Monitoring the performance and estimating the remaining useful life of aging civil infrastructure in the United States has been identified as a major objective in the civil engineering community. Structural health monitoring has emerged as a central tool to fulfill this objective. This paper presents a review of the major structural monitoring programs that have been recently implemented in the United States, focusing on the integrity and performance assessment of large-scale structural systems. Applications where response data from a monitoring program have been used to detect and correct structural deficiencies are highlighted. These applications include (but are not limited to): i) Post-earthquake damage assessment of buildings and bridges; ii) Monitoring of cables vibration in cable-stayed bridges; iii) Evaluation of the effectiveness of technologies for retrofit and seismic protection, such as base isolation systems; and iv) Structural damage assessment of bridges after impact loads resulting from ship collisions. These and many other applications show that a structural health monitoring program is a powerful tool for structural damage and condition assessment, that can be used as part of a comprehensive decision-making process about possible actions that can be undertaken in a large-scale civil infrastructure system after potentially damaging events.
Structural control systems can effectively protect structures from dynamic loads. Passive control systems are widely accepted, but active and hybrid systems remain under development with a variety of implementation related issues yet to be resolved. The current research focuses on overcoming some of these problems. A hybrid sliding isolation system is considered. This nonlinear controller is ideal for examining many practical issues; moreover, results obtained with this system may be applied to a variety of active and hybrid controllers. New nonlinear control algorithms, which account for implementation imperfections, are developed and validated with realistic experimental models. The results show that the control system is able to significantly reduce the peak responses and the energy input, proving that many of the implementation issues may be overcome with well designed controllers and current technology. © 1997 Published by Elsevier Science Ltd.
This paper presents a nonlinearly parameterized controller for the adaptive control of base-isolated buildings subjected to a set of near-fault earthquakes. The control scheme is based on discrete direct adaptive control, wherein the system response is minimized under parameter uncertainties. Stable tuning laws for the controller parameters are derived using the Lyapunov approach. The controller utilizes a linear combination of nonlinear basis functions, and estimates the desired control force online. The measurements that are necessary to generate the control force to reduce the system responses under earthquake excitations are developed based on the adaptive systems theory. The main novelty in this paper is to approximate the nonlinear control law using a nonlinearly parameterized neural network, without an explicit training phase. A perturbed model is used to initialize the controller parameters in order to simulate the uncertainty in the mathematical modeling that typically exists in representing civil structures. Performance of the proposed control scheme is evaluated on a full-scale nonlinear three-dimensional (3-D) base-isolated benchmark structure. The lateral-torsion superstructure behavior and the bi-axial interaction of the nonlinear bearings are incorporated. The results show that the proposed controller scheme can achieve good response reductions for a wide range of near-fault earthquakes, without a corresponding increase in the superstructure response. Copyright © 2011 John Wiley & Sons, Ltd.
Tracking control of systems with variable stiffness hysteresis using a gain-scheduled (GS) controller is developed in this paper. Variable stiffness hysteretic system is represented as quasi linear parameter dependent system with known bounds on parameters. Assuming that the parameters can be measured or estimated in real-time, a GS controller that ensures the performance and the stability of the closed-loop system over the entire range of parameter variation is designed. The proposed method is implemented on a spring-mass system which consists of a semi-active independently variable stiffness (SAIVS) device that exhibits hysteresis and precisely controllable stiffness change in real-time. The SAIVS system with variable stiffness hysteresis is represented as quasi linear parameter varying (LPV) system with two parameters: linear time-varying stiffness (parameter with slow variation rate) and stiffness of the friction-hysteresis (parameter with high variation rate). The proposed LPV-GS controller can accommodate both slow and fast varying parameter, which was not possible with the controllers proposed in the prior studies. Effectiveness of the proposed controller is demonstrated by comparing the results with a fixed robust <TEX>$\mathcal{H}_{\infty}$</TEX> controller that assumes the parameter variation as an uncertainty. Superior performance of the LPV-GS over the robust <TEX>$\mathcal{H}_{\infty}$</TEX> controller is demonstrated for varying stiffness hysteresis of SAIVS device and for different ranges of tracking displacements. The LPV-GS controller is capable of adapting to any parameter changes whereas the <TEX>$\mathcal{H}_{\infty}$</TEX> controller is effective only when the system parameters are in the vicinity of the nominal plant parameters for which the controller is designed. The robust <TEX>$\mathcal{H}_{\infty}$</TEX> controller becomes unstable under large parameter variations but the LPV-GS will ensure stability and guarantee the desired closed-loop performance.
The effectiveness of multiwalled carbon nanotubes (MWCNTs) as strain sensors is investigated. The key contribution of this paper is the study of real-time strain response at the macroscale of MWCNT film under tensile load. In addition, real-time voltage change as a function of temperature is examined. MWCNT films attached to a brass specimen by epoxy using vacuum bonding have been studied. The brass specimen is subjected to tensile loading, and voltage output from the MWCNT film is obtained using a four-point probe and a sensitive voltage measurement device. Experimental results show that there is a linear change in voltage across the film when subjected to tension, and the MWCNT film both fully recovers its unstressed state upon unloading and exhibits stable electromechanical properties. The effect of temperature on the voltage output of the nanotube film under no load condition is investigated. From the results obtained it is evident that MWCNT films exhibit a stable and predictable voltage response as a function of temperature. An increase in temperature leads to an increase in conductivity of the nanotube film. The study of MWCNT film for real-time strain sensing at the macroscale is very promising, and the effect of temperature on MWCNT film (with no load) can be reliably predicted.
