Institute of Fundamental Technological Research

This paper investigates the problem of parametric identification of highly uncertain bolted connections. The unknown parameters representing stiffness of the connections are estimated using two commonly accepted methods: (1) the traditional mode matching approach and (2) a probabilistic Bayesian framework based on the maximum a posteriori (MAP) formulation. Additionally, the uncertainties of the unknown parameters are also estimated and compared for both methods. A numerical example and a real lab-scale frame structure with highly uncertain bolted connections were used in the tests. In the experimental case, the system eigenvalues (squares of the natural frequencies) and the mode shapes measured in a broad frequency range were employed. The measured mode shapes were strongly disturbed by assembly discrepancies of the bolted connections. Finally, both methods were compared in terms of computational efficiency on a large-scale FE model (31,848 degrees of freedom). Despite the sophistication of the Bayesian approach in treating the trade-off between measurement errors and expected modeling errors, the results indicate that the two tested methods yield similar values for the unknown parameters. The Bayesian approach requires numerical regularization to calculate the parameter covariance matrix, which may decrease its reliability. In contrast, the mode matching method avoids such numerical difficulties. Furthermore, the Bayesian approach requires a much larger number of iterations and a careful selection of the weighting parameters.

Mode matching, Bayesian approach, Parametric identification, Uncertain bolted connections, Parameter uncertainty, Convergence

Nowadays, consumer electronics offer computer-vision-based (CV) measurements of dynamic displacements with some trade-offs between sampling frequency, resolution and low cost of the device. This study considers a consumer-grade smartphone camera based on complementary metal-oxide semiconductor (CMOS) technology and investigates the influence of its hardware limitations on the estimation of dynamic displacements, modal parameters and stiffness parameters of bolted connections in a laboratory structure. An algorithm that maximizes the zero-normalized cross-correlation function is employed to extract the dynamic displacements. The modal parameters are identified with the stochastic subspace identification method. The stiffness parameters are identified using a model-updating technique based on modal sensitivities. The results are compared with the corresponding data obtained with accelerometers and a laser distance sensor. The CV measurement allows lower-order vibration modes to be identified with a systematic (bias) error that is nearly proportional to the vibration frequency: from 2% for the first mode (9.4 Hz) to 10% for the third mode (71.4 Hz). However, the measurement errors introduced by the smartphone camera have a significantly lower influence on the values of the identified stiffness parameters than the numbers of modes and parameters taken into account. This is due to the bias–variance trade-off. The results show that consumer-grade electronics can be used as a low-cost and easy-to-use measurement tool if lower-order modes are required.

computer vision,smartphone camera,system identification,model updating,uncertain bolted connections

Computer vision (CV) methods for measurement of structural vibration are less expensive, and their application is more straightforward than methods based on sensors that measure physical quantities at particular points of a structure. However, CV methods produce significantly more measurement errors. Thus, computer vision-based structural health monitoring (CVSHM) requires appropriate methods of damage assessment that are robust with respect to highly contaminated measurement data. In this paper a complete CVSHM framework is proposed, and three damage assessment methods are tested. The first is the augmented inverse estimate (AIE), proposed by Peng et al. in 2021. This method is designed to work with highly contaminated measurement data, but it fails with a large noise provided by CV measurement. The second method, as proposed in this paper, is based on the AIE, but it introduces a weighting matrix that enhances the conditioning of the problem. The third method, also proposed in this paper, introduces additional constraints in the optimization process; these constraints ensure that the stiff ness of structural elements can only decrease. Both proposed methods perform better than the original AIE. The latter of the two proposed methods gives the best results, and it is robust with respect to the selected coefficients, as required by the algorithm.

computer vision,structural health monitoring,physics-based graphical models,augmented inverse estimate,model updating,non-negative least square method

Structural vibrations have adverse effects and can lead to catastrophic failures. Among various methods for mitigation of vibrations, the semi-active control approaches have the advantage of not requiring a large external power supply. In this paper, we propose and test a sliding mode control method for the semi-active mitigation of vibrations in frame structures. The control forces are generated in a purely dissipative manner by means of on/off type actuators that take the form of controllable structural nodes. These nodes are essentially lockable hinges, modeled as viscous dampers, which are capable of the on/off control of the transmission of bending moments between the adjacent beams. The control aim is formulated in terms of the displacement of a selected degree of freedom. A numerically effective model of such a node is developed, and the proposed control method is verified in a numerical experiment of a four-story shear structure subjected to repeated random seismic excitations. In terms of the root-mean-square displacement, the control reduced the response by 48.4-78.4% on average, depending on the number and placement of the applied actuators. The peak mean amplitude at the first mode of natural vibrations was reduced by as much as 70.6-96.5%. Such efficiency levels confirm that the proposed control method can effectively mitigate vibrations in frame structures.

