Showing papers in "Structural Control & Health Monitoring in 2017"

Concrete dam deformation prediction model for health monitoring based on extreme learning machine

Abstract: Summary Structural health monitoring via quantities that can reflect behaviors of concrete dams, like horizontal and vertical displacements, rotations, stresses and strains, seepage, and so forth, is an important method to evaluate operational states of concrete dams correctly and predict the future structural behaviors accurately. Traditionally, statistical model is widely applied in practical engineering for structural health monitoring. In this paper, an extreme learning machine (ELM)-based health monitoring model is proposed for displacement prediction of gravity dams. ELM is one type of feedforward neural networks with a single layer of hidden nodes, where the weights connecting inputs to hidden nodes are randomly assigned. The model can produce good generalization performance and learns faster than networks trained using the back propagation algorithm. The advantages such as easy operating, high prediction accuracy, and fast training speed of the ELM health monitoring model are verified by monitoring data of a real concrete dam. Results are also compared with that of the back propagation neural networks, multiple linear regression, and stepwise regression models for dam health monitoring.

Completely contactless structural health monitoring of real‐life structures using cameras and computer vision

Abstract: Summary A newly developed, completely contactless structural health monitoring system framework based on the use of regular cameras and computer vision techniques is introduced for obtaining displacements and vibrations of structures, which are critical responses for performance-based design and evaluation of structures. To provide contactless and practical monitoring, the current vision-based displacement measurement methods are improved by eliminating the physical target attachment. This is achieved by means of utilizing imaging key-points as virtual targets. As a result, pixel-based displacements of a monitored structural location are determined by using an improved detection and match key-points algorithm, in which false matches are identified and discarded almost completely. To transform pixel-based displacements to engineering units, a practical camera calibration method is developed because calibration standard on a physical target no longer exists. Moreover, a framework for evaluating the accuracy of vision-based displacement measurements is established for the first time, which, in return, provides users with the most crucial information of a measurement. The proposed framework along with a conventional sensor network and a data acquisition system are applied and verified on a real-life stadium during football games for structural assessment. The results obtained by the new method are successfully validated with the data acquired from sensors such as linear variable differential transformers and accelerometers. Because the proposed method does not require any type of sensor and target attachment, common field works such as sensor installation, wiring, maintaining conventional data acquisition systems are not required. This advantage enables an inexpensive and practical way for structural assessment, especially for real-life structures. Copyright © 2016 John Wiley & Sons, Ltd.

Automated modal identification and tracking: Application to an iron arch bridge

Abstract: Copyright © 2016 John Wiley & Sons, Ltd. Challenges concerning the automation of modal identification and tracking procedures in permanent monitoring systems for Structural Health Monitoring purposes are discussed. In this context, an automated procedure based on parametric identification methods that involve the interpretation of stabilization diagrams is proposed. The methodology comprehends two key points: (i) automatic analysis of stabilization diagrams, performed through a first check of reasonable damping ratio, a subsequent modal complexity check and a final clustering of structural modes; (ii) automated tracking of the evolution in time of the identified modal properties. The proposed modal clustering and tracking steps exploit the introduction of self-adaptable dynamic thresholds, that do not require any a priori manual tuning for the different recorded data set. Finally, the proposed approach was successfully validated using real data collected on a historic iron arch bridge. Copyright © 2016 John Wiley & Sons, Ltd.

