• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2008.04c
• /
• pp.98-102
• /
• 2008

Methods and analysis of a simple wireless sensor concept for detecting and locating faults as well as for load monitoring are presented. The concept is based on distributed wireless sensors that are attached to the incoming and outgoing power lines of secondary substations. A sensor measures only phase current characteristics of the wire it is attached to, is not synchronized to other sensors and does not need configuration of triggering levels. The main novelty of the concept is in detecting and locating faults by combining power distribution network characteristics on system level with low power sampling methods for individual sensors. This concept enables the sensor design to be simple, energy efficient and thus applicable in new installations and for retrofit purposes in both overhead and underground electrical distribution systems.

• Journal of the Korean Society of Safety
• /
• v.21 no.4 s.76
• /
• pp.95-101
• /
• 2006

It is well known that the thermal load in PSC(prestressed concrete) box-girder bridge is the principal cause of detrimental crack. The longitudinal stress caused by the lateral stress from the temperature gradient in slab of PSC box-girder bridge has a considerable influence on the durability and economy of bridge structures. As the basic study for the rational consideration of thermal load and the derivation of design guide, the inverse thermal analysis program for PSC box-girder bridges using field measurement data is developed. In this paper, thermal analyses are performed using field monitoring data for the sample PSC box-girder bridge. It is proposed that the link between monitoring program and the inverse analysis program is available.

• Journal of Computing Science and Engineering
• /
• v.7 no.4
• /
• pp.220-230
• /
• 2013

In recent years, progress in hardware technology has resulted in the possibility of monitoring many events in real time. The volume of incoming data may be so large, that monitoring all individual data might be intractable. Revisiting any particular record can also be impossible in this environment. Therefore, many database schemes, such as aggregation, join, frequent pattern mining, and indexing, become more challenging in this context. This paper surveys the previous efforts to resolve these issues in processing data streams. The emphasis is on specifying and processing sliding window queries, which are supported in many stream processing engines. We also review the related work on stream query processing, including synopsis structures, plan sharing, operator scheduling, load shedding, and disorder control.

• Proceedings of the KIEE Conference
• /
• 2005.07a
• /
• pp.554-556
• /
• 2005

Distribution Automation System (DAS) will provide supervision and remote control of switches and reclosers such as pole pounted switches and pad-mounted switchgears on high voltage distribution line. Kepco had developed basic function such as remote monitoring, remote control, remote measuring and remote setting at first. As a next step, Kepco has been developed diverse application programs such as single line diagram drawing program, relay coordination program, feeder reconfiguration program, over load elimination program, bad data detection program, section load management program, fault processing program and so on. Kepco is examining to develop more powerful functions for special specification of foreign distribution automation system. This paper explains what is the target for overseas DAS market.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.1
• /
• pp.219-226
• /
• 2016

In this paper, adaptive home power peak-cut control system is developed using PLC. The developed scheme provides monitoring of power usage, power peak-cut control and additional function. In test bed, zone is presented by bedroom, living room, kitchen and bathroom. And individual load is presented by lighting, heater and fan in zone. In developed scheme, zone control is implemented by single PLC modem. And individual load control is implemented by key-map table. In addition, power peak-cut control system S/W, which can perform setting of power peak, power peak-cut control and monitoring of power usage.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2004.11b
• /
• pp.33-37
• /
• 2004

Photovoltaic energy and wind energy are highly dependent on the season, time and extremely intermittent energy sources. Because of these reasons, in view of the reliability the photovoltaic and the wind power generation system have many problems(energy conversion, energy storage, load control etc.) comparing with conventional power plant. In order to solve these existing problems, hybrid generation system composed of photovoltaic(500W) and wind power system(400W) was suggested But, hybrid generation system cannot always generate stable output due to the varying weather condition So, the auxiliary power compensation unit that uses elastic energy of spiral spring was added to hybrid generation system for the present study. It was partly confirmed that hybrid generation system was generated a stable outputs by spiral spring was continuously provided to load.