semi-active control,sliding mode control,structural control,controllable nodes,on/off nodes,damping of vibrations

The area affected by the earthquake is vast and often difficult to entirely cover, and the earthquake itself is a sudden event that causes multiple defects simultaneously, that cannot be effectively traced using traditional, manual methods. This article presents an innovative approach to the problem of detecting damage after sudden events by using interconnected set of deep machine learning models organized in a single pipeline and allowing for easy modification and swapping models seamlessly. Models in the pipeline were trained with a synthetic dataset and were adapted to be further evaluated and used with unmanned aerial vehicles (UAVs) in real-world conditions. Thanks to the methods presented in the article, it is possible to obtain high accuracy in detecting buildings defects, segmenting constructions into their components and estimating their technical condition on the basis of a single drone flight.

Seismic measurements, Safety, Training data, Earthquakes, Computer vision, Machine learning, Autonomous aerial vehicles, Drones, Synthetic data

Although the study of oscillatory motion has a long history, going back four centuries, it is still an active subject of scientific research. In this review paper prospective research directions in the field of mechanical vibrations were pointed out. Four groups of important issues in which advanced research is conducted were discussed. The first are energy harvester devices, thanks to which we can obtain or save significant amounts of energy, and thus reduce the amount of greenhouse gases. The next discussed issue helps in the design of structures using vibrations and describes the algorithms that allow to identify and search for optimal parameters for the devices being developed. The next section describes vibration in multi-body systems and modal analysis, which are key to understanding the phenomena in vibrating machines. The last part describes the properties of granulated materials from which modern, intelligent vacuum-packed particles are made. They are used, for example, as intelligent vibration damping devices.

mechanical vibrations, energy harvesting, modal analysis, granular material

In this study, a novel modal control strategy by means of semi-actively lockable joints is proposed. The control strategy allows for a directed flow of energy between vibrational modes, which makes it suitable not only for vibration attenuation purposes but also for energy scavenging driven by electromechanical energy harvesters. The proposed control strategy is an extension of the prestress-accumulation release (PAR) technique; however, it introduces also new concepts that increase the efficiency of the overall control system. Contrary to the PAR, the proposed method requires measurement of both strains in the vicinity of the semi-active joints and translational velocities that provide global information about system behavior. The latter aspect requires the control system to be organized within a hierarchical feedback architecture. The benefit from this higher complexity of the control system is its better performance compared to the PAR. The proposed semi-active modal control not only attenuates structural vibration faster, but it also achieves this goal with a smaller number of switches implemented in the joints. The effectiveness of the proposed methodology has been demonstrated on structures equipped with two lockable joints. Two practical examples have been investigated: one employs the concept of vibration-based energy harvesting for a two-story frame structure, while the second one reduces vibration of an eight-story frame structure subjected to kinematic excitation.

energy harvesting, lockable joint, modal coupling, semi-active control, vibration attenuation

This paper proposes a computationally effective framework for load‐dependent optimal sensor placement in large‐scale civil engineering structures subjected to moving loads. Two common problems are addressed: selection of modes to be monitored and computational effectiveness. Typical sensor placement methods assume that the set of modes to be monitored is known. In practice, determination of such modes of interest is not straightforward. A practical approach is proposed that facilitates the selection of modes in a quasi‐automatic way based on the structural response at the candidate sensor locations to typical operational loads. The criterion used to assess sensor placement is based on Kammer's Effective Independence (EFI). However, in contrast to typical implementations of EFI, which treat the problem as a computationally demanding discrete problem and use greedy optimization, an approach based on convex relaxation is proposed. A notion of sensor density is applied, which converts the original combinatorial problem into a computationally tractable continuous optimization problem. The proposed framework is tested in application to a real tied‐arch railway bridge located in central Poland.

optimal sensor placement, effective independence method, Fisher information matrix

