Vibration-based Damage Detection Research Articles

Evaluation of low cost vibration based damage detection systems

This paper evaluates the results that can be obtained with different strategies of instrumentation for an utility-scale wind turbine, considering variations on the number of sensors, on their distribution in the wind turbine tower and on their noise level. With the goal of reducing the investment in monitoring equipment, layouts based on a reduced number of low cost sensors are tested. The data processing strategy is based on the continuous tracking of the wind turbine main vibration modes using Operational Modal Analysis techniques combined with algorithms that deal with the particularities of operation of the wind turbines and that permit an online automated identification. After the mitigation of the influence of the environmental and operation factors on the tracked natural frequencies, it is possible to detect abnormal variations of the natural frequencies, which might flag the appearance of damage. The alternative monitoring scenarios are recreated using a database of acceleration time series collected during one year in an onshore 2MW wind turbine, by a quite extensive monitoring system, using low noise accelerometers.

Output-only damage detection in buildings using proportional modal flexibility-based deflections in unknown mass scenarios

Methods based on the evaluation of structural deflections from experimental modal flexibility matrices are important tools in vibration-based damage detection, especially for building structures. Modal flexibility matrices, however, can not be directly estimated when dealing with output-only vibration data (e.g. in the important case of structures tested under ambient vibrations). One can use an a-priori estimate of the mass matrix of the structure or the added mass method to obtain the modal normalization constants needed to assemble the flexibility matrix, but these operations can be challenging for real-life civil structures. To address this problem, a modal flexibility-based approach for output-only damage detection and localization in building structures that can be applied with minimal or no a-priori information on the structural masses is proposed in this paper. This approach is also able to deal with the general case in which mass modifications, e.g. due to operational variability in structures, are present before and after damage. The approach is based on the estimation (directly from output-only data) of modal flexibility-based deflections of building structures that are proportional with respect to the corresponding true deflections. From analytical investigations it was found that the missing scaling factor between the two deflections can be made theoretically equal to the total mass of the structure, as proposed in the paper. Then, interstory drifts evaluated from the proportional deflections are used for damage detection and localization according to two proposed strategies. The first strategy can be applied with minimal a-priori information on the masses (i.e. using a parameter that quantifies an eventual relative modification of the total mass of the structure before and after damage). The second one is a more advantageous strategy that can be applied from output-only data without any a-priori information on the masses, even in the case in which the masses are varied before and after damage. The effectiveness of the proposed approach was demonstrated using both numerical simulations and experimental vibration tests on frame building structures.

A damage detection method based on strain modes for structures under ambient excitation

Vibration-based damage detection methods play a vital role in structural health monitoring, but there are many problems in the application of those traditional damage detection methods; for instance, the ability to promptly sense and accurately locate realistic damage in structures are the primary challenges confronting traditional damage detection methods. Strain modes typically have high sensitivity in structural damage detection. Thus, this paper defined a novel damage detection method based on strain modes. According to the relationship between strain and displacement, the natural excitation technique based on the strain response combined with the eigensystem realization algorithm was applied to identify the strain modal parameters of structures under ambient excitation. The detection index was also employed to localize damage. Crack and corrosion damage of beam-type structures was simulated under experimental conditions. Next, single-damage and multi-damage cases with different degrees and locations were prefabricated experimentally. The results demonstrated that all damage cases were detected in a reasonable manner, thereby demonstrating the validity of the proposed method in structural damage detection.

Vibration-based damage detection for a population of nominally identical structures: Unsupervised Multiple Model (MM) statistical time series type methods

The problem of vibration-based damage detection for a population of nominally identical structures is considered via unsupervised statistical time series type methods. For this purpose a population sample comprising 31 nominally identical composite beams with significant beam-to-beam variability in the dynamics is employed, with impact-induced damage at various positions and two distinct energy levels. Two Multiple Model, MM, based statistical time series type methods are postulated, assessed, and compared with two ‘conventional’ methods. The assessment is based on a comprehensive and systematic procedure, making use of thousands of test cases via a ‘rotation’ procedure, with the results presented in the form of Receiver Operating Characteristic, ROC, curves. These indicate that ‘conventional’ methods are mostly ineffective, especially with low impact energy damages. On the other hand, the postulated Multiple Model parameter based methods achieve significantly improved performance, characterized as very good and providing overall correct damage detection rates approaching 100% for false alarm rates at or above 5%.

