• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.11
• /
• pp.1119-1123
• /
• 2006

The flame image processing and analysis system has been investigated for the optimal pulverized coal firing of thermal power plant, especially for lower nitrogen oxide generation and more safe operation. We aimed at gaining the relationship between burner flame image information and emissions of nitrogen oxide and unburned carbon in furnace utilizing the flame image processing methods, by which we quantitatively determine the condition of combustion on the individual humors. Its feasibility test was undertaken with a pilot furnace for coal firing, through which the system was observed to be effective for the monitoring of the combustion condition of pulverized coal firing boilers.

• Smart Structures and Systems
• /
• v.30 no.5
• /
• pp.433-446
• /
• 2022

Despite efforts to reduce unexpected accidents at confined construction sites, choking accidents continue to occur. Because of the poorly ventilated atmosphere, particularly in long, confined underground spaces, workers are subject to dangerous working conditions despite the use of artificial ventilation. Moreover, the traditional monitoring methods of using portable gas detectors place safety inspectors in direct contact with hazardous conditions. In this study, a long-range (LoRa)-based wireless safety monitoring system that features the network organization, fault-tolerant, power management, and a graphical user interface (GUI) was developed for underground construction sites. The LoRa wireless data communication system was adopted to detect hazardous gases and oxygen deficiency within a confined underground space with adjustable communication range and low power consumption. Fault tolerance based on the mapping information of the entire wireless sensor network was particularly implemented to ensure the reliable operation of the monitoring system. Moreover, a sleep mode was implemented for the efficient power management. The GUI was also developed to control the entire safety-monitoring system and to manage the measured data. The developed safety-monitoring system was validated in an indoor testing and at two full-scale water pipeline construction sites.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.4
• /
• pp.407-413
• /
• 2011

This paper presents an electrical power monitoring system for home energy management and an automatic appliance-identification algorithm based on the electricity-usage patterns collected during the monitoring tests. This paper also discusses the results of the field tests of which the proposed system was voluntarily deployed at 13 homes. The proposed monitoring system periodically measures the amount of power consumption of each appliance with a pre-specified time interval and effectively displays the essential information provided by the monitored data which is required users to know in order to save power consumption. Regarding the field tests of the monitoring system, the households responded that the system was useful in saving electricity and especially the electricity-usage patterns per appliances. They also considered that the predicted amount of the monthly power consumption was effective. The proposed appliance-identification algorithm uses 4 patterns: Zero-Crossing Rate(ZC), Variation of On State(VO), Slope of On State(SO) and Duty Cycle(DC), which are applied over the 2 hour interval with 25% of it on state, and it yielded 82.1% of success rate in identifying 5 kinds of appliances: refrigerator, TV, electric rice-cooker, kimchi-refrigerator and washing machine.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.19 no.4
• /
• pp.393-399
• /
• 2009

Historically, industrial condition monitoring has been performed by costly hard-wired sensors or infrequent checks by maintenance personnel equipped with hand held monitoring equipment. Self- powered wireless condition monitoring systems provides on-line monitoring of critical plant and machinery providing major operating cost benefits. A vibration energy harvester(VEH) is a device that converts kinetic energy occurred by machine vibration into useable electrical energy. Using VEHs to power wireless monitoring systems can yield significant benefits: increased reliability, lower life time costs and no battery disposal issues, etc. This paper proposes the novel prototype design and manufacturing of a VEH that can eliminate the effect by failed batteries.

• Nuclear Engineering and Technology
• /
• v.36 no.4
• /
• pp.346-356
• /
• 2004

14 Pressurized Water Reactors (PWR) in Korea use a remote monitoring system (RMS), which have been used in Korea since 1998. A Memorandum of Understanding on Remote Monitoring, based on Enhanced Cooperation on PWRs, was signed at the 10th Safeguards Review Meeting in October 2001 between the International Atomic Energy Agency (IAEA) and Ministry Of Science and Technology (MOST). Thereafter, all PWR power plants applied for remote monitoring systems. However, the existing method is high cost (involving expensive telephone costs). So, it was eventually applied to an Internet system for Remote Monitoring. According to the Internet-based Virtual Private Network (VPN) applied to Remote Monitoring, the Korea Atomic Energy Research Institute (KAERI) came to an agreement with the IAEA, using a Member State Support Program (MSSP). Phase I is a Lab test. Phase II is to apply it to a target power plant. Phase III is to apply it to all the power plants. This paper reports on the penetration testing of Phase I. Phase I involved both domestic testing and international testing. The target of the testing consisted of a Surveillance Digital Integrated System (SDIS) Server, IAEA Server and TCNC (Technology Center for Nuclear Control) Server. In each system, Virtual Private Network (VPN) system hardware was installed. The penetration of the three systems and the three VPNs was tested. The domestic test involved two hacking scenarios: hacking from the outside and hacking from the inside. The international test involved one scenario from the outside. The results of tests demonstrated that the VPN hardware provided a good defense against hacking. We verified that there was no invasion of the system (SDIS Server and VPN; TCNC Server and VPN; and IAEA Server and VPN) via penetration testing.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2007.06a
• /
• pp.529-530
• /
• 2007