The main drawback of vibration-based energy harvesting is its poor efficiency due to small amplitudes of vibration and low sensitivity at frequencies far from resonant frequency. The performance of electromagnetic energy harvester can be improved by using mechanical enhancements such as mechanical amplifiers or spring bumpers. The mechanical amplifiers increase range of movement and velocity, improving also significantly harvester efficiency for the same level of excitation. As a result of this amplitude of motion is much larger comparing to the size of the electromagnetic coil. This in turn imposes the need for modelling of electromagnetic circuit parameters as the function of the moving magnet displacement. Moreover, high velocities achieved by the moving magnet reveal nonlinear dynamics in the electromagnetic circuit of the energy harvester. Another source of nonlinearity is the collision effect between magnet and spring bumpers. It has been shown that this effect should be carefully considered during design process of the energy harvesting device. The present paper investigates the influence of the above-mentioned nonlinearities on power level generated by the energy harvester. A rigorous model of the electromagnetic circuit, derived with aid of the Hamilton's principle of the least action, has been proposed. It includes inductance of the electromagnetic coil as the function of the moving magnet position. Additionally, nonlinear behaviour of the overall electromagnetic device has been tested numerically for the case of energy harvester attached to the quarter car model moving on random road profiles. Such a source of excitation provides wide band of excitation frequencies, which occur in variety of real-life applications.

energy harvesting, velocity amplification, nonlinear electromagnetic circuit, spring bumper, quarter car model

This paper describes a semi-active control strategy that allows to transfer the vibration energy from an arbitrarily induced to a selected structural mode. The intended aim of the proposed control strategy is energy harvesting from structural vibrations. Another potential application is related to structural safety. In the paper, a mathematical model is first introduced to describe the phenomenon of vibrational energy transfer, and then, based on this model, an efficient semi-active control strategy is proposed. Finally, some problems related to measurement techniques are discussed. The effectiveness of the proposed methodology is demonstrated in an example of energy transfer between vibrational modes of a three-bar planar frame structure.

vibration energy, modal control, lockable joint, modal coupling

The paper presents application of the MFC actuator and selected control algorithms to the suppression of the composite cantilever beam vibrations. The first part concentrates on the identification of the real structure’s parameters. The numerical model is based on the Euler-Bernoulli beam theory with a nonlinear curvature component. The second part draws on numerical simulations and leads to the identification of optimal control parameters. Finally, the determined parameters are examined in an experimental laboratory system equipped with a DSP controller.

MFC actuator, control algorithm, active beam, DSP controller

A method for a sizing of an electromechanical battery for electrical go-kart was presented in the paper. The main goal of this research was to replace the internal combustion (IC) engine by an electric drive system taking into account the traction properties, on the one hand and the duration of operation on a single charge and the number of the battery life cycles on the other. The proposed method permits an entire depreciation of the price of the vehicle before the degradation of the battery occurs. The results of the study have been used to adjust the source for electric go-karts that will be mass produced.

electrical vehicle, go-kart, optimal battery sizing, traction simulation

W artykule zaprezentowano metodę adaptacji algorytmu sterowania aktuatorem MFC służącym do redukcji drgań nieliniowych belki wysięgnikowej. Zastosowany opis matematyczny regulatora PD zaprojektowano jako strukturę MRAS, a algorytm adaptacji oparty jest o zasadę Lapunowa. Przeprowadzone badania symulacyjne określiły odporność algorytmu na błędy modelowania oraz na występujące w rzeczywistych systemach opóźnienia sprzętowe.

regulacja adaptacyjna, algorytm adaptacji Lapunowa, drgania belki wysięgnikowej, aktuator MFC

Classical approaches to attenuation of vibrations usually aim at dissipation or absorption of the vibration energy in especially designed devices mounted to the structure. A less common approach but recognised as very effective is to induce mechanisms of transferring the vibration energy associated with low-frequency modes into higher-order vibration modes, where it is quickly dissipated by material damping (in structural volume). In the present work, a novel semi-active modal control methodology is proposed for precise control of mechanical energy transfer between vibration modes by means of lockable joints. Moreover, this control strategy is well-suited also for energy harvesting purposes. Energy of the currently induced vibration modes can be transferred into a preselected structural vibration mode that is tuned with an energy harvester. The proposed control strategy is verified numerically, whereas its experimental validation is shown in the accompanying article within the present proceedings.

