• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2012.05a
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• pp.586-591
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• 2012

The solution of maintenance decision support system for the gas turbine engine, which is currently operating in GUNSAN combined cycle power plant, was developed and is consist of online monitoring module, periodic performance trending module, optimal compressor washing interval analysis module and hot component management module. Also, GUI platform was applied to this solution for the user to monitoring the analyzed result of engine performance condition and then to make a decision of the consequent maintenance action. In online condition monitoring module, the performance degradation of engine is provided by the analysis of difference between the real time measurement data compared to exist engine performance. The optimal compressor washing interval module produced the washing interval of maximum net profit value by researching the maintenance expense and the loss profit value corresponds to the performance degradation with economic assessment algorithm. Thus, this solution support the user to enable the optimal maintenance and operation of gas turbine engine with overall analysis of engine condition and main information.

• Tribology and Lubricants
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• v.10 no.4
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• pp.51-58
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• 1994

Condition monitoring technology has recently been received much attention in the light of its significance on the maintenance of complex machineries such as turbines in power plants. Currently, turbines in power plants are maintained by scheduled overhaul based on the manufacturer's recommendations and the utility's experience. Although this preventive maintenance is known to be very effective, operators have less access to identify failure of elements when it happens between overhaul period. Therefore, in this study, a development of a on-line condition monitoring system through wear debris analysis of lubricating oils is aimed with a view to detecting abnormal wear behaviour of bearings and other wet-components at an early stage, allowing better outage scheduling and minimizing forced outages. For field application purposes, the on-line system developed was installed on the turbine of the No.4 unit at Ulsan Power Plant and its performance has been evaluated on site.

• Tribology and Lubricants
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• v.36 no.6
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• pp.297-306
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• 2020

This paper reviews studies on the types and functions of oil sensors used for machine condition monitoring. Machine condition monitoring is essential for maintaining the reliability of machines and can help avoid catastrophic failures while ensuring the safety and longevity of operation. Machine condition monitoring involves several components, such as compliance monitoring, structural monitoring, thermography, non-destructive testing, and noise and vibration monitoring. Real-time monitoring with oil analysis is also utilized in various industries, such as manufacturing, aerospace, and power plants. The three main methods of oil analysis are off-line, in-line, and on-line techniques. The on-line method is the most popular among these three because it reduces human error during oil sampling, prevents incipient machine failure, reduces the total maintenance cost, and does not need complicated setup or skilled analysts. This method has two advantages over the other two monitoring methods. First, fault conditions can be noticed at the early stages via detection of wear particles using wear particle sensors; therefore, it provides early warning in the failure process. Second, it is convenient and effective for diagnosing data regardless of the measurement time. Real-time condition monitoring with oil analysis uses various oil sensors to diagnose the machine and oil statuses; further, integrated oil sensors can be used to measure several properties simultaneously.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.172-174
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• 2021

In the existing industry, maintenance was carried out in the form of preventive maintenance such as occurrence of unnecessary idle time due to limited monitoring and maintenance. However, with the advent of the Fourth Industrial Revolution, real-time monitoring is possible in many industries including mining, manufacturing, oil and gas, and commercial agriculture, and it is desired to minimize idle time due to maintenance. In particular, there is a growing interest in predictive maintenance that can reduce costs and maximize operational efficiency by predicting and maintaining a failure before equipment and equipment fail. In this study, we look at the predictive maintenance technology that can verify the abnormal condition of the equipment of the smart factory in advance and monitor the abnormal condition in real time.

• Tribology and Lubricants
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• v.14 no.2
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• pp.75-81
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• 1998

Condition monitoring technology was applied for an air compressor lubricating system to achieve a proactive maintenance, which could prevent a catastrophic failure and detect root causes of the conditional failure of the system. For this work, various types of wear monitoring technology were used and compared with the results of vibration and temperature measurements. The Results generally showed that every technology has a limitation to failure detection, and integrated-based condition monitoring should be performed for the best results. In this work, an idea for the implementing integrated wear monitoring was suggested and demonstrated.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.1245-1247
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• 2001

This paper discusses that the maintenance of the propulsion equipment in railway rolling stock. Condition monitoring of railway equipment is the need for integration of remote condition monitoring with maintenance management strategies. The paper outlines research leading to the design and development of a prototype control and monitoring system for propulsion equipment.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.291-295
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• 2009

We did the blooth module test as a pre-test of wireless sensor monitoring system, which for the improving of on-condition maintenance reliability, on the train. In this test, we examined the communication environment of wireless sensor monitoring system by the acceleration date and frequency date in the real train structure during the operation. Also based on this results, we did the experimental verification of the sensor power system which use piezoelectric energy conversion technology by the theoretical modeling for the applying on the train on-condition maintenance.

• The Journal of Engineering Geology
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• v.26 no.4
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• pp.473-484
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• 2016

This study aims to establish a monitoring method for managing the effective maintenance of tailings dams. The monitoring of a tailings dump area involves several parameters and their investigation through a selection of evaluation items. The extents of defects and progressive failures also need to be effectively estimated. Therefore, the monitoring items can be subdivided into categories relating to the retaining wall structure (concrete wall, reinforcing stone wall, mesh gabions) and general facilities (liner, covering soil, slope, tailings, rain protection facility, leachate, planting), and quantitative evaluations can then be conducted for each condition. In doing so, we developed a systematic monitoring method that assesses the dam maintenance condition with grades and scores. The field application of the monitoring method results showed it to provide a more detailed evaluation than existing monitoring methods: the method detected an additional 16 defects missed by conventional methods. The evaluation gave scores of 89.3, 22.2, and 27.8 to the Geumjang mine tailings dam, the Gupoong mine tailings dam, and the Hwachun mine tailings dam, respectively. The advanced method can provide quantitative evaluation and perform detailed monitoring of the dams. This quantitative evaluation can be used to decide on maintenance priorities, select the main management items, and establish schedules of maintenance.

• 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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.4
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• pp.393-399
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• 2009

Historically, industrial condition monitoring has been performed by costly hard-wired sensors or infrequent checks by maintenance personnel equipped with hand held monitoring equipment. Self- powered wireless condition monitoring systems provides on-line monitoring of critical plant and machinery providing major operating cost benefits. A vibration energy harvester(VEH) is a device that converts kinetic energy occurred by machine vibration into useable electrical energy. Using VEHs to power wireless monitoring systems can yield significant benefits: increased reliability, lower life time costs and no battery disposal issues, etc. This paper proposes the novel prototype design and manufacturing of a VEH that can eliminate the effect by failed batteries.