Structural Health Monitoring for Multi-story Shear Frames Based on Signal Processing Approach

Non-destructive vibration-based global structural health monitoring and damage detection methods are divided into modal-based and signal-based methods. There is much research in these areas, but each one has some advantages and disadvantages. The combination of these two areas can greatly overcome these disadvantages and thus can enhance the robustness of the damage detection methods. This article presents a signal-modal-based structural health monitoring technique for multi-story shear buildings subjected to an earthquake event. The proposed method utilizes the combination of wavelet transform and FFT as signal processing tools and also Hilbert transform with the aim of final modal parameters extraction, in order to determine the existence, location, and extent of damage in the multi-story shear frames. In fact, extraction of final modal parameters from the acceleration response signals is desired. To demonstrate the capabilities of the proposed algorithm, numerical simulations are performed on a four-story two-bay and ten-story two-bay shear frame with different damage scenarios using OpenSees. The results show that this method can detect the occurrence, location, and severity of the damage with good accuracy even in different levels of multi-damage scenarios and also in the presence of measurement noise.

Vibration-based damage assessment of structures using signal decomposition and two-dimensional visualization techniques

The objective of this study was to develop a technique for vibration-based damage detection through data reduction and a visualization technique known as Sammon mapping, which directly uses sensing signals. Based on the instrumented accelerometer, damage assessment of the structure is done using either ambient vibration or seismic response for centralized and sensor-level data analyses in the time or frequency domain. For the centralized data analysis, the embedded data matrix [X]m × n was constructed, with m as the number of sensing nodes and n as the number for discrete Fourier amplitude/time series data. Incorporated with the principal component analysis, data compression and pattern recognition were used for damage detection and localization. First, the matrix of mutual distances of data sets from each sensing node on the high-dimensional space was calculated. The two-dimensional space was then generated to create a Sammon mapping configuration. Damage detection and localization could be evaluated through the change in two-dimensional visualization on a Sammon map between different damage states. The proposed two-dimensional visualization technique, which uses multivariate signal-processing algorithms to identify structural damage, was verified using experimental test data of two different damage types of structures (damages occurring either in lower modes or in non-linearity). Using the proposed technique and based on the building’s seismic response data, we can systematically detect the damage occurrence (Level 1 damage detection) and localization (Level 2 damage detection).

Vibration-based damage detection in wind turbine blades using Phase-based Motion Estimation and motion magnification

Vibration-based Structural Health Monitoring (SHM) techniques are among the most common approaches for structural damage identification. The presence of damage in structures may be identified by monitoring the changes in dynamic behavior subject to external loading, and is typically performed by using experimental modal analysis (EMA) or operational modal analysis (OMA). These tools for SHM normally require a limited number of physically attached transducers (e.g. accelerometers) in order to record the response of the structure for further analysis. Signal conditioners, wires, wireless receivers and a data acquisition system (DAQ) are also typical components of traditional sensing systems used in vibration-based SHM. However, instrumentation of lightweight structures with contact sensors such as accelerometers may induce mass-loading effects, and for large-scale structures, the instrumentation is labor intensive and time consuming. Achieving high spatial measurement resolution for a large-scale structure is not always feasible while working with traditional contact sensors, and there is also the potential for a lack of reliability associated with fixed contact sensors in outliving the life-span of the host structure. Among the state-of-the-art non-contact measurements, digital video cameras are able to rapidly collect high-density spatial information from structures remotely. In this paper, the subtle motions from recorded video (i.e. a sequence of images) are extracted by means of Phase-based Motion Estimation (PME) and the extracted information is used to conduct damage identification on a 2.3-m long Skystream® wind turbine blade (WTB). The PME and phased-based motion magnification approach estimates the structural motion from the captured sequence of images for both a baseline and damaged test cases on a wind turbine blade. Operational deflection shapes of the test articles are also quantified and compared for the baseline and damaged states. In addition, having proper lighting while working with high-speed cameras can be an issue, therefore image enhancement and contrast manipulation has also been performed to enhance the raw images. Ultimately, the extracted resonant frequencies and operational deflection shapes are used to detect the presence of damage, demonstrating the feasibility of implementing non-contact video measurements to perform realistic structural damage detection.

