Structural Health Monitoring Purposes Research Articles

Statistical analysis of modal parameters of a suspension bridge based on Bayesian spectral density approach and SHM data

Abstract Uncertainty of modal parameters estimation appear in structural health monitoring (SHM) practice of civil engineering to quite some significant extent due to environmental influences and modeling errors. Reasonable methodologies are needed for processing the uncertainty. Bayesian inference can provide a promising and feasible identification solution for the purpose of SHM. However, there are relatively few researches on the application of Bayesian spectral method in the modal identification using SHM data sets. To extract modal parameters from large data sets collected by SHM system, the Bayesian spectral density algorithm was applied to address the uncertainty of mode extraction from output-only response of a long-span suspension bridge. The posterior most possible values of modal parameters and their uncertainties were estimated through Bayesian inference. A long-term variation and statistical analysis was performed using the sensor data sets collected from the SHM system of the suspension bridge over a one-year period. The t location-scale distribution was shown to be a better candidate function for frequencies of lower modes. On the other hand, the burr distribution provided the best fitting to the higher modes which are sensitive to the temperature. In addition, wind-induced variation of modal parameters was also investigated. It was observed that both the damping ratios and modal forces increased during the period of typhoon excitations. Meanwhile, the modal damping ratios exhibit significant correlation with the spectral intensities of the corresponding modal forces.

Biomechanically influenced mobile and participatory pedestrian data for bridge monitoring

Future structural health monitoring systems are evolving toward crowdsourced, autonomous, sustainable forms based on which damage-indicative structural features can be identified. Unlike conventional sensor systems, they serve as non-stationary, mobile, and distributed sensor network components. For example, smartphone sensors carried by pedestrians decouple from the structure of interest, making it difficult to measure structural vibration. Taking bridges as instances, smartphone sensor data contain not only the bridge vibration but also the pedestrians’ biomechanical features. In this article, pedestrians’ smartphone data are used to conduct force estimation and modal identification for structural health monitoring purposes. Two major pedestrian activities, walking and standing, are adopted to estimate walk-induced forces on structures and identify modal parameters, respectively. First, vibration time history of a walking pedestrian combined with pedestrian weight is a measure of dynamic forces imposed on the structure. Second, standing pedestrian’s smartphone sensors provide spectral peaks which are mixtures of structural and biomechanical vibrations. Eliminating biomechanical content reveals structural modal properties which are sensitive to structural integrity. This study presents the first structural health monitoring application recruiting pedestrians in a testbed bridge monitoring example. Orchestrating pervasive and participatory pedestrian data might bring new frontiers to structural health monitoring through a smart, mobile, and urban sensing framework.

Refined Frequency Domain Decomposition modal dynamic identification from earthquake-induced structural responses

In the present work, earthquake-induced structural responses at heavy damping are considered towards the assessment of current strong-motion output-only modal parameters via a novel refined Frequency Domain Decomposition (rFDD) approach. Classical FDD assumptions of stationary white noise input and light damping no longer hold in such a case, leading to extreme operational conditions for this Frequency-Domain modal dynamic identification technique. The present non-parametric output-only rFDD procedure effectively tackles such issues, through dedicated algorithmic and computational strategies, resulting in a robust identification tool within this challenging identification context. Synthetic earthquake-induced responses are generated from a set of shear-type frames, which are taken as target structural models for the purposes of validation and comparison. Twenty-two “Far-Field” multi-component (NS, WE) seismic base excitations are taken into account from the FEMA P695 strong motion database. In particular, heavy-damped structures (in terms of output-only identification challenge) are considered, raising the modal damping ratios up to 10%. Natural frequencies, mode shapes and modal damping ratios are effectively estimated through the implemented rFDD procedure. The achieved estimates are statistically compared to the target values, by proving the effectiveness of the developed rFDD approach in working with synthetic earthquake-induced responses at concurrent heavy damping. This shall demonstrate a necessary condition for the feasibility of the developed rFDD approach towards Earthquake Engineering and Structural Health Monitoring purposes.

