• Smart Structures and Systems
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• v.21 no.5
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• pp.601-609
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• 2018

The estimated probabilistic model of wind data based on the conventional approach may have high discrepancy compared with the true distribution because of the uncertainty caused by the instrument error and limited monitoring data. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method has been developed in the companion paper and is conducted to formulate the joint probability density function (PDF) of wind speed and direction using the wind monitoring data of the investigated bridge. The established bivariate model of wind speed and direction only represents the features of available wind monitoring data. To characterize the stochastic properties of the wind parameters with the subsequent wind monitoring data, in this study, Bayesian inference approach considering the uncertainty is proposed to update the wind parameters in the bivariate probabilistic model. The slice sampling algorithm of Markov chain Monte Carlo (MCMC) method is applied to establish the multi-dimensional and complex posterior distribution which is analytically intractable. The numerical simulation examples for univariate and bivariate models are carried out to verify the effectiveness of the proposed method. In addition, the proposed Bayesian inference approach is used to update and optimize the parameters in the bivariate model using the wind monitoring data from the investigated bridge. The results indicate that the proposed Bayesian inference approach is feasible and can be employed to predict the bivariate distribution of wind speed and direction with limited monitoring data.

• 유체기계공업학회:학술대회논문집
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• 2004.12a
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• pp.385-389
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• 2004

Test facilities for the wind turbine performance monitoring and mechanical load measurements are installed in Vestas 100 kW wind turbine in Wollyong test site, Jeju island. The monitoring system consists of Garrad-Hassan T-MON system, telemetry system for blade load measurement, various sensors such as anemometer, wind vane, strain gauge, power meter, and etc. The experimental procedure for the measurement of wind turbine loads, such as edgewise(lead-lag) bending moment, flapwise bending moment, and tower base bending moment, has been established. Strain gauges are on-site calibrated against load cell prior to monitoring the wind turbine loads. Using the established monitoring system, the wind turbine is remotely monitored. From the measured load data, the load analysis has been performed to obtain the load power spectral density and the fatigue load spectra of the wind turbine.

• Smart Structures and Systems
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• v.12 no.2
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• pp.209-233
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• 2013

With an annual growth rate of about 30%, wind energy systems, such as wind turbines, represent one of the fastest growing renewable energy technologies. Continuous structural health monitoring of wind turbines can help improving structural reliability and facilitating optimal decisions with respect to maintenance and operation at minimum associated life-cycle costs. This paper presents an integrated monitoring system that is designed to support structural assessment and life-cycle management of wind turbines. The monitoring system systematically integrates a wide variety of hardware and software modules, including sensors and computer systems for automated data acquisition, data analysis and data archival, a multiagent-based system for self-diagnosis of sensor malfunctions, a model updating and damage detection framework for structural assessment, and a management module for monitoring the structural condition and the operational efficiency of the wind turbine. The monitoring system has been installed on a 500 kW wind turbine located in Germany. Since its initial deployment in 2009, the system automatically collects and processes structural, environmental, and operational wind turbine data. The results demonstrate the potential of the proposed approach not only to ensure continuous safety of the structures, but also to enable cost-efficient maintenance and operation of wind turbines.

• Wind and Structures
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• v.24 no.4
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• pp.333-350
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• 2017

Differing from the fixed-type, the dynamic motion of floating-type offshore wind turbines is very sensitive to wind and wave excitations. Thus, the sensing and monitoring of its motion is important to evaluate the dynamic responses to the external excitation. In this context, a monitoring system for sensing and processing the wind-induced dynamic motion of spar-type floating offshore wind turbine is developed in this study. It is developed by integrating a 1/00 scale model of 2.5MW spar-type floating offshore wind turbine, water basin equipped with the wind generator, sensing and data acquisition systems, real-time CompactRIO controller and monitoring program. The scale model with the upper rotatable blades is installed within the basin by means of three mooring lines, and its translational and rotational motions are detected by 3-axis inclinometer and accelerometers and gyroscope. The detected motion signals are processed using a real-time controller CompactRIO to calculate the acceleration and tilting angle of nacelle and the attitude of floating platform. The developed monitoring system is demonstrated and validated by measuring and evaluating the time histories and trajectories of nacelle and platform motions for three different wind velocities and for eight different fairlead positions.