• Smart Structures and Systems
• /
• v.16 no.3
• /
• pp.435-457
• /
• 2015

The most widely known form of multifunctional aircraft structure is smart structures for structural health monitoring (SHM). The aim is to provide automated systems whose purposes are to identify and to characterize possible damage within structures by using a network of actuators and sensors. Unfortunately, environmental and operational variability render many of the proposed damage detection methods difficult to successfully be applied. In this paper, an original robust damage detection approach using output-only vibration data is proposed. It is based on independent component analysis and matrix perturbation analysis, where an analytical threshold is proposed to get rid of statistical assumptions usually performed in damage detection approach. The effectiveness of the proposed SHM method is demonstrated numerically using finite element simulations and experimentally through a conformal load-bearing antenna structure and composite plates instrumented with piezoelectric ceramic materials.

• Transactions of Materials Processing
• /
• v.31 no.2
• /
• pp.103-108
• /
• 2022

Systematic quality control based on real time data is required for modern factories. This study introduced a method of predicting punch wear in the trimming process of automobile parts. Based on monitoring data of the mass production process using a bolt-type piezo sensor, it was shown that precursor symptoms of die wear could be predicted from the change in load pattern with respect to production volume. The load pattern that changed according to the wear of the die was verified by numerical analysis.

• Smart Structures and Systems
• /
• v.6 no.3
• /
• pp.183-196
• /
• 2010

Monitoring and economical design of alternative energy generators such as wind turbines is becoming increasingly critical; however acquisition of the dynamic output data can be a time-consuming and costly process. In recent years, low-cost wireless sensors have emerged as an enabling technology for structural monitoring applications. In this study, wireless sensor networks are installed in three operational turbines in order to demonstrate their efficacy in this unique operational environment. The objectives of the first installation are to verify that vibrational (acceleration) data can be collected and transmitted within a turbine tower and that it is comparable to data collected using a traditional tethered system. In the second instrumentation, the wireless network includes strain gauges at the base of the structure. Also, data is collected regarding the performance of the wireless communication channels within the tower. In both turbines, collected wireless sensor data is used for off-line, output-only modal analysis of the ambiently (wind) excited turbine towers. The final installation is on a turbine with embedded braking capabilities within the nacelle to generate an "impulse-like" load at the top of the tower. This ability to apply such a load improves the modal analysis results obtained in cases where ambient excitation fails to be sufficiently broad-band or white. The improved loading allows for computation of true mode shapes, a necessary precursor to many conditional monitoring techniques.

• Smart Structures and Systems
• /
• v.24 no.6
• /
• pp.723-732
• /
• 2019

Globally road transport networks are subjected to continuous levels of stress from increasing loading and environmental effects. As the most popular mean of transport in the UK the condition of this civil infrastructure is a key indicator of economic growth and productivity. Structural Health Monitoring (SHM) systems can provide a valuable insight to the true condition of our aging infrastructure. In particular, monitoring of the displacement of a bridge structure under live loading can provide an accurate descriptor of bridge condition. In the past B-WIM systems have been used to collect traffic data and hence provide an indicator of bridge condition, however the use of such systems can be restricted by bridge type, assess issues and cost limitations. This research provides a non-contact low cost AI based solution for vehicle classification and associated bridge displacement using computer vision methods. Convolutional neural networks (CNNs) have been adapted to develop the QUBYOLO vehicle classification method from recorded traffic images. This vehicle classification was then accurately related to the corresponding bridge response obtained under live loading using non-contact methods. The successful identification of multiple vehicle types during field testing has shown that QUBYOLO is suitable for the fine-grained vehicle classification required to identify applied load to a bridge structure. The process of displacement analysis and vehicle classification for the purposes of load identification which was used in this research adds to the body of knowledge on the monitoring of existing bridge structures, particularly long span bridges, and establishes the significant potential of computer vision and Deep Learning to provide dependable results on the real response of our infrastructure to existing and potential increased loading.