• Smart Structures and Systems
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• v.21 no.5
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• pp.687-694
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• 2018

The problem of wheel tread defects has become a major challenge for the health management of high-speed rail as a wheel defect with small radius deviation may suffice to give rise to severe damage on both the train bogie components and the track structure when a train runs at high speeds. It is thus highly desirable to detect the defects soon after their occurrences and then conduct wheel turning for the defective wheelsets. Online wheel condition monitoring using wheel impact load detector (WILD) can be an effective solution, since it can assess the wheel condition and detect potential defects during train passage. This study aims to develop an FBG-based track-side wheel condition monitoring method for the detection of wheel tread defects. The track-side sensing system uses two FBG strain gauge arrays mounted on the rail foot, measuring the dynamic strains of the paired rails excited by passing wheelsets. Each FBG array has a length of about 3 m, slightly longer than the wheel circumference to ensure a full coverage for the detection of any potential defect on the tread. A defect detection algorithm is developed for using the online-monitored rail responses to identify the potential wheel tread defects. This algorithm consists of three steps: 1) strain data pre-processing by using a data smoothing technique to remove the trends; 2) diagnosis of novel responses by outlier analysis for the normalized data; and 3) local defect identification by a refined analysis on the novel responses extracted in Step 2. To verify the proposed method, a field test was conducted using a test train incorporating defective wheels. The train ran at different speeds on an instrumented track with the purpose of wheel condition monitoring. By using the proposed method to process the monitoring data, all the defects were identified and the results agreed well with those from the static inspection of the wheelsets in the depot. A comparison is also drawn for the detection accuracy under different running speeds of the test train, and the results show that the proposed method can achieve a satisfactory accuracy in wheel defect detection when the train runs at a speed higher than 30 kph. Some minor defects with a depth of 0.05 mm~0.06 mm are also successfully detected.

• Korea lubricating oil industries association bulletin
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• no.9
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• pp.5-11
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• 1985

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.1
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• pp.11-18
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• 2010

Tool condition monitoring (TCM) is crucial for improvement of productivity in manufacturing process. However, TCM techniques have not been applied to monitor tool failure in an industrial gear shaving application. Therefore, this work studied a statistical TCM method for monitoring gear shaving tool condition. The method modeled the vibration signal of the shaving process using beta probability distribution in order to extract the effective features for TCM. Modeling includes rectifying for converting a bi-modal distribution into a unimodal distribution, estimating the parameters of beta probability distribution based on method of moments. The performance of features obtained from the proposed method was evaluated and discussed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.12
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• pp.1593-1598
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• 2011

The purpose of this study is to perform parameter selection and develop a method for the condition monitoring of an LCD conveyance robot. To determine the vibration characteristics of the driving part of the robot, the gear mesh frequency (GMF) of the speed-reducing gearbox is calculated and confirmed by frequency analysis. In order to ensure reproducibility of the measured data, an appropriate working pattern is selected and experiments are carried out. For condition monitoring of the robot, a wireless measurement system is constructed and used in parameter selection, with the GMF as the center. A method involving the use of the standard deviation of the measured data and another method involving the use of multiple value of amplitude are proposed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1597-1603
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• 2017

The incidence of fire in underground utility tunnel is lower than other fires, but the damage caused by fire can cause social loss due to social management paralysis as well as economic loss. Hereupon, this paper presents the results of an empirical test on the construction of the underground utility tunnel condition monitoring system using the leakage coaxial cable installed in the underground utility tunnel. For this reason, a verification test was conducted by connecting a inductive coupler 200 Mbps power line communication modem with insertion loss characteristics of $-6{\pm}2dB$ to the installed the leakage coaxial cable installed in the underground utility tunnel. As a result, We confirmed sending/receiving of IP cameras up to 500 m. Therefore, it is judged that it is possible to construct a condition monitoring system for underground utility tunnel by using the leakage coaxial cables installed in the underground utility tunnels without installing additional communication lines for data transmission.