Assessing the effect of nonlinearities on the performance of a tuned inerter damper

Abstract: Summary In this paper, the use of a tuned inerter damper (TID) as a vibration absorber is studied numerically and experimentally, with civil engineering applications in mind. Inerters complete the analogy between mechanical and electrical networks, as the mechanical element equivalent to a capacitor and were developed in the 2000s. Initially, inerters were used for applications in automotive engineering, where they are known as J-dampers. Recently, research has suggested that inerter-based networks could be used for civil engineering applications, offering interesting advantages over traditional tuned mass dampers. In the civil engineering context, research has been mainly theoretical, considering ideal inerters. Because the dynamics of an inerter device include nonlinearities, especially at the low frequencies associated with civil engineering applications, the performance of the TID device using an off-the-shelf inerter has been experimentally tested in the work presented here. The chosen system, comprising a host structure with a TID attached to it, was tested using real-time dynamic substructuring (RTDS) or hybrid testing. The inerter was tested physically, while the remaining components of the TID device, the spring and damper, together with the host structure, were simulated numerically. Displacements and forces at the interface between numerical and physical components are updated in real time. This numerical–physical split allows the optimisation of the TID parameters, because the values of the spring and the damper can be changed without altering the experimental setup. In addition, this configuration takes into account the inerter's potentially complex dynamics by testing it experimentally, together with the characteristics of the host structure. Developing RTDS tests for physical inertial substructures, where part of the fed back interface forces are proportional to acceleration, is a challenging task because of delays arising at the interface between the experimental and the numerical substructures. Problems associated with stability issues caused by delay and causality arise, because we are dealing with neutral and advanced delayed differential equations. A new approach for the substructuring algorithm is proposed, consisting of feeding back the measured force deviation from the ideal inerter instead of the actual force at the interface. The experimental results show that with appropriate retuning of the components in the TID device, the performance in the TID incorporating the real inerter device is close to the ideal inerter device. © 2016 The Authors. Structural Control and Health Monitoring published by John Wiley & Sons, Ltd.

Modeling and harnessing sparse and low‐rank data structure: a new paradigm for structural dynamics, identification, damage detection, and health monitoring

Abstract: This paper presents a new paradigm of explicitly modeling and harnessing the data structure to address the inverse problems in structural dynamics, identification, and data-driven health monitoring. In particular, it is shown that the structural dynamic features and damage information, intrinsic within the structural vibration response measurement data, possesses sparse and low-rank structure, which can be effectively modeled and processed by emerging mathematical tools such as sparse representation and compressed sensing, low-rank matrix decomposition and completion, as well as the unsupervised multivariate blind source separation. It is also discussed that explicitly modeling and harnessing the sparse and low-rank data structure could benefit future work in developing datadriven approaches toward rapid, unsupervised, and effective system identification, damage detection, as well as massive SHM data sensing and management. Copyright © 2016 John Wiley & Sons, Ltd.

Optimal configurations for a linear vibration suppression device in a multi-storey building

Abstract: Summary This paper investigates the use of a two-terminal vibration suppression device in a building. The use of inerter-spring-damper configurations for a multi-storey building structure is considered. The inerter has been used in Formula 1 racing cars and applications to various systems such as road vehicles have been identified. Several devices that incorporate inerter(s), as well as spring(s) and damper(s), have also been identified for vibration suppression of building structures. These include the tuned inerter damper and the tuned viscous mass damper. In this paper, a three-storey building model with a two-terminal absorber located at the bottom subjected to base excitation is studied. The brace stiffness is also taken into consideration. Four optimum absorber layouts, in terms of how spring, damper and inerter components should be arranged, for minimising the maximum relative displacements of the building are obtained with respect to the inerter's size and the brace stiffness. The corresponding parameter values for the optimum absorber layouts are also presented. Furthermore, a real-life earthquake data is used to show the advantage of proposed absorber configurations. Copyright © 2016 John Wiley & Sons, Ltd.