Sensor yarns for real-time in situ detection of damage behavior for the purpose of structural health monitoring of textile-reinforced thermoset composites: development of a continuous wet-chemical silvering process for high-performance filament yarn

High-performance textile yarns such as glass filament (GF) yarn will be used as the base material for the development of sensor yarns because glass filament yarns offer both high tensile strengths and moduli of elasticity, as well as high melting temperatures and elongation. A new continuous wet-chemical metallization process has been developed for GF yarns on a laboratory scale to achieve special properties such as electrical conductivity. The aim of the work is to develop a continuous wet-chemical silver plating process for the GF-filament yarn in order to achieve electrical conductivity on the GF-surface. The process was carried out continuously in order to metallize the GF, which is sensitive to the shear force. A homogeneous, completely covered and adhered silver layer on the GF yarn surfaces was obtained by the application of this technology. The surface morphology was been determined by light and scanning electron microscopy to assess the silver layer properties such as structure, homogeneity, and cracking. The chemical structure of the surfaces was analyzed by means of energy dispersive x-ray spectroscopy. For structural analysis, GF yarns were investigated using a Fourier transform infrared spectrometer. The dispersive and polar component of the surface energy of the sized and silvered GF yarn was measured by using a single fiber Tensiometer K100. The silver layer thickness and the silver content were determined after the metallization. Textile physical tests of the tensile strength, elasticity modulus, elongation at break, and yarn fineness of the single GF yarns as well as GF bundle were carried out.

Structural Health Monitoring Using Textile Reinforcement Structures with Integrated Optical Fiber Sensors.

Optical fiber-based sensors “embedded” in functionalized carbon structures (FCSs) and textile net structures (TNSs) based on alkaline-resistant glass are introduced for the purpose of structural health monitoring (SHM) of concrete-based structures. The design aims to monitor common SHM parameters such as strain and cracks while at the same time acting as a structural strengthening mechanism. The sensor performances of the two systems are characterized in situ using Mach-Zehnder interferometric (MZI) and optical attenuation measurement techniques, respectively. For this purpose, different FCS samples were subjected to varying elongation using a tensile testing machine by carefully incrementing the applied force, and good correlation between the applied force and measured length change was observed. For crack detection, the functionalized TNSs were embedded into a concrete block which was then exposed to varying load using the three-point flexural test until destruction. Promising results were observed, identifying that the location of the crack can be determined using the conventional optical time domain reflectometry (OTDR) technique. The embedded sensors thus evaluated show the value of the dual achievement of the schemes proposed in obtaining strain/crack measurement while being utilized as strengthening agents as well.

Seismic FDD modal identification and monitoring of building properties from real strong-motion structural response signals

In the present study, output-only modal dynamic identification and monitoring of building properties is attempted successfully by processing real earthquake-induced structural response signals. This is achieved through an enhanced version of a recently-developed refined Frequency Domain Decomposition (rFDD) approach, which in the earlier implementation was adopted to analyse synthetic seismic response signals only. Despite that short duration, nonstationary seismic response data and heavy structural damping shall not fulfil traditional Operational Modal Analysis assumptions, the present rFDD response-only algorithm allows for the effective estimation of strong-motion natural frequencies, mode shapes, and modal damping ratios, with real seismic response signals. The present rFDD enhancement derives from a preprocessing time-frequency analysis and from an integrated approach for Power Spectral Density matrix computation, which constitute crucial innovative issues for the treatment of real earthquake response data. A monitoring case study is analysed by taking the real strong-motion response records from a seven-storey reinforced concrete building in Van Nuys, California, from 1987 to the latest 2014 events (Center of Engineering Strong Motion Data database), as recorded before, during and after the 1994 Northridge earthquake, which severely damaged the building (then retrofitted). This paper proves the effectiveness of the proposed enhanced rFDD algorithm as a robust method for monitoring current structural modal properties under real earthquake excitations. This shall allow for identifying possible variations of structural features along experienced seismic histories, providing then a fundamental tool towards Earthquake Engineering and Structural Health Monitoring purposes.

Inspection of Piezoceramic Transducers Used for Structural Health Monitoring.

The use of piezoelectric wafer active sensors (PWAS) for structural health monitoring (SHM) purposes is state of the art for acousto-ultrasonic-based methods. For system reliability, detailed information about the PWAS itself is necessary. This paper gives an overview on frequent PWAS faults and presents the effects of these faults on the wave propagation, used for active acousto-ultrasonics-based SHM. The analysis of the wave field is based on velocity measurements using a laser Doppler vibrometer (LDV). New and established methods of PWAS inspection are explained in detail, listing advantages and disadvantages. The electro-mechanical impedance spectrum as basis for these methods is discussed for different sensor faults. This way this contribution focuses on a detailed analysis of PWAS and the need of their inspection for an increased reliability of SHM systems.

