• Smart Structures and Systems
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• v.22 no.5
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• pp.587-609
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• 2018

There is greater significance in identifying the incipient damages in structures at the time of their initiation as timely rectification of these minor incipient cracks can save huge maintenance cost. However, the change in the global dynamic characteristics of a structure due to these subtle damages are insignificant enough to detect using the majority of the current damage diagnostic techniques. Keeping this in view, we propose a hybrid damage diagnostic technique for detection of minor incipient damages in the structures. In the proposed automated hybrid algorithm, the raw dynamic signatures obtained from the structure are decomposed to uni-modal signals and the dynamic signature are reconstructed by identifying and combining only the uni-modal signals altered by the minor incipient damage. We use these reconstructed signals for damage diagnostics using ARMAX model. Numerical simulation studies are carried out to investigate and evaluate the proposed hybrid damage diagnostic algorithm and their capability in identifying minor/incipient damage with noisy measurements. Finally, experimental studies on a beam are also presented to compliment the numerical simulations in order to demonstrate the practical application of the proposed algorithm.

• Structural Engineering and Mechanics
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• v.15 no.3
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• pp.285-297
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• 2003

Complementing recent advances made in the field of structural health monitoring and damage detection, the concept of a wireless sensing network with distributed computational power is proposed. The fundamental building block of the proposed sensing network is a wireless sensing unit capable of acquiring measurement data, interrogating the data and transmitting the data in real time. The computational core of a prototype wireless sensing unit can potentially be utilized for execution of embedded engineering analyses such as damage detection and system identification. To illustrate the computational capabilities of the proposed wireless sensing unit, the fast Fourier transform and auto-regressive time-series modeling are locally executed by the unit. Fast Fourier transforms and auto-regressive models are two important techniques that have been previously used for the identification of damage in structural systems. Their embedment illustrates the computational capabilities of the prototype wireless sensing unit and suggests strong potential for unit installation in automated structural health monitoring systems.

• Smart Structures and Systems
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• v.12 no.2
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• pp.209-233
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• 2013

With an annual growth rate of about 30%, wind energy systems, such as wind turbines, represent one of the fastest growing renewable energy technologies. Continuous structural health monitoring of wind turbines can help improving structural reliability and facilitating optimal decisions with respect to maintenance and operation at minimum associated life-cycle costs. This paper presents an integrated monitoring system that is designed to support structural assessment and life-cycle management of wind turbines. The monitoring system systematically integrates a wide variety of hardware and software modules, including sensors and computer systems for automated data acquisition, data analysis and data archival, a multiagent-based system for self-diagnosis of sensor malfunctions, a model updating and damage detection framework for structural assessment, and a management module for monitoring the structural condition and the operational efficiency of the wind turbine. The monitoring system has been installed on a 500 kW wind turbine located in Germany. Since its initial deployment in 2009, the system automatically collects and processes structural, environmental, and operational wind turbine data. The results demonstrate the potential of the proposed approach not only to ensure continuous safety of the structures, but also to enable cost-efficient maintenance and operation of wind turbines.

• Structural Monitoring and Maintenance
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• v.6 no.3
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• pp.237-254
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• 2019

This paper presents an improved time series based damage detection approach with experimental verifications for detection, localization, and quantification of damage in shear-type structures under varying mass effects using output-only vibration data. The proposed method can be very effective for automated monitoring of buildings to develop proactive maintenance strategies. In this method, Auto-Regressive Moving Average models with eXogenous inputs (ARMAX) are built to represent the dynamic relationship of different sensor clusters. The damage features are extracted based on the relative difference of the ARMAX model coefficients to identify the existence, location and severity of damage of stiffness and mass separately. The results from a laboratory-scale shear type structure show that different damage scenarios are revealed successfully using the approach. At the end of this paper, the methodology limitations are also discussed, especially when simultaneous occurrence of mass and stiffness damage at multiple locations.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1994.04a
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• pp.1-8
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• 1994

An automated procedure which allows adaptation of spatial and time discretization simultaneously in finite element analysis of linear elastodynamic problems is presented. For dynamic problems having responses dominated by high frequency modes, such as those with impact, explosive, traveling and earthquake loads high gradient stress regions change their locations from time to time. And the time step size may need to vary in order to deal with whole process ranging from transient phase to steady state phase. As the sizes of elements in space vary in different regions, the procedure also permits different time stepping. In such a way, the best performance attainable by the finite element method can be achieved. In this study, we estimate both of the kinetic energy error and stran energy error induced by spatial and time discretization in a consistent manner. Numerical examples are used to demonstrate the performance of the procedure.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.10
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• pp.74-80
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• 2020

Crawler-type hydraulic devices facilitate forward and backward driving of construction equipment by converting power into mechanical energy. The existing hydraulic device performance test process is time- and labor-intensive. This study aims to improve efficiency and productivity by automating the hydraulic device production performance test processes, which have been separately conducted so far. We also used SolidWorksⓇ, a 3D modeling program, and ANSYSⓇ, a structural analysis tool, for structural analysis and to verify the suitability of fixing pins required for connecting a hydraulic device to performance test equipment. Our results that employing an automated hydraulic device performance test process improves efficiency.

