• Smart Structures and Systems
• /
• 제19권4호
• /
• pp.361-369
• /
• 2017

Electromechanical impedance method as an efficient tool in Structural Health Monitoring (SHM) utilizes the electromechanical impedance of piezoelectric materials which is directly related to the mechanical impedance of the host structure and will be affected by damages. In this paper, electromechanical impedance of piezoelectric patches attached to simply support rectangular plate is determined theoretically and experimentally in order to detect damage. A pairs of piezoelectric wafer active sensor (PWAS) patches are used on top and bottom of an aluminum plate to generate pure bending. The analytical model and experiments are carried out both for undamaged and damaged plates. To validate theoretical models, the electromechanical impedances of PWAS for undamaged and damaged plate using theoretical models are compared with those obtained experimentally. Both theoretical and experimental results demonstrate that by crack generation and intensifying this crack, natural frequency of structure decreases. Finally, in order to evaluate damage severity, damage metrics such as Root Mean Square Deviation (RMSD), Mean Absolute Percentage Deviation (MAPD), and Correlation Coefficient Deviation (CCD) are used based on experimental results. The results show that generation of crack and crack depth increasing can be detectable by CCD.

• Computers and Concrete
• /
• 제20권5호
• /
• pp.583-593
• /
• 2017

Applications of fibre-reinforced polymer (FRP) composites for retrofitting, strengthening and repairing concrete structures have been expanded dramatically in the last decade. FRPs have high specific strength and stiffness compared to conventional construction materials, e.g., steel. Ease of preparation and installation, resistance to corrosion, versatile fabrication and adjustable mechanical properties are other advantages of the FRPs. However, there are major concerns about long-term performance, serviceability and durability of FRP applications in concrete structures. Therefore, structural health monitoring (SHM) and damage detection in FRP-retrofitted concrete structures need to be implemented. This paper presents a study on investigating the application of Rayleigh wave for detecting debonding defect in FRP-retrofitted concrete structures. A time-of-flight (ToF) method is proposed to determine the location of a debonding between the FRP and concrete using Rayleigh wave. A series of numerical case studies are carried out to demonstrate the capability of the proposed debonding detection method. In the numerical case studies, a three-dimensional (3D) finite element (FE) model is developed to simulate the Rayleigh wave propagation and scattering at the debonding in the FRP-retrofitted concrete structure. Absorbing layers are employed in the 3D FE model to reduce computational cost in simulating the practical size of the FRP-retrofitted structure. Different debonding sizes and locations are considered in the case studies. The results show that the proposed ToF method is able to accurately determine the location of the debonding in the FRP-retrofitted concrete structure.

• Smart Structures and Systems
• /
• 제17권6호
• /
• pp.1067-1085
• /
• 2016

Nonstationary features existing in tropical storms have been frequently captured in recent field measurements, and the applicability of the stationary theory to the analysis of wind characteristics needs to be discussed. In this study, a tropical storm called Nakri measured at Taizhou Bridge site based on structural health monitoring (SHM) system in 2014 is analyzed to give a comparison of the stationary and nonstationary characteristics. The stationarity of the wind records in the view of mean and variance is first evaluated with the run test method. Then the wind data are respectively analyzed with the traditional stationary model and the wavelet-based nonstationary model. The obtained wind characteristics such as the mean wind velocity, turbulence intensity, turbulence integral scale and power spectral density (PSD) are compared accordingly. Also, the stationary and nonstationary PSDs are fitted to present the turbulence energy distribution in frequency domain, among which a modulating function is included in the nonstationary PSD to revise the non-monotonicity. The modulated nonstationary PSD can be utilized to unconditionally simulate the turbulence presented by the nonstationary wind model. The results of this study recommend a transition from stationarity to nonstationarity in the analysis of wind characteristics, and further in the accurate prediction of wind-induced vibrations for engineering structures.

