• Title/Summary/Keyword: Global Maximum Point

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Fatigue Analysis of Welded Toe of Wind Turbine Tower Access Door (Wind Turbine Tower의 Door 용접부에 대한 피로 강도 연구)

  • Han Dong-Young;Koh Jang-Wook;Choi Won-Ho;Lee Seung-Kuh
    • 한국신재생에너지학회:학술대회논문집
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    • 2005.06a
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    • pp.72-75
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    • 2005
  • Recently, as the global warming by fossil fuels become social issues. the interest of renewable energy producing system is increasing rapidly. Among these, wind turbines are most highlighted because of its economic competitiveness. The tower occupying about $20\%$ of overall turbine costs, is one of the main components of wind turbine. Tower access door located to base part of the tower, is used to enter the tower. This is the main structural weak point because of door hole, weldment, etc. In this study, by FEM, we retrieved the maximum van Mises stress at door location and carried out fatigue analysis using stresses at weld toe locations of tower access door part.

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High Accuracy of Indoor Hybrid Positioning Method based on Mobile Device (모바일 단말 기반 고정밀 실내 융합 측위 방법)

  • Lee, J.K.;So, W.S.;Lee, J.S.;Yoo, S.J.
    • Electronics and Telecommunications Trends
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    • v.29 no.6
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    • pp.113-125
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    • 2014
  • 최근 모바일 단말 기술의 발전과 무선망의 성능 향상에 따른 다양한 서비스가 제공되고 있는 추세이며, 위치정보인식시스템과 결합된 서비스에 많은 관심이 높아졌다. 본고에서는 GPS(Global Positioning System)의 신호가 미치지 못하는 건물의 실내환경에 적합한 경로 안내서비스 및 지하시설물 안내 등 초정밀 실내 측위 서비스를 제공하기 위한 융합 측위 방안을 제안한다. 융합 측위 방안은 실내외 연속 측위를 위해 실외에서는 GPS를 이용하고 실내환경에서는 WLAN 기반의 측위 전용 AP(Access Point)를 이용, 전파신호의 LoS(Line of Sight)를 확보하여 측위하고 전파음영지역에서는 스마트폰의 가속도, 자이로센서 등 여러 가지 관성센서를 활용하여 PDR(Pedestrian Dead Reckoning) 알고리즘 등을 적용하여 측위한다. 또한 측위 정확도 향상 및 오차를 줄이기 위한 방법으로 LSE(Least Squire Estimation) 및 EKF(Extended Kalman Filter), KNN(K-Neighbor Node)/MSSM(Maximum Signal Strength Model) Algorithm 등 다양한 융합 측위 알고리즘을 적용하여 실내환경에 적합한 최적의 초정밀 실내 측위 서비스를 제공한다.

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Inelastic displacement-based design approach of R/C building structures in seismic regions

  • Rubinstein, Marcelo;Moller, Oscar;Giuliano, Alejandro
    • Structural Engineering and Mechanics
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    • v.12 no.6
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    • pp.573-594
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    • 2001
  • A two-level displacement-based design procedure is developed. To obtain the displacement demands, elastic spectra for occasional earthquakes and inelastic spectra for rare earthquakes are used. Minimum global stiffness and strength to be supplied to the structure are based on specified maximum permissible drift limits and on the condition that the structure responds within the elastic range for occasional earthquakes. The performance of the structure may be assessed by an inelastic push-over analysis to the required displacement and the evaluation of damage indices. The approach is applied to the design of a five-story reinforced concrete coupled wall structure located in the most hazardous seismic region of Argentina. The inelastic dynamic response of the structure subjected to real and artificially generated acceleration time histories is also analyzed. Finally, advantages and limitations of the proposed procedure from the conceptual point of view and practical application are discussed.

A Novel Partial Shading Detection Algorithm Utilizing Power Level Monitoring

  • Wellawatta, Thusitha;Seo, Young-Tae;Choi, Sung-Jin
    • Proceedings of the KIPE Conference
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    • 2017.07a
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    • pp.136-137
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    • 2017
  • Maximum power point tracking (MPPT) under partial shading condition (PSC) is a challenging process in the PV array system. The shaded PV panel makes different peak patterns on the P-V curve and misguides the MPPT algorithm. Various kinds of global MPP (GMPP) detecting algorithms are used to overcome this issue. Generally, too frequent execution of GMPP tracking algorithm reduces the achievable power of PV panel due to time spent on the scanning process. Thus, partial shading detection algorithm is essential for efficient utilization of solar energy source. While conventional method only detects fast shading patterns, the proposed algorithm always shows superb performance regardless of the speed of partial shading patterns.