• Structural Monitoring and Maintenance
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• v.1 no.1
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• pp.111-130
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• 2014

The increased use of carbon fiber reinforced polymer (CFRP) in retrofitting reinforced concrete (RC) members has led to the need to develop non-destructive techniques that can monitor and characterize the unique damage mechanisms exhibited by such structural systems. This paper presented the damage characterization results of six CFRP retrofitted RC beam specimens tested in the laboratory and monitored using acoustic emission (AE). The focus of this study was to continuously monitor the change in AE parameters and analyze them both qualitatively and quantitatively, when brittle failure modes such as debonding occur in these beams. Although deterioration of structural integrity was traceable and can be quantified by monitoring the AE data, individual failure mode characteristics could not be identified due to the complexity of the system failure modes. In all, AE was an effective non-destructive monitoring tool that can trace the failure progression in RC beams retrofitted with CFRP. It would be advantageous to isolate signals originating from the CFRP and concrete, leading to a more clear understanding of the progression of the brittle damage mechanism involved in such a structural system. For practical applications, future studies should focus on spectral analysis of AE data from broadband sensors and automated pattern recognition tools to classify and better correlate AE parameters to failure modes observed.

• Journal of Mechanical Science and Technology
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• v.20 no.2
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• pp.251-261
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• 2006

The objective of this work is to apply artificial neural networks for solving inverse problems in the structural optimization of a fiber optic pressure sensor. For the sensor under investigation to achieve a desired accuracy, the change in the distance between the tips of the two fibers due to the applied pressure should not interfere with the phase change due to the change in the density of the air between the two fibers. Therefore, accurate dynamic analysis and structural optimization of the sensor is essential to ensure the accuracy of the measurements provided by the sensor. To this end, a normal mode analysis and a transient response analysis of the sensor were performed by combining commercial finite element analysis package, MSC/NASTRAN, and MATLAB. Furthermore, a parametric study on the design of the sensor was performed to minimize the size of the sensor while fulfilling a number of constraints. In performing the parametric study, the need for a relationship between the design parameters and the response of the sensor was fulfilled by using a neural network. The whole process of the dynamic analysis using commercial finite element analysis package and the parameter optimization of the sensor were automated within the MATLAB environment.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.241-246
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• 2008

Design of a high-speed railway line requires collaboration of heterogeneous application systems and of engineers with different background. Object-based 3D models with metadata can be a shared information model for the effective collaborative design. In this paper, railway infrastructure information model is proposed to enable integrated and inter-operable works throughout the life-cycle of the railway infrastructures, from planning to maintenance. In order to develop the model, object-based 3-D models were built for a 10km railway among Korea high-speed railway lines. The model has basically three information layers for designers, contractors and an owner, respectively. Prestressed concrete box-girders are the most common superstructure of bridges. The design information layer has metadata on requirements, design codes, geometry, analysis and so on. The construction layer has data on drawings, real data for material and products, schedules and so on. The maintenance layer for the owner has the final geometry, material data, products and their suppliers and so on. These information has its own data architecture which is derived from similar concept of product breakdown structure(PBS) and work breakdown structure(WBS). The constructed RIIM for the infrastructures of the high-speed railway was successfully applied to various areas such as design check, structural analysis, automated estimation, construction simulation, virtual viewing, and digital mock-up. The integrated information model can realize virtual construction system for railway lines and dramatically increase the productivity of the whole engineering process.

• Proceedings of the KSR Conference
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• 1999.11a
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• pp.558-565
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• 1999

Rubber wheel-type AGT has two major kinds of bogie; one is the bogie type and the other and passenger loads. This paper deals with the statics analysis for two types of bogie frame subjected to combined external forces, as well as independent ones specified in UIC 515-4. Furthermore, the dynamics analysis is performed under vibrational loading conditions so as to compare dynamic characteristics, Numerical results by using commercial packages, Ⅰ-DEAS and NASTRAN show that maximum stresses do not exceed the yielding level of material used for both bogies. From an overall viewpoint of strength, the bogie type turns out to be superior to the steering type except the case of a lateral loading. It is also observed that the steering type shows a be stiffened. It is strongly anticipated that vibrational fatigue analysis should be carried out under realistic loading conditions closely matching to situations such as running surface and lateral clearances along the guideway.