Modal Parameters Of Structure Research Articles

Estimating aeroelastic effects from full bridge responses by operational modal analysis

This paper deals with the estimation of structural modal parameters of long-span bridges from their recorded wind-excited response, by separating structural properties from aeroelastic effects using information on the incoming wind velocity. Specific attention is devoted to structural damping ratios, as their accurate estimations are of crucial importance in bridge engineering. However, uncertainties affecting damping ratios estimates often complicate any attempt towards their accurate assessment. More importantly, in the case of long-span bridges, aerodynamic damping often hides the actual structural one, even at low wind velocities. In this paper, the use of a data-driven stochastic subspace approach, specifically conceived to eliminate, as much as possible, analyst's arbitrariness and to deal with the non-whiteness of the wind excitation, is proposed for system identification. Structural properties are then separated from aeroelastic effects via nonlinear regressions of the modal parameter estimates at different mean wind velocities. Application of this technique to field measurements and numerically simulated buffeting response data referred to a real suspension bridge is finally presented, showing its effectiveness for separating structural from aerodynamic damping in practical case studies.

Application of Wavelet Transform to Modal Parameter Identification of the Concrete-Filled Steel Tube Arch Bridge

It’s important to identify structural modal parameter in time and accurately for structural health monitoring and damage identification. Wavelet analysis is one of the various kinds of identification methods, which has been used in linear and nonlinear system response data since it can decompose signals simultaneously both in time-domain and frequency-domain with adaptive windows. In this paper, taking Bariba Bridge as an example, the modal analysis results obtained from the finite element model are compared with those estimated from the wavelet transform method. Good coincidence of results can be observed, which demonstrates that the built-up finite element model reflects the bridge’s real dynamic properties, and can serve as a baseline model for its dynamic response analysis under complicated excitations, long-term health monitoring and structural service state assessment.

Modal analysis by free vibration response only for discrete and continuous systems

This work aims to develop the algorithm for modal analysis by free vibration response only (MAFVRO), in particular for the general or non-proportional viscous damping system model. If the structural displacement or acceleration response due to free vibration can be measured, the system response matrices, including the displacement, velocity and acceleration, can be obtained through numerical differential or integration methods. These response matrices can then be applied to the developed MAFVRO method to determine the structural modal parameters. The numerical differential and integration methods are introduced and adopted to establish the modal parameter prediction program for the non-proportional damping model of MAFVRO. This work also shows the applications of MAFVRO to the multiple degree-of-freedom (mdof) systems and the cantilever beam, respectively. Both the discrete and continuous systems are demonstrated for the feasibility of the MAFVRO algorithm. The developed method uses the free vibration output response only and can obtain the structural modal parameters successfully.

Eigen-Level Data Fusion Model by Integrating Rough Set and Probabilistic Neural Network for Structural Damage Detection

In this paper, a new eigen-level data fusion model, whereby rough set data and a probabilistic neural network (PNN) are integrated using a data fusion technique, is proposed for structural damage detection. This model is used for structural damage detection and identification, particularly for cases where the measurement data has many uncertainties. More specifically, structural modal parameters derived from vibration responses are first discretized by the K-means clustering technique and the rough set technique is then employed to deal with the great volume of data and to extract optimal feature parameters. After that, the processed data and information are input to the fusion centre of the data fusion technique and fused with the PNN to give a fusion-based damage detection result. To verify the proposed method, two numerical examples are presented to identify both single and multi-damage case patterns. The effects of measurement noise and of non pre-processed rough set data on the damage detection results are also discussed. The results show that the proposed model not only has good damage detection capability and noise tolerance, but also significantly reduces data storage memory requirements and saves runtime as a consequence of the data fusion processing.

DAMAGE DETECTION IN A COMPOSITE BEAM WITH A DOUBLE EDGE CRACK USING FINITE ELEMENT ANALYSIS

Cracks in vibrating component can initiate catastrophic failures. The presences of cracks change the physical characteristics of a structure which in turn alter its dynamic response characteristics. Therefore there is need to understand dynamics of cracked structures. Crack depth and location are the main parameters for the vibration analysis. So it becomes very important to monitor the changes in the response parameters of the structure to access structural integrity, performance and safety. A number of analytical, numerical and experimental techniques are available for the study of damage identification in beams. The objective of this paper is to develop a damage detection method in a composite cantilever beam with a double edge crack has been studied using finite element method. The vibration-based damage detection methods are based on the fact that changes of physical properties (stiffness, mass and damping) due to damage will manifest themselves as changes in the structural modal parameters (natural frequencies, mode shapes and modal damping). The task is then to monitor the selected indicators derived from modal parameters to distinguish between undamaged and damaged states. In the present study, vibration analysis is carried out on a cantilever beam with two open transverse cracks, to study the response characteristics and damage identification is based on the damage index method. Suitable boundary conditions are used to find out natural frequency and mode shapes. The results obtained numerically are validated with the results obtained from the simulation. The simulations have done with the help of ANSYS software. The importance of using damage patterns from the damage index method, (which is based on changes in modal strain energies) is that only measured mode shapes are required in the damage identification. The results shows, the damage index based method is capable of identification of damage and severity of damage in a structure.