Sequential projection pursuit for optimised vibration-based damage detection in an experimental wind turbine blade

To advance the concept of smart structures in large systems, such as wind turbines (WTs), it is desirable to be able to detect structural damage early while using minimal instrumentation. Data-driven vibration-based damage detection methods can be competitive in that respect because global vibrational responses encompass the entire structure. Multivariate damage sensitive features (DSFs) extracted from acceleration responses enable to detect changes in a structure via statistical methods. However, even though such DSFs contain information about the structural state, they may not be optimised for the damage detection task. This paper addresses the shortcoming by exploring a DSF projection technique specialised for statistical structural damage detection. High dimensional initial DSFs are projected onto a low-dimensional space for improved damage detection performance and simultaneous computational burden reduction. The technique is based on sequential projection pursuit where the projection vectors are optimised one by one using an advanced evolutionary strategy. The approach is applied to laboratory experiments with a small-scale WT blade under wind-like excitations. Autocorrelation function coefficients calculated from acceleration signals are employed as DSFs. The optimal numbers of projection vectors are identified with the help of a fast forward selection procedure. To benchmark the proposed method, selections of original DSFs as well as principal component analysis scores from these features are additionally investigated. The optimised DSFs are tested for damage detection on previously unseen data from the healthy state and a wide range of damage scenarios. It is demonstrated that using selected subsets of the initial and transformed DSFs improves damage detectability compared to the full set of features. Furthermore, superior results can be achieved by projecting autocorrelation coefficients onto just a single optimised projection vector.

Features of vibration-based damage detection in stepped shafts of steam turbines

The vibration-based damage detection has practically no alternative as applied to the rotating shafts of steam turbines during operation. However, taking into account the heavy operating conditions of turbines and the complex shape of turbines shaft, the choice of most effective method of vibration diagnostics is not an easy problem. To solve this problem, a relatively simple method of comparative evaluation of the effectiveness of vibration diagnostics of damage as applied to the stepped rotors and shafting of steam turbine was developed. The method is based on the determination of relative change of shaft's compliance caused by a crack with the use of linear fracture mechanics. As an example there was performed the comparative analysis of efficiency of vibration diagnostics, namely the change of natural bending, longitudinal or torsional frequency of vibration and the nonlinear effects, to detect transverse or longitudinal crack in rotors and shafting of steam turbine K-215-130.

Features of vibration-based damage detection in stepped shafts of steam turbines

The vibration-based damage detection has practically no alternative as applied to the rotating shafts of steam turbines during operation. However, taking into account the heavy operating conditions of turbines and the complex shape of turbines shaft, the choice of most effective method of vibration diagnostics is not an easy problem. To solve this problem, a relatively simple method of comparative evaluation of the effectiveness of vibration diagnostics of damage as applied to the stepped rotors and shafting of steam turbine was developed. The method is based on the determination of relative change of shaft's compliance caused by a crack with the use of linear fracture mechanics. As an example there was performed the comparative analysis of efficiency of vibration diagnostics, namely the change of natural bending, longitudinal or torsional frequency of vibration and the nonlinear effects, to detect transverse or longitudinal crack in rotors and shafting of steam turbine K-215-130.

Random vibration based damage detection for a composite beam under environmental and operational variability via a stochastic Functional Model based method

The problem of random vibration response based damage detection for a composite beam under non-measurable environmental and operational variability, presently temperature and tightening torque, is considered via a Functional Model based method. The method is based on proper representation of the healthy structural dynamics under any environmental/operating conditions via a data based Functional Model obtained in the method’s baseline phase and used to define a ‘healthy subspace’. Damage detection is, in the method’s inspection phase, achieved by examining whether or not the current dynamics belongs to the healthy subspace. The experimental results obtained for damage detection on a composite beam indicate excellent detection performance, with correct detection rate of 100% for false alarm rate as small as 1%. The superiority of the proposed method is confirmed via comparisons with a state-of-the-art Principal Component Analysis based method.

Vibration Based Damage Detection of Rotating Beams

The early detection and localization of damages is essential for operation, maintenance and cost of the structures. Because the frequency of vibration cannot be controlled in real-life structures, the methods for damage detection should work for wide range of frequencies. In the current work, the equation of motion of rotating beam is derived and presented and the damage is modelled by reduced thickness. Vibration based methods which use Poincaré maps are implemented for damage localization. It is shown that for clamped-free boundary conditions these methods are not always reliable and their success depends on the excitation frequency. The shapes of vibration of damaged and undamaged beams are shown and it is concluded that appropriate selection criteria should be defined for successful detection and localization of damages.

