• Tribology and Lubricants
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• v.32 no.6
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• pp.189-194
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• 2016

Wear debris in lubricating oil can be indicative of potential damage to mechanical parts in rotating and reciprocating machinery. Therefore, on-line or in-line monitoring of lubricating components in machinery is of great importance. This work presents a device based on inductive measurement of lubricating oil to detect magnetic wear particles in a tested volume. The circuit in the device consists of Maxwell Bridge and LVDT to measure inductance differences between pure and contaminated oil. The device detects the passage of ferrous particles by monitoring inductance change in a coil. The sensing principle is initially demonstrated at the microscale using a solenoid. The device is then tested using iron particles ranging from $50{\mu}m$ to $100{\mu}m$, which are often found in severely worn mechanical components. The test results show that the device is capable of detecting and distinguishing ferrous particles in lubricating oil. The design concept demonstrated here can be extended to an in-line monitoring device for real-time monitoring of ferrous debris particles. A simulation using the CST code is performed to better understand the inductive response in the presence of magnetic bodies in the oil. The CST simulation further verifies the effectiveness of inductance measurement for monitoring magnetic particles within a tube.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.1048-1054
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• 2003

In laser surface hardening processes, the geometrical parameters such as the depth and the width of a hardened layer can be utilized to assess the hardened layer quality. However, accurate monitoring of the geometrical parameters for on-line process control as well as for on-line quality evaluation is very difficult because the hardened layer is formed beneath a material surface and is not visible. Therefore, temperature monitoring of a point of specimen surface has most frequently been used as a process monitoring method. But, a hardened layer depends on the temperature distribution and the thermal history of a specimen during laser surface hardening processing. So, this paper describes the estimation results of the geometric parameters using multi-point surface temperature monitoring. A series of hardening experiments were performed to find the relationships between the geometric parameters and the measured temperature. Estimation results using a neural network show the enhanced effectiveness of multi-point surface temperature monitoring compared to one-point monitoring.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.476-478
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• 1993

Instead of installing new communication wiring to each house in the apartment house building. the power distribution network. which is already installed in the building. can be use as communication medium. In a safty management, by adoption of power line communication system, at remote we can monitor safty related sensors such as fire, gas leakage, burglar intrusion and emergency call which are located at each house. From this viewpoint, we developed security monitoring system for apartment house building using power lines. Security monitoring system consists of Power Line Communication-Sub Controller (PLC-SC). Power Line Communication-Main Controller (PLC-MC) and Management System (MS). Between a PLC-MC and a PLC-SC, the transmission rate is 1200 bps in power lines and modulation technique is frequency shirt keying (FSK). In between a PLC-MC and a MS, the transmission rate is 1200 bps in communication line (RS-485). As a result of this research. transmission loss is 0.1dB per meter of intrabuilding distribution network. Transmission can be reach in 250 meters. So it is enough to communicate for security monitoring system in apartment house building.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.193-195
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• 2003

This paper presents an approach to estimate the power transmission line parameter by phasor measurement units(PMUs), which are synchronized to 1 pps signal of GPS. Existing approaches to estimate power transmission line parameter, are mainly off-line ones, based on faults or switching events on other neighboring lines. In this paper, to obtain static and dynamic properties of power transmission line parameter in service, the prototype of pmu-based Transmission Line Parameter Monitoring System (TLPMS) is proposed. Also, an technique to estimate parameters of transmission line described as 2-port network model and the soundness of estimated parameters are addressed.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.2
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• pp.103-111
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• 2002

Out of all metal-cutting process, the hole-making process is the most widely used. It is estimated to be more than 30% of the total metal-cutting process. It is therefore desirable to monitor and detect drill wear during the hole-drilling process. One important aspect in controlling the drilling process is monitoring drill wear status. There are two systems, Basic system and Online system, to detect the drill wear. Basic system comprised of spindle rotational speed, feed rates, thrust torque and flank wear measured by tool microscope. Outline system comprised of spindle rotational speed feed rates, AE signal, flank wear area measured by computer vision, On-line monitoring system does not need to stop the process to inspect drill wear. Backpropagation neural networks (BPNs) were used for on-line detection of drill wear. The output was the drill wear state which was either usable or failure. This paper deals with an on-line drill wear monitoring system to fit the detection of the abnormal tool state.

