• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2001.04a
• /
• pp.529-532
• /
• 2001

A Remote Monitoring Server(RMS) server which uses Internet and World Wide Web is constructed for SMD in-line system. Hardware base consists of server computer, virtual SMD in-line system and other computers. Software includes assignment of server, RDBMS and various modules in server home page. Web browser provide production quantity, bad PCB quantity, error number and error message in virtual SMD module, user information in setup module, detailed error information in fault diagnosis module, fault history in fault history module and customer information in customer service management module. These functions of the RMS helps a decrease of non-operation time and a service response as fast as possible.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39A no.6
• /
• pp.357-364
• /
• 2014

In this paper deals with PON Remote monitoring solution using Reflecting Filter. The current FTTH-PON can not be monitored in real time that Optical cable fault and Quality degradation of Splitter. To solve this problem, Monitoring can make Feeder Network and Splitter that Reflecting filter development using the basic structure of Fiber Bragg grating. Reflecting Filter is Quality Monitoring System shall provide tools for user to view and analyze degradation of cables and splitter in particular predict any gradual component degradation(Optical cable bending, splice, connector, etc) before it becomes service impacting. The Reflecting Filter solution is splitter down and confirm the fault location of optical cable and it will send central control station can be monitored system an alarm to the OLT. In other words, wavelength side branches Mating existing communication affairs (Coupler) using the core of one optical wavelength for live monitoring two wavelengths and sends the subscriber side modem and aggregation switch device remotely using a reflective optical line filter monitoring the study of the system. this study can development of Reflecting filter improve the average processing time of Optical cable fault and efficient Maintenance of the network.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.2
• /
• pp.416-424
• /
• 2016

In this study, automatic detection of stator winding inter-turn short circuit fault (SWISCFs) in surface-mounted permanent magnet synchronous motors (SPMSMs) and automatic classification of fault severity via a pattern recognition system (PRS) are presented. In the case of a stator short circuit fault, performance losses become an important issue for SPMSMs. To detect stator winding short circuit faults automatically and to estimate the severity of the fault, an artificial neural network (ANN)-based PRS was used. It was found that the amplitude of the third harmonic of the current was the most distinctive characteristic for detecting the short circuit fault ratio of the SPMSM. To validate the proposed method, both simulation results and experimental results are presented.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.2
• /
• pp.155-163
• /
• 2013

As the increasing HIF(High Impedance Fault) with the arc cannot be easily detected for the low fault current magnitude compared to actual load in distribution line. However, the arcing current shows that the magnitude varies with time and the signal is asymmetric. In addition, discontinuous changes occur at starting point of arc. Considering these characteristics, wavelet transformation of actual current data shows difference between before and after the fault. Althogh raw data(detail coefficient) of wavelet transform may not be directly applied to HIF detection logic in a device, there are several developing methods of HIF monitoring data using the original wavelet coefficients. In this paper, a simple and effective developing methods of HIF monitoring data were analized by using the signal data through an actual HIF experiment to apply them to economic devices. The methods using the sumation of the wavelet coefficient squares in one cycle of the fundamental frequency as the energies of the wavelet coefficeits and the sumation of the absolute values were compared. Besides, the improved method which less occupies H/W resouces and can be applied to field detection devices was proposed. and also Verification of this HIF detection method through field test on distribution system in KEPCO power testing center was performed.

• Journal of Advanced Navigation Technology
• /
• v.28 no.1
• /
• pp.1-14
• /
• 2024

Global navigation satellite system (GNSS) providing position, navigation and timing (PNT) services consist of satellite, ground, and user systems. Monitoring stations, a key element of the ground segment, play a crucial role in continuously collecting satellite navigation signals for service provision and fault detection. These stations detect anomalies such as threats to the signal-in-space (SIS) of satellites, receiver issues, and local threats. They deliver received data and detection results to the master station. This paper introduces the main monitoring algorithms and measurement pre-processing processes for quality assessment and fault detection of received satellite signals in current satellite navigation system monitoring stations. Furthermore, it proposes a strategy for the development of components, architecture, and algorithms for the new regional navigation satellite system (RNSS) monitoring stations.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.7
• /
• pp.2169-2178
• /
• 2000

