• Smart Structures and Systems
• /
• v.13 no.6
• /
• pp.975-991
• /
• 2014

The objective of this study is to develop a reliable method for locating cracks in a beam using data fusion of fractal dimension features of operating deflection shapes. The Katz's fractal dimension curve of an operating deflection shape is used as a basic feature of damage. Like most available damage features, the Katz's fractal dimension curve has a notable limitation in characterizing damage: it is unresponsive to damage near the nodes of structural deformation responses, e.g., operating deflection shapes. To address this limitation, data fusion of Katz's fractal dimension curves of various operating deflection shapes is used to create a sophisticated fractal damage feature, the 'overall Katz's fractal dimension curve'. This overall Katz's fractal dimension curve has the distinctive capability of overcoming the nodal effect of operating deflection shapes so that it maximizes responsiveness to damage and reliability of damage localization. The method is applied to the detection of damage in numerical and experimental cases of cantilever beams with single/multiple cracks, with high-resolution operating deflection shapes acquired by a scanning laser vibrometer. Results show that the overall Katz's fractal dimension curve can locate single/multiple cracks in beams with significantly improved accuracy and reliability in comparison to the existing method. Data fusion of fractal dimension features of operating deflection shapes provides a viable strategy for identifying damage in beam-type structures, with robustness against node effects.

• Smart Structures and Systems
• /
• v.25 no.5
• /
• pp.605-617
• /
• 2020

The existence of damages in structures causes changes in the physical properties by reducing the modal parameters. In this paper, we develop a two-stages approach based on normalized Modal Strain Energy Damage Indicator (nMSEDI) for quick applications to predict the location of damage. A two-dimensional IsoGeometric Analysis (2D-IGA), Machine Learning Algorithm (MLA) and optimization techniques are combined to create a new tool. In the first stage, we introduce a modified damage identification technique based on frequencies using nMSEDI to locate the potential of damaged elements. In the second stage, after eliminating the healthy elements, the damage index values from nMSEDI are considered as input in the damage quantification algorithm. The hybrid of Teaching-Learning-Based Optimization (TLBO) with Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) are used along with nMSEDI. The objective of TLBO is to estimate the parameters of PSO-ANN to find a good training based on actual damage and estimated damage. The IGA model is updated using experimental results based on stiffness and mass matrix using the difference between calculated and measured frequencies as objective function. The feasibility and efficiency of nMSEDI-PSO-ANN after finding the best parameters by TLBO are demonstrated through the comparison with nMSEDI-IGA for different scenarios. The result of the analyses indicates that the proposed approach can be used to determine correctly the severity of damage in beam structures.

• Smart Structures and Systems
• /
• v.26 no.5
• /
• pp.657-666
• /
• 2020

A rotational pulse-echo ultrasonic propagation imager that can inspect cylindrical specimens for material nondestructive evaluations is proposed herein. In this system, a laser-generated ultrasonic bulk wave is used for inspection, which enables a clear visualization of subsurface defects with a precise reproduction of the damage shape and size. The ultrasonic waves are generated by a Q-switched laser that impinges on the outer surface of the specimen walls. The generated waves travel through the walls and their echo is detected by a Laser Doppler Vibrometer (LDV) at the same point. To obtain the optimal Signal-to-Noise Ratio (SNR) of the measured signal, the LDV requires the sensed surface to be at a right angle to the laser beam and at a predefined constant standoff distance from the laser head. For flat specimens, these constraints can be easily satisfied by performing a raster scan using a dual-axis linear stage. However, this arrangement cannot be used for cylindrical specimens owing to their curved nature. To inspect the cylindrical specimens, a circular scan technology is newly proposed for pulse-echo laser ultrasound. A rotational stage is coupled with a single-axis linear stage to inspect the desired area of the specimen. This system arrangement ensures that the standoff distance and beam incidence angle are maintained while the cylindrical specimen is being inspected. This enables the inspection of a curved specimen while maintaining the optimal SNR. The measurement result is displayed in parallel with the on-going inspection. The inspection data used in scanning are mapped from rotational coordinates to linear coordinates for visualization and post-processing of results. A graphical user interface software is implemented in C++ using a QT framework and controls all the individual blocks of the system and implements the necessary image processing, scan calculations, data acquisition, signal processing and result visualization.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.26 no.8
• /
• pp.710-717
• /
• 2015

In this paper, we design an array antenna structure based on a patch ESPAR(Electronically Steerable Parasitic Array Radiator) antenna with three elements for reliable communication in high-speed railway wireless communication. The ESPAR antenna consists of the active element with a single RF-chain and the parasitic elements surrounding an active element. The ESPAR antenna is capable of beamforming by adjusting the reactance of the parasitic element. We propose a vertical array antenna structure based on the patch ESPAR antenna and simulate it according to the change of the number of antennas and the distance between antenna rows. The simulation results show that we can get the maximum beam gain and highest directivity when the distance between antenna rows is ${\lambda}$.