In this work an experimental study is presented aiming at demonstration of a controlled modal energy transfer concept in frame structures equipped with semi-active members. The proposed semi-active members – lockable joints – allow for local modification of the frame’s stiffness. The objective of the introduced control approach is to provide mechanical energy transfer between particular eigenmodes. A demonstrator has been fabricated for the purpose of the investigation consisting of a double beam frame structure in a cantilever configuration, which is equipped with the semi-active members. The investigated control algorithm employs two types of input signals: local velocity of the structure and local strain of the frame. As a result, a verification of the system effectiveness has been revealed in a variety of frequency ranges. The excitation bandwidth has been appropriately suited to the particular tested cases. The experimentally obtained results confirmed a possibility of the energy transfers between particular structural eigenmodes.

Vibration control is a crucial issue in engineering, necessitating the continuous development and refinement of effective control strategies. In the present study, a semi-active control methodology utilizing lockable joints is investigated. The lockable joints provide a modal coupling effect, resulting in controlled energy transfer between vibration modes. Numerical simulations demonstrate that energy can be transferred to higher-order vibration modes and rapidly dissipated through inherent material damping or transferred to a preselected vibration mode for energy harvesting.

Semi-active modal control, Smart Structures, Lockable joints, Energy transfer, Vibration damping

In this study an experimental program for verification of modal control algorithm for semi-active structures is proposed. The considered control approach assumes redirecting of mechanical energy between vibrational modes. The presented research is focused on development of an investigation method that would allow for demonstrating the control concept. Moreover, a suitable flexible structure equipped with semi-active elements is introduced. The proposed laboratory structure is a flat slender frame equipped with a set of six joints. A deliberate design of the joints provides a feasibility for a controllable transfer of the bending moments between chosen adjacent elements of the frame. Such a structure delivers a possibility of real-time modification of its local bending stiffness and therefore can be categorised as semi-active. The investigation covers identification of the modal parameters of the laboratory model, implementation of the control algorithm on an FPGA processor, providing a testing program that exemplifies the process of energy management between the eigenfrequencies. The results reveal that the response of the semi-active structure reflects the derived control algorithm assumptions. To sum up, the modal control algorithm based on real-time monitoring of the structure's modal parameters is experimentally implemented and verified in a laboratory environment.

vibration control, semi-active, modal control, experimental verification, lockable joints

This contribution presents a sliding-mode control approach for the mitigation of vibrations in frame-like structures. The control is implemented in a semi-active manner, that is, without significant external control forces and substantial power consumption, which are typical for active control approaches. Here, the control is achieved through dynamic, lowcost modification of properties at selected structural nodes. The employed actuators have the untypical form of two-state hinges, which can switch between two extreme states: no transfer of bending moments (effectively a hinge) and full transfer of bending moments (a locked hinge or a typical frame node). Consequently, the control forces are dissipative and coupled to the response. Previous research in this area focused on purely energetic considerations, aiming for global damping of vibrations. In contrast, this paper formulates the control objective in terms of local displacements of a selected degree of freedom, which can be interpreted as the task of isolating it from external excitations. This formulation is employed to define the target sliding hyperplane. The state of the actuators is chosen such that the effective control forces push the structural state toward the target hyperplane. The approach is verified in a numerical example of a six-story shear-type structure subjected to random seismic excitation.

Structural control, Semi-active control, Sliding mode control, On/off nodes

In the present study a comparison of frequently used computer vision (CV)-based methods for structural health monitoring of truss structures is shown. The attention is paid to template matching methods that can be classified into one of two groups: area-based and feature-based methods. Synthetic but realistic video is used in this study. Results of the comparison are reliable due to the fact that the exact displacements are known from the finite element model of the investigated structure. From the variety of tested CV methods, the Kanade–Lucas–Tomasi algorithm with FREAK-based repetitive correction outperforms the remaining tested methods in terms of the computation time with a negligibly greater estimation error.

computer vision, structural health monitoring, physics-based graphics models (PBGM), IC-SHM 2021, benchmark test

In this study we show pros and cons of two frequently used approaches for model updating and parametric identification of structural system assembled by uncertain bolted connections. The comparison between classical mode matching and a recently proposed Bayesian approach is demonstrated. Classical methods for modal updating based on modal sensitivity require matching of modal parameters extracted from measurement data with those obtained numerically. Alternative approach is based on a probabilistic framework with the aid of Bayesian methodology. Such an approach explicitly includes the problem of a trade-off between modeling and measurement errors. These two methods are compared an a laboratory-scale three-story frame with unknown parameters corresponding to bolted connections. A total of 82 degrees of freedom are measured using 4 bidirectional accelerometers and roving sensor technique.