Vibration-based damage detection of structural joints in presence of uncertainty

Early damage detection of structure’s joints is essential in order to ensure the integrity of structures. Vibration-based methods are the most popular way of diagnosing damage in machinery joints. Any technique that is used for such a purpose requires dealing with the variability inherent to the system due to manufacturing tolerances, environmental conditions or aging. The level of variability in vibrational response can be very high for mass-produced complex structures that possess a large number of components. In this study, a simple and efficient time frequency method is proposed for detection of damage in connecting joints. The method suggests using singular spectrum analysis for building a reference space from the signals measured on a healthy structure and then compares all other signals to that reference space in order to detect the presence of faults. A model of two plates connected by a series of mounts is used to examine the effectiveness of the method where the uncertainty in the mount properties is taken into account to model the variability in the built-up structure. The motivation behind the simplified model is to identify the faulty mounts in trim-structure joints of an automotive vehicle where a large number of simple plastic clips are used to connect the trims to the vehicle structure.

Vibration-based damage detection in beams by genetic algorithm encoding locations and damage factors as decision variables

Vibration-based damage detection is based on the fact that vibration characteristics such as natural frequencies and mode shapes of structures are changed when the damage is happened. The vibration-based damage detection of a beam is formulated as a single-objective optimization problem in which genetic algorithm (GA) is used as the optimizer. This paper presents the encoding by locations and damage factor (ELD) which employs location and damage amount as the decision variables. The proposed encoding can reduce the number of decision variables that used in the previous encoding, the encoding by damage factor of each element (EDE). The search space of GA with ELD is then smaller than that of GA with EDE. The simulation results reveal that GA with ELD can identify the damage occurred in the beam more correctly than GA with EDE. Moreover, the damage predicted by GA with ELD is quite close to the actual damage for all 3 test cases.

Damage detection of rotating wind turbine blades using local flexibility method and long-gauge fiber Bragg grating sensors

Wind turbines are a cost-effective alternative energy source; however, their blades are susceptible to damage. Therefore, damage detection of wind turbine blades is of great importance for condition monitoring of wind turbines. Many vibration-based structural damage detection techniques have been proposed in the last two decades. The local flexibility method, which can determine local stiffness variations of beam-like structures by using measured modal parameters, is one of the most promising vibration-based approaches. The local flexibility method does not require a finite element model of the structure. A few structural modal parameters identified from the ambient vibration signals both before and after damage are required for this method. In this study, we propose a damage detection approach for rotating wind turbine blades using the local flexibility method based on the dynamic macro-strain signals measured by long-gauge fiber Bragg grating (FBG)-based sensors. A small wind turbine structure was constructed and excited using a shaking table to generate vibration signals. The structure was designed to have natural frequencies as close as possible to those of a typical 1.5 MW wind turbine in real scale. The optical fiber signal of the rotating blades was transmitted to the data acquisition system through a rotary joint fixed inside the hollow shaft of the wind turbine. Reversible damage was simulated by aluminum plates attached to some sections of the wind turbine blades. The damaged locations of the rotating blades were successfully detected using the proposed approach, with the extent of damage somewhat over-estimated. Nevertheless, although the specimen of wind turbine blades cannot represent a real one, the results still manifest that FBG-based macro-strain measurement has potential to be employed to obtain the modal parameters of the rotating wind turbines and then locations of wind turbine segments with a change of rigidity can be estimated effectively by utilizing these identified parameters.

Dynamic identification and continuous dynamic monitoring of bridges: different applications along bridges life cycle

This paper aims at stressing the major role that Dynamic Identification and Continuous Dynamic Monitoring can play in the observation and understanding of the structural behaviour of bridges along the different phases of their life cycle, based on the authors’ experience got at the Laboratory of Vibrations and Structural Monitoring (ViBest) of the University of Porto during the last 20 years. The paper comprehends two initial sections summarising some relevant aspects regarding the evolution observed in terms of excitation devices and instrumentation, as well as in the field of modal identification of large Civil structures. Subsequently, the importance of dynamic identification along bridges’ life cycle (design, construction, commissioning, and service or rehabilitation phases) is illustrated on the basis of relevant case studies, involving several outstanding structures. Lastly, the interest and potential of Continuous Dynamic Monitoring is also emphasised, describing several dynamic monitoring programmes implemented with different perspectives, such as: (i) the vibration serviceability safety checking in lively footbridges; (ii) the evaluation of dynamic effects of traffic loads in roadway and railway bridges and fatigue assessment; (iii) the vibration based damage detection; (iv) or the dynamic monitoring of wind effects on large bridges.

