Compared to the ambient vibration test mainly identifying the structural modal parameters, such as frequency, damping and mode shapes, the impact testing, which benefits from measuring both impacting forces and structural responses, has the merit to identify not only the structural modal parameters but also more detailed structural parameters, in particular flexibility. However, in traditional impact tests, an impacting hammer or artificial excitation device is employed, which restricts the efficiency of tests on various bridge structures. To resolve this problem, we propose a new method whereby a moving vehicle is taken as a continuous exciter and develop a corresponding flexibility identification theory, in which the continuous wheel forces induced by the moving vehicle is considered as structural input and the acceleration response of the bridge as the output, thus a structural flexibility matrix can be identified and then structural deflections of the bridge under arbitrary static loads can be predicted. The proposed method is more convenient, time-saving and cost-effective compared with traditional impact tests. However, because the proposed test produces a spatially continuous force while classical impact forces are spatially discrete, a new flexibility identification theory is required, and a novel structural identification method involving with equivalent load distribution, the enhanced Frequency Response Function (eFRFs) construction and modal scaling factor identification is proposed to make use of the continuous excitation force to identify the basic modal parameters as well as the structural flexibility. Laboratory and numerical examples are given, which validate the effectiveness of the proposed method. Furthermore, parametric analysis including road roughness, vehicle speed, vehicle weight, vehicle's stiffness and damping are conducted and the results obtained demonstrate that the developed method has strong robustness except that the relative error increases with the increase of measurement noise.
Alcover-Sanchez, R.;Soria, J.M.;Perez-Aracil, J.;Pereira, E.;Diez-Jimenez, E.
Smart Structures and Systems
/
v.29
no.3
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pp.499-512
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2022
This work proposes a novel contactless vibration damping and thermal isolation tripod platform based on Superconducting Magnetic Levitation (SML). This prototype is suitable for cryogenic environments, where classical passive, semi active and active vibration isolation techniques may present tribological problems due to the low temperatures and/or cannot guarantee an enough thermal isolation. The levitating platform consists of a Superconducting Magnetic Levitation (SML) with inherent passive static stabilization. In addition, the use of Operational Modal Analysis (OMA) technique is proposed to characterize the transmissibility function from the baseplate to the platform. The OMA is based on the Stochastic Subspace Identification (SSI) by using the Expectation Maximization (EM) algorithm. This paper contributes to the use of SSI-EM for SML applications by proposing a step-by-step experimental methodology to process the measured data, which are obtained with different unknown excitations: ambient excitation and impulse excitation. Thus, the performance of SSI-EM for SML applications can be improved, providing a good estimation of the natural frequency and damping ratio without any controlled excitation, which is the main obstacle to use an experimental modal analysis in cryogenic environments. The dynamic response of the 510 g levitating platform has been characterized by means of OMA in a cryogenic, 77 K, and high vacuum, 1E-5 mbar, environment. The measured vertical and radial stiffness are 9872.4 N/m and 21329 N/m, respectively, whilst the measured vertical and radial damping values are 0.5278 Nm/s and 0.8938 Nm/s. The first natural frequency in vertical direction has been identified to be 27.39 Hz, whilst a value of 40.26 Hz was identified for the radial direction. The determined damping values for both modes are 0.46% and 0.53%, respectively.
The absence of excitation measurements may pose a big challenge in the application of structural damage identification owing to the fact that substantial effort is needed to reconstruct or identify unknown input force. To address this issue, in this paper, an iterative strategy, a synergy of Tikhonov regularization method for force identification and modified Jaya algorithm (M-Jaya) for stiffness parameter identification, is developed for damage identification with partial output-only responses. On the one hand, the probabilistic clustering learning technique and nonlinear updating equation are introduced to improve the performance of standard Jaya algorithm. On the other hand, to deal with the difficulty of selection the appropriate regularization parameters in traditional Tikhonov regularization, an improved L-curve method based on B-spline interpolation function is presented. The applicability and effectiveness of the iterative strategy for simultaneous identification of structural damages and unknown input excitation is validated by numerical simulation on a 21-bar truss structure subjected to ambient excitation under noise free and contaminated measurements cases, as well as a series of experimental tests on a five-floor steel frame structure excited by sinusoidal force. The results from these numerical and experimental studies demonstrate that the proposed identification strategy can accurately and effectively identify damage locations and extents without the requirement of force measurements. The proposed M-Jaya algorithm provides more satisfactory performance than genetic algorithm, Gaussian bare-bones artificial bee colony and Jaya algorithm.