Determining Structural Modes of HSK Tool System Based on FEM and EMA

In this research, we computationally analyzed the structural modes of an HSK63E type tool system and verified the results with experimental modal analysis (EMA). The computation was implemented using the finite element method (FEM) based on a linear-elastic theory, with which we computed the natural frequency and obtained the modal shapes under both free and operating conditions. With the method of experimental modal analysis, we also obtained structural modal parameters including the natural frequency, modal shapes and damping ratio under the same free and operating conditions. The computational data were compared with the experimental findings. The reasonable agreement between the two data sets indicated the validity and provided a theoretical basis for using computational methods for determining the natural characteristics and influencing factors of HSK tool system. With this validated FEM model, further analyses were performed to evaluate the unique dynamic performance of the HSK tool system, and to apply dynamic optimum design to other types of HSK tool system.

Two-stage structural damage detection using fuzzy neural networks and data fusion techniques

It is proposed in this paper a novel two-stage structural damage detection approach using fuzzy neural networks (FNNs) and data fusion techniques. The method is used for structural health monitoring and damage detection, particularly for cases where the measurement data is enormous and with uncertainties. In the first stage of structural damage detection, structural modal parameters derived from structural vibration responses are fed into an FNN as the input. The output values from the FNN are defuzzified to produce a rough structural damage assessment. Later, in the second stage, the values output from three different FNN models are input directly to the data fusion center where fusion computation is performed. The final fusion decision is made by filtering the result with a threshold function, hence a refined structural damage assessment of superior reliability. The proposed approach has been applied to a 7-degree of freedom building model for structural damage detection, and proves to be feasible, efficient and satisfactory. Furthermore, the simulation result also shows that the identification accuracy can be boosted with the proposed approach instead of FNN models alone.

Direct multivariate subspace time identification

The paper presents a time domain method to identify structural modal parameters by fitting a discrete multivariate space-time model into noise corrupted, input–output measurement data. The subspace identification scheme proposed is an important characteristic of the method, leading to a deterministic and statistically bias free estimation of parameters. The identification model in this scheme, is kept to the minimum description order, in spite of the presence of noise in the system's input and output The method is used to estimate natural frequencies, damping factors and mode shapes in an experimental modal analysis test.

Design and fabrication of flexible piezo-microgenerator by depositing ZnO thin films on PET substrates

In this study, a new design of PET-based (polyethylene terephthalate) flexible power harvesting system is proposed. It consists of flexible PET vibration substrate, piezoelectric ZnO (zinc oxide) thin film, design of lump structures and electrodes. The relationship between the dynamic response of PET substrate and its power output is realized. High electromechanical transformation of piezoelectric material and efficient energy transfer of mechanical structure make the piezoelectric generator a high performance. The flexible devices of cantilevers with lump structures and piezoelectric ZnO thin film is designed. A layer of aluminum (Al) thin film is placed as a top electrode and a copper (Cu) foil as a bottom electrode. The piezoelectric cantilever plate is designed by using ANSYS ® software. Both modal analysis and harmonic response analysis are performed to obtain the structural modal parameters and frequency response functions, respectively. Then, imprinting process is applied to transfer the configuration of geometric lump structure, based on the simulated result, onto the flexible substrate to improve the power output. The lump material is ultraviolet-curable (UV) resin. The high-quality ZnO piezoelectric thin film has an even distribution of crystal grains. The angle obtained from diffraction diagram approaches 34.5°. It was deposited to the Al/PET flexible substrate by using RF (radio frequency) magnetron sputtering under 75 W power. In comparison of simulation and experiments with and without the lump structure, the lump structures on the flexible generator do improve the power output. The generator achieves maximum OCV (open-circuit voltage) up to 2.25 V and CCV (closed-circuit voltage) up to 1.55 V which is 0.276 μW per centimeter square. In addition, the devices are fabricated by a new process where the piezoelectric active areas on the cantilever are supported to achieve a large displacement with low residual stress. With low elastic constant of the PET-based layer, the cantilever structure can achieve better displacement compared with the conventional SOI (silicon on insulator) structures or other metal substrates.