Performance of any Structural Health Monitoring (SHM) system strongly depends on a set of sensors which are distributed over the structure under investigation. Optimal deployment of sensors on large scale structures such as tied-arch bridges is quite a challenging problem. Moreover, deployment of a sensor network consisting of different types of sensors (accelerometers, inclinometers or strain gauges) over a large scale bridge renders the task of optimization even more demanding. In the present study, a conventional sensor placement method for distribution of a homogenous sensor network is expanded to the heterogeneous case. First, the basic equations governing the estimation error will be recalled. Then, the Fisher information matrix is assembled using normalized translational and rotational mode shapes. Finally, a computational procedure is proposed which allows optimal sensor positions to be selected among thousands candidate locations. The effectiveness of the proposed strategy is demonstrated using a realistic example of a tied-arch bridge located in Poland.

optimal sensor placement, structural health monitoring, tied-arch bridges, multi-type sensor network

The success of virtually all structural health monitoring (SHM) methods depends on the information content of the measurements, and thus on the placement of the available sensors. This paper presents an efficient method for finding optimal sensor distribution over structural system with many degrees of freedom (DOFs). The objective function is based on the classical Fisher information matrix. Originally, this yields a computationally hard discrete optimization problem. However, the proposed numerical solution method is based on a concept taken from structural topology optimization, where a discrete optimization problem is replaced with a continuous one. Two numerical examples demonstrate the effectiveness of the proposed methodology. These are a 5-bay truss with 24 DOFs and a two-story frame structure whose finite element model has been condensed to 14 DOFs.

This contribution proposes a semi-active control approach for a directed energy transfer between structural vibrational modes. The motivation is the intended localization of the vibration energy in a selected mode for the purpose of energy harvesting and mitigation of structural vibrations. The proposed control strategy aims at the instantaneous maximization of the energy transfer to the target mode. It is based on an untypical approach of dynamic structural reconfiguration and implemented using a semi-actively controllable node: a lockable joint. Such a joint, depending on the control signal, can act as a hinge or as a typical frame node. Effectively, it provides thus an on/off ability to control the transfer of bending moments between the adjacent structural elements. The effectiveness of the approach is demonstrated in a numerical example of a plane frame structure.

Modal control, Semi-active control, Lockable joints, Energy harvesting

The topic of smart civil infrastructure has attracted significant attention. An important component of such structural systems is the network of sensors used to monitor the structure and deliver information about its current health status. The task of optimal sensor placement is not trivial due to the discrete, combinatorial nature of the problem. The brute force search is unfeasible for large structures, which calls for approximate and heuristic approaches. This problem has been investigated for several decades, beginning probably with the landmark 1978 paper of Shah [1]. A recent review can be found in [2].

The criteria typically used for assessing candidate placements are based either on Kammer’s Effective Independence (EFI) and the Fisher Information Matrix (FIM) [3], and quantify the amount of information provided by sensors, or on covariance matrices obtained within the Kalman filtering procedure used to quantify the uncertainty of the unknown response of interest being estimated [4]. However ingenious, most of the proposed procedures are computationally costly in large-scale problems.

This talk will discuss two optimal placement methods that have been recently developed with the objective of computational efficiency [5, 6]. One of them is based on Kalman filter covariance matrices and has—instead of typically quadratic—a linear complexity in the number of potential sensor locations. The other method uses the technique of convex relaxation to represent the problem in a computationally tractable continuous form and speed up the solution procedure even further. The presented application examples will use models of bridge structures.

[1] P.C. Shah, F.E. Udwadia, A methodology for optimal sensor locations for identification of dynamic systems, J. Appl. Mech. 45(1), 188–196 (1978)
[2] Y. Tan, L. Zhang, Computational methodologies for optimal sensor placement in structural health monitoring: A review, Struct. Health Monit. 19(4), 1287–1308 (2020)
[3] D.C. Kammer, Sensor placement for on-orbit modal identification and correlation of large space structures, J. Guid. Control Dyn. 14(2), 251–259 (1991)
[4] C. Zhang, Y.-L. Xu, Optimal multi-type sensor placement for response and excitation reconstruction, J. Sound Vib. 360, 112–128 (2016)
[5] B. Błachowski, A. Świercz A., M. Ostrowski, P. Tauzowski, P. Olaszek, L. Jankowski, Convex relaxation for efficient sensor layout optimization in large-scale structures subjected to moving loads, Comput.-Aided Civ. Inf. 35(10), 1085–1100 (2020)
[6] B. Błachowski, A. Świercz, P. Olaszek, Ł. Jankowski, Implementation of multi-type sensor placement strategy for large-scale engineering structures, 10th ECCOMAS Thematic Conference on Smart Structures and Materials (SMART 2023), July 3–5, 2023, Patras, Greece, pp. 498–506 (2023)