Structural health monitoring of cylindrical bodies under impulsive hydrodynamic loading by distributed FBG strain measurements

Various mechanical, ocean, aerospace and civil engineering problems involve solid bodies impacting the water surface and often result in complex coupled dynamics, characterized by impulsive loading conditions, high amplitude vibrations and large local deformations. Monitoring in such problems for purposes such as remaining fatigue life estimation and real time damage detection is a technical and scientific challenge of primary concern in this context. Open issues include the need for developing distributed sensing systems able to operate at very high acquisition frequencies, to be utilized to study rapidly varying strain fields, with high resolution and very low noise, while scientific challenges mostly relate to the definition of appropriate signal processing and modeling tools enabling the extraction of useful information from distributed sensing signals.Building on previous work by some of the authors, we propose an enhanced method for real time deformed shape reconstruction using distributed FBG strain measurements in curved bodies subjected to impulsive loading and we establish a new framework for applying this method for structural health monitoring purposes, as the main focus of the work. Experiments are carried out on a cylinder impacting the water at various speeds, proving improved performance in displacement reconstruction of the enhanced method compared to its previous version. A numerical study is then carried out considering the same physical problem with different delamination damages affecting the body. The potential for detecting, localizing and quantifying this damage using the reconstruction algorithm is thoroughly investigated. Overall, the results presented in the paper show the potential of distributed FBG strain measurements for real time structural health monitoring of curved bodies under impulsive hydrodynamic loading, defining damage sensitive features in terms of strain or displacement reconstruction errors at selected locations along the structure.

Simultaneous identification of damage and input dynamic force on the structure for structural health monitoring

In this paper, we present an approach for simultaneous identification of the system parameters and the input dynamic force time history. The inverse problem associated with the system identification is formulated as an optimization problem and is solved using a newly developed dynamic hybrid adaptive firefly algorithm (DHAFA). A modified version of Tikhonov regularization is employed while solving the inverse problem associated with the force identification in order to improve the quality of the solution. Numerical simulation studies have been carried out by solving three distinct numerical examples. Studies presented in this paper indicate that the proposed algorithm is effective in identifying the system parameters as well as the input dynamic force simultaneously and can be effectively used for structural health monitoring purposes. Convergence studies presented in this paper on the newly developed dynamic hybrid firefly algorithm indicate that the proposed algorithm has better convergence characteristics and can be effectively employed for solving complex nonlinear optimization problems associated with system identification.

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.

Assessment of a Pedestrian Bridge Dynamics Using Interferometric Radar System IBIS-FS

Traffic loads are increasing, trucks are getting larger and heavier and this is a trend expected to continue. This may cause an increase in the rate of a bridge structural deterioration. As such there needs to be innovative methods of assessing bridge structural health for an improved structural asset management. IBIS-FS is a new piece of equipment based on interferometric radar developed recently for the purpose of structural health assessment and monitoring. It is presented as offering unique advantages over conventional monitoring solutions such as its portability and that it does not require direct contact with the structure. This study explores the use of IBIS-FS to detect changes in a pedestrian bridge natural frequencies over time from which a change in bridge stiffness, and subsequently, the level of structural deterioration, can be obtained. In particular, the focus of this study centers on validating the natural frequencies obtained from the interferometric measurements with those determined from more conventional methods. It was found that IBIS is capable of capturing the natural frequencies of the bridge investigated demonstrating its potential use in the structural health monitoring of bridges.

Scattering of the Fundamental Anti-symmetric Lamb Wave by a Mid-plane Edge Delamination in a Fiber-composite Laminate

This paper investigates the scattering of the fundamental anti-symmetric Lamb wave mode by a delamination along the edge of a quasi-isotropic fiber-composite laminate. Delaminations pose a serious threat to the structural integrity of composite laminates as they often show no visible signs of damage on the surface. Due to the anisotropic nature of composites, analytical solutions are often complicated to derive for such problems. This investigation uses 3D Finite Element (FE) analysis and experimental tools to characterize the scatter by a mid-plane delamination in composites. A 5.5 cycle Hann windowed wave train was used as the input signal for both FE and experiments. A 2D Fast Fourier Transform was used to identify the mode and amplitude of the scattered field along various scattered directions. The experimental wave field image was captured using a 3D Laser Vibrometer. The results indicate that the scatter pattern is much more complex than previously obtained results for an isotropic plate. Even for the simple case of mid-plane delamination, the fiber steering effects in the outermost plies have a significant effect on the scattering pattern, relative to the isotropic case where the dominant part of the scattered field is an edge-guided wave. Computational and experimental results are presented for the scattering pattern and scattering amplitude as a function of damage size relative to wavelength. The implications of these results for the optimal placement of actuators and sensors for Structural Health Monitoring (SHM) purposes, and for devising effective approaches for the inverse problem of damage detection and sizing, are briefly discussed.

