTM method is suitable for local damage identification in large structures.

Damage Detection Strategy Using Strain-Mode Residual Trends for Long-Span Bridges

In this paper, a damage detection strategy based on distributed strain responses measured by long-gauge fiber Bragg grating (FBG) sensors is investigated. First, the distributed strain modes of a system with multiple degrees of freedom (DOFs) are derived via the frequency response function (FRF) of distributed strain response. Then the distributed strain mode is used to identify different degrees of damage incurred in a long-span, cable-stayed bridge under ambient excitation. The robustness of the distributed strain mode for detecting damage is analyzed, and it is found that its robustness is affected by ambient excitation, mode normalization, degree of damage, and noise pollution. To improve the robustness of the distributed strain-mode method, a damage detection strategy based on distributed strain-mode residual trends is developed using statistical tendency analysis and confidence probability. Finally, a numerical analysis is performed on the bridge structure under different operational conditions. The analytical results show that the proposed strategy can reduce the effects of loading variability and environmental diversity on the identified strain mode and locate damage accurately with good damage severity assessment and a high level of robustness.

Piezoelectric dynamic strain monitoring for detecting local seismic damage in steel buildings

This research presents a methodology for damage detection along with a sensing system for monitoring seismic damage in steel buildings. The system extracts the location and extent of local damage, such as fracture at a beam–column connection, from changes in the bending moment distribution in a steel moment-resisting frame. We developed a dynamic strain-based sensing system utilizing piezoelectric film sensors and wireless sensing techniques to estimate the bending moments resisted by individual structural members under small amplitude loadings such as ambient vibrations and minor earthquakes. We introduce a new damage index that extracts local damage information from the comparative study of the dynamic strain responses of the structural members before and after a large earthquake event. The damage detection scheme was examined both analytically and numerically using a simple frame example. Then, the entire local damage detection scheme was verified through a series of vibration tests using a one-quarter-scale steel testbed that simulated seismic damage at member ends.

Identification of damage in dome-like structures using hybrid sensor measurements and artificial neural networks

A damage detection scheme using multi-type sensor-based hybrid sensing and artificial-neural-network- (ANN-) based information processing was developed for dome-like structures used in civil infrastructure. Accelerometers and strain sensors were used to provide a hybrid measurement with the purpose of acquiring rich information associated with structural damage. The optimal placement of multiple sensors was explored so as to capture the most appropriate and sensitive signal features (damage parameter vectors) for damage characterization. A back-propagation ANN was constructed with the inputs extracted from the hybrid measurement. To validate the capacity of the proposed damage identification scheme, finite element analysis was conducted to identify damage in a Schwedler dome structure as an example. The performance of ANNs, trained by three kinds of damage parameter vector extracted from signals captured by (i) a sole accelerometer, (ii) a sole strain sensor, and (iii) both kinds of sensor was compared, to observe that the one trained by hybrid sensor measurement outperformed the others. Error analysis for a series of parametric studies, in which noise at different levels was included in the training input, was further carried out, and robustness of the proposed damage identification scheme under noisy measurement was demonstrated.

ADAPTIVE-SCALE DAMAGE DETECTION FOR FRAME STRUCTURES USING BEAM-TYPE WAVELET FINITE ELEMENT: EXPERIMENTAL VALIDATION

The superior human vision system provides ingenious insight into an ideal damage detection strategy in which structural modeling scales are not only spatially varying but also dynamically changed according to actual needs. This paper experimentally examines the efficacy of a multi-scale damage detection method based on wavelet finite element model (WFEM). The beam-type wavelet finite element in this study utilizes the second-generation cubic Hermite multi-wavelets as interpolation functions. The dynamic testing results of a one-bay steel portal frame with multiple damages are employed in the experimental validation. Through a multi-stage updating of the WFEM, the multiple damages in the steel portal frame are detected in a progressive manner: the suspected region is first identified using a low-scale structural model, and the more accurate location and severity of the damage can be identified using a multi-scale model with local refinement. As the multi-scale WFEM considerably facilitates the adaptive change of modeling scales, the proposed multi-scale damage detection method can efficiently locate and quantify damage with minimal computation effort and a limited number of updating parameters and sensors, compared with conventional finite element methods.

Comparative Study of Robust Novelty Detection Techniques

The central target of this work is to provide an alternative to machine learning approaches to structural health monitoring with one of robust multivariate statistic novelty detection. Damage detection and identification is a procedure that is hierarchical in nature. At its most sophisticated, diagnosis of the damage could include localisation, classification and severity assessment and even go so far as to estimate the time-to-failure of the structure. In this paper, robust multivariate statistics were investigated focused mainly on a high level estimation of the outliers which determines only the presence or absence of novelty - something that is of fundamental interest. These methods allow a diagnosis of deviation from normality and the option of identifying the presence of masking effects caused by multiple outliers. This paper is trying to introduce a new scheme for damage detection by adopting simple measurements and exploiting robust multivariate statistics.

