• Smart Structures and Systems
• /
• v.24 no.2
• /
• pp.209-221
• /
• 2019

The classical Kalman filter (KF) provides a practical and efficient way for state estimation. It is, however, not applicable when the external excitations applied to the structures are unknown. Moreover, it is known the classical KF is only suitable for linear systems and can't handle the nonlinear cases. The aim of this paper is to extend the classical KF approach to circumvent the aforementioned limitations for the joint estimation of structural states and the unknown inputs. On the basis of the scheme of the classical KF, analytical recursive solution of an improved KF approach is derived and presented. A revised form of observation equation is obtained basing on a projection matrix. The structural states and the unknown inputs are then simultaneously estimated with limited measurements in linear or nonlinear systems. The efficiency and accuracy of the proposed approach is verified via a five-story shear building, a simply supported beam, and three sorts of nonlinear hysteretic structures. The shaking table tests of a five-story building structure are also employed for the validation of the robustness of the proposed approach. Numerical and experimental results show that the proposed approach can not only satisfactorily estimate structural states, but also identify unknown loadings with acceptable accuracy for both linear and nonlinear systems.

• The korean journal of orthodontics
• /
• v.51 no.4
• /
• pp.293-300
• /
• 2021

In this report, we demonstrate the effectiveness of the Invisalign^® system in the treatment of severe gingival recession and bone dehiscence through torque, translation, and intrusion movements in a young woman. Cone-beam computed tomography was used to assess bone parameters and check the teeth during treatment. The root of the mandibular right central incisor, which was buccally positioned and exhibited bone dehiscence of 9.4 mm, was moved toward the center of the alveolar process by using the Invisalign^® system and SmartForce^® features. The patient was monitored by a periodontist throughout the orthodontic treatment period. Her gingival recession reduced, while the bone dehiscence reduced from 9.40 mm to 3.14 mm. Thus, movement of the root into the alveolus promoted bone neoformation and treated the gingival recession. The findings from this case suggest that orthodontic treatment using the Invisalign^® system, along with periodontal monitoring, can aid in the treatment of gingival recession and alveolar defects.

• Structural Engineering and Mechanics
• /
• v.72 no.2
• /
• pp.217-227
• /
• 2019

The methodology known as "shape sensing" allows the reconstruction of the displacement field of a structure starting from strain measurements, with considerable implications for structural monitoring, as well as for the control and implementation of smart structures. An approach to shape sensing is based on the inverse Finite Element Method (iFEM) that uses a variational principle enforcing a least-squares compatibility between measured and analytical strain measures. The structural response is reconstructed without the knowledge of the mechanical properties and load conditions but based only on the relationship between displacements and strains. In order to efficiently apply iFEM to the most common structural typologies of civil engineering, its formulation according to the kinematical assumptions of the Bernoulli-Euler theory is presented. Two beam inverse finite elements are formulated for different loading conditions. Depending on the type of element, the relationship between the minimum number of required measurement stations and the interpolation order is defined. Several examples representing common applications of civil engineering and involving beams and frames are presented. To simulate the experimental strain data at the station points and to verify the accuracy of the displacements obtained with the iFEM shape sensing procedure, a direct FEM analysis of the considered structures is performed using the LUSAS software.

• Smart Structures and Systems
• /
• v.30 no.3
• /
• pp.273-286
• /
• 2022

In recent years, vision-based monitoring has received great attention. However, structural identification using vision-based displacement measurements is far less established. Especially, simultaneous identification of structural systems and unknown excitation using vision-based displacement measurements is still a challenging task since the unknown excitations do not appear directly in the observation equations. Moreover, measurement accuracy deteriorates over a wider field of view by vision-based monitoring, so, only a portion of the structure is measured instead of targeting a whole structure when using monocular vision. In this paper, the identification of structural system and excitations using vision-based displacement measurements is investigated. It is based on substructure identification approach to treat of problem of limited field of view of vision-based monitoring. For the identification of a target substructure, substructure interaction forces are treated as unknown inputs. A smoothing extended Kalman filter with unknown inputs without direct feedthrough is proposed for the simultaneous identification of substructure and unknown inputs using vision-based displacement measurements. The smoothing makes the identification robust to measurement noises. The proposed algorithm is first validated by the identification of a three-span continuous beam bridge under an impact load. Then, it is investigated by the more difficult identification of a frame and unknown wind excitation. Both examples validate the good performances of the proposed method.

• Smart Structures and Systems
• /
• v.28 no.6
• /
• pp.827-838
• /
• 2021

The dynamic displacement is considered to be an important indicator of structural safety, and becomes an indispensable part of Structural Health Monitoring (SHM) system for high-speed railway bridges. This paper proposes an indirect strain based dynamic displacement reconstruction methodology for high-speed railway box girders. For the typical box girders under eccentric train load, the plane section assumption and elementary beam theory is no longer applicable due to the bend-torsion coupling effects. The monitored strain was decoupled into bend and torsion induced strain, pre-trained multi-output support vector regression (M-SVR) model was employed for such decoupling process considering the sensor layout cost and reconstruction accuracy. The decoupled strained based displacement could be reconstructed respectively using box girder plate element analysis and mode superposition principle. For the transformation modal matrix has a significant impact on the reconstructed displacement accuracy, the modal order would be optimized using particle swarm algorithm (PSO), aiming to minimize the ill conditioned degree of transformation modal matrix and the displacement reconstruction error. Numerical simulation and dynamic load testing results show that the reconstructed displacement was in good agreement with the simulated or measured results, which verifies the validity and accuracy of the algorithm proposed in this paper.