Identification of time-varying cable tension forces based on adaptive sparse time-frequency analysis of cable vibrations

Abstract: For cable bridges, the cable tension force plays a crucial role in their construction, assessment and long-term structural health monitoring. Cable tension forces vary in real time with the change of the moving vehicle loads and environmental effects, and this continual variation in tension force may cause fatigue damage of a cable. Traditional vibration-based cable tension force estimation methods can only obtain the time-averaged cable tension force and not the instantaneous force. This paper proposes a new approach to identify the time-varying cable tension forces of bridges based on an adaptive sparse time-frequency analysis method. This is a recently developed method to estimate the instantaneous frequency by looking for the sparsest time-frequency representation of the signal within the largest possible time-frequency dictionary (i.e. set of expansion functions). In the proposed approach, first, the time-varying modal frequencies are identified from acceleration measurements on the cable, then, the time-varying cable tension is obtained from the relation between this force and the identified frequencies. By considering the integer ratios of the different modal frequencies to the fundamental frequency of the cable, the proposed algorithm is further improved to increase its robustness to measurement noise. A cable experiment is implemented to illustrate the validity of the proposed method. For comparison, the Hilbert–Huang transform is also employed to identify the time-varying frequencies, which are then used to calculate the time-varying cable-tension force. The results show that the adaptive sparse time-frequency analysis method produces more accurate estimates of the time-varying cable tension forces than the Hilbert–Huang transform method.

Inertial mass damper for mitigating cable vibration

Abstract: Summary Stay cables used in cable-stayed bridges are prone to vibration due to their low-inherent damping characteristics. Many methods have been implemented in practice to mitigate such vibration. Recently, negative stiffness dampers have gained attention because of their promising energy dissipation ability. The viscous inertial mass damper (VIMD) has been shown to have properties similar to negative stiffness dampers. This paper examines the potential of the VIMD to enhance the damping, and mitigate the vibration, of stay cables. First, a control-oriented model of the cable is employed to formulate a system level model of the cable–VIMD system for small in-plane motion. After carefully classifying and labeling the mode order, the modal characteristics of the system are analyzed, and the optimal damper parameters for the several lower frequency modes are determined numerically. The results show that the achievable modal damping ratio can be up to nearly an order of magnitude larger than that of the traditional linear viscous damper; note that the optimal parameters of the VIMD are distinct for each mode of interest. These results are further validated through analysis of the cable responses due to the distributed sinusoidal excitation. Finally, a case study is conducted for a cable with a length of 307 m, including the design of practical damper parameters, modal-damping enhancement, and vibration mitigation under wind loads. The results show that the VIMD is a promising practical passive damper that possesses greater energy dissipation capacity than the traditional viscous damper for such cable–damper systems.

Improving performance of a super tall building using a new eddy-current tuned mass damper

Abstract: Summary Two kinds of methods have been primarily used to improve the vibration performance of high-rise buildings. One approach is to enhance the structural lateral stiffness, which may increase the component size and inefficiently use material. The other approach is to employ vibration control devices, such as tuned mass dampers (TMDs), tuned liquid dampers (TLD) and other supplemental damping devices. This latter approach has proved to be quite economical and efficient, and as such, increasingly used in practice. The Shanghai Center Tower (SHC) is a super high-rise landmark building in China, with a height of 632 m. In order to mitigate its vibration during wind storms, a new eddy-current TMD was installed at the 125th floor. Special protective mechanisms were incorporated to prevent excessively large amplitude motion of the TMD under extreme wind or earthquake scenarios. Results of reduced-scale laboratory tests and field tests are presented in this paper to characterize the dynamic properties of the damping device and validate the fidelity of the numerical results. Results of structural analyses indicate that for SHC the eddy-current TMD was able to reduce wind-induced structural acceleration by 45%–60% and earthquake-induced structural displacement by 5%–15%. The installation of the TMD was completed in December 2014, and the performance observed to date is judged to be good. Copyright © 2016 John Wiley & Sons, Ltd.