Coupling effect of piezoelectric wafer transducers in distortions of primary Lamb wave modes

Piezoelectric wafer transducers (PWT) are widely used for Lamb wave based damage detection schemes. The size of the damage that can be detected is dependent on the wavelength of the Lamb wave employed. Thus it is essential to explore the higher frequency range within the (fundamental) bandwidth of S0 and A0 modes, however below the cut-off frequencies of A1 and S1. It is observed that the Lamb wave modes S0 and A0 generated using PWT undergo distortion within this fundamental bandwidth. This behavior is experimentally observed for different PWT sizes and types. The nature of this observed distortion is very different from the distortion of wave modes due to dispersion. In addition, the distortion, in many cases, tends towards the appearance of new wave modes close to the S0 and A0 modes. To understand this experimental observation, a theoretical study is performed. First, finite element (FE) simulations of Lamb waves considering pin-force, thermal analogy, and couple field models of surface mounted PWT are carried out. These simulation studies reveal that the wavepacket distortion can be attributed mostly to electro-mechanical coupling effect of the PWT. Next, the dispersion plot of piezoelectric layer considering electro-mechanical coupling is obtained using spectral finite element (SFE) method. These dispersion characteristics of the PWT are found to be significantly different from the conventional Lamb wave dispersion characteristics and may explain the experimental observation.

Multi-stage identification scheme for detecting damage in structures under ambient excitations

Structural damage identification methods are critical to the successful application of structural health monitoring (SHM) systems to civil engineering structures. The dynamic response of civil engineering structures is usually characterized by high nonlinearity and non-stationarity. Accordingly, an improved Hilbert–Huang transform (HHT) method which is adaptive, output-only and applicable to system identification of in-service structures under ambient excitations is developed in this study. Based on this method, a multi-stage damage detection scheme including the detection of damage occurrence, damage existence, damage location and the estimation of damage severity is developed. In this scheme, the improved HHT method is used to analyse the structural acceleration response, the obtained instantaneous frequency detects the instant of damage occurrence, the instantaneous phase is sensitive to minor damage and provides reliable damage indication, and the damage indicator developed based on statistical analysis of the Hilbert marginal spectrum detects damage locations. Finally, the response sampled at the detected damage location is continuously analysed to estimate the damage severity. Numerical and experimental studies of frame structures under ambient excitations are performed. The results demonstrate that this scheme accomplishes the above damage detection functions within one flow. It is robust, time efficient, simply implemented and applicable to the real-time SHM of in-service structures.

Modal analysis of delaminated composite plates using the finite element method and damage detection via combined Ritz/2D-wavelet analysis

Structural studies to find defects (in particular delaminations) in composite plates have been very prevalent in the Structural Health Monitoring field. The present work develops a new method to detect delaminations in CFRP (Carbon Fiber Reinforced Polymer) plates. In this paper the method is validated with numerical simulations, which come to support its adequacy for use with real acquisition data. This is done firstly through the implementation of a delaminated plate finite element. Using the classical lamination plate theory, delamination is considered in the kinematic equations through jump functions and additional degrees of freedom. The element allows the introduction of nd delaminations through its thickness. Classical QMITC (Quadrilateral Mixed Interpolation Tensorial Components) and DKQ (Discrete Kirchhoff Quadrilateral) elements are used for the membrane and bending FEM (Finite Element Method) formulation. Second, using the vibration modes obtained with the FEM, a damage location technique based on the variational Ritz method and Wavelet Analysis is proposed. The approach has the advantage of requiring only damaged modes and not the healthy ones. Both FEM simulations and Ritz/Wavelet damage detection schemes are applied in an orthotropic CFRP plate with the stacking sequence [0/90]3S. In addition, the influence of delamination thickness position, boundary conditions and added noise (in order to simulate experimental measures) was studied.