• Proceedings of the KIEE Conference
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• summer
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• pp.590-593
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• 2004

This paper presents recent trends on the on-line monitoring and diagnostic systems for oil-immersed transformers. Specially, our system on YeoSu thermal power plant is introduced for high sensitivity and accuracy of ours. It is combined with communication networks to provide an on-line remote monitoring system. Several alarm criteria are formulated to enable a superimposed monitoring system to perform decisive action. The reasons for monitoring the condition and maintaining the health of electrical apparatus were discussed. The experience at the fields and the criteria for the judgment are also discussed in detail.

• Journal of Drive and Control
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• v.9 no.2
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• pp.28-38
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• 2012

Monitoring of system cleanliness levels and counting of particulate contaminant are fundamental to achieving hydraulic system reliability as any departure from the specified cleanliness level is often a precursor to future failures. On-line monitoring of cleanliness levels has the advantage of giving data both very quickly and accurately as environmental influences are eliminated. In this way, corrective actions can be promptly implemented. Most on-line instruments are sensitive to system conditions to a greater or lesser extent, but Automatic Particle Counters (APCs) working on light extinction principles are especially sensitive to the presence of optical interfaces caused by such conditions as fluid mixtures, emulsions, free water and air bubbles. These conditions give erroneous data and can result in drawing incorrect conclusions, wasting maintenance time and ultimately, reduced user confidence in cleanliness monitoring. This paper describes such conditions and shows how the correct selection of the analysis technique can result in reliable cleanliness level data.

• Journal of Welding and Joining
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• v.20 no.6
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• pp.45-45
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• 2002

This study is a middle report on the development of intelligent spot welding monitoring technology applicable to the production line. An intelligent algorithm has been developed to predict the quality of welding in real time. We examined whether it is effective or not through the In-Line and the Off-Line tests. The purpose of the present study is to provide a reliable solution which can prevent welding defects in production site. In this study, the process variables, which were monitored in the primary circuit of the welding, are used to estimate the weld quality by Hidden Markov Model(HMM). The primary dynamic resistance patterns are recognized and the quality is estimated in probability method during the welding. We expect that the algorithm proposed in the present study is feasible to the applied in the production sites for the purpose of in-process real time quality monitoring of spot welding.

• Journal of Welding and Joining
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• v.20 no.6
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• pp.769-775
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• 2002

This study is a middle report on the development of intelligent spot welding monitoring technology applicable to the production line. An intelligent algorithm has been developed to predict the quality of welding in real time. We examined whether it is effective or not through the In-Line and the Off-Line tests. The purpose of the present study is to provide a reliable solution which can prevent welding defects in production site. In this study, the process variables, which were monitored in the primary circuit of the welding, are used to estimate the weld quality by Hidden Markov Model(HMM). The primary dynamic resistance patterns are recognized and the quality is estimated in probability method during the welding. We expect that the algorithm proposed in the present study is feasible to the applied in the production sites for the purpose of in-process real time quality monitoring of spot welding.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.6
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• pp.48-57
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• 1998

Abrasive waterjet(AWJ)은 가공시 열에 의한 가공경화가 없기 때문에 유리, 세라믹, 타이타늄및 금속복합재료와 같은 난삭재의 가공기술로 사용이 증가되었다. Acoustic emission(AE)신호에 의한 AWJ 세라믹 drilling가공시 On-Line Monitoring의 가능성이 고찰되었다. 기계 적인 물성이 서로 상이한 3종류의 세라믹이 본 연구에서 사용되었으며, AE신호는 AWJ drilling의 깊이를 monitoring하는데 유용함을 알 수 있었고 또한 세라믹의 material removal mechanisms을 규명하였다.