• Smart Structures and Systems
• /
• 제15권3호
• /
• pp.593-608
• /
• 2015

In many of the industrialized countries an increasing amount of infrastructure is ageing. This has become specifically critical to bridges which are a major asset with respect to keeping an economy alive. Life of this infrastructure is scattering but often little quantifiable information is known with respect to its damage condition. This article describes how a damage tolerance approach used in aviation today may even be applied to civil infrastructure in the sense that operational life can be applied in the context of modern life cycle management. This can be applied for steel structures as a complete process where much of the damage accumulation behavior is known and may even be adopted to concrete structures in principle, where much of the missing knowledge in damage accumulation has to be substituted by enhanced inspection. This enhanced and continuous inspection can be achieved through robotic systems in a first approach as well as built in sensors in the sense of structural health monitoring (SHM).

• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2013년도 추계학술대회 논문집
• /
• pp.799-804
• /
• 2013

The sensor/actuator active sensor diagnostics procedure, where the sensors/actuators are confirmed to be functioning properly during operation, is a critical component to successfully complete the structural health monitoring (SHM) process with large numbers of active sensors typically installed in a structure. The basis of this process is to track the changes in the capacitive value of piezoelectric materials, which shows up in measured admittance. Due to the temperature dependent nature of piezoelectric materials, we investigated the effects of temperature variations on sensor diagnostic process. The effect of temperature variations found to be remarkable, modifying the measured capacitive values significantly. In addition we analyzed the effect of bonding agents between a PZT patch and a host structure. This paper summarizes considerations needed to develop such sensor diagnostic processes, experimental procedures and results, and additional issues that can be used as guidelines for future investigations.

• Smart Structures and Systems
• /
• 제31권6호
• /
• pp.545-559
• /
• 2023

Nanoparticle strips (NPS) are widely used as external reinforcers for two-way reinforced concrete slabs. However, the Structural Health Monitoring (SHM) of these slabs is a very important issue and was evaluated in this study. This study has been done analytically and numerically to optimize the placement of sensors. The properties of slabs and carbon nanotubes as composite sheets were considered isotopic and orthotropic, respectively. The nonlinear Finite Element Method (FEM) approach and suitable optimal placement of sensor approach were developed as a new MATLAB toolbox called DECOMAC by the authors of this paper. The Suitable multi-objective function was considered in optimized processes based on distributed ECOMAC method. Some common concrete slabs in construction with different aspect ratios were considered as case studies. The dimension and distance of nano strips in retrofitting process were selected according to building codes. The results of Optimal Sensor Placement (OSP) by DECOMAC algorithm on un-retrofitted and retrofitted slabs were compared. The statistical analysis according to the Mann-Whitney criteria shows that there is a significant difference between them (mean P-value = 0.61).

• Smart Structures and Systems
• /
• 제22권5호
• /
• pp.631-641
• /
• 2018

This paper outlines a computational procedure for the effective merging of diverse sensor measurements, displacement and acceleration signals in particular, in order to successfully monitor and simulate the current health condition of civil structures under dynamic loadings. In particular, it investigates a Kalman Filter implementation for the Heterogeneous Data Fusion of displacement and acceleration response signals of a structural system toward dynamic identification purposes. The procedure is perspectively aimed at enhancing extensive remote displacement measurements (commonly affected by high noise), by possibly integrating them with a few standard acceleration measurements (considered instead as noise-free or corrupted by slight noise only). Within the data fusion analysis, a Kalman Filter algorithm is implemented and its effectiveness in improving noise-corrupted displacement measurements is investigated. The performance of the filter is assessed based on the RMS error between the original (noise-free, numerically-determined) displacement signal and the Kalman Filter displacement estimate, and on the structural modal parameters (natural frequencies) that can be extracted from displacement signals, refined through the combined use of displacement and acceleration recordings, through inverse analysis algorithms for output-only modal dynamics identification, based on displacements.