This paper reports the structural health monitoring benchmark study results for the Canton Tower using Bayesian methods. In this study, output-only modal identification and finite element model updating are considered using a given set of structural acceleration measurements and the corresponding ambient conditions of 24 hours. In the first stage, the Bayesian spectral density approach is used for output-only modal identification with the acceleration time histories as the excitation to the tower is unknown. The modal parameters and the associated uncertainty can be estimated through Bayesian inference. Uncertainty quantification is important for determination of statistically significant change of the modal parameters and for weighting assignment in the subsequent stage of model updating. In the second stage, a Bayesian model updating approach is utilized to update the finite element model of the tower. The uncertain stiffness parameters can be obtained by minimizing an objective function that is a weighted sum of the square of the differences (residuals) between the identified modal parameters and the corresponding values of the model. The weightings distinguish the contribution of different residuals with different uncertain levels. They are obtained using the Bayesian spectral density approach in the first stage. Again, uncertainty of the stiffness parameters can be quantified with Bayesian inference. Finally, this Bayesian framework is applied to the 24-hour field measurements to investigate the variation of the modal and stiffness parameters under changing ambient conditions. Results show that the Bayesian framework successfully achieves the goal of the first task of this benchmark study.
Nowadays, there are a great number of various structures that have been retrofitted by using different FRP Composites. Due to this, more researches need to be conducted to know more the characteristics of these structures, not only that but also a comparison among them before and after the retrofitting is needed. In this research, a model steel structure is tested using a bench-scale earthquake simulator on the shake table, using recorded micro tremor data, in order to get the dynamic behaviors. Beams of the model steel structure are then retrofitted by using CFRP composite, and then tested on the Quanser shake table by using the recorded micro tremor data. At this stage, it is needed to evaluate the dynamic behaviors of the retrofitted model steel structure. Various types of methods of OMA, such as EFDD, SSI, etc. are used to take action in the ambient responses. Having a purpose to learn more about the effects of FRP composite, experimental model analysis of both types (retrofitted and no-retrofitted models) is conducted to evaluate their dynamic behaviors. There is a provision of ambient excitation to the shake table by using recorded micro tremor ambient vibration data on ground level. Furthermore, the Enhanced Frequency Domain decomposition is used through output-only modal identification. At the end of this study, moderate correlation is obtained between mode shapes, periods and damping ratios. The aim of this research is to show and determine the effects of CFRP Composite implementation on structural responses of the model steel structure, in terms of changing its dynamical behaviors. The frequencies for model steel structure and the retrofitted model steel structure are shown to be 34.43% in average difference. Finally, it is shown that, in order to evaluate the period and rigidity of retrofitted structures, OMA might be used.
Nowadays, there are a great number of various structures that have been retrofitted by using different FRP Composites. Due to this, more researches need to be conducted to know more the characteristics of these structures, not only that but also a comparison among them before and after the retrofitting is needed. In this research, a model steel structure is tested using a bench-scale earthquake simulator on the shake table, using recorded micro tremor data, in order to get the dynamic behaviors. Columns of the model steel structure are then retrofitted by using GFRP composite, and then tested on the Quanser shake table by using the recorded micro tremor data. At this stage, it is needed to evaluate the dynamic behaviors of the retrofitted model steel structure. Various types of methods of OMA, such as EFDD, SSI, etc. are used to take action in the ambient responses. Having a purpose to learn more about the effects of GFRP composite, experimental model analysis of both types (retrofitted and no-retrofitted models) is conducted to evaluate their dynamic behaviors. There is a provision of ambient excitation to the shake table by using recorded micro tremor ambient vibration data on ground level. Furthermore, the Enhanced Frequency Domain Decomposition is used through output-only modal identification. At the end of this study, moderate correlation is obtained between mode shapes, periods and damping ratios. The aim of this research is to show and determine the effects of GFRP Composite implementation on structural responses of the model steel structure, in terms of changing its dynamical behaviors. The frequencies for model steel structure and the retrofitted model steel structure are shown to be 33.916% in average difference. Finally, it is shown that, in order to evaluate the period and rigidity of retrofitted structures, OMA might be used.
Sun, Ke;Zhang, Wei;Ding, Huaping;Kim, Robin E.;Spencer, Billie F. Jr.