Refined FDD modal dynamic identification from earthquake responses with Soil-Structure Interaction

“Non-parametric” structural system identification via a refined Frequency Domain Decomposition (rFDD) algorithm is developed here to evaluate current modal properties of civil engineering buildings subjected to earthquake excitation. Innovatively, the algorithm is expanded to operate under Soil-Structure Interaction (SSI) conditions, in order to deal with both flexible- and fixed-base conditions. At first, the modal dynamic identification technique is explored analytically, by dealing with a variable stiffness and damping foundation system. The standard fixed-base condition (no SSI) may simulate well the response to ambient loadings or weak seismic excitations; rather, a flexible-base model shall better deal with more realistic earthquake-induced structural responses embedding SSI effects. The developed analyses are performed on earthquake-induced synthetic response signals, which are computed from a benchmark linear frame structure under several earthquake excitations and at variable foundation properties. The rFDD expansion originally operates within an OMAX (Operational Modal Analysis with eXogenous input) environment on the base-excited buildings. The OMAX condition comes from the adoption of base excitation records too, which are employed as exogenous input. This aims at detecting also the underlying fixed-base conditions and to quantify the amount of SSI to which the building under analysis is subjected to. The present identification method demonstrates its full effectiveness in detecting both flexible- and fixed-base modal parameters identified based on earthquake excitation, also in the presence of close modes and heavy damping (in terms of identification challenge). This work proves a necessary condition for the effectiveness of the present rFDD-OMAX algorithm as a robust method for inspecting current flexible- and fixed-base strong ground motion modal parameters. This shall help in identifying possible variations of structural features and SSI effects along experienced seismic histories, thus providing an effective tool towards potential Earthquake Engineering and Structural Health Monitoring purposes.

Post-impact damage detection on a winglet structure realized in composite material

In this work, a structural health monitoring system has been implemented with damage identification purpose on a winglet of a general aviation aircraft. Using a pitch-catch approach, guided waves (Lamb waves) have been measured by means of an array of piezoelectric sensors able to excite and record the dynamic response of the structure. The undamaged configuration has been used as reference state (baseline) for the structural health monitoring (SHM) purpose while the damaged configuration (current state) has been obtained by low velocity impact test. The effectiveness of the damage has been verified using a Non-Destructive Inspection (NDI) by means of a C-SCAN Olympus Omni SX. The calculation of the damage index obtained comparing the measured wave propagation data in a reference state and the current state is introduced as a determinant of structural damage. Its calculation in different paths associated with the Probability Ellipse (PE) method has been used to identify the position of the damage. Additional radar graphs have been developed for the measurement of the directionality of the Lamb waves and further considerations have been introduced in order to evaluate the sensitivity of the Lamb waves with the aerodynamic load.

ALTERNATE AND DIRECT CURRENT ANALYSIS OF CONCRETE

We live in an era where houses and other institutional buildings are getting more and more automated and sophisticated; this boom in the construction industry is accompanied by an increasing risk of structural failures. This paper illustrates the determination of electrical properties of concrete for the purpose of structural health monitoring. Concrete blocks of size (150 x 150 x 150 mm) were used as test specimen and 2-point probe method was used for plotting I-V characteristics, for both direct and alternating current supply. The semiconductor nature of cement matrix was studied as a combination of Resistance-Capacitance Circuit along with its applications. It was found that conductivity of concrete decreases on ageing in a definite pattern, and conductivity can be used to comment on durability and quality of concrete. However, under loading, an impedance jump is observed, owing to induction of cracks or voids in concrete.

Monitoring Poisson’s Ratio Degradation of FRP Composites under Fatigue Loading Using Biaxially Embedded FBG Sensors

The significance of strain measurement is obvious for the analysis of Fiber-Reinforced Polymer (FRP) composites. Conventional strain measurement methods are sufficient for static testing in general. Nevertheless, if the requirements exceed the capabilities of these conventional methods, more sophisticated techniques are necessary to obtain strain data. Fiber Bragg Grating (FBG) sensors have many advantages for strain measurement over conventional ones. Thus, the present paper suggests a novel method for biaxial strain measurement using embedded FBG sensors during the fatigue testing of FRP composites. Poisson’s ratio and its reduction were monitored for each cyclic loading by using embedded FBG sensors for a given specimen and correlated with the fatigue stages determined based on the variations of the applied fatigue loading and temperature due to the autogenous heating to predict an oncoming failure of the continuous fiber-reinforced epoxy matrix composite specimens under fatigue loading. The results show that FBG sensor technology has a remarkable potential for monitoring the evolution of Poisson’s ratio on a cycle-by-cycle basis, which can reliably be used towards tracking the fatigue stages of composite for structural health monitoring purposes.