Optimization design and experimental verification of track nonlinear energy sink for vibration control under seismic excitation

Abstract: Summary Nonlinear energy sinks (NES) are efficient vibration control devices, which have been studied and applied in mechanical, automobile, and aerospace engineering. However, there are few applications in civil engineering. A new type of NES, which is termed as track NES, is proposed in this paper. The optimal mass ratio and track shape expression of NES were determined based on a preliminary optimization design process. To verify its vibration control effects on building structures, a series of shake table tests were conducted on a five-story steel frame. Tracks of the NES were installed at the roof of the frame with rigid connections and the mass of the NES was constrained to slide along the track by using wheels. Five earthquake waves with different frequency spectrums were selected to excite the frame coupled with NES under minor, moderate, and major levels. Accelerations and displacements on each story of the frame were measured, recorded, and evaluated. The experimental results demonstrate that with small mass ratio (2%) of main structure, NES has good performance in reducing the dynamic responses of the frame under seismic excitations. The reduction ratio for peak response is up to 50%, while for root mean square response is up to 80%. NES also exhibits wide-band frequency vibration controlling attributes, and the responses of the frame are reduced in multiple vibration modes. In addition, the vibration reduction capability of the NES with steel wheels and that with rubber wheels are compared, and it is verified that different damping of NES makes a difference to the vibration control effects. The displacement reduction performance is not sensitive to the damping factor of the NES, but acceleration response is highly affected by the damping feature of the NES.

Damage detection under varying temperature using artificial neural networks

Abstract: Summary To avoid false alarms for vibration-based structural damage detection methods, temperature effects on damage-sensitive features should be eliminated. In this paper, a novel two-step damage identification method combining a multilayer neural network and novelty detection is developed to differentiate the changes in natural frequencies (one of the most commonly used damage features that can be obtained reliably and relatively easily) due to damage from those induced by temperature variations. In the first step, a multilayer artificial neural network, which resembles an auto-associative neural network but uses temperature variables in addition to the frequencies as the inputs, is explored to identify patterns in frequencies of undamaged structures under varying temperatures. Euclidean distance is then utilized as a novelty index to quantify the discordancy between patterns in undamaged cases and candidate cases. Numerical studies using a simply supported beam and finite element models based on an experimental grid structure, which simulate different levels of stiffness reductions under varying temperature conditions, are used to verify the detectability and robustness of the proposed approach. It is shown that the incorporation of the proposed artificial neural network with novelty detection enables one to robustly distinguish damage occurrence and severity regardless of temperature variations and noise perturbations. Using an unsupervised learning scheme, the proposed approach transforms a multivariate analysis using modal frequencies and temperature data into a straightforward univariate discordancy test using the novelty index. Given these competitive advantages, this approach is very attractive for the development of an automated continuous monitoring system in practical applications.

Railroad bridge monitoring using wireless smart sensors

Abstract: Summary Railroads carry more than 40% of the freight, in terms of tons per mile transported in North America. A critical portion of the railroad infrastructure is the more than 100,000 bridges, which occur, on the average, every 1.4 miles of track. Railroads have a limited budget for capital investment. Therefore, decisions on which bridges to repair/replace become critical for both safety and economy. North American railroads regularly inspected bridges to ensure safe operation that can meet transport demands, using inspection reports to decide which bridges may need maintenance, replacement, or further investigation. Current bridge inspection practices recommend observing bridge responses under live load to help assess bridge condition. However, measuring bridge responses under train loads in the field is a challenging, expensive, and complex task. This research explores the potential of using wireless smart sensors (WSS) to measure bridge responses under revenue service traffic that can be used to inform bridge management decisions. Wireless strain gages installed on the rail measure real-time train loads. Wireless accelerometers and magnetic strain gages installed in the bridge measure associated bridge responses. The system is deployed and validated on a double-track steel truss bridge on the south side of Chicago, Illinois, owned by the Canadian National Railway. A calibrated finite element model of the bridge with known train input load estimated the responses of the bridge at arbitrary, unmeasured locations, showing the possibility of applying the system for decision making process. These results demonstrate the potential of WSS technology to assist with railroad bridge inspection and management practice. Copyright © 2016 John Wiley & Sons, Ltd.