Smart Structures and Systems
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v.19
no.1
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pp.1-10
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2017
The operation of subway trains induces secondary structure-borne vibrations in the nearby underground spaces. The vibration, along with the associated noise, can cause annoyance and adverse physical, physiological, and psychological effects on humans in dense urban environments. Traditional tethered instruments restrict the rapid measurement and assessment on such vibration effect. This paper presents a novel approach for Wireless Smart Sensor (WSS)-based autonomous evaluation system for the subway train-induced vibrations. The system was implemented on a MEMSIC's Imote2 platform, using a SHM-H high-sensitivity accelerometer board stacked on top. A new embedded application VibrationLevelCalculation, which determines the International Organization for Standardization defined weighted acceleration level, was added into the Illinois Structural Health Monitoring Project Service Toolsuite. The system was verified in a large underground space, where a nearby subway station is a good source of ground excitation caused by the running subway trains. Using an on-board processor, each sensor calculated the distribution of vibration levels within the testing zone, and sent the distribution of vibration level by radio to display it on the central server. Also, the raw time-histories and frequency spectrum were retrieved from the WSS leaf nodes. Subsequently, spectral vibration levels in the one-third octave band, characterizing the vibrating influence of different frequency components on human bodies, was also calculated from each sensor node. Experimental validation demonstrates that the proposed system is efficient for autonomously evaluating the subway train-induced ambient vibration of underground spaces, and the system holds the potential of greatly reducing the laboring of dynamic field testing.
In this paper, we propose an effective speech reinforcement technique base on ITU-T G.729A CS-ACELP codec under the near-end background noise environments. In general, since the intelligibility of the far-end speech for the near-end listener is significantly reduced under near-end noise environments, we require a far-end speech reinforcement approach to avoid this phenomena. In contrast to the conventional speech reinforcement algorithm, we reinforce the excitation signal of the codec's parameters received from the far-end speech signal based on the G.729A speech codec under various background noise environments. Specifically, we first estimate the excitation signal of ambient noise at the near-end through the encoder of the G.729A speech codec, reinforcing the excitation signal of the far-end speech transmitted from the far-end. we specially propose a novel approach to directly reinforce the excitation signal of far-end speech signal based on the decoder of the G.729A. The performance of the proposed algorithm is evaluated by the CCR (Comparison Category Rating) test of the method for subjective determination of transmission quality in ITU-T P.800 under various noise environments and shows better performances compared with conventional SNR Recovery methods.
Altunisik, Ahmet Can;Bayraktar, Alemdar;Ozdemir, Hasan
Smart Structures and Systems
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v.10
no.2
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pp.131-154
/
2012
In this paper, it is aimed to determine the seismic behaviour of highway bridges by nondestructive testing using ambient vibration measurements. Eynel Highway Bridge which has arch type structural system with a total length of 216 m and located in the Ayvaclk county of Samsun, Turkey is selected as an application. The bridge connects the villages which are separated with Suat U$\breve{g}$urlu Dam Lake. A three dimensional finite element model is first established for a highway bridge using project drawings and an analytical modal analysis is then performed to generate natural frequencies and mode shapes in the three orthogonal directions. The ambient vibration measurements are carried out on the bridge deck under natural excitation such as traffic, human walking and wind loads using Operational Modal Analysis. Sensitive seismic accelerometers are used to collect signals obtained from the experimental tests. To obtain experimental dynamic characteristics, two output-only system identification techniques are employed namely, Enhanced Frequency Domain Decomposition technique in the frequency domain and Stochastic Subspace Identification technique in time domain. Analytical and experimental dynamic characteristic are compared with each other and finite element model of the bridge is updated by changing of boundary conditions to reduce the differences between the results. It is demonstrated that the ambient vibration measurements are enough to identify the most significant modes of highway bridges. After finite element model updating, maximum differences between the natural frequencies are reduced averagely from 23% to 3%. The updated finite element model reflects the dynamic characteristics of the bridge better, and it can be used to predict the dynamic response under complex external forces. It is also helpful for further damage identification and health condition monitoring. Analytical model of the bridge before and after model updating is analyzed using 1992 Erzincan earthquake record to determine the seismic behaviour. It can be seen from the analysis results that displacements increase by the height of bridge columns and along to middle point of the deck and main arches. Bending moments have an increasing trend along to first and last 50 m and have a decreasing trend long to the middle of the main arches.
Femtosecond laser ablation mechanism was systematically investigated on sodalime glass in ambient conditions. The ablation crater diameter was measured for varying numbers of laser pulses as for varying well as the laser fluence. The analysis of the results with a one dimensional spatial Gaussian fluence distribution reveals that the inherent ablation mechanism has been altered from a multi-photon process to a single photon excitation due to defect sites that have been accumulated by successive laser pulses. Furthermore, the transition between the two regimes was found to be a function of both the laser fluence and the number of laser shots.
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