• Journal of the Korean Society of Propulsion Engineers
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• v.17 no.2
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• pp.71-83
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• 2013

Recently, the advanced condition monitoring methods such as the model-based method and the artificial intelligent method have been applied to maximize the availability as well as to minimize the maintenance cost of the aircraft gas turbines. Among them the non-linear GPA(Gas Path Analysis) method and the GA(Genetic Algorithms) have lots of advantages to diagnose the engines compared to other advanced condition monitoring methods such as the linear GPA, fuzzy logic and neural networks. Therefore this work applies both the non-linear GPA and the GA to diagnose AE3007 turbofan engine for an aircraft, and in case of having sensor noise and bias it is confirmed that the GA is better than the GPA through the comparison of two methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10B
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• pp.630-638
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• 2005

As real-time media applications based on IP multicast networks spread widely, the end-to-end QoS (quality of service) provisioning for these applications have become very important. To guarantee the end-to-end QoS of multi-party media applications, it is essential to monitor the time-varying status of both network metrics (i.e., delay, jitter and loss) and system metrics (i.e., CPU and memory utilization). In this paper, targeting the multicast-enabled AG (Access Grid) group collaboration tool based on multi-Party real-time media services, a hybrid monitoring scheme that can monitor the status of both multicast network and node system is investigated. It combines active monitoring and passive monitoring approaches to measure multicast network. The active monitoring measures network-layer metrics (i.e., network condition) with probe packets while the passive monitoring checks application-layer metrics (i.e., user traffic condition by analyzing RTCP packets). In addition, it measures node system metrics from system API. By comparing these hybrid results, we attempt to pinpoint the causes of performance degradation and explore corresponding reactions to improve the end-to-end performance. The experimental results show that the proposed hybrid monitoring can provide useful information to coordinate the performance improvement of multi-party real-time media applications.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.11
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• pp.521-527
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• 2002

The Hemodialysis system is the device for the patients who have suffered from end stage renal failure as the kidney which removes the waste products in a human body. The existing hemodialysis is based on a 8-bit micro-controller and it is not a touch-screen type but a manual type. This paper is focused on hemodialysis system based on high control and expension embedded system. The whole system consists of main control unit and sub control unit(dialysis control unit, blood control unit, monitoring control unit, networking unit). The dialysis control unit, blood control unit, monitoring control unit are processed by 3 microcontrollers and network unit is for monitoring a renal failure patient's condition. For the evaluation of the system performance, the saline was pured into blood unit and then water removal rate, conductivity and temperature of hemodialysis liquid were measured 10 times in an each state suing the UF pump in the fluid unit varing the quantity of saline to 1000cc, 2000cc, 3000cc and 4000cc. As a result, the rates of water removal are 98.6% in condition of 000cc saline, 96.9% in 2000cc, 98.9% in 3000cc and 98.3% in 4000cc. The conductivities of hemodialysis liquid are 99.6% in the first to third condition and 99.7% in the forth condition. The temperatures of hemodialysis liquid are 99.8% in the first to third condition and 99.6% in th forth condition.

• Journal of Convergence Society for SMB
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• v.5 no.4
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• pp.5-10
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• 2015

With the advance of ICT, understanding the condition of network and analysing network monitoring have become an important issue. On the TCP/IP network, SNMP is the typical protocol that catches the condition of network by using polling method. If polling method is implemented for a long period, to catch the change of the condition of the network is not easy. On the other hand, in case of short-term polling, even if it could catch the condition of the network in real time, responsive messages to results of the polling cause the increase of traffic and therefore burden the network. There have been studies to control the overhead of responsive messages by controlling the polling period. However, not considering the characteristics of an agent, and running randomly, they cannot decrease the overhead although they would have an instant effect. This paper suggests an efficient polling method that decreases the traffic overhead of polling and catches the condition of the network in real time. Proposed method an polling for a short period and gave weight based on the characteristics of agents to catch the network condition, and a manager decided polling differentially based on the weight so that it decreased the overhead of polling traffic.

• Journal of the Society of Naval Architects of Korea
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• v.55 no.6
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• pp.505-513
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• 2018

Main engine failures in ship operations can lead to a major damage in terms of the vessel itself and the financial cost. In this respect, monitoring of a vessel's main engine condition is crucial in ensuring the vessel's performance and reducing the maintenance cost. The collection of a huge amount of vessel operational data in the maritime industry has never been easier with the advent of advanced data collection technologies. Real-time monitoring of the condition of a vessel's main engine has a potential to create significant value in maritime industry. This study presents a case study on the establishment of upper control limit to detect vessel's main engine failures using multivariate control chart. The case study uses sample data of an ocean-going vessel operated by a major marine services company in Korea, collected in the period of 2016.05-2016.07. This study first reviews various main engine-related variables that are considered to affect the condition of the main engine, and then attempts to detect abnormalities and their patterns via multivariate control charts. This study is expected to help to enhance the vessel's availability and provide a basis for a condition-based maintenance that can support proactive management of vessel's main engine in the future.