• Smart Structures and Systems
• /
• v.32 no.2
• /
• pp.83-99
• /
• 2023

The temperature prediction approaches of three important locations in an operational longitudinal slab track-bridge structure by using three typical neural network methods based on the field measuring platform of four meteorological factors and internal temperature. The measurement experiment of four meteorological factors (e.g., ambient temperature, solar radiation, wind speed, and humidity) temperature in the three locations of the longitudinal slab and base plate of three important locations (e.g., mid-span, beam end, and Wide-Narrow Joint) were conducted, and then their characteristics were analyzed, respectively. Furthermore, temperature prediction effects of three locations under five various meteorological conditions are tested by using three neural network methods, respectively, including the Artificial Neural Network (ANN), the Long Short-Term Memory (LSTM), and the Convolutional Neural Network (CNN). More importantly, the predicted effects of solar radiation in four meteorological factors could be identified with three indicators (e.g., Root Means Square Error, Mean Absolute Error, Correlation Coefficient of R2). In addition, the LSTM method shows the best performance, while the CNN method has the best prediction effect by only considering a single meteorological factor.

• Computers and Concrete
• /
• v.31 no.5
• /
• pp.371-384
• /
• 2023

Precast roofing systems employing prestressed elements often serve as smart structural solutions for the construction of industrial buildings. The precast concrete elements usually employed are highly engineered, and often consist in thin-walled members, characterised by a complex behaviour in fire. The present study was carried out after a fire event damaged a precast industrial building made with prestressed beam and roof elements, and non-prestressed curved barrel vault elements interposed in between the spaced roof elements. As a consequence of the exposure to the fire, the main elements were found standing, although some locally damaged and distorted, and the local collapse of few curved barrel vault elements was observed in one edge row only. In order to understand and interpret the observed structural performance of the roof system under fire, a full fire safety engineering process was carried out according to the following steps: (a) realistic temperature-time curves acting on the structural elements were simulated through computational fluid dynamics, (b) temperature distribution within the concrete elements was obtained with non-linear thermal analysis in variable regime, (c) strength and deformation of the concrete elements were checked with non-linear thermal-mechanical analysis. The analysis of the results allowed to identify the causes of the local collapses occurred, attributable to the distortion caused by temperature to the elements causing loss of support in early fire stage rather than to the material strength reduction due to the progressive exposure of the elements to fire. Finally, practical hints are provided to avoid such a phenomenon to occur when designing similar structures.

• Steel and Composite Structures
• /
• v.49 no.6
• /
• pp.603-614
• /
• 2023

In this paper, frequency analysis of curved functionally graded (FG) nanobeam by consideration of deepness effect has been studied. Differential transform method (DTM) has been used to obtain frequency responses. The nonlocal theory of Eringen has been applied to consider nanoscales. Material properties are supposed to vary in radial direction according to power-law distribution. Differential equations and related boundary conditions have been derived using Hamilton's principle. Finally, by consideration of nonlocal theory, the governing equations have been derived. Natural frequencies have been obtained using semi analytical method (DTM) for different boundary conditions. In order to study the effect of deepness, the deepness term is considered in strain field. The effects of the gradient index, radius of curvature, the aspect ratio, the nonlocal parameter and interaction of aforementioned parameters on frequency value for different boundary conditions such as clamped-clamped (C-C), clamped-hinged (C-H), and clamped-free (C-F) have been investigated. In addition, the obtained results are compared with the results in previous literature in order to validate present study, a good agreement was observed in the present results.

• Smart Structures and Systems
• /
• v.33 no.3
• /
• pp.201-215
• /
• 2024

Spline chirplet transform and local maximum synchrosqueezing are introduced to present a novel structural instantaneous frequency (IF) identification method named local maximum synchrosqueezing spline chirplet transform (LMSSSCT). Namely spline chirplet transform (SCT), a transform is firstly introduced based on classic chirplet transform and spline interpolated kernel function. Applying SCT in association with local maximum synchrosqueezing, the LMSSSCT is then proposed. The index of accuracy and Rényi entropy show that LMSSSCT outperforms the other time-frequency analysis (TFA) methods in processing analytical signals, especially in the presence of noise. Numerical examples of a Duffing nonlinear system with single degree of freedom and a two-layer shear frame structure with time-varying stiffness are used to verify the effectiveness of structural IF identification. Moreover, a nonlinear supported beam structure test is conducted and the LMSSSCT is utilized for structural IF identification. Numerical simulation and experimental results demonstrate that the presented LMSSSCT can effectively identify the IFs of nonlinear structures and time-varying structures with good accuracy and stability.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.46 no.12
• /
• pp.105-112
• /
• 2009

In this paper, we investigated abnormal ESD failure on guard-rings in the smart power IC fabricated with $0.35{\mu}m$ Bipolar-CMOS-DMOS (BCD) technology. Initially, ESD failure occurred below 200 V in the Machine Model (MM) test due to current crowding in the parasitic diode associated with the guard-rings which are generally adopted to prevent latch-up in high voltage devices. Optical Beam Induced Resistance Charge (OBIRCH) and Scanning Electronic Microscope (SEM) were used to find the failure spot and 3-D TCAD was used to verify cause of failure. According to the simulation results, excessive current flows at the comer of the guard-ring isolated by Local Oxidation of Silicon (LOCOS) in the ESD event. Eventually, the ESD failure occurs at that comer of the guard-ring. The modified comer design of the guard-ring is proposed to resolve such ESD failure. The test chips designed by the proposed modification passed MM test over 200 V. Analyzing the test chips statistically, ESD immunity was increased over 20 % in MM mode test. In order to avoid such ESD failure, the automatic method to check the weak point in the guard-ring is also proposed by modifying the Design Rule Check (DRC) used in BCD technology. This DRC was used to check other similar products and 24 errors were found. After correcting the errors, the measured ESD level fulfilled the general industry specification such as HBM 2000 V and MM 200V.