This paper proposes the structure of an agent and rules for fault detection and location on LAN. To find out a reason of critical fault incurred LAN, collision detection rule, error detection rule, broadcast detection rule, system location rule, and Internet application location rule ar shown. Also, the structure of multi-agent system and state transition diagram is portrayed to have connectivity with he set of rules. To verify availability of proposed rules, the process to find a faulty system is shown by monitoring and analyzing the LAN fault occurrences from the proposed set of rules. Such an rule based agent system is helpful to an Internet manager to solve a reason of fault and make ad decision from gathering management information.

• Journal of the Korean Society for Precision Engineering
• /
• v.15 no.2
• /
• pp.35-44
• /
• 1998

This paper describes multiple fault diagnosis method in complex system with hierarchical structure. Complex system is divided into subsystem, item and component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. We introduced Modular Artificial Neural Network(MANN) for this purpose. MANN consists of four level neural network, first level for symptom classification, second level for item fault diagnosis, third level for component symptom classification, forth level for component fault diagnosis. Each network is multi layer perceptron with 7 inputs, 30 hidden node and 7 outputs trained by backpropagation. UNIX IPC(Inter Process Communication) is used for implementing MANN with multitasking and message transfer between processes in SUN workstation. We tested MANN in reactor system.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.7
• /
• pp.1183-1190
• /
• 2007

This paper proposes the improved fault decision algorithm using DWT(Discrete Wavelet Transform) and ANNs for the FRTU(Feeder Remote Terminal Unit) on the feeder in the power distribution system. Generally, the FRTU has the fault decision scheme detecting the phase fault, the ground fault. Especially FRTU has the function for 2000ms. This function doesn't operate FI(Fault Indicator) for the Inrush current generated in switching time. But it has a defect making it impossible for the FI to be operated from the real fault current in inrush restraint time. In such a case, we can not find the fault zone from FI information. Accordingly, the improved fault recognition algorithm is needed to solve this problem. The DWT analysis gives the frequency and time-scale information. The neural network system as a fault recognition was trained to distinguish the inrush current from the fault status by a gradient descent method. In this paper, fault recognition algorithm is improved by using voltage monitoring system, DWT and neural network. All of the data were measured in actual 22.9kV power distribution system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.28 no.2
• /
• pp.24-30
• /
• 2014

In this paper, a new remote terminal unit(hereafter RTU) is proposed to manage a wide range of applications and a variety of sensors (eg, pressure, water quality, temperature and humidity sensors, the amount of pollutants, $CO_2$, etc.) to monitor and control the facility such as water treatment plant, intake and effluent pumping station, water tank and distribution network. Fault status of local sensor devices and network are alerted by using the embedded fault handling capabilities of the RTU in the system and also sent to the fault handling server, by which fault can be easily monitored to users. The developed system was applied to one of K-water branch offices in Geoje city and improved its reliability and stability for controlling and monitoring water facility.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.1
• /
• pp.27-33
• /
• 2013

Nowadays, the utilization of renewable energy sources like wind energy is considered one of the most effective means of generating massive amounts of electricity. This is evident in the rapid increase of wind farms all over the world which comprise a huge number of wind turbines. However, the drawback of utilizing wind turbines is that it requires maintenance, which could be a costly operation. To keep the wind turbines in pristine condition so as to reduce downtime, the implementation of CMS (Condition Monitoring System) and FDS (Fault Detection System) is mandatory. The efficiency and accuracy of these systems are crucial in deciding when to carry out a maintenance process. In this paper, a fault detection system based on intelligent clustering method is proposed. Using SCADA data, the clustering model was trained and evaluated for its accuracy through rigorous simulations. Results show that the proposed approach is able to accurately detect the deteriorating condition of a wind turbine as it nears a downtime period.