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The Improved Joint Bayesian Method for Person Re-identification Across Different Camera

  • Hou, Ligang;Guo, Yingqiang;Cao, Jiangtao
    • Journal of Information Processing Systems
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    • v.15 no.4
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    • pp.785-796
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    • 2019
  • Due to the view point, illumination, personal gait and other background situation, person re-identification across cameras has been a challenging task in video surveillance area. In order to address the problem, a novel method called Joint Bayesian across different cameras for person re-identification (JBR) is proposed. Motivated by the superior measurement ability of Joint Bayesian, a set of Joint Bayesian matrices is obtained by learning with different camera pairs. With the global Joint Bayesian matrix, the proposed method combines the characteristics of multi-camera shooting and person re-identification. Then this method can improve the calculation precision of the similarity between two individuals by learning the transition between two cameras. For investigating the proposed method, it is implemented on two compare large-scale re-ID datasets, the Market-1501 and DukeMTMC-reID. The RANK-1 accuracy significantly increases about 3% and 4%, and the maximum a posterior (MAP) improves about 1% and 4%, respectively.

Optimization of Gaussian Mixture in CDHMM Training for Improved Speech Recognition

  • Lee, Seo-Gu;Kim, Sung-Gil;Kang, Sun-Mee;Ko, Han-Seok
    • Speech Sciences
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    • v.5 no.1
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    • pp.7-21
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    • 1999
  • This paper proposes an improved training procedure in speech recognition based on the continuous density of the Hidden Markov Model (CDHMM). Of the three parameters (initial state distribution probability, state transition probability, output probability density function (p.d.f.) of state) governing the CDHMM model, we focus on the third parameter and propose an efficient algorithm that determines the p.d.f. of each state. It is known that the resulting CDHMM model converges to a local maximum point of parameter estimation via the iterative Expectation Maximization procedure. Specifically, we propose two independent algorithms that can be embedded in the segmental K -means training procedure by replacing relevant key steps; the adaptation of the number of mixture Gaussian p.d.f. and the initialization using the CDHMM parameters previously estimated. The proposed adaptation algorithm searches for the optimal number of mixture Gaussian humps to ensure that the p.d.f. is consistently re-estimated, enabling the model to converge toward the global maximum point. By applying an appropriate threshold value, which measures the amount of collective changes of weighted variances, the optimized number of mixture Gaussian branch is determined. The initialization algorithm essentially exploits the CDHMM parameters previously estimated and uses them as the basis for the current initial segmentation subroutine. It captures the trend of previous training history whereas the uniform segmentation decimates it. The recognition performance of the proposed adaptation procedures along with the suggested initialization is verified to be always better than that of existing training procedure using fixed number of mixture Gaussian p.d.f.

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Point Cloud-based Automated Building Tilt Measurement (포인트 클라우드 기반 건축물 기울기 측정 자동화)

  • Dayoung Yu;Chaeeun Lee;Sung-Han Sim
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.27 no.5
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    • pp.84-88
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    • 2023
  • This study proposes an automated tilt measurement method using point cloud for buildings. The proposed method consists of two main steps: 1) exterior wall plane extraction, and 2) edge estimation and angle calculation. To validate the performance of the proposed method, the algorithm is applied to a target building, of which the estimated tilt values are compared with those obtained from a total station, a commonly used tool for tilt measurement. The result shows that most estimated tilt values are within the maximum and minimum ranges of the total station measurement, suggesting that the proposed algorithm provides sufficient measurement accuracy. Furthermore, the proposed method is shown to be automated and reliable as well as free from human-induced errors compared to the total station.

Seismic retrofit of steel structures with re-centering friction devices using genetic algorithm and artificial neural network

  • Mohamed Noureldin;Masoum M. Gharagoz;Jinkoo Kim
    • Steel and Composite Structures
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    • v.47 no.2
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    • pp.167-184
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    • 2023
  • In this study, a new recentering friction device (RFD) to retrofit steel moment frame structures is introduced. The device provides both self-centering and energy dissipation capabilities for the retrofitted structure. A hybrid performance-based seismic design procedure considering multiple limit states is proposed for designing the device and the retrofitted structure. The design of the RFD is achieved by modifying the conventional performance-based seismic design (PBSD) procedure using computational intelligence techniques, namely, genetic algorithm (GA) and artificial neural network (ANN). Numerous nonlinear time-history response analyses (NLTHAs) are conducted on multi-degree of freedom (MDOF) and single-degree of freedom (SDOF) systems to train and validate the ANN to achieve high prediction accuracy. The proposed procedure and the new RFD are assessed using 2D and 3D models globally and locally. Globally, the effectiveness of the proposed device is assessed by conducting NLTHAs to check the maximum inter-story drift ratio (MIDR). Seismic fragilities of the retrofitted models are investigated by constructing fragility curves of the models for different limit states. After that, seismic life cycle cost (LCC) is estimated for the models with and without the retrofit. Locally, the stress concentration at the contact point of the RFD and the existing steel frame is checked being within acceptable limits using finite element modeling (FEM). The RFD showed its effectiveness in minimizing MIDR and eliminating residual drift for low to mid-rise steel frames models tested. GA and ANN proved to be crucial integrated parts in the modified PBSD to achieve the required seismic performance at different limit states with reasonable computational cost. ANN showed a very high prediction accuracy for transformation between MDOF and SDOF systems. Also, the proposed retrofit showed its efficiency in enhancing the seismic fragility and reducing the LCC significantly compared to the un-retrofitted models.