• Smart Structures and Systems
• /
• 제21권5호
• /
• pp.601-609
• /
• 2018

The estimated probabilistic model of wind data based on the conventional approach may have high discrepancy compared with the true distribution because of the uncertainty caused by the instrument error and limited monitoring data. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method has been developed in the companion paper and is conducted to formulate the joint probability density function (PDF) of wind speed and direction using the wind monitoring data of the investigated bridge. The established bivariate model of wind speed and direction only represents the features of available wind monitoring data. To characterize the stochastic properties of the wind parameters with the subsequent wind monitoring data, in this study, Bayesian inference approach considering the uncertainty is proposed to update the wind parameters in the bivariate probabilistic model. The slice sampling algorithm of Markov chain Monte Carlo (MCMC) method is applied to establish the multi-dimensional and complex posterior distribution which is analytically intractable. The numerical simulation examples for univariate and bivariate models are carried out to verify the effectiveness of the proposed method. In addition, the proposed Bayesian inference approach is used to update and optimize the parameters in the bivariate model using the wind monitoring data from the investigated bridge. The results indicate that the proposed Bayesian inference approach is feasible and can be employed to predict the bivariate distribution of wind speed and direction with limited monitoring data.

• 비파괴검사학회지
• /
• 제30권4호
• /
• pp.359-366
• /
• 2010

램파를 구조물 안전진단(structural health monitoring, 이하 SMH) 기법에 효과적으로 적용하기 위해서 구조물의 손상과 램파간의 물리적 특성 및 상호관계를 정확히 이해하는 것이 중요하다. 본 연구에서는 modal decomposition 방법을 이용하여 비대칭 불연속면에서 램파의 투과와 반사, 모드 변이를 모사하고, 그 진폭 비율을 불연속면의 깊이에 따라 예측하였다. 또한 이론적으로 예측된 결과를 압전센서(PZT)를 모사한 유한요소법(FEM) 모델과 실험을 통해 검증하였다. 그 결과, modal decomposition 방법을 이용한 이론적 예측이 압전센서를 이용한 유한요소 해석 및 실험 결과와 근접한 것을 확인하였으며, 불연속면의 깊이에 따른 램파의 반사와 투과, 모드 변이의 양을 이용하여 손상의 크기를 정량적으로 측정할 수 있는 방법을 제안하였다.

• Smart Structures and Systems
• /
• 제25권1호
• /
• pp.111-122
• /
• 2020

Researchers up to date have introduced several Structural Health Monitoring (SHM) techniques with varying advantages and drawbacks for each. Satellite positioning systems (GPS, GLONASS and GALILEO) based techniques proved to be promising, especially for high natural period structures. Particularly, the GPS has proved sufficient performance and reasonable accuracy in tracking real time dynamic displacements of flexible structures independent of atmospheric conditions, temperature variations and visibility of the monitored object. Tall structures are particularly sensitive to oscillations produced by different sources of dynamic actions; such as typhoons. Wind forces induce in the structure both longitudinal and perpendicular displacements with respect to the wind direction, resulting in torsional effects, which are usually more complex to be detected. To efficiently track the horizontal rotations of the in-plane sections of such flexible structures, two main issues have to be considered: a suitable sensor topology (i.e., location, installation, and combination of sensors), and the methodology used to process the data recorded by sensors. This paper reports the contributions of the measurements recorded from dual frequency GPS receivers and uni-axial accelerometers in a full-scale experimental campaign. The Canton tower in Guangzhou-China is the case study of this research, which is instrumented with a long-term structural health monitoring system deploying both accelerometers and GPS receivers. The elaboration of combining the obtained rather long records provided by these two types of sensors in detecting the torsional behavior of the tower under ambient vibration condition and during strong wind events is discussed in this paper. Results confirmed the reliability of GPS receivers in obtaining the dynamic characteristics of the system, and its ability to capture the torsional response of the tower when used alone or when they are combined with accelerometers integrated data.