Early detection of anomalies in dam performance: A methodology based on boosted regression trees

Abstract: Summary The advances in information and communication technologies led to a general trend towards the availability of more detailed information on dam behaviour. This allows applying advanced data-based algorithms in its analysis, which has been reflected in an increasing interest in the field. However, most of the related literature is limited to the evaluation of model prediction accuracy, whereas the ulterior objective of data analysis is dam safety assessment. In this work, a machine-learning algorithm (boosted regression trees) is the core of a methodology for early detection of anomalies. It also includes a criterion to determine whether certain discrepancy between predictions and observations is normal, a procedure to compute a realistic estimate of the model accuracy, and an original approach to identify extraordinary load combinations. The performance of causal and noncausal models is assessed in terms of their ability to detect different types of anomalies, which were artificially introduced on reference time series generated with a numerical model of a 100-m-high arch dam. The final approach was implemented in an online application to visualise the results in an intuitive way to support decision making.

Guided waves for damage identification in pipeline structures: A review

Abstract: Summary Guided waves find their niche in cost-effective damage identification in comparison with conventional nondestructive evaluation. Comprehensive research has been conducted since the 1980s, focusing on the detection of a wide variety of types of damage in metallic and composite structures. The main scope of this paper is to present a review of state-of-the-art guided wave-based approaches for damage identification in pipeline structures. Theoretical analyses of the interaction between linear and nonlinear guided waves and damage are addressed in detail. Numerical simulations and experimental studies of damage identification in pipeline structures using both linear and nonlinear guided waves are elaborated. Other issues including bends in pipes, effects of environmental and operational conditions on the performance of guided waves are another focus of this review. Future challenge in this field is summarised at the end of this review.

Impact load identification for composite structures using Bayesian regularization and unscented Kalman filter

Abstract: Summary In structural health monitoring of composite structures, one important task is to detect and identify the low-velocity impact events, which may cause invisible internal damages. This paper presents a novel approach for simultaneously identifying the impact location and reconstructing the impact force time history acting on a composite structure using dynamic measurements recorded by a sensor network. The proposed approach consists of two parts: (1) an inner loop to reconstruct the impact force time history and (2) an outer loop to search for the impact location. In the inner loop, a newly developed inverse analysis method with Bayesian inference regularization is employed to solve the ill-posed impact force reconstruction problem using a state-space model. In the outer loop, a nonlinear unscented Kalman filter (UKF) method is used to recursively estimate the impact location by minimizing the error between the measurements and the predicted responses. The newly proposed impact load identification approach is illustrated by numerical examples performed on a composite plate. Results have demonstrated the effectiveness and applicability of the proposed approach to impact load identification. Copyright © 2016 John Wiley & Sons, Ltd.

Structural time-dependent reliability assessment of the vibration active control system with unknown-but-bounded uncertainties

Abstract: Summary The active control system for structural vibration is extremely sensitive to the parametric uncertainty so that more and more concerns of its reliability estimation have been given recently. In view of the insufficiency of the uncertainty information in practical engineering, a non-probabilistic time-dependent reliability method that combines the active vibration control theory with interval analysis is proposed in this paper to effectively estimate the dynamic safety of the controlled structures, in which circumstances the unknown-but-bounded uncertainties in structural parameters are considered. The uncertain structural responses based on the closed-loop control are firstly analyzed and embodied by the interval process model. By virtue of the first-passage theory, an integral procedure of non-probabilistic time-dependent reliability analysis of the active control system for structural vibration is then conducted. Two engineering examples and one experimental application are eventually presented to demonstrate the validity and applicability of the methodology developed.

Experimental studies on the effectiveness and robustness of a pounding tuned mass damper for vibration suppression of a submerged cylindrical pipe

Abstract: Summary Pounding tuned mass damper (PTMD) is a novel type of passive damper. The PTMD utilizes collisions or impacts of a tuned mass with viscoelastic materials to efficiently dissipate the vibration energy of primary structures. The previous studies have verified its effective damping performance on a full-scale subsea jumper and other structures in air. This paper presents the first-ever experimental verification of a submerged PTMD system for vibration control of pipelike structures underwater. To facilitate the experimental studies, a vertical vibration system consisting of 4 springs and a cylindrical steel pipe was designed and set up in a water tank. Furthermore, a numerical method considering the effect of the added mass is described to estimate the natural frequencies of a submerged cylindrical pipe. Therefore, experimental results demonstrate that the PTMD system is effective and efficient to suppress the forced vibrations of the submerged cylindrical pipe at the tuned frequency and is also robust over a range of detuning frequencies.

