• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.2
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• pp.84-91
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• 2014

This paper introduces the application of supervisory monitoring system for substation automation based on IEC 61850. The objective of proposed system is detection of such a malfunction or degradation of devices. The supervisory monitoring procedure consists of a two step - topology processor and state estimation. The topology processor using artificial intelligence is a preprocessing step of state estimation. Topology processor identifies the topology structure of switches in substation and detects an error of ON/OFF state data. The state estimation is an algorithm that minimizes an error between optimal estimation values and real values. The proposed system is applied to standard digital substation based on IEC 61850 for performance verification.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.6 s.171
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• pp.109-117
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• 2005

In case of fine machining processes, the cutting state monitoring by a skilled operator is impossible because the physical changes generated during fine machining are very weak. To realize the high efficient and precise fine machining, it is necessary to develop the sensor based monitoring system which is able to detect the fine changes of cutting state. In this paper, the fine acoustic emission monitoring system is developed to monitor the state of the fine machining process. The developed system consists of the AE sensor and the AE signal processing unit. And this has the high-sensitivity and bandwidth which can detect fine AE signal generated during fine machining process. In order to investigate the feasibility of the developed system, evaluation experiments were performed in the fine fixed-abrasive machining processes such as polishing and glass ferrule slicing. Experimental results show that the developed monitoring system possesses an excellent real-time monitoring capability at fine machining processes.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.1
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• pp.38-43
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• 2012

For safe and stable operations of power plants, it is essential to monitor closely crucial measurement values related to power plant trips. In this paper, an intelligent power plant operating state monitoring technique enabling the operating crew member to monitor conveniently the status of the important measurement values and to perceive almost instantly the significance of the implications of those measurement values is developed. The proposed technique is called a "POST(Plant Operating State Tracking) Chart" technique and provides the foundations in developing an intelligent and integrated power plant operating state monitoring support system called the "P-OASIS"(Plant Operation Assessment and Support Intelligent System). The P-OASIS is applied to a thermal power plant of 500[MW] capacity and exhibited impressive performances.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.6
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• pp.133-140
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• 1999

In this study, a monitoring method to detect chip disposal state in drilling system based on neural network was proposed and its performance was evaluated. If chip flow is bad during drilling, not only the static component but also the fluctuation of dynamic component of drilling. Drilling torque is indirectly measured by sensing spindle motor power through a AC spindle motor drive system. Spindle motor power being measured drilling, four quantities such as variance/mean, mean absolute deviation, gradient, event count were calculated as feature vectors and then presented to the neural network to make a decision on chip disposal state. The selected features are sensitive to the change of chip disposal state but comparatively insensitive to the change of drilling condition. The 3 layerd neural network with error back propagation algorithm has been used. Experimental results show that the proposed monitoring system can successfully recognize the chip disposal state over a wide range of drilling condition even though it is trained under a certain drilling condition.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.842-850
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• 2021

Real Time Simulation (RTS) has long been used in the nuclear power industry for operator training and engineering purposes. And, Online Simulation (OLS) is based on RTS and with connection to the plant information system to acquire the measurement data in real time for calibrating the simulation models and following plant operation, for the purposes of analyzing plant events and providing indicative signs of malfunctioning. An OLS system has been developed to support PWR operations for CPR1000 plants. The OLS system provides graphical user interface (GUI) for operators to monitor critical plant operations for preventing faulty operation or analyzing plant events. Functionalities of the OLS system are depicted through the maneuvering of the GUI for various OLS functional modules in the system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.30
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• pp.107-116
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• 1994

This paper formulates a dynamic monitoring and control model with a machine state by quality variations in a single lot production system. A monitoring model is based on estimate of machine state obtained using control theory. The model studied in this paper has a great advance from a point of view the combination between quality control (Sampling, Control Chart) and automatic control theory, and can be extended in a several ways.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.5
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• pp.280-287
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• 2022

An open rack vaporizer is a facility that vaporizes liquefied natural gas using sea water. When a vaporization efficiency of the open rack vaporizer decreases, liquefied natural gas can leak, which can cause great damage to the facility. Operators have to monitor the operation state of the facility in real-time to prevent the accident. However, operators have visited the site and have checked the state by looking at the value of sensors installed in the open rack vaporizer through indicators. For the safe operation of the open rack vaporizer, a monitoring system is needed to monitor the operation state of the open rack vaporizer in real-time without the need for operators to visit the site. In this paper, we developed a long term evolution based monitoring system to monitor the operation state of the open rack vaporizer. The developed system can monitor the real-time operation state of the open rack vaporizer at a control center far from the facility. For the system development, data transmission infrastructure using long term evolution was built. Afterwards a software was developed to monitor the operation state of the open rack vaporizer in real-time using the transmitted data. Finally, performance evaluation was conducted to confirm that the developed system operated successfully without data transmission delay or data missing.

• 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.

• Journal of Power System Engineering
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• v.12 no.6
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• pp.18-23
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• 2008

This paper describes development of real-time condition monitoring system to observe state of a container crane in a port. To analyze the state of a crane, the strength and the direction of wind are measured with sensors along with the load resulted a crane at the moment. The measured signals are processed by especially developed conditioning board and converted into digital data. Measured data are analyzed to define the state of the crane at an indicator. For transmission of these data to the indicator, we implemented wireless sensor network based on IEEE 802.15.4 MAC(Media Access Control) protocol and Bluetooth network protocol. To extend the networking distance between the indicator and sensor nodes, the shortest path routing algorithm was applied for WSN(Wireless Sensor Network) networks. The indicator sends the state information of the crane to monitoring server through IEEE 802.11 b wireless LAN(Local Area Network). Monitoring server decides whether alarm should be issued or not. The performance of developed WSN and Bluetooth network were evaluated and analyzed in terms of communication delay and throughput.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.5
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• pp.1082-1086
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• 2007

This research has a purpose of constructing the data monitoring system that makes two-tier work state in the brick production factory to unification by reusing cinder. Monitoring system automatically manages data by using data managing processes such as a state managing process, a location managing process, a badness managing process, a circumstances managing process. In this research, the data management monitoring system manufactures state information of each processes received from RFID and transmits them to data monitoring system. Analyzed data through this system reuses the cinder, so it can effectively manage the production process of the factory which produces bricks through processing automation, faulty-ratio minimization, real-time monitoring and loading managing.