• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.9
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• pp.1788-1794
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• 2011

The mold transformer is a complex and critical component of DC substations in Metro system. In this paper, a cost effective and intelligent condition monitoring system for mold transformers in DC substations was developed. This paper also provides an overview of the management program using PD (partial discharge) data on mold transformers. Prior to application of the proposed system to Metro DC substations, experiments were performed at the metro line substation located in Seoul and presented case studies for the use of the intelligent condition monitoring system for mold transformer in DC substations. The experiment results indicated that the developing system can be need in helping mange the risk of unexpected failure of mold type transformers.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1069-1074
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• 2008

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 shaving process using beta probability distribution in order to extract the effective features. Modeling includes rectifying for converting a bi-modal distribution into a unimodal distribution, estimating parameters of beta probability distribution based on method of moments. The usefulness of features obtained from the proposed method was evaluated and discussed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.739-742
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• 2014

In the process of MLCC manufacturing, MLCC stacking process is the key process of making high quality MLCC. Since MLCC is small components, the entire process of MLCC stacking process is minute and sensitive to micro errors. To prevent micro error, we suggest condition-based monitoring which quantifies error based on feature extraction and quantifying error method. As results, it has been shown that the suggested algorithm has effectiveness of condition based monitoring of MLCC stacker.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.950-955
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• 2003

This paper introduces an enhanced condition monitoring and diagnosis system recently developed for rotating machinery. In the system, the data aquisition/monitoring signal processing, machine condition classifier, case-based reasoning and demonstration modules are effectively integrated with user-friendliness so that machine operators can easily monitor and diagnose the status of rotating machinery in operation. Some of the new features include the directional spectrum, case-based reasoning and neural network techniques. And the demonstrator modules for fault diagnosis of a Bear driving system and for basic understanding of the rotor dynamics are provided to help the potential users better understand the system.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.06a
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• pp.478-479
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• 2007

With increasing interest in the reduction of cost for operation and maintenance of overhead catenary system, various methods of condition monitoring have been developed. In this paper, we proposed network-based telemetry system for condition monitoring in railway and acquired data from any kind of sensor in catenary line and structure at high voltage. This development gives the solution for online condition monitoring in railway. To check the validity of our approach in terms of application, we realized network-based telemetry System.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.4
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• pp.244-258
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• 2019

The reliability of power electronic systems becomes increasingly important, as power electronic systems have gradually gained an essential status in a wide range of industrial applications. Accordingly, recent research has made an effort to improve the reliability of power electronic systems to comply with stringent constraints on safety, cost, and availability. The condition monitoring of power electronic components is one of the main topics in the research area of the reliability of power electronic systems. In this paper, condition-monitoring methods of reliability-critical components in power electronic systems are discussed to provide the current state of knowledge by organizing and evaluating current representative literature.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.50-57
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• 1997

In order to make unmanned machining systems with satisfactory performances, it is necessary to incorporate appropriate condition monitoring systems in the machining workstations to provide the required intelligence of the expert. This paper deals with condition monitoring for chatter, tool wear and breakage during turning operation. To develop economic sensing and identiffication methods for turning processes, sound pressure measurement and digital signal processing technique were proposed. We suppressed chatter by stability control methodology, which was studied through manipulation of spindle speeds regarding to chatter frequencies. It was shown that tool wear and fracture were identified and to be estimated by using the wear indices. The validity of the proposed system was confirmed through the large number of cutting tests.

• Tribology and Lubricants
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• v.26 no.1
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• pp.73-77
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• 2010

One of the important trends for condition monitoring in the 21st century is the development of smart sensors that will permit the cost-effective continuous monitoring of key machine equipments. In this study, an integrated in-line oil monitoring sensor assigned for continuous in situ monitoring multiple parameters of oil performance is presented. The sensor estimates oil deterioration based on the information about chemical degradation, total contamination, water content of oil and oil temperature. The oil oxidation is estimated by "chromatic ratio", total contamination is measured by the changes in optical density of oil in three optical wave-bands ('Red', 'Green' and 'Blue') and water content is evaluated as relative saturation of oil by water. In order to evaluate the sensor's effectiveness, the sensor was applied to several used oil samples in steel making industry and the results were compared with those measured by standard test methods.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.04c
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• pp.106-110
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• 2008

Continuous on-line temperature monitoring allows corrective measures to be taken to prevent upcoming failure. Continuous temperature monitoring and event recording provides information on the energized equipment's response to normal and emergency conditions. On-line temperature monitoring helps to coordinate equipment specifications and ratings, determine the real limits of the monitored equipment and optimize facility operations. Using wireless technique eliminates any need for special cables and wires with lower installation costs if compared to other types of online condition monitoring equipment. In addition, wireless temperature monitoring works well under difficult conditions in strategically important locations. Wireless technology for on-line condition monitoring of energized equipment is applicable both as standalone system and with an interface with power quality monitoring system.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.562-569
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• 2022

The alarm monitoring technology applied to existing operating ships manages data items such as temperature and pressure with AMS (Alarm Monitoring System) and provides an alarm to the crew should these sensing data exceed the normal level range. In addition, the maintenance of existing ships follows the Planned Maintenance System (PMS). whereby the sensing data measured from the equipment is monitored and if it surpasses the set range, maintenance is performed through an alarm, or the corresponding part is replaced in advance after being used for a certain period of time regardless of whether the target device has a malfunction or not. To secure the reliability and operational safety of ship engine operation, it is necessary to enable advanced diagnosis and prediction based on real-time condition monitoring data. To do so, comprehensive measurement of actual ship data, creation of a database, and implementation of a condition diagnosis monitoring system for condition-based predictive maintenance of auxiliary equipment and piping must take place. Furthermore, the system should enable management of auxiliary equipment and piping status information based on a responsive web, and be optimized for screen and resolution so that it can be accessed and used by various mobile devices such as smartphones as well as for viewing on a PC on board. This update cost is low, and the management method is easy. In this paper, we propose CBM (Condition Based Management) technology, for autonomous ships. This core technology is used to identify abnormal phenomena through state diagnosis and monitoring of pumps and purifiers among ship auxiliary equipment, and seawater and steam pipes among pipes. It is intended to provide performance diagnosis and failure prediction of ship auxiliary equipment and piping for convergence analysis, and to support preventive maintenance decision-making.