• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.5
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• pp.520-526
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• 2016

Squeal noise is a typical brake noise that is annoying to both passengers and pedestrians. Its frequency range is fairly wide from 1 kHz to 18 kHz, which can be distressful to people. The brake squeal noise occurs due to various mechanisms, such as the mode coupling of the brake system, self-excited vibration, unstable wear, and others. In this study, several parameters involved in the generation of a squeal noise are investigated experimentally by using a brake noise dynamometer. The speed, caliper pressure, torque, and friction coefficient are measured as functions of time on the dynamometer. The contact pressure and temperature distributions of the disc and the pad are also measured by using a thermal imaging camera and a pressure mapping system. As a result of the simultaneous measurement of the friction coefficient and squeal amplitude as functions of the velocity, it is found that the onset of the squeal may be predicted from the ${\mu}-v$ curve. It is also found that a non-uniform contact pressure causes instability and, in turn, a squeal. Based on the analysis results, design modifications of the pad are suggested for improved noise characteristics.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.2
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• pp.131-138
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• 2009

Analytical modal verification is considered as the process to provide an acceptable description of the subject structure's behaviour. In general, results of original analytical model are different with actual structure results to uncertainty like non-linearity of material, boundary and modified shape, etc. In this paper, the dynamic model of glider's wing is correlated with static deformation and vibration test results by goal-attainment method, multi-objects optimization technique. The structural responses are predicted by using finite element method and optimization is carried out by using the SQP(sequential quadratic programming) method which is widely used in the constrained nonlinear optimization problem. The MAC(Modal Assurance Criterion) is used to modify the mode shapes and quantify the similarity.

• Transactions on Electrical and Electronic Materials
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• v.9 no.5
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• pp.181-185
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• 2008

Using the extensional vibration mode of PZT ring, a piezopump is successfully made. The PZT ring is polarized with thickness direction. The traveling extensional wave along the circumference of the ring is obtained by dividing two standing waves which are temporally and spatially phase shifted by 90 degrees from each other. The proposed piezopump is consisted of coaxial cylindrical shells that are bonded piezoelectric ceramic ring. The pump takes an unobtrusive operation into the simple displacing mechanism using peristaltic traveling waves without the physical moving parts. The finite elements analysis on the proposed pump model is carried out to verify its operation principle and design by the commercial FEM software. Components of piezopump were made, assembled, and tested to validate the concepts of the proposed pump and confirm the simulation results. The performance of the proposed piezopump is about 580 ${\mu}l/min$ in flow rate with the highest pressure level of 0.85 kPa, when the driving voltage is 150 $V_p$, 57 kHz.

• Steel and Composite Structures
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• v.35 no.2
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• pp.249-260
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• 2020

The main purpose of this research work is to investigate the free vibration of conical shell structures reinforced by graphene platelets (GPLs) and the elastic properties of the nanocomposite are obtained by employing Halpin-Tsai micromechanics model. To this end, a shell model is developed based on Donnell's theory. To solve the problem, the analytical Galerkin method is employed together with beam mode shapes as weighting functions. Due to importance of boundary conditions upon mechanical behavior of nanostructures, the analysis is carried out for different boundary conditions. The effects of boundary conditions, semi vertex angle, porosity distribution and graphene platelets on the response of conical shell structures are explored. The correctness of the obtained results is checked via comparing with existing data in the literature and good agreement is eventuated. The effectiveness and the accuracy of the present approach have been demonstrated and it is shown that the Donnell's shell theory is efficient, robust and accurate in terms of nanocomposite problems.

• Smart Structures and Systems
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• v.2 no.2
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• pp.189-208
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• 2006

Monitoring large-scale civil engineering structures such as offshore platforms and high-large buildings requires a large number of sensors of different types. Innovative sensor data information technologies are very extremely important for data transmission, storage and retrieval of large volume sensor data generated from large sensor networks. How to obtain the optimal sensor set and placement is more and more concerned by researchers in vibration-based SHM. In this paper, a method of determining the sensor location which aims to extract the dynamic parameter effectively is presented. The method selects the number and place of sensor being installed on or in structure by through the tolerance domain statistical inference algorithm combined with second order sensitivity technology. The method proposal first finds and determines the sub-set sensors from the theoretic measure point derived from analytical model by the statistical tolerance domain procedure under the principle of modal effective independence. The second step is to judge whether the sorted out measured point set has sensitive to the dynamic change of structure by utilizing second order characteristic value sensitivity analysis. A 76-high-building benchmark mode and an offshore platform structure sensor optimal selection are demonstrated and result shows that the method is available and feasible.