This contribution reviews a recently proposed semi-active control approach based on the Prestress-Accumulation Release strategy, which aims at damping of structural vibrations by promoting vibration energy transfer from lower- into higher-order modes that have significant material damping. Unlike typical semi-active control, which focuses on local dissipation in actuators, the aim is to trigger natural global damping mechanisms. The actuators are controllable truss-frame nodes: lockable hinges that can change their mode of operation from a frame node (locked hinge) into truss node (free rotation). Sudden removal of such a kinematic constraint releases the accumulated bending energy into high-frequency quickly damped local vibrations. Two formulations are reviewed: decentralized with local-only feedback, and global, which aims at a targeted energy transfer between specific modes. Experimental results confirm the effectiveness using free, forced harmonic and random vibrations.

In practice, the broadly used finite element (FE) models can have very large number of degrees of freedom (DOFs). A small subset of DOFs representing sensor locations that provides an extremum of a selected objective function corresponding to a metric of the expected measurement accuracy is sought. Thus, optimal sensor placement is characterized by its complex combinatorial nature and tremendous computational effort required. With the aid of convex relaxation, the proposed approach allows one to transform the original combinatorial problem into its continuous counterpart, which requires smaller computational effort – by a few orders of magnitude than famous Effective Independence method. The effectiveness of the method has been demonstrated using an example of a FE model of an existing railway bridge. First, the FE model has been calibrated with measured responses of the bridge under the moving load of a passing train. Then, sensor layout has been obtained in such a way that it optimises the estimate of modal coordinates of the mode shapes participating most significantly in the measured structural response. The authors acknowledge the support of the National Science Centre, Poland (grant agreement 2018/31/B/ST8/03152).

Parametric identification of structures and their components can be encountered in many engineering problems such as damage assessment or model updating for the control purposes. In the present study the attention is on two approaches to model updating. The first approach is the classical penalty func-tion that minimizes the square norm of the error between experimental and numerical modal data. The second one is a probabilistic Bayesian framework that maximizes the a posteriori probability density function of the unknown parameters based on the experimental data. The main difference between these two approaches is related to the fact that the penalty function methods requires matching of the numerical data with those obtained experimentally. The Bayesian approach is not vulnerable to this problem, but it requires more weighting parameters to be selected. An improper selection of these parameters leads to a worse identification accuracy. In this work, the two approaches are compared using data obtained from experiments on a laboratory-scale frame with highly uncertain bolted connec-tions. 17 uncertain stiffness parameters are to be identified: 16 of them correspond to the bolted con-nections and one to the Young modulus of the beams. 82 degrees of freedom are measured with the aid of 4 bidirectional accelerometers and roving sensor technique. Experimental modal data used for model updating contain nine mode shapes and the corresponding natural frequencies within the fre-quency range from 0 to 1 kHz. The research is divided into three steps: (1) model class selection, (2) assessment of the parameter identifiability and (3) updating of the selected model with the aid of both examined model updating methods.

This contribution reviews a recently proposed control strategy for mitigation of vibrations based on the Prestress-Accumulation Release (PAR) approach [1]. The control is executed by means of semi-actively controllable truss-frame nodes. Such nodes have an on/off ability to transfer bending moments: they are able to temporary switch their operational characteristics between the truss-like and the frame-like behaviors. The focus is not on local energy dissipation in the nodes treated as friction dampers, but rather on stimulating the global transfer of vibration energy to high-order modes. Such modes are high-frequency and thus highly dissipative by means of the standard mechanisms of material damping. The transfer is triggered by temporary switches to the truss-like state performed at the moments of a high local bending strain. A sudden removal of a kinematic constraint releases the locally accumulated strain energy into high-frequency and quickly damped vibrations.
The first formulation investigated global control laws [1]. Recent approaches generalized it to decen-tralized control with a local-only feedback, which was tested in damping of free vibrations [2] as well as forced vibrations [3]. Recently, a global formulation was proposed that aims at a targeted energy transfer between specific vibration modes [4], and attempts were made to go beyond skeletal struc-tures [5]. Numerical and experimental results will be presented to confirm the high effectiveness of the approach in mitigation of free, forced random and forced harmonic vibrations.