Experimental damage evaluation of open and fatigue cracks of multi‐cracked beams by using wavelet transform of static response via image analysis

Abstract: Summary In this study, a method for crack detection and quantification in beams based on wavelet analysis is presented. The static deflection is measured at particular points along the length of (i) real damaged structures, using few displacement transducers and a laser sensor, and (ii) simulated structures, using closed-form analysis, for a given location of a concentrated load along the beam. Furthermore, the measurement of the beam displacements in a large number of spatially distributed points is made by processing digital photographs of the beam. The smoothed deflection responses of the cracked beams are then analyzed using the wavelet transform. For this purpose, a Gaus2 wavelet with two vanishing moments is utilized. The wavelet transform spikes are used as indicators to locate and quantify the damage; furthermore, the multi-scale theory of wavelet is employed, in order to eliminate or at least reduce the spurious peaks and enhance the true ones. Simply supported beams with single and double cracks are used to demonstrate the devised methodology. Open and fatigue cracks of different sizes and locations have been used in the examples. In a closed-form analysis, the damage is modeled as a bilinear rotational spring with reduced stiffness in the neighborhood of the crack location. Damage calibration of simply supported steel beams with open and fatigue cracks has been carried out experimentally using this technique. A generalized curve has been proposed to quantify the damage in a simply supported beam. Based on the experimental study, the spatial wavelet transform is proven to be effective to identify the damage zone even when the crack depth is around 3% of the height of the beam. Copyright © 2016 John Wiley & Sons, Ltd.

Vibration-based bridge scour detection: A review

Abstract: Summary Scour around bridge foundations is regarded as one of the predominant causes of bridge failures. Traditional methods primarily employ underwater instruments to detect bridge scour depths, which thus have difficulties in instrument installations and operations. The concept of scour detection derived from vibration-based damage detection has been explored in recent years to address such difficulties by investigating the natural frequency spectrum of a bridge or a bridge component. This paper presents a comprehensive review of existing studies on scour detection using the natural frequency spectrum of a bridge or a bridge component. Underlying mechanisms, laboratory and field tests, numerical studies, and data processing schemes are reviewed to summarize the state of the art, which are absent but urgently needed. Updates on recently developed scour monitoring sensors are also provided to complement the introduction. Based on the review, in-depth discussions in existing studies are made regarding a few controversial and unsolved issues to shed light on future research, highlighting issues such as the soil–structure interaction, locations of the sensor installation, and the influence of shapes of scour holes.

Monitoring bolt tightness of rail joints using axle box acceleration measurements

Abstract: Rail joints are a weak component in railway tracks because of the large impact and wheel-rail contact forces. Every train passage contributes to the deterioration of rail joints, causing visible (e.g. battered rails) and invisible (e.g. loose bolts) damages. The invisible damage cannot be detected by the commonly performed visual inspection, which is labor intensive, unreliable, intrusive and unsafe. In this paper, a vehicle-borne monitoring system is used to automatically detect and assess the tightness condition of bolts at rail joints. The monitoring method is developed based on field Axle Box Acceleration (ABA) measurements using different bolt tightness conditions. The suitability of the method is assessed by bolt tightness prediction and verification of a set of rail joints in the tram network of Sheffield, United Kingdom. The results show that ABA system can be employed to monitor bolt tightness conditions at rail joints.With this information better planning for selective preventive maintenance actions can be taken over rail joints.