The paper considers the relation between on-line monitoring and diagnostics on the one hand and high-voltage (HV) withstand and partial discharge (PD) on-site testing on the other. HV testing supplies the basic data (fingerprints) for diagnostics. In case of warnings by on-line diagnostic systems, off-line withstand and PD testing delivers the best possible information about defects and enables the classification of the risk. Because alternating voltage (AC) is the most important test voltage, the AC generation on site is considered. Frequency tuned resonant (ACRF) test systems are best adapted to on-site conditions. They can be simply combined with PD measuring equipment. The available ACRF test systems and their application to electric power equipment -from cable systems to power transformers - is described.

• Smart Structures and Systems
• /
• v.32 no.3
• /
• pp.179-193
• /
• 2023

This study explores an alternative to the existing centralized process for data anomaly detection in modern Internet of Things (IoT)-based structural health monitoring (SHM) systems. An edge intelligence framework is proposed for the early detection and classification of various data anomalies facilitating quality enhancement of acquired data before transmitting to a central system. State-of-the-art deep neural network pruning techniques are investigated and compared aiming to significantly reduce the network size so that it can run efficiently on resource-constrained edge devices such as wireless smart sensors. Further, depthwise separable convolution (DSC) is invoked, the integration of which with advanced structural pruning methods exhibited superior compression capability. Last but not least, quantization-aware training (QAT) is adopted for faster processing and lower memory and power consumption. The proposed edge intelligence framework will eventually lead to reduced network overload and latency. This will enable intelligent self-adaptation strategies to be employed to timely deal with a faulty sensor, minimizing the wasteful use of power, memory, and other resources in wireless smart sensors, increasing efficiency, and reducing maintenance costs for modern smart SHM systems. This study presents a theoretical foundation for the proposed framework, the validation of which through actual field trials is a scope for future work.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.9
• /
• pp.144-155
• /
• 2013

This paper presents a low-cost remote power-quality-failure monitoring system (RPMS) using Android App and TI MCU (micro-controller unit), which is appliable to a micro-grid. The designed RPMS testbed consists of smart nodes, a server, and Android APPs. Especially, the C2000-series MCU-based RPMS smart node that is low-cost compared to existing monitoring systems has both a signal processing function for power signal processing and a data transmission function for power-quality monitoring data transmission. The signal processing function implements both a wavelet-based power failure detection algorithm including sag, swell, and interruption, and a FFT-based power failure detection algorithm including harmonics such that reliable and real-time power quality monitoring is guaranteed. The data transmission function implements a low-complexity RPMS transmission protocol and defines a simple data format (msg_Diag) for power monitoring message transmission. We may watch the monitoring data in real time both at a server and Android phone Apps connected to the WiFi network (or WAN). We use RS-232 (or Bluetooth) as the wired (or wireless) communication media between a server and nodes. We program the RPMS power-quality-failure monitoring algorithm using C language in the CCS (Code Composer Studio) 3.3 environment.

• Proceedings of the KIEE Conference
• /
• 2008.07a
• /
• pp.273-274
• /
• 2008

Recently, the most wide-area blackout in North America, Canada and Europe had shown us indirectly the importance of Wide-Area Power System Protection and had influence on the direction of domestic electric power industry. After reorganization of the electric power industry in 2001, market incentives controls the power generation, transmission and distribution rather than stability of power grid, and moreover it produce bad results like inefficient facility management and too much competition. In addition, we can easily predict the massive loss of social and economic when the wide-area outage occurs by north direction load flow which is a pending problems of domestic power system and in a changed industry likes hi-tech manufacture and information technology industries. This paper introduces the development of infra systems for prevent wide-area blackout in situations of the power system operations.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.3 no.1
• /
• pp.112-120
• /
• 2003

This paper reports the development work carried out in respect of a proposed application of Neural Network approach for the Korean Next generation Reactor (KNGR) now referred as APR-1400. The emphasis is on establishing the methodology and the approach to be adopted towards realizing this application in the next generation reactors. Keeping in view the advantages and limitation of Artificial Neural Network Approach, the role of ANN has been limited to plant status or to be more precise plant transient monitoring. The simulation work carried out so far and the results obtained shows that artificial neural network approach caters to the requirements of plant status monitoring and qualifies to be incorporated as a part of proposed operator support systems of the referenced nuclear power plant.