Damage detection on a full-scale highway sign structure with a distributed wireless sensor network

Wireless sensor networks (WSNs) have emerged as a novel solution to many of the challenges of structural health monitoring (SHM) in civil engineering structures. While research projects using WSNs are ongoing worldwide, implementations of WSNs on full-scale structures are limited. In this study, a WSN is deployed on a full-scale 17.3m-long, 11-bay highway sign support structure to investigate the ability to use vibration response data to detect damage induced in the structure. A multi-level damage detection strategy is employed for this structure: the Angle-between-String-and-Horizon (ASH) flexibility-based algorithm as the Level I and the Axial Strain (AS) flexibility-based algorithm as the Level II. For the proposed multi-level damage detection strategy, a coarse resolution Level I damage detection will be conducted first to detect the damaged region(s). Subsequently, a fine resolution Level II damage detection will be conducted in the damaged region(s) to locate the damaged element(s). Several damage cases are created on the full-scale highway sign support structure to validate the multi-level detection strategy. The multi-level damage detection strategy is shown to be successful in detecting damage in the structure in these cases.

Study of open crack in rotor shaft using changes in frequency response function phase

In recent years, significant efforts have been devoted to developing non-destructive techniques for damage identification in structures. This study investigated the effects of cracks and damages on the integrity of structures, with a view to detect, quantify, and determine their extents and locations. Previous works have used parameters, such as, changes in natural frequencies and mode shapes, as detectors. However, such parameters are not sensitive enough to detect early defects. In this paper, phase measurements are sought. Measurements of the acceleration frequency responses at different points on each rotor shaft were taken using a multi-channel frequency analyzer. The damage detection schemes used in this study depended on the changes in the phase of the measured acceleration frequency response functions. To study the changes of phases, it was interpreted in phase spectrum and Nyquist plot. Nyquist plot was used as it includes both real and imaginary parts of the amplitude and this was used to study phase shifts due to the presence of crack. The changes in phase depended on crack depth and how close the crack is to that mode shape node. Meanwhile, the changes in phase of lower eigenvectors were observed clearly. Thus, first mode shape was helpful in identifying the location of the crack. The vibration behavior of the rotor shaft was shown to be very sensitive to the crack depth, crack location and mode number. It is concluded that changes in phase as a function of crack depths and locations can be effective in crack detection methodology.

Thermal sensitivity of Lamb waves for structural health monitoring applications

One of the drawbacks of the current Lamb wave structural health monitoring methods are the false positives due to changing environmental conditions such as temperature. To create an environmental insensitive damage detection scheme, the physics of thermal effects on Lamb waves must be understood. Dispersion and thermal sensitivity curves for an isotropic plate with thermal stress and thermally varying elastic modulus are presented. The thermal sensitivity of dispersion curves is analytically developed and validated by experimental measurements. The group velocity thermal sensitivity highlights temperature insensitive features at two critical frequencies. The thermal sensitivity gives us insight to how temperature affects Lamb wave speeds in different frequency ranges and will help those developing structural health monitoring algorithms.

Structural Health Monitoring of Composite Material Typical of Wind Turbine Blades by Novelty Detection on Vibration Response

New generations of offshore wind turbines are playing a leading role in the energy arena. One of the target challenges is to achieve reliable Structural Health Monitoring (SHM) of the blades. Fault detection at the early stage is a vital issue for the structural and economical success of the large wind turbines. In this study, experimental measurements of Frequency Response Functions (FRFs) are used and identification of mode shapes and natural frequencies is accomplished via an LMS system. Novelty detection is introduced as a robust statistical method for low-level damage detection which has not yet been widely used in SHM of composite blades. Fault diagnosis of wind turbine blades is a challenge due to their composite material, dimensions, aerodynamic nature and environmental conditions. The novelty approach combined with vibration measurements introduces an online condition monitoring method. This paper presents the outcomes of a scheme for damage detection of carbon fibre material in which novelty detection approaches are applied to FRF measurements. The approach is demonstrated for a stiffened composite plate subject to incremental levels of impact damage.

In situ mechanical characterization of isotropic structures using guided wave propagation

Guided waves are widely used in structural health monitoring (SHM). Their behaviour is highly sensitive to the mechanical properties of a structure. The performance of damage detection strategies based on guided waves therefore relies on an accurate knowledge of the mechanical properties. This paper presents an integrated characterization technique that identifies the mechanical properties of isotropic structures, namely the elastic modulus and Poisson’s ratio. The approach is based on a modified version of an imaging algorithm (Excitelet), where mechanical properties, instead of geometrical scattering features, are set as the variables to be identified. The methodology, accuracy, repeatability, and robustness are assessed, first via a finite element model (FEM) and then experimentally for an aluminum plate with attached piezoceramic (PZT) transducers. The plate is instrumented with two PZTs located 15 cm from each other in a pitch–catch configuration, distant enough to ensure proper mode discrimination. The algorithm accuracy and robustness with respect to slight variations in the geometrical inputs (PZT to PZT distance and thickness of the plate) are validated within ± 1% and ± 2%, respectively, with the FEM. Experimental results are validated within ± 1% of supplier properties, demonstrating the ability of this approach to allow accurate characterization of a structure in situ without the need for complex and expensive devices or ASTM testing.