• Wind and Structures
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• v.19 no.4
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• pp.353-370
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• 2014

A new method is proposed in this study for estimating the damping ratio of a super tall building under strong wind loads with short-time measured acceleration signals. This method incorporates two main steps. Firstly, the power spectral density of wind-induced acceleration response is obtained by the wavelet transform, then the dynamic characteristics including the natural frequency and damping ratio for the first vibration mode are estimated by a nonlinear regression analysis on the power spectral density. A numerical simulation illustrated that the damping ratios identified by the wavelet spectrum are superior in precision and stability to those values obtained from Welch's periodogram spectrum. To verify the efficiency of the proposed method, wind-induced acceleration responses of the Guangzhou West Tower (GZWT) measured in the field during Typhoon Usagi, which affected this building on September 22, 2013, were used. The damping ratios identified varied from 0.38% to 0.61% in direction 1 and from 0.22% to 0.59% in direction 2. This information is expected to be of considerable interest and practical use for engineers and researchers involved in the wind-resistant design of super-tall buildings.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.7
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• pp.1-7
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• 2019

A chatter lobe analysis is frequently used to look at the chatter state. Even if there is a lot of research on chatter, chatter lobe characteristics are not well defined. In this study, the chatter lobe behavior according to several variables of vibration mode is verified for further clarity. The dynamic variables of the chatter model are defined and their behaviors on chatter lobe boundary are analyzed in detail. In this sense, the chatter model with 2-DOF (2-DOF) was used to analyze chatter stability characteristics. The discussed results are satisfying and these can be used for the prediction of chatter existence in machining processes of 2-DOF systems in several revolution range. These analyses indicate a better agreement for predicting an appropriate stability lobe over a wide detailed range of critical depths of cut in machining operation. The results allow an excellent prediction of chatter according to various static and dynamic variables in machining states. The behavior of chatter dynamic variables in machining were also discussed in detail. All these results can also be applied to other machining processes by establishing a chatter model in a 2-DOF system.

• Journal of Drive and Control
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• v.18 no.1
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• pp.24-30
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• 2021

There is an increasing interest in condition-based maintenance for the prevention of economic loss due to failure. Moreover, immense research is being carried out in related technologies in the field of construction machinery. In particular, data-based failure diagnosis methods that employ AI (machine & deep learning) algorithms are in the spotlight. In this study, we have focused on the failure diagnosis and mode classification of reduction gear of excavator's travel device by using the AI algorithm. In addition, a remote monitoring system has been developed that can monitor the status of the reduction gear by using the developed diagnosis algorithm. The failure diagnosis algorithm was performed in the process of data acquisition of normal and abnormal under various operating conditions, data processing and analysis by the wavelet transformation, and learning. The developed algorithm was verified based on three-evaluation conditions. Finally, we have built a system that can check the status of the reduction gear of travel devices on the web using the Edge platform, which is embedded with the failure diagnosis algorithm and cloud.

• Structural Engineering and Mechanics
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• v.77 no.4
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• pp.495-508
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• 2021

This study devises a novel approach, namely quadruple 1D convolutional neural network, for detecting connection stiffness reduction in steel truss bridge structure using experimental and numerical modal data. The method is developed based on expertise in two domains: firstly, in Structural Health Monitoring, the mode shapes and its high-order derivatives, including second, third, and fourth derivatives, are accurate indicators in assessing damages. Secondly, in the Machine Learning literature, the deep convolutional neural networks are able to extract relevant features from input data, then perform classification tasks with high accuracy and reduced time complexity. The efficacy and effectiveness of the present method are supported through an extensive case study with the railway Nam O bridge. It delivers highly accurate results in assessing damage localization and damage severity for single as well as multiple damage scenarios. In addition, the robustness of this method is tested with the presence of white noise reflecting unavoidable uncertainties in signal processing and modeling in reality. The proposed approach is able to provide stable results with data corrupted by noise up to 10%.

• Structural Engineering and Mechanics
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• v.84 no.1
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• pp.77-83
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• 2022

In the last ten years, many researchers have studied the vibrations of carbon nanotubes using different beam theories. The nano- and micro-scale systems have wavy shape and there is a demand for a powerful tool to mathematically model waviness of those systems. In accordance with the above mentioned lack for the modeling of the waviness of the curved tiny structure, a novel approach is employed by implementing the Timoshenko-beam model. Owing to the small size of the micro beam, these structures are very appropriate for designing small instruments. The vibrations of double walled carbon nanotubes (DWCNTs) are developed using the Timoshenko-beam model in conjunction with the wave propagation approach under support conditions to calculate the fundamental frequencies of DWCNTs. The frequency influence is observed with different parameters. Vibrations of the double walled carbon nanotubes are investigated in order to find their vibrational modes with frequencies. The aspect ratios and half axial wave mode with small length are investigated. It is calculated that these frequencies and ratios are dependent upon the length scale and aspect ratio.