Strain sensing of beams in flexural vibrations using rotation rate sensors

This study investigated the application of rotation rate sensors to measure flexural vibrations of beams. This new area of the application of rotational sensors can be beneficial for monitoring various structures, particularly civil engineering structures like reinforced concrete beams and frames and masonry structures, which are difficult to assess using vibration-based damage detection techniques. In a small-scale laboratory experiment, Horizon HZ1-100-100 rotation rate sensors were put in the middle of a plexiglass cantilever beam along with four strain gauges. The beam underwent kinematic excitations, during which variations of the rotations and strains are observed simultaneously. Results of the tests are presented in detail and it was concluded that the rotation rate sensors can be effectively used to monitor flexural vibrations of beams, with particular attention to indirect strain monitoring. In addition, a simple test to check the effectiveness of the rotation rate sensors to monitor stiffness drops in localized locations was carried out. The experiments demonstrated that rotation rate sensors have potential to dramatically improve SHM of civil engineering structures and with improved accuracy, these sensors can find wide application in on-line and post-earthquake structural assessment.

Damage localization and quantification of composite beam structures using residual force and optimization

Structural Health Monitoring (SHM) and impact monitoring of composite structures have become important research topics in the recent year. In this research, a non-destructive vibration-based damage detection method is formulated using Genetic Algorithm (GA) and compared with classical method. The robustness and reliability of the capability to locate and to estimate the severity of damage, based on changes in dynamic characteristics of a structure, is investigated. The objective function for the damage identification problem is established by using the residual force method (FRM). Numerical experiments using finite element analysis are performed on composite beams with different damage scenarios in order to clarify the validity of the developed technique. The comparison between estimated and real damage illustrates the efficiency of the algorithm in damage detection. The results show that the present approach is correct and efficient for detecting structural local damages in composite beam structures.

Method development of damage detection in asymmetric buildings

Aesthetics and functionality requirements have caused most buildings to be asymmetric in recent times. Such buildings exhibit complex vibration characteristics under dynamic loads as there is coupling between the lateral and torsional components of vibration, and are referred to as torsionally coupled buildings. These buildings require three dimensional modelling and analysis. In spite of much recent research and some successful applications of vibration based damage detection methods to civil structures in recent years, the applications to asymmetric buildings has been a challenging task for structural engineers. There has been relatively little research on detecting and locating damage specific to torsionally coupled asymmetric buildings. This paper aims to compare the difference in vibration behaviour between symmetric and asymmetric buildings and then use the vibration characteristics for predicting damage in them. The need for developing a special method to detect damage in asymmetric buildings thus becomes evident. Towards this end, this paper modifies the traditional modal strain energy based damage index by decomposing the mode shapes into their lateral and vertical components and to form component specific damage indices. The improved approach is then developed by combining the modified strain energy based damage indices with the modal flexibility method which was modified to suit three dimensional structures to form a new damage indicator. The procedure is illustrated through numerical studies conducted on three dimensional five-story symmetric and asymmetric frame structures with the same layout, after validating the modelling techniques through experimental testing of a laboratory scale asymmetric building model. Vibration parameters obtained from finite element analysis of the intact and damaged building models are then applied into the proposed algorithms for detecting and locating the single and multiple damages in these buildings. The results obtained from a number of different damage scenarios confirm the feasibility of the proposed vibration based damage detection method for three dimensional asymmetric buildings.

Vibration-based structural health monitoring of the aircraft large component

In the presented paper there are investigated the basic problems of the local system of SHM of large scale aircraft component. Vibration-based damage detection is accepted as a basic condition, and main attention focused to a low-cost solution that would be attractive for practice. The conditions of small damage detection in the full scale structural component at low-frequency excitation were defined in analytical study and modal FEA. In experimental study the dynamic test of the helicopter Mi-8 tail beam was performed at harmonic excitation with frequency close to first natural frequency of the beam. The index of correlation coefficient deviation (CCD) was used for extraction of the features due to embedded pseudo-damage. It is shown that the problem of vibration-based detection of a small damage in the large scale structure at low-frequency excitation can be solved successfully.