Synchronization of dynamic response measurements for the purpose of structural health monitoring

This paper presents a technique for offline time synchronization of data acquisition systems for linear structures with proportional damping. The technique can be applied when direct synchronization of data acquisition systems is impossible or not sufficiently accurate. The synchronization is based on the acquired dynamic response of the structure only, and does not require the acquisition of a shared sensor signal or a trigger signal. The time delay is identified from the spurious phase shift of the mode shape components that are obtained from system identification. A demonstration for a laboratory experiment on a cantilever steel beam shows that the proposed methodology can be used for accurate time synchronization, resulting in a significant improvement of the accuracy of the identified mode shapes.

Model updating of real structures with ambient vibration data

It is important to develop reliable finite element models (FEMs) for real structures not only in the design-phase but also for the structural health monitoring and life-cycle management purposes. To do so, model updating is often carried out to minimise the discrepancies between FEMs and real structures. Among existing model updating approaches, sensitivity based model updating methods which can be either manual or automated, have proven to be very effective in the application of real structures and have been widely used on flexible bridge structures. However, very few studies were reported on buildings especially those with medium-rise characteristics which are often associated with complicated initial modelling and different degrees of parameter uncertainties. In addition, even-though a handful of studies has been done on manual model updating for bridge structures, not much research has taken into account the influence of external structural components on manual model updating process. To address these issues, two case studies with real structures are established in this research. One is conducted with a 10-story concrete building to demonstrate the importance of having sufficiently detailed initial FEMs in automated model updating of medium-rise buildings and effective use of boundary limits and parameter groups to maintain the physical relevance of the updated FEMs. Other is an investigation with a single span inflexible foot bridge to highlight the necessity to consider external structural components in manual model updating of inflexible structures. Both studies employ actual ambient vibration monitoring data obtained from the test structures for the model updating processes.

Probabilistic Assessment of High-Throughput Wireless Sensor Networks.

Structural health monitoring (SHM) using wireless smart sensors (WSS) has the potential to provide rich information on the state of a structure. However, because of their distributed nature, maintaining highly robust and reliable networks can be challenging. Assessing WSS network communication quality before and after finalizing a deployment is critical to achieve a successful WSS network for SHM purposes. Early studies on WSS network reliability mostly used temporal signal indicators, composed of a smaller number of packets, to assess the network reliability. However, because the WSS networks for SHM purpose often require high data throughput, i.e., a larger number of packets are delivered within the communication, such an approach is not sufficient. Instead, in this study, a model that can assess, probabilistically, the long-term performance of the network is proposed. The proposed model is based on readily-available measured data sets that represent communication quality during high-throughput data transfer. Then, an empirical limit-state function is determined, which is further used to estimate the probability of network communication failure. Monte Carlo simulation is adopted in this paper and applied to a small and a full-bridge wireless networks. By performing the proposed analysis in complex sensor networks, an optimized sensor topology can be achieved.

A Novel Wireless Accelerometer Board for Measuring Low-Frequency and Low-Amplitude Structural Vibration

Structural health monitoring (SHM) plays an important role in maintaining system integrity of aging structures and machinery parts. Microelectromechanical system (MEMS) accelerometers, because of their low cost and small dimensions, have emerged as attractive sensing tools for monitoring structural condition based on changes in structural vibration characteristics. For SHM applications, these sensors need to detect low-amplitude and low-frequency vibrations (microvibrations). Those are not always feasible with the conventional low-cost digital sensor boards. In this paper, a novel accelerometer board, named acceleration evaluator (ALE), is developed to achieve more accurate wireless vibration measurements using the full bandwidth of the installed MEMS accelerometer by a voltage-to-frequency converter, instead of the conventional analog-to-digital converter. The effectiveness of the prototype is evaluated through laboratory tests, demonstrating its measurement accuracy comparable to that of wire-based integral electronics piezoelectric accelerometers. Furthermore, ALE performance for SHM purposes is validated by carrying out shaking table tests on the real-size model of a stone pinnacle of the Washington D.C. National Cathedral.