A decentralized receptance-based damage detection strategy for wireless smart sensors

Various structural health monitoring strategies have been proposed recently that can be implemented in the decentralized computing environment intrinsic to wireless smart sensor networks (WSSN). Many are based on changes in the experimentally determined flexibility matrix for the structure under consideration. However, the flexibility matrix contains only static information; much richer information is available by considering the dynamic flexibility, or receptance, of the structure. Recently, the stochastic dynamic damage locating vector (SDDLV) method was proposed based on changes of dynamic flexibility matrices employing centrally collected output-only measurements. This paper investigates the potential of the SDDLV method for implementation on a network of wireless smart sensors, where a decentralized, hierarchical, in-network processing approach is used to address issues of scalability of the SDDLV algorithm. Two approaches to aggregate results are proposed that provide robust estimates of damage locations. The efficacy of the developed strategy is first verified using wired sensors emulating a wireless sensor network. Subsequently, the decentralized damage detection strategy is implemented on MEMSIC’s Imote2 smart sensor platform and validated experimentally on a laboratory scale truss bridge.

Structural damage detection of controlled building structures using frequency response functions

If a building structure requires both a vibration control system and a health monitoring system, the integration of the two systems will be cost-effective and beneficial. One of the key problems of this integrated system is how to use control devices to enhance system identification and damage detection. This paper presents a new method for system identification and damage detection of controlled building structures equipped with semi-active friction dampers through model updating based on frequency response functions. The two states of the building are first created by adding a known stiffness using semi-active friction dampers. A scheme based on the frequency response functions of the two states of the building is then presented to identify stiffness parameters of structural members in consideration of structural connectivity and transformation information. By applying the proposed model updating scheme to the damaged building, a damage detection scheme is proposed based on the identified stiffness parameters of structural members of both the original and damaged buildings. The feasibility of the proposed schemes is finally demonstrated through a detailed numerical investigation in terms of an example building, in which the effects of measurement noise and excitation conditions are discussed. The numerical results clearly show that the proposed method can locate and quantify damage satisfactorily even though measurement noise is taken into consideration.

Damage detection strategies based on propagation of guided elastic waves

This paper demonstrates the effectiveness of certain structural health monitoring (SHM) strategies based on propagation of guided elastic waves within thin-walled shell structures. This is realized based on results of numerical and experimental investigations obtained by the use of the spectral finite element method (SFEM) together with laser scanning vibrometry (LSV) and subsequent application of two different integral-based indices for damage quantification, these being the integral mean value (IMV) and the root mean square (RMS). Numerical tests by SFEM were carried out for a square plate with through-hole damage, a cracked fuselage section with two stiffeners and a cracked wing section skin, all made out of aluminium. Experimental measurements by LSV included tests on a square aluminium plate, composite plate and a composite stabilizer of a PZL W-3A helicopter, all with simulated damage. During numerical and experimental investigations damage sensitivity of both IMV and RMS indices was tested by considering various displacement components, signal timescales or weighting factors. A certain practical method for quick construction of RMS damage maps based on experimental measurements by LSV was also presented.

Optimal Damage Detection Sensor Placement Using PSO

An optimal damage detection sensor placement methodology is presented. The techniques utilize a Particle Swarm Optimization (PSO) algorithm. The proposed method is iterative in nature and it permits the use of incomplete measurements. Also, it allows diversity of damage detection algorithms to be used to generate the PSO required fitness function. However, in this work Linear Matrix Inequalities are used as the damage detection schemes. Computer simulations of a cantilevered beam will be used to demonstrate the effectiveness of the methodology.

Energy Damage Detection Strategy Based on Strain Responses for Long-Span Bridge Structures

An energy damage detection strategy through disposing strain responses has been developed. First, the strain-based energy dynamic indexes for a system with multiple degrees of freedom were derived from the frequency response function (FRF) of strain responses and energy spectra density. Then, the traditional mode-shape curvature strategy and the proposed strain-based energy damage detection strategy were both used to analyze a long-span cable-stayed bridge, and it was found through comparison that the proposed strain-based energy damage detection strategy solved the shortcomings of the traditional mode-shape curvature strategy. Finally, damage location, damage quantification, and noise pollution resistance analysis for a long-span cable-stayed bridge with different degrees of damage were carried out to verify the effectiveness of the proposed strain-based energy damage detection strategy. The numerical analysis showed that the proposed strain-based energy damage detection strategy can locate damage positions accurately, and it also has good damage quantification and noise pollution resistance abilities.