• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.92-95
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• 2019

Automation control and the data for control of industrial equipment for the diagnosis and prediction is a key to success in the 4th industrial revolution. It increases process efficiency and productivity through data collection, realtime monitoring, and the data analysis. However, university and research environment are still suffering from logging the data in manual way, and we occasionally loss the equipment data logging due to the lack of automatic data logging system. State variable presents the current condition of the equipment operation which is closely related to process result, and it is valuable to monitor and analyze the data for the equipment health monitoring. In this paper, we demonstrate the collection of equipment state variable data via programmable logic controller (PLC) and the visualization of the collected data over the Web access supervisory control and data acquisition (SCADA). Test vehicle for the implementation of the suggested SCADA system is a relay switched physical vapor deposition system in the university environment.

• Journal of Advanced Navigation Technology
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• v.13 no.2
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• pp.252-256
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• 2009

In this paper, the emergency light where is being scattered always inspection and will be able to manage from the management center. Is not interfered in data neck of a bottle actual condition and the data communication will be possible and the cluster monitor network will grow and uses establishes the emergency light monitoring system. Will not be interfered in location of emergency light and not to be will be able to establish the system. And the monitoring network there is by a destroyer and the communication relay system is born breakdown but the dead zone without condition of emergency light proposes the emergency light management system where the monitoring and management are possible.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.04a
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• pp.321-327
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• 1998

This paper presented a case study on the application of on-line wear monitoring technique to a high duty air-turbo-compressor system. Main objects monitored were a gear unit and metal bearings, both shown frequent troubles due to the severe operation conditions at heavy dynamic load. The air-turbo-compressor system needs secure condition monitoring because it is one of the main utilities in steel making industry. Temperature and vibration characteristics have been mainly on-line monitored in this system for a predictive maintenance; however, it has been shown that they are not fairly good enough to give an early warning prior to the machine failure. In this work, an on-line Opto Magnetic Detector(OMD) was implemented for an on-line wear monitoring, which quantitatively measured the contamination level of both ferrous and non-ferrous wear particles by detecting the change in optical density of used oil. Results showed that the application of on-line OMD system was satisfactory in diagnosis of the machine system.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.2
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• pp.1-9
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• 2012

In this paper, we design and implement a DCS (Distributed Control System) based on dual field-bus for ship engine. For monitoring and controlling the condition of the ship engine, an implemented DCS is consisted of two-tier communication structure by using CAN (Controller Area Network) and MODBUS protocols. The first-tier is consisted of CAN protocol for sharing the condition of the ship engine by each implemented monitoring system. By using MODBUS protocol, the second-tier is used for communicating the monitoring data from an implemented DCS to AMS(Alarm Monitoring System). We verified and tested our scheme and implemented DCS by KR (Korea Register) technical rules through experimental tests.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.8
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• pp.662-668
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• 2005

This paper presents a realization of check valve condition monitoring system based on fault diagnosis algorithm and Fieldbus communication. We first acquired AE(acoustic emission) sensor data at the check valve test loop, extract fault features through the teamed neural network, and send the processed data to a remote site. The overall system has been implemented and experimented results are given to show its effectiveness.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.633-639
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• 2001

This paper proposes a knowledge-based expert system. which is assembled into hardware organized with sensor module. AID converter, USB. data acquisition PC and software composed of monitoring and diagnosis module combined with a frame-based method using Sohre's chart and a rule-based method. Vibration signals using various sensors are acquired by AID converter. transferred into PC and processed to obtain a continuous monitoring of the machine status displayed into several plots. Through combining frame-base which covers wide vibration causes with rule-base which gives relatively specified diagnosis results, high accuracy of fault diagnosis can be guaranteed and knowledge base can be easily extended by adding new causes or symptoms. Some examples using experimental data show the good feasibility of the proposed algorithm for condition monitoring and diagnosis of industrial rotating machinery.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2012.06a
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• pp.119-120
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• 2012

In the various industry plant, it need a condition monitoring system for an active machine that used an detachable wireless sensors. In this paper, IEEE802.15.4 standard based detachable wireless sensor monitoring system configure results will be introduced.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.703-704
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• 2013

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.923-924
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• 2008

• 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.