Despite significant advances in structural health monitoring (SHM), the design of contact sensor networks and their power supply for large-scale structures is still expensive and difficult. Due to the recent progress in computer vision (CV) it is possible to monitor structural components or even whole structures with the aid of digital cameras that allow to avoid the use of the contact sensors. However, CV-based measurements have a significantly lower accuracy than the techniques based on the contact sensors. Moreover, the amount of benchmark data available for development, testing and comparison of CV-based methods is limited. This problem has been partially overcome in recent years by the use of the physics-based graphical models (PBGM) in generation of synthetic but realistic video data. In this work, a comparison of two popular methods of CV-based object tracking applicable in SHM is discussed. PBGM-based videos used in this study are a part of The 2nd International Competition for Structural Health Monitoring'. Exact structural displacements are available due to the fact that PBGM-based video are generated using the structural model. Hence, calculation of the error metrics is straightforward and reliable. The PBGM-based videos show a spatial truss subjected to an unknown excitation.

Nowadays engineering studies require the use of the sophisticated finite element (FE) models consisting of hundreds if not thousands of degrees of freedom. However, using only such models does not allow for accurate reproduction of physical properties of real structures. To overcome this problem usually model updating (MU) techniques are employed. MU usually has one of two goals: 1) modification of some parameters of the model in order to minimize error between output of the FE model and experimental data obtained from the real system, and 2) identification of some properties of the real system using both experimental data and updated FE model. The former case relates to finding the model for performing simulations of the behaviour of the real system. In the later case MU can be applied in damage assessment process. Due to modelling uncertainties minimization of the error between measured and model output does not always provides the most accurate parametric identification. In this research unknown parameters describing rotational stiffness of bolted connections in a frame structure are estimated. Effectiveness of the two competitive model updating methods are compared. The first is based on modal sensitivities and minimizes error between numerical and experimental modal data. It requires matching of the numerical modes with the experimental ones, hence it is often called mode matching. The second is based on probabilistic Bayesian framework. In this approach maximum a posteriori (MAP) estimate of the unknown parameters is searched. It provides an augmented optimization allowing for model updating without mode matching. Moreover, this method is intended for parametric identification and explicitly includes the modelling errors into the problem formulation. In this study vibration modes are obtained from laboratory-scale frame with uncertain bolted connections. It is shown that assembly imperfections have significant influence on the mode shapes of the frame. The results also show that the two methods for model updating provide significantly different values of the identified stiffness parameters for the investigated bolted connections.

In the present study a benchmark test of selected methods of template matching-bated methods for computer vision-based object tracking is performed. The attention is paid to compare these methods in terms of estimation of nodal displacements in a flexible truss structure, aiming at assessment of their reliability in Structural Health Monitoring (SHM) applications. Thanks to the use of synthetic but realistic videos generated with the aid of physics-based graphics models (PBGM), exact displacement of tracked structural nodes are known. Therefore, reliable assessment of the accuracy of the examined methods is possible.

computer vision, structural health monitoring, physics-based graphics models (PBGM)

The uNET neural network architecture has shown very promising results when applied to semantic segmentation of biomedical images. The aim of this work is to check whether this architecture is equally applicable to semantic segmentation distinguishing the structural elements of railway viaducts. Artificial images generated by a computer graphics program rendering the 3D model of the viaduct in a photorealistic manner will be used as data sets. This approach produces a large number of
images that provide a solid training set for machine learning model.

Computer vision, deep learning, semantic segmentation

The paper presents the parametric identification of structural connections characterised by highly uncertain stiffness. Such uncertainties often appear in structural bolted connections. One of the common problems in parametric identification with the use of modal data is the problem of the mode matching. In this work the model updating method based on the Bayesian approach was used to identify the unknown parameters. Due to the probabilistic framework it allows to avoid the problem of the mode matching. A laboratory-scale frame structure is considered in this research, however this structure contains bolted connections common also in large-scale light-weight structures. The problem of parametric identification has been decomposed into the following tasks: (a) selection of the finite element model, (b) evaluation of the identifiability of the parameters, and (c) updating the finite element model with the use of available measurement data.