Intelligent Wireless Sensors with Application to the Identification of Structural Modal Parameters and Steel Cable Forces: From the Lab to the Field

Wireless sensing systems have been proposed for structural heath monitoring in recent years. While wireless sensors are cost-competitive compared to tethered monitoring systems, their significant merit also lies in their embedded computational capabilities. In this paper, performance of the two embedded engineering algorithms, namely the fast Fourier transform and peak-picking algorithm implemented in the wireless sensing nodes codeveloped at Stanford University and the University of Michigan is investigated through laboratory and field experimental studies. Furthermore, the wireless sensor network embedded with the engineering algorithms is adopted for the identification of structural modal parameters and forces in steel bridge cables. Identification results by the embedded algorithms in the intelligent wireless sensors are compared with those obtained by conventional offline analysis of the measured time-history data. Such a comparison serves to validate the effectiveness of the intelligent wireless sensor network. In addition, it is shown that self-interrogation of measurement data based upon the two embedded algorithms in wireless sensor nodes greatly reduces the amount of data to be transmitted by the wireless sensing network. Thus, the intelligent wireless sensors offer scalable network solutions that are power-efficient for the health monitoring of civil infrastructures.

A Dynamic Life Evolution Method Based On Timedependent Reliability By Health Monitoring Data

Abstract This paper aims at the disadvantage of traditional calculation mode of reliability and proposes a new idea to calculate resistance of structure. This idea uses identification of structure modal parameters, structure physical parameters and EWMA control map. Reliability by load effects taken and life prediction can be achieved. In addition, by utilization of high order statistical predicting function for life prediction, meanwhile, modification of dynamic evolution in reliability calculation and life prediction are completed.

Wavelet Analysis in Damage Detection for Bridge Structure

The damage of structure leads to variation of structural modal parameter，so the wavelet transform for damage detection is introduced in this paper for considering the variation. First, structural dynamic response signal on the basis of the vibration-based structural damage diagnosis methods is calculated by structural analysis in the paper, then, each of sub-signals is calculated according to wavelet analysis, also, the sub-signal energy spectrum of dynamic response signal and energy spectrum variation are known. By observing the difference of the sub-signal and the variation of the sub-signal energy spectrum, we can get the variation of structural modal parameter and the sub-signal energy spectrum due to the performance degradation of the whole structure and local variations of damage level and location ,so that this method can be used in on-line damage detection for bridge structure.

Modal identification of bridges under varying environmental conditions: Temperature and wind effects

Numerous investigations have indicated that structural modal parameters are significantly impacted by varying environmental and operational conditions. This phenomenon will cause confusion when conducting modal-based damage detection and model updating. This paper investigates the dependency of modal frequencies, modal shapes and the associated damping ratios on temperature and wind velocity. The nonlinear principal component analysis (NLPCA) is first employed as a signal pre-processing tool to distinguish temperature and wind effects on structural modal parameters from other environmental factors. The pre-processed dataset by NLPCA implies the relationship between modal parameters and temperature as well as wind velocity. Consequently, the artificial neural network (ANN) technique is employed to model the relationship between the pre-processed modal parameters and environmental factors. Numerical results indicate that pre-processed modal parameters by NLPCA can retain the most features of original signals. Furthermore, the pre-processed modal frequency and damping ratios are dramatically affected by temperature and wind velocity. The ANN regression models have good capacities for mapping relationship of environmental factors and modal frequency, damping ratios. However, environmental effects on the entire modal shapes are insignificant. Copyright © 2009 John Wiley & Sons, Ltd.

Online automatic identification of the modal parameters of a long span arch bridge

The “Infante D. Henrique” bridge is a concrete arch bridge, with a span of 280 m that crosses the Douro River, linking the cities of Porto and Gaia located in the North of Portugal. This structure is being monitored by a recently installed dynamic monitoring system that comprises 12 acceleration channels. This paper describes the bridge structure, its dynamic parameters identified with a previously developed ambient vibration test, the installed monitoring equipment and the software that continuously processes the data received from the bridge through an Internet connection. Special emphasis is given to the algorithms that have been developed and implemented to perform the online automatic identification of the structure modal parameters from its measured responses during normal operation. The proposed methodology uses the covariance driven stochastic subspace identification method (SSI-COV), which is then complemented by a new algorithm developed for the automatic analysis of stabilization diagrams. This new tool, based on a hierarchical clustering algorithm, proved to be very efficient on the identification of the bridge first 12 modes. The results achieved during 2 months of observation, which involved the analysis of more than 2500 datasets, are presented in detail. It is demonstrated that with the combination of high-quality equipment and powerful identification algorithms, it is possible to estimate, in an automatic manner, accurate modal parameters for several modes. These can then be used as inputs for damage detection algorithms.