• Smart Structures and Systems
• /
• v.17 no.6
• /
• pp.957-980
• /
• 2016

Structural damage detection (SDD) is a challenging task in the field of structural health monitoring (SHM). As an exploring attempt to the SDD problem, a hybrid self-adaptive Firefly-Nelder-Mead (SA-FNM) algorithm is proposed for the SDD problem in this study. First of all, the basic principle of firefly algorithm (FA) is introduced. The Nelder-Mead (NM) algorithm is incorporated into FA for improving the local searching ability. A new strategy for exchanging the information in the firefly group is introduced into the SA-FNM for reducing the computation cost. A random walk strategy for the best firefly and a self-adaptive control strategy of three key parameters, such as light absorption, randomization parameter and critical distance, are proposed for preferably balancing the exploitation and exploration ability of the SA-FNM. The computing performance of the SA-FNM is evaluated and compared with the basic FA by three benchmark functions. Secondly, the SDD problem is mathematically converted into a constrained optimization problem, which is then hopefully solved by the SA-FNM algorithm. A multi-step method is proposed for finding the minimum fitness with a big probability. In order to assess the accuracy and the feasibility of the proposed method, a two-storey rigid frame structure without considering the finite element model (FEM) error and a steel beam with considering the model error are taken examples for numerical simulations. Finally, a series of experimental studies on damage detection of a steel beam with four damage patterns are performed in laboratory. The illustrated results show that the proposed method can accurately identify the structural damage. Some valuable conclusions are made and related issues are discussed as well.

• Smart Structures and Systems
• /
• v.15 no.3
• /
• pp.717-733
• /
• 2015

Modal parameters of a structure are commonly used quantities for system identification and damage detection. With a limited number of studies on the statistics assessment of modal parameters, this paper presents procedures to properly account for the uncertainties present in the process of extracting modal parameters. Particularly, this paper focuses on how to deal with the measurement error in an ambient vibration test and the modeling error resulting from a modal parameter extraction process. A bootstrap approach is adopted, when an ensemble of a limited number of noised time-history response recordings is available. To estimate the modeling error associated with the extraction process, a model prediction expansion approach is adopted where the modeling error is considered as an "adjustment" to the prediction obtained from the extraction process. The proposed procedures can be further incorporated into the probabilistic analysis of applications where the modal parameters are used. This study considers the effects of the measurement and modeling errors and can provide guidance in allocating resources to improve the estimation accuracy of the modal data. As an illustration, the proposed procedures are applied to extract the modal data of a damaged beam, and the extracted modal data are used to detect potential damage locations using a damage detection method. It is shown that the variability in the modal parameters can be considered to be quite low due to the measurement and modeling errors; however, this low variability has a significant impact on the damage detection results for the studied beam.

• Smart Structures and Systems
• /
• v.26 no.3
• /
• pp.391-401
• /
• 2020

The present article reports the feasibility of the electrical energy generation from ambient low-frequency vibration using a piezoelectric material mounted on a bimorph cantilever beam actuator. A corresponding higher-order analytical model is developed using MATLAB in conjunction with finite element method under low-frequency with both damped and undamped conditions. An alternate model is also developed to check the material and dimensional viability of both piezoelectric materials (mainly focussed to PVDF and PZT) and the base material. Also, Genetic Algorithm is implemented to find the optimum dimensions which can produce the higher values of voltage at low-frequency frequencies (≤ 100 Hz). The delamination constraints are employed to avoid inter-laminar stresses and to increase the fracture toughness. The delamination has been done using a Teflon sheet sandwiched in between base plates and the piezo material is stuck to the base plate using adhesives. The analytical model is tested for both homogenous and isotropic material characteristics of the base material and extended to investigate the effect of the different geometrical parameters (base plate dimensions, piezo layer dimensions and placement, delamination thickness and placement, excitation frequency) on the model responses of the bimorph cantilever beam. It has been observed that when the base material characteristics are homogenous, the efficiency of the model remains higher when compared to the condition when it is of isotropic material. The necessary convergence behaviour of the current numerical model has been established and checked for the accuracy by comparing with available published results. Finally, using the results obtained from the model, a prototype is fabricated for the experimental validation via a suitable circuit considering Glass fibre and Aluminium as the bimorph material.