The Variations of Stratospheric Ozone over the Korean Peninsula 1985~2009 (한반도 상공의 오존층 변화 1985~2009)

  • Park, Sang Seo;Kim, Jhoon;Cho, Nayeong;Lee, Yun Gon;Cho, Hi Ku
    • Atmosphere
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    • v.21 no.4
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    • pp.349-359
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    • 2011
  • The climatology in stratospheric ozone over the Korean Peninsula, presented in previous studies (e.g., Cho et al., 2003; Kim et al., 2005), is updated by using daily and monthly data from satellite and ground-based data through December 2009. In addition, long-term satellite data [Total Ozone Mapping Spectrometer (TOMS), Ozone Monitoring Instrument (OMI), 1979~2009] have been also analyzed in order to deduce the spatial distributions and temporal variations of the global total ozone. The global average of total ozone (1979~2009) is 298 DU which shows a minimum of about 244 DU in equatorial latitudes and increases poleward in both hemispheres to a maximum of about 391 DU in Okhotsk region. The recent period, from 2006 to 2009, shows reduction in total ozone by 6% relative to the values for the pre-1980s (1979~1982). The long-term trends were estimated by using a multiple linear regression model (e.g., WMO, 1999; Cho et al., 2003) including explanatory variables for the seasonal variation, Quasi-Biennial Oscillation (QBO) and solar cycle over three different time intervals: a whole interval from 1979 to 2009, the former interval from 1979 to 1992, and the later interval from 1993 to 2009 with a turnaround point of deep minimum in 1993 is related to the effect of Mt. Pinatubo eruption. The global trend shows -0.93% $decade^{-1}$ for the whole interval, whereas the former and the later interval trends amount to -2.59% $decade^{-1}$ and +0.95% $decade^{-1}$, respectively. Therefore, the long-term total ozone variations indicate that there are positive trends showing a recovery sign of the ozone layer in both North/South hemispheres since around 1993. Annual mean total ozone (1985~2009) is distributed from 298 DU for Jeju ($33.52^{\circ}N$) to 352 DU for Unggi ($42.32^{\circ}N$) in almost zonally symmetric pattern over the Korean Peninsula, with the latitudinal gradient of 6 DU $degree^{-1}$. It is apparent that seasonal variability of total ozone increases from Jeju toward Unggi. The annual mean total ozone for Seoul shows 323 DU, with the maximum of 359 DU in March and the minimum of 291 DU in October. It is found that the day to day variability in total ozone exhibits annual mean of 5.7% in increase and -5.2% in decrease. The variability as large as 38.4% in increase and 30.3% in decrease has been observed, respectively. The long-term trend analysis (e.g., WMO, 1999) of monthly total ozone data (1985~2009) merged by satellite and ground-based measurements over the Korean Peninsula shows increase of 1.27% $decade^{-1}$ to 0.80% $decade^{-1}$ from Jeju to Unggi, respectively, showing systematic decrease of the trend magnitude with latitude. This study also presents a new analysis of ozone density and trends in the vertical distribution of ozone for Seoul with data up to the end of 2009. The mean vertical distributions of ozone show that the maximum value of the ozone density is 16.5 DU $km^{-1}$ in the middle stratospheric layer between 24 km and 28 km. About 90.0% and 71.5% of total ozone are found in the troposphere and in the stratosphere between 15 and 33 km, respectively. The trend analysis reconfirms the previous results of significant positive ozone trend, of up to 5% $decade^{-1}$, in the troposphere and the lower stratosphere (0~24 km), with negative trend, of up to -5% $decade^{-1}$, in the stratosphere (24~38 km). In addition, the Umkehr data show a positive trend of about 3% $decade^{-1}$ in the upper stratosphere (38~48 km).

Maximum Power Point Tracking operation of Thermoelectric Module without Current Sensor (전류센서가 없는 열전모듈의 최대전력점 추적방식)

  • Kim, Tae-Kyung;Park, Dae-Su;Oh, Sung-Chul
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.9
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    • pp.436-443
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    • 2017
  • Recently, the development of new energy technologies has become a hot topic due to problems,such as global warming. Unlike renewable energy technologies, such as solar energy generation, solar power, and wind power, which are optimized to achieve medium or above output power, the output power of energy harvesting technology is very small and has not received much attention. On the other hand, as the mobile industry has been revitalized recently, the utility of energy harvesting technology has been reevaluated. In addition, the technology of tracking the maximum power point has been actively researched. This paper proposes a new MPPT(Maximum Power Point Tracking) control method for a TEM(thermoelectric module) for load resistance. The V-I curve characteristics and internal resistance of TEM were analyzed and the conventional MPPT control methods were compared. The P&O(Perturbation and Observation) control method is more accurate, but it is less economical than the CV (Constant Voltage)control method because it usestwo sensors to measure the voltage and current source. The CV control method is superior to the P&O control method in economic aspects because it uses only one voltage sensor but the MPP is not matched precisely. In this paper, a method wasdesigned to track the MPP of TEM combining the advantages of the two control method. The proposed MPPT control method wasverified by PSIM simulation and H/W implementation.