Vibration analysis of a circular plate in interaction with an acoustic cavity leading to extraction of structural modal parameters

When carrying out vibration health monitoring (VHM) of a structure it is usually assumed that the structure is in the absence of fluid interaction and that any environmental effects which can cause changes in natural frequency either remain constant or are negligible. In certain cases, this condition cannot be assumed and therefore it is necessary to extract values of natural frequencies of the structure for the condition with no fluid interaction from those values measured. This paper considers the case of a thin circular plate in contact with a fluid cavity giving rise to strong structural/fluid vibration interaction. The paper details the free vibration analysis of the coupled system and through consideration of modal energy, illustrates how the affined modes of vibration of the plate and the fluid can be qualitatively described. The paper then introduces a method by which the natural frequencies of the plate in the absence of fluid interaction can be obtained from those of the plate in interaction with the fluid.

Vibration-based damage detection with structural modal characteristics

A challenging problem in structural health monitoring systems is the requirement of a systematic, effective method for damage localisation and assessment severity of structures, based on vibration data measured by sensors. To address this issue, a novel technique, referred to as damage estimator with modal parameters of structure before and after damage, is applied to detect the location and estimate the severity of existing damage of complex structures. Specifically, a series of experimental tests using a scaled offshore platform model of a 4-story jacket type has been conducted to verify the efficiency of proposed approach, with white noise excitations applied to the top plate of test model. For 6 scenarios of damage conditions simulated by bolt adjustment in the 3rd layer, vibration-based impulse data are induced by an impact hammer and recorded to analyse the variations of modal parameters. Upon the investigation, the results highlight that damage estimator is capable of tracking damage orientation and severity longitudinally, using data from only the fundamental mode shape before and after damage. However, detection accuracy declines considerably for small-scale damages.

Modal analysis of mdof system by using free vibration response data only

Conventional modal testing requires the actuator and sensor to perform FRF measurement so as to determine the structural modal parameters. This paper presents a new idea of experimental modal analysis by only using the structural free vibration response due to initial conditions. If the structural displacement can be measured, the displacement response matrices that are the discrete-time-domain data for all measured dofs can be formulated. The velocity and acceleration response matrices can then be calculated by finite difference methods. With the input of these response matrices to the developed algorithm, the system natural frequencies and their corresponding mode shapes can be determined simultaneously. Numerical examples for a 3-dof and 10-dof systems are presented, to show, respectively, the feasibility and effectiveness of the developed method. Results show the proposed method is very promising. Only the structural displacement response in free vibration condition need to be measured and as the input to the modal parameter extraction algorithm such that all of the structural modal frequencies and mode shapes of the system can be determined successfully. The presented idea can also be extended and applied to the general structure with non-proportional damping case. The proposed methodology can therefore enhance the structural modal analysis technique.

Experimental study of modal parameter identification in a simulated ambient-excited structure

Structure modal parameter online identification was used to monitor the structural health as evidenced by changes in the vibration characteristics. The natural excitation technique and the eigensystem realization algorithm were combined to identify the modal parameters in the time domain of a structure excited by simulated ambient vibrations. The mass-normalized mode shapes were obtained from the eigen-sensitivity analysis. The experimental modal analysis was performed on a two-story steel braced frame model excited by simulated ambient vibrations and hammer impacts. The mass-normalized mode shapes were acquired by changing the structural mass and by eigen-sensitivity analysis. From finite element analysis results and the experimental data, it is shown that this method is effective.

State-space analysis of mode-coupling in orthogonal metal cutting under wave regeneration

In this paper, mode-coupling in orthogonal metal cutting is analyzed in the state-space domain. Closed-form equations are obtained for eigenvalues and eigenvectors of the joint system formed by the cutting process and the mechanical structure, as a function of cutting conditions and structure modal parameters. System stability is analyzed and variations of the joint system natural frequencies are proposed for monitoring stability, forces and indirectly tool condition. Finally, experimental tests are presented to validate theoretical formulations in orthogonal aluminium cutting. By means of a state-space domain analysis of the joint system, formed by the cutting process and the machine structure, it is possible to obtain mathematical formulations that quantitatively relate joint system natural frequencies to system stability. Therefore, it is possible to detect chatter vibrations before work piece quality is affected by monitoring vibrations during machining. These formulations facilitate the development of robust active vibration control system which will improve machine tool stability in the future.

Low frequency sound insulation using stiffness control with honeycomb panels

A new honeycomb core design has been used to increase the stiffness of the panel and applied to improve the noise transmission loss at frequencies between 100 and 200 Hz. A model is presented to predict the transmission loss of the honeycomb panels based on the structural modal parameters. A new test specimen with fiber reinforced plastic cores and face sheets had been used to investigate the effect of stiffness and damping on noise transmission loss. The measurements of noise transmission loss have been compared with data for common structural panels. The results show that the new core fabrication techniques using moulding to improve the noise transmission are effective. In comparison to a cement panel of the same mass, the honeycomb panels have higher TL at low frequencies between 100 and 200 Hz due to higher stiffness and damping. The honeycomb panels have more significant vibration responses above 500 Hz but these are limited by damping.