• Wind and Structures
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• v.15 no.4
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• pp.301-311
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• 2012

This paper presents results from the structural monitoring of a steel wind tower characterized and presented in Part I of the paper. Monitoring period corresponds to about fifteen months of measurements. Results presented refer to stress distribution on shell and in bolts at different heights, stress fatigue spectra, section forces along height evaluated from the stress measurements and comparison with design forces, dynamic response in terms of accelerations, stresses, deflections and rotations.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.5
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• pp.92-98
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• 2003

A wind turbine monitoring system is essential equipment fur the performance evaluation and mechanical load analysis of a wind turbine. A monitoring system using LabVIEW is developed in this study. This system monitors signals from a meteorological mast, wind turbine generator, and tower. The discrete signals which are sampled at t Hz are automatically saved on a data file in the unit of a day. Besides these basic functions, the developed monitoring system has the other several capabilities. One of them is the information access from a remote PC through the internet. A vision image of the test site area and data files that are produced by LabVIBW software can be uploaded to the main computer located in a remote site. An emergency backup system using UPS fur the power loss on the monitoring HW is also prepared, A detail explanation for the developed wind turbine monitoring system is presented in this study.

• Journal of Industrial Technology
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• v.28 no.A
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• pp.63-69
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• 2008

The exact load measurements for the mechanical parts of wind turbine are important step both for evaluation of specific wind turbine design and for a certification process. A wind turbine monitoring system is essential equipment for mechanical load analysis of a wind turbine. This monitoring system is based on IEC 61400-13 and strain gage are used to measure a mechanical load of wind turbine. Also this system monitors signals from a meteorological mast. The measured signals which are sampled at 200 Hz are automatically saved on a data file in the unit of ten minutes. A detail explanation for the developed wind turbine monitoring system is presented in this study.

• 한국태양에너지학회:학술대회논문집
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• 2009.04a
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• pp.277-280
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• 2009

Wind monitoring system is an absolutely-required system for assessing a performance and fatigue load of the wind energy generator in an on-shore wind energy experimental research complex. It was implemented for the purpose of monitoring the wind information measured from a meteorological tower at the monitoring house and of utilizing the measured data for the performance assessment, by using the LabVIEW program. Then, by adding the performance assessment-related data acquired from the wind energy generator during the performance assessment and the data recorder for synchronizing the data of meteorological tower, the system was implemented. Because it transmitted the data by converting the output 'RS-232' of data logger which measures the wind condition into CAN protocol, the data error rate was minimized, This paper is intended to explain the developed wind data monitoring system.

• Journal of the Korean Solar Energy Society
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• v.29 no.6
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• pp.69-74
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• 2009

Monitoring system is an absolutely-required system for assessing a performance and fatigue load of the wind turbine in an on-shore wind energy experimental research complex. It was implemented for the purpose of monitoring the wind information measured from a meteorological tower at the monitoring house, and of utilizing the measured data(fatigue data and electric analyzing data of wind turbine)for the performance assessment, by using the LabVIEW program. Then, by adding the performance assessment-related data acquired from the wind turbine during the performance assessment and the data recorder for synchronizing the data of meteorological tower, the system(BusDAQ) was implemented. Because it transmitted the data by converting the output 'RS-232' of data logger which measures the wind condition into CAN protocol, the data error rate was minimized. Also, This paper is introduced to make the best use of the developed monitoring system and to explain about construct of the system and detailed data communication of its system.

• Wind and Structures
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• v.16 no.4
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• pp.373-391
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• 2013

This is the first of two companion papers that analyse ten years of on-site monitoring data for the Confederation Bridge to determine the validity of the original wind speeds and wind loads predicted in 1994 when the bridge was being designed. The check of the original design values is warranted because the design wind speed at the middle of Northumberland Strait was derived from data collected at shore-based weather stations, and the design wind loads were based on tests of section and full-aeroelastic models in the wind tunnel. This first paper uses wind, tilt, and acceleration monitoring data to determine the static and dynamic responses of the bridge, which are then used in the second paper to derive the static and dynamic wind loads. It is shown that the design ten-minute mean wind speