• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.669-674
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• 2007

To develop a promising hybrid structural health monitoring (SHM) system, a combined use of structural vibration and electro-mechanical (EM) impedance is proposed. The hybrid SHM system is designed to use vibration characteristics as global index and EM impedance as local index. The proposed health monitoring scheme is implemented into prestressed concrete (PSC) girder bridges for which a series of damage scenarios are designed to simulate various prestress-loss situations at which the target bridges car experience during their service life. The measured experimental results, modal parameters and electro-magnetic impedance signatures, are carefully analyzed to recognize the occurrence of damage and furthermore to indicate its location.

• Journal of Welding and Joining
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• v.35 no.3
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• pp.75-81
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• 2017

Recently in the welding field, the establishment of unmanned and automated systems are rapidly developing. Accurate interpretation of the welding phenomenon is applied a number of monitoring systems. In this paper, butt welding (6t) type I using Plasma-MIG welding was carried out. And we evaluated characteristics of the Al-5083 aluminium alloy in Plasma-MIG hybrid welding. Process variables including the plasma current, MIG voltage, wire feeding rate and the welding speed were used. Butt welding was conducted 1 pass. Argon gas was used as the protective gas that results from the experiment were able to achieve full penetration. In addition to monitoring the welding process occurring during MIG welding current, welding votage and Plasma current, voltage were collected in real time, the photodiode and CCD cameras observing the phenomenon that the welding is in progress were measured using a quantity of light.

• Computational Structural Engineering
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• v.9 no.2
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• pp.163-171
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• 1996

A hybrid knowledge model which amalgamates an object-oriented modeling approach and logic programming implementation is presented for structural health monitoring and diagnosis of instrumented structures. Domain knowledge in structural monitoring and diagnosis is formalized and represented in a logic-based object-oriented modeling environment. The model and environment have been implemented and illustrated in the context of a laboratory case study of damage detection in a successively damaged steel structure.

• Proceedings of the Korea Concrete Institute Conference
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• 2005.05a
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• pp.359-362
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• 2005

Self diagnosis monitoring system is defined as concrete structural carbon and glass hybrid fiber materials, in response to the change in external disturbance and environments, toward structural safety and serviceability as well as the extension of structural service life. In this study, carbon and glass hybrid fiber materials were investigated fundamentally for the applicability of self diagnosis in smart concrete structural system as embedded functions of sensors.

• 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.40 no.5
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• pp.719-743
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• 2011

A hybrid damage monitoring scheme using parallel acceleration-impedance approaches is proposed to detect girder damage and support damage in steel plate-girder bridges which are under ambient train-induced excitations. The hybrid scheme consists of three phases: global and local damage monitoring in parallel manner, damage occurrence alarming and local damage identification, and detailed damage estimation. In the first phase, damage occurrence in a structure is globally monitored by changes in vibration features and, at the same moment, damage occurrence in local critical members is monitored by changes in impedance features. In the second phase, the occurrence of damage is alarmed and the type of damage is locally identified by recognizing patterns of vibration and impedance features. In the final phase, the location and severity of the locally identified damage are estimated by using modal strain energy-based damage index methods. The feasibility of the proposed scheme is evaluated on a steel plate-girder bridge model which was experimentally tested under model train-induced excitations. Acceleration responses and electro-mechanical impedance signatures were measured for several damage scenarios of girder damage and support damage.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.197-202
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• 2008

In this paper, a hybrid vibration-impedance approaches is newly proposed to detect the occurrence of damage, the location of damage, and extent of damage in steel plate-girder bridges. The hybrid scheme mainly consists of three sequential phases: 1) to alarm the occurrence of damage, 2) to classify the alarmed damage, and 3) to estimate the classified damage in detail. Damage types of interest include flexural stiffness-loss in girder and bolts-loose in supports. In the first phase, the global occurrence of damage is alarmed by monitoring changes in acceleration features. In the second phase, the alarmed damage is classified into subsystems by recognizing patterns of impedance features. In the final phase, the location and the extent of damage are estimated by using modal strain energy-based damage index method and root mean square deviation method. The feasibility of the proposed system is evaluated on a laboratory-scaled steel plate-girder bridge model for which hybrid vibration-impedance signatures were measured for several damage scenarios.

• Structural Monitoring and Maintenance
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• v.9 no.2
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• pp.179-200
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• 2022

This paper proposes a data-driven methodology for online early damage identification under changing environmental conditions. The proposed method relies on two data analysis methods: feature-based method and hybrid principal component analysis (PCA) and kernel PCA to separate damage from environmental influences. First, spectral sub-band features, namely, spectral sub-band centroids (SSCs) and log spectral sub-band energies (LSSEs), are proposed as damage-sensitive features to extract damage information from measured structural responses. Second, hybrid modeling by integrating PCA and kernel PCA is performed on the spectral sub-band feature matrix for data normalization to extract both linear and nonlinear features for nonlinear procedure monitoring. After feature normalization, suppressing environmental effects, the control charts (Hotelling T² and SPE statistics) is implemented to novelty detection and distinguish damage in structures. The hybrid PCA-KPCA technique is compared to KPCA by applying support vector machine (SVM) to evaluate the effectiveness of its performance in detecting damage. The proposed method is verified through numerical and full-scale studies (a Bridge Health Monitoring (BHM) Benchmark Problem and a cable-stayed bridge in China). The results demonstrate that the proposed method can detect the structural damage accurately and reduce false alarms by suppressing the effects and interference of environmental variations.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.3 no.4
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• pp.20-29
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• 2004

A Tool wear monitoring system is indispensable for better machining productivity with guarantee of machining safety by informing the tool changing time in automated and unmanned CNC machining. Different from monitoring using other signals, the monitoring of spindle current has been used without requiring additional sensors on machine tools. For the reliable tool wear monitoring, current signal only of tool wear should be extracted from other parameters to avoid exhaustive analyses on signals in which all parameters are fused. In this paper, influences of force components of parameters on measured spindle current are investigated and a hybrid approach to cutting force regulation is employed for tool wear signal extraction in the spindle current. Finally, wear levels are verified with experimental results by means of real-time feedrate aspects changed to regulate the force component of tool wear.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.338-342
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• 2003

Hybrid machine is based on hardware technologies of machine tool and software technologies of open architecture controller. In machining technology, combination technology of turning, milling, and grinding and in machining energy technology. combination of mechanical, electrical, and chemical technology are developed. This paper describes hybrid machine technology for combination of machining, on-machine measurement, on-machine CAM, and on-machine remote monitoring and control in open architecture controller environment. For on-machine measurement, non-contact measurement technology based on CAD information is developed. For on-machine CAM, interactive CAM program for automatic NC program generation and tool path simulation is developed. For generation on-machine remote monitoring and control, suitable interface method between web program and CNC is proposed. The developed hybrid machine technology is implemented in 3 axes milling machine for evaluation of operablity.