• Proceedings of the KIPE Conference
• /
• 2006.06a
• /
• pp.219-221
• /
• 2006

This paper presents the performance results of 50kW grid-connected PV (Photovoltaic) system for monitoring periods. Form these performance monitoring results, the PV system performance has been evaluated and analyzed for component perspective (PV array and power conditioning unit) and global perspective (system efficiency, capacity factor, and electrical power energy and power quality etc.).

• 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.

• Proceedings of the Korean Nuclear Society Conference
• /
• 2003.05a
• /
• pp.99.1-99.1
• /
• 2003

• Proceedings of the Korean Radioactive Waste Society Conference
• /
• 2017.10a
• /
• pp.239-240
• /
• 2017

• Journal of Radiation Protection and Research
• /
• v.26 no.3
• /
• pp.155-159
• /
• 2001

Beta radiation is measured for an environmental monitoring purpose or for an internal radiation exposure monitoring of nuclear power plant's worker. In korea, strontium 89 and strontium 90 is measured for an environmental monitoring purpose. Also tritium and carbon 14 contained in urine is measured for an internal radiation exposure monitoring of nuclear power plant's worker. Because above isotopes emits low energy beta radiations having a wide range of energy, very complicated isotope separation preprocess is needed. In this study, two mixed beta emitting isotopes are measured simultaneously using a liquid scintillation counter(LSC) and analyzed by using a developed statistical method. Banded least square method is used to analyze the mixed spectrum, and the goodness-of-fitness test is proposed. Test results show that the developed procedure can be very useful for analyzing a mixed beta emitting isotopes.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2006.04a
• /
• pp.15-20
• /
• 2006

Real time health monitoring system was studied to detect the . generation of defects in the composite structures during service life. The PZT sensors were embedded into the woven-glass/phenol composite plate during the fabrication. VARTM (Vacuum Assisted Resin Transfer Molding) process were used to fabricate the composite plate. A Teflon tape was embedded between glass fiber layers to mimic delamination induced during service. Normalized maximum amplitude and energy analyses were used for the acquired signals. Both amplitude and energy of acquired signals were extremely sensitive to the delamination. Therefore, it was successful to detect and to locate the defects in composite plate by monitoring signals from sensors and using the proposed method.

• Structural Engineering and Mechanics
• /
• v.23 no.1
• /
• pp.75-95
• /
• 2006

Two-step identification approaches for effective bridge health monitoring are proposed to alleviate the issues associated with many unknown parameters faced in real structures and to improve the accuracy in the estimate results. It is suitable for on-line monitoring scheme, since the damage assessment is not always needed to be carried out whereas the alarming for damages is to be continuously monitored. In the first step for screening potentially damaged members, a damage indicator method based on modal strain energy, probabilistic neural networks and the conventional neural networks using grouping technique are utilized and then the conventional neural networks technique is utilized for damage assessment on the screened members in the second step. The effectiveness of the proposed methods is investigated through a field test on the northern-most span of the old Hannam Grand Bridge over the Han River in Seoul, Korea.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.8
• /
• pp.941-950
• /
• 1999

This paper presents a DSM monitoring methodology that is able to evaluate the impact of DSM programs especially focused on the strategic conservation i.e. the enhancement of end-use energy efficiency. For an effective assessment of DSM programs, it is foremost necessary to examine the market characteristics on the specific end-use appliance according to the customer's adoption of DSM programs. The proposed monitoring methodology contains a diffusion process of high efficient end-uses considering major factors of DSM impact such as, price, reference capacity, forecasted capacity and lifetime of end-use appliances. Case studies show the projection of power reductions and energy savings resulted from DSM monitoring in order to diagnose the current status properly and provide a baseline of DSM policy and analysis.

• Journal of Wind Energy
• /
• v.9 no.4
• /
• pp.16-23
• /
• 2018

A damage detection method for the tripod support structure of offshore wind turbines is presented for structural health monitoring. A finite element model of a prototype tripod support structure is established and the modal properties are calculated. The degree and location of the damage are estimated based on the neural network technique using the changes of natural frequencies and mode shape due to the damage. The stress distribution occurring in the support structure is obtained by a dynamic analysis for the wind turbine system to select the output data of the neural network. The natural frequencies and mode shapes for 36 possible damage scenarios were used for the input data of the learned neural network for damage assessment. The estimated damages agreed reasonably well with the accurate ones. The presented method could be effectively applied for damage detection and structural health monitoring of various types of support structures of offshore wind turbines.

• Journal of the Korean Society for Precision Engineering
• /
• v.12 no.1
• /
• pp.15-21
• /
• 1995

Automatic monitoring of cutting process is one of the most important technologies for increasing the stability and the reliability of unmanned manufacturing system. In this study, the methods which use laser displacement signals and banded energy method are proposed to monitor chatter vibration in the turning process. From this method, the monitoring system of the chatter vibration was developed and investigated its practical possibility. As a result, it is shown by experiments that the chatter vibration can be detected accurately, and it can be widely used in most turning processes.