Bayesian approach, mode matching, system identification, model updating, bolted connections

W ostatnim czasie wiele prac naukowych poświęcono problemom półaktywnego sterowania drganiami układów mechanicznych. Większość tych prac jednak dotyczy zagadnienia tłumienia drgań, natomiast znacznie mniej z nich obejmuje strategie sterowania na potrzeby odzyskiwania energii z drgających układów. Celem niniejszej pracy jest opracowanie strategii półaktywnego sterowania drganiami, mającej za zadanie przenosić energię drgań wzbudzanych losowo do jednej wybranej postaci drgań własnych. Sterowanie takie realizowane jest przy pomocy dynamicznie rozłączanych węzłów konstrukcyjnych. Węzły w zależności od sygnału sterowania mogą być blokowane w celu przenoszenia momentu zginającego pomiędzy łączonym członami konstrukcji lub odblokowywane, aby pracować jak połączenie przegubowe. Prowadzone badania podstawowe mają wiele potencjalnych zastosowań. Wraz ze zmianą postaci drgań, istnieje możliwość zmiany amplitudy w miejscach, w których zainstalowany jest tłumik lub urządzenie odzyskujące energię (ang. energy-harvester). Możliwe jest również szybkie przeniesienie energii mechanicznej do postaci drgań, która nie zakłóca funkcjonalności konstrukcji lub nie powoduje jej uszkodzenia bądź zmęczenia. W porównaniu do sterowania aktywnego stosowanie sterowania półaktywnego pozwala obniżyć koszty układu, dodatkowo nie powodując destabilizacji konstrukcji [1]. Sterowanie takie może z powodzeniem znaleźć zastosowanie w konstrukcjach o wielu stopniach swobody [2]. Strategia półaktywnego sterowania z użyciem blokowalnych węzłów pierwotnie została opracowana w celu przeniesienia energii drgań do wyższych postaci własnych w celu skutecznej ich redukcji przez tłumienie materiałowe [3]. W niniejszej pracy zaprezentowany zostanie model matematyczny transferu energii oraz oparte na nim prawo sterowania. Dodatkowo przedstawiony zostanie przykład numeryczny pokazujący, że transfer energii mechanicznej jest możliwy nawet wtedy, gdy mierzone są tylko pierwsze – podstawowe – postacie drgań własnych. Prowadzone badania zostały wsparte przez Narodowe Centrum Nauki w ramach projektu Re-Conf (DEC-2017/25/B/ST8/01800).

sterowanie półaktywne, analiza modalna, blokowane węzły

The present study provides a comprehensive framework for sensor layout optimization aiming at accurate estimation of the modal coordinates coming from the structural response. The proposed procedure consists of two steps briefly described below. The first step is a selection of vibrational modes taking part in the motion of structures during their normal operation – in this case subjected to traveling load. Among these structures there are various types of bridges especially railway bridges. In the case of present study structural responses are obtained from rigorous finite element (FE) model of the bridge. The FE model is calibrated with measured response of real bridge located in Huta Zawadzka. The calibration process is based on the displacement signals of the bridge under the traveling load. In the second step modes of interest are selected and a set of candidate sensor locations is proposed. It is a subset of all degrees of freedom (DOFs) of the FE model from which several locations are chosen as best possible locations for the displacement sensors. The above sensor placement problem is a combinatorial task. Many methods for solving such problems have been developed previously, but in the case of large scale structures they require tremendous computational effort. To reduce this effort the so-called convex relaxation is incorporated into optimization process. The technique consists in reformulation of combinatorial problem into continuous convex one. Then, the convex relaxation is achieved by introducing the so-called sensor density function, which assigns a certain metric for individual candidate sensor location. Next, the value of this function is optimized in such a way that it maximize determinant of the Fisher Information Matrix. It has been shown that above algorithm is very effective and is distributing a number of sensors in several iterations only. Finally, it is worth noting that presented method can be used to distribute sensors for structural health monitoring. Moreover, it can be also applied in modal control strategies in vibration suppression.

The vibration attenuation problem has been solved using many different methods, some of which involve the use of advanced control algorithms. The topic of harvesting the energy of structural vibrations is less explored. For that reason, this contribution studies the problem of conversion of mechanical energy of vibrations. The paper presents a method of semi-active control, which is applied to dynamically transfer the vibration energy into a selected vibration mode. The target mode is selected in such a way that the amount of energy that can be recovered during the vibration process is maximized. In other words, switching between two modes is not intended to dissipate the energy of vibrations, but rather to maximize the energy-harvesting potential of the overall system. The concept will be illustrated using an example of a simple frame structure, in which semi-actively controlled lockable joints modify the modal properties of the structure.

semi-active control, lockable joints, energy-harvesting