A passive electromagnetic eddy current friction damper (PEMECFD): Theoretical and analytical modeling

Abstract: Summary The focus of this paper is on analytical modeling of a novel type of passive friction damper for seismic hazard mitigation of structures. The proposed seismic damping device, which is termed as passive electromagnetic eddy current friction damper, utilizes a solid-friction mechanism in parallel with an eddy current damping mechanism to maximize the dissipation of input seismic energy through a smooth sliding in the damper. In this passive damper, friction force is produced through magnetic repulsive action between two permanent magnetic sources magnetized in the direction normal to the friction surface, and the eddy current damping force is generated because of the motion of the permanent magnetic sources in the vicinity of a conductor. The friction and eddy current damping parts are able to individually produce ideal rectangular and elliptical hysteresis loops, respectively; which, when combined in the proposed device, are able to accomplish a higher input seismic energy dissipation than that only by the friction mechanism. This damper is implemented on a two-degree-of-freedom system to demonstrate its capability in reducing seismic responses of frame building structures. The numerical results show that the seismic performance of the proposed damper is comparable with that of passive magnetorheological damper of the same force capacity. However, the cost of the device is likely to be quite lesser than that of a magnetorheological damper.

Dynamic investigation of a large historical cathedral

Abstract: Summary The presented research aimed at studying the dynamic behavior of Mallorca cathedral (Mallorca Island, Spain) under ambient sources of vibration and seismic events. The cathedral is one of the greatest built masonry structures worldwide. It is characterized for its audacious dimensions and slender structural members. Because of it, the study of its dynamic behavior is a clear concern. The cathedral dynamic properties were firstly identified using ambient vibration testing. Afterwards, a dynamic monitoring system was implemented to continuously measure, record, and wirelessly transfer the acceleration records without having to set up an activating threshold. This monitoring type was implemented because of the low seismic intensity of Mallorca Island with a basic ground acceleration of only 0.04 g according to the Spanish seismic standard. The continuous monitoring allowed for capturing some seismic events and some drops in the natural frequencies were noticed because of a breathing crack effect. Using both ambient vibration testing and continuous monitoring system, global modes could be more accurately identified than more local ones. The identification of the global modes was more attainable than in the case of more local ones. The temperature was a more influential environmental parameter than humidity and wind for all of the identified modes except for one more directly depended on wind. Copyright © 2016 John Wiley & Sons, Ltd.

Robust data transmission and recovery of images by compressed sensing for structural health diagnosis

Abstract: Summary Digital cameras are cost-effective vision sensors and able to directly provide two-dimensional information of structural condition in monitoring and assessment applications. For example, digital cameras are essential components of unmanned aerial vehicles (UAVs) and robotic agents for mobile sensing and inspection of pipelines, buildings, transportation infrastructure, etc, especially in post-natural disaster and man-made extreme events assessment. Additionally, while surveillance cameras have been widely used for transportation systems (e.g., traffic monitoring), if appropriately mounted on the large-scale structures such as the bridges, they can continuously monitor the structural condition under operational loads and hazards, complementing the regular visual inspection and assessment conducted by experts. In these or other applications, efficiently and reliably transferring the structural images or videos, which are as such large-scale, are important and challenging, especially in wireless platform that is either required (e.g., UAVs and robotic agents) or more suitable (e.g., camera monitoring networks) with only limited power and communication resources. This paper studies the computational algorithms for efficient and reliable transmission of the structural monitoring images; in particular, the compressed sensing (CS) technique is explored for robust data transmission and recovery. The sparse representation or data structure of the structural images is exploited, leading to the CS based central strategy: on some sparse domain, randomly encode large-scale image data into few relevant coefficients, which are then transferred (robust to random data loss) and recovered (in base station) for subsequent structural health diagnosis. Image data of bench scale pipe structure, concrete structure and full scale stay cable are employed for validation of the CS based method. Its performance is also compared with traditional transform coding and low-dimensional encoding (sampling), and their advantages and drawbacks are discussed. Copyright © 2016 John Wiley & Sons, Ltd.