Structural health monitoring (SHM) is a necessity for reliable and efficient functioning of engineering systems. Damage detection (DD) is a crucial component of any SHM system. Lamb waves are a popular means to DD owing to their sensitivity to small damages over a substantial length. This typically involves an active sensing paradigm in a pitch-catch setting, that involves two piezo-sensors, a transmitter and a receiver. In this paper, we propose a data-intensive DD approach for beam structures using high frequency signals acquired from beams in a pitch-catch setting. The key idea is to develop a statistical learning-based approach, that harnesses the inherent sparsity in the problem. The proposed approach performs damage detection, localization in beams. In addition, quantification is possible too with prior calibration. We demonstrate numerically that the proposed approach achieves 100% accuracy in detection and localization even with a signal to noise ratio of 25 dB.
Effect of passive vibration isolation heavily depends on force–displacement characteristic of the isolation system. In view of this dependence, this paper investigates the influence of negative stiffness device (NSD) on the effect of vibration isolation system. Detailed evaluation of transmissibility is performed. The critical parameters are identified. It is found that with NSD, significant vibration reduction for both absolute and relative displacement transmissibility is obtained. A modified Lindstedt–Poincaré method (modified L–P method) is used to obtain analytical periodic solutions for the approximated piecewise linear dynamic system. The analytical limit cycles by the modified L–P solution agree satisfactorily with the ones by numerical simulation. The most important finding of this study is that larger damping in a system with NSD helps in reducing transmissibility, thus increasing the efficacy of the isolation system; this is in contrast to other conventional isolation systems, wherein increased structural damping decreases the efficacy of vibration control in the frequency range of interest. It is worth noting that this finding of NSD enhancing the structural damping is consistent with earliest studies by senior author and collaborators.
Strain sensing characteristic of carbon nanotubes has been established in the past at nanoscale. In this study, it is shown that the carbon nanotube film sensors, made up of randomly oriented carbon nanotubes, can be used as strain sensors at macro level. A nearly linear trend between the change in voltage, measured using a movable four point probe, and strains, measured using conventional electrical strain gage, indicates the potential of such carbon nanotube films for measuring flexural strains at macro level. Isotropic strain sensing capability of the carbon nanotube film sensors, due to randomly oriented carbon nanotubes, allows multidirectional and multi‐location measurements.
A characteristic property of semiconducting single-wall carbon nanotubes (SWCNTs) is distinct near-infrared photoluminescence following excitation by visible light. Theory and experiment show that these optical emission peaks shift predictably in wavelength as nanotubes are compressed or stretched along their axis. We are exploiting this effect in a powerful new method intended for measuring mechanical strain in critical infrastructure components such as airframes, pressurized vessels, pipelines, support beams, etc. The method involves applying a dilute dispersion of nanotubes in a polymeric host onto the surface of the specimen to form a sub-micron thick film in which SWCNTs act as strain sensors. This layer is overcoated with a transparent protective top coat such as a polyurethane varnish. Subsequent strains in the substrate are transmitted to the nanotubes by load transfer. The substrate strain magnitude and direction are then measured by illuminating the surface at any point of interest with a small visible laser beam and spectrally analyzing the resulting near-IR nanotube emission. Single-point measurements currently provide strain magnitude resolution of ca. 100 microstrain, strain angle resolution of ca. 5 degrees, and spatial resolution of ca. 50 mm. Each reading takes less than one second, allowing compilation of strain maps from scanned data. In contrast to digital image correlation, which is currently the only commercial non-contact strain technology, the new method can measure strains induced when the specimen is not under observation. It thus has the potential for routine use in industrial structural health monitoring as well as in testing and development laboratories. We will also describe recent progress in adapting the technology to camera-based measurements using spectrally resolved fluorescence imaging.
The rising fossil energy prices and global warming phenomenon is driving researchers to look for alternative renewable and clean energy. Wind energy is considered as one of the most important alternative resources. Considering the space and other public requirements, offshore wind turbine could be larger. Technically, deepwater wind turbines are feasible since long-term viability of floating platforms has already been successfully demonstrated by the offshore oil and gas industries over decades. However, there are certain vibration issues which require critical attention for designing floating wind turbines. Flow-induced vibrations is the most important design criteria for most offshore structures and will also be important for floating wind turbines. Both the main structural elements as well as supporting structural members must be designed to withstand such oscillations. In addition to inline vibrations, the flow induced vibrations are known to initiate oscillations in a direction transverse to the general direction of motion. Most of the previous research has been concentrated on flap-wise vibration of wind turbine. This paper investigates the use of semi-active tuned mass dampers (STMDs) in controlling the edgewise vibration and the stability of floating wind turbines modeled as discrete dynamical systems in the blade rotation plane. Morison's equation is used to represent the interaction between the flow field and the offshore platform supporting the wind turbine. Numerical simulations prove that STMD has higher vibration reduction efficiency than TMD in the edge-wise blade direction under either steady or turbulent wind load, even with parameter changes such as rotation speed, nacelle stiffness loss and blade stiffness loss.