• Smart Structures and Systems
• /
• v.15 no.1
• /
• pp.99-117
• /
• 2015

The Stonecutters Bridge (SCB) in Hong Kong is the third-longest cable-stayed bridge in the world with a main span stretching 1,018 m between two 298 m high single-leg tapering composite towers. A Wind and Structural Health Monitoring System (WASHMS) is being implemented on SCB by the Highways Department of The Hong Kong SAR Government, and the SCB-WASHMS is composed of more than 1,300 sensors in 15 types. In order to establish a linkage between structural health monitoring and maintenance management, a Structural Health Rating System (SHRS) with relevant rating tools and indices is devised. On the basis of a 3D space frame finite element model (FEM) of SCB and model updating, this paper presents the development of an SHR-oriented 3D multi-scale FEM for the purpose of load-resistance analysis and damage evaluation in structural element level, including modeling, refinement and validation of the multi-scale FEM. The refined 3D structural segments at deck and towers are established in critical segment positions corresponding to maximum cable forces. The components in the critical segment region are modeled as a full 3D FEM and fitted into the 3D space frame FEM. The boundary conditions between beam and shell elements are performed conforming to equivalent stiffness, effective mass and compatibility of deformation. The 3D multi-scale FEM is verified by the in-situ measured dynamic characteristics and static response. A good agreement between the FEM and measurement results indicates that the 3D multi-scale FEM is precise and efficient for WASHMS and SHRS of SCB. In addition, stress distribution and concentration of the critical segments in the 3D multi-scale FEM under temperature loads, static wind loads and equivalent seismic loads are investigated. Stress concentration elements under equivalent seismic loads exist in the anchor zone in steel/concrete beam and the anchor plate edge in steel anchor box of the towers.

• Smart Structures and Systems
• /
• v.10 no.4_5
• /
• pp.411-426
• /
• 2012

The Canton Tower (formerly named Guangzhou New TV Tower) of 610 m high has been instrumented with a long-term structural health monitoring (SHM) system consisting of over 700 sensors of sixteen types. Under the auspices of the Asian-Pacific Network of Centers for Research in Smart Structures Technology (ANCRiSST), an SHM benchmark problem for high-rise structures has been developed by taking the instrumented Canton Tower as a host structure. This benchmark problem aims to provide an international platform for direct comparison of various SHM-related methodologies and algorithms with the use of real-world monitoring data from a large-scale structure, and to narrow the gap that currently exists between the research and the practice of SHM. This paper first briefs the SHM system deployed on the Canton Tower, and the development of an elaborate three-dimensional (3D) full-scale finite element model (FEM) and the validation of the model using the measured modal data of the structure. In succession comes the formulation of an equivalent reduced-order FEM which is developed specifically for the benchmark study. The reduced-order FEM, which comprises 37 beam elements and a total of 185 degrees-of-freedom (DOFs), has been elaborately tuned to coincide well with the full-scale FEM in terms of both modal frequencies and mode shapes. The field measurement data (including those obtained from 20 accelerometers, one anemometer and one temperature sensor) from the Canton Tower, which are available for the benchmark study, are subsequently presented together with a description of the sensor deployment locations and the sensor specifications.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.1
• /
• pp.709-714
• /
• 2017

Structures like bridges or buildings need to be checked continuously to diagnose their safety. However, it is extremely difficult for the people who access such structures to check all areas directly. To overcome this problem, there is a lot of active research into structural health monitoring (SHM) with wireless sensor nodes (WSNs). In this paper, for more accurate checking of SHM with WSNs, we experimentally compare and evaluate the performance of Xenomai, which provides real-time processing under the traditional Linux kernel. For this purpose, we patch Xenomai into the traditional Linux kernel of a commercial embedded board, Raspberry Pi, and implement a task that periodically reads vibration data of the z-axis from an accelerometer in order to analyze the natural frequency of cantilever beams. Reading the data from the traditional Linux kernel with the same method, we analyze the natural frequency of the cantilever beams using Smart Office Analyzer. Finally, to review the validity of Xenomai for WSNs, we obtain vibration data on the z-axis from the accelerometer via wired network and compared and analyzed them the same way.