Seismic performance of a damping outrigger system for tall buildings

Abstract: Summary A novel damping outrigger system is proposed for tall buildings by replacing the diagonal members with buckling restrained bracings. To investigate the conceptual design of the system, a simplified mechanical model for the outrigger system is first put forward in this paper. Four configurations of outriggers, which are commonly used in practical engineering, are compared from the aspects of stiffness, strength, and energy-dissipating capacity. The damping outriggers of the best configuration with buckling restrained braces acting as diagonal web members of outriggers are then proposed. The effect of the system on the whole structure is demonstrated through a 632-m-tall building. The results indicate that the damping outrigger can serve as stiffness member under the frequently occurred earthquakes and energy dissipating member under the rarely occurred earthquakes to protect the main structure from severe damages. Copyright © 2016 John Wiley & Sons, Ltd.

Bayesian model updating of a full-scale finite element model with sensitivity-based clustering

Abstract: Summary Model updating based on vibration response measurements is a technique for reducing inherent modeling errors in finite element (FE) models that arise from simplifications, idealized connections, and uncertainties with regard to material properties. Updated FE models, which have relatively fewer discrepancies with their real structural counterparts, provide more in-depth predictions of the dynamic behaviors of those structures for future analysis. In this study, we develop a full-scale FE model of a major long-span bridge and update the model to improve an agreement between the identified modal properties of the real measured data and those from the FE model using a Bayesian model updating scheme. Sensitivity-based cluster analysis is performed to determine robust and efficient updating parameters, which include physical parameters having similar effects on targeted natural frequencies. The hybrid Monte Carlo method, one of the Markov chain Monte Carlo sampling methods, is used to obtain the posterior probability distributions of the updating parameters. Finally, the uncertainties of the updated parameters and the variability of the FE model's modal properties are evaluated.

Nonlinear imaging of damage in composite structures using sparse ultrasonic sensor arrays

Abstract: In different engineering fields, there is a strong demand for diagnostic methods able to provide detailed information on material defects. Low velocity impact damage can considerably degrade the integrity of structural components and, if not detected, can result in catastrophic failures. This paper presents a nonlinear structural health monitoring imaging method, based on nonlinear elastic wave spectroscopy, for the detection and localisation of nonlinear signatures on a damaged composite structure. The proposed technique relies on the bispectral analysis of ultrasonic waveforms originated by a harmonic excitation and it allows for the evaluation of second order material nonlinearities due to the presence of cracks and delaminations. This nonlinear imaging technique was combined with a radial basis function approach in order to achieve an effective visualisation of the damage over the panel using only a limited number of acquisition points. The robustness of bispectral analysis was experimentally demonstrated on a damaged carbon fibre reinforced plastic (CFRP) composite panel, and the nonlinear source's location was obtained with a high level of accuracy. Unlike other ultrasonic imaging methods for damage detection, this methodology does not require any baseline with the undamaged structure for the evaluation of the defect, nor a priori knowledge of the mechanical properties of the specimen.

Transducer placement optimisation scheme for a delay and sum damage detection algorithm

Abstract: Summary In this work, a transducer placement scheme based on wave propagation is proposed, which enhances damage localisation. The method was tailored to seek an optimal transducer network placement for a delay and sum damage detection algorithm. The proposed method determines a coverage index map and utilises a genetic algorithm to determine an optimal transducer network. It can also minimise the impact of faulty transducers, incorporate the effect of stiffeners and different damage types. The method is initially verified using numerically simulated signals. The optimal network outperformed the suboptimal for detection of holes and debonding in a stiffened panel. It is also shown that the coverage index reflected the localisation accuracy. The method is then validated with experimental results and the generated optimal transducer network compared with a suboptimal arrangement. The optimal network is shown to locate an actual crack with significantly higher accuracy than the suboptimal arrangement. © 2016 The Authors. Structural Control and Health Monitoring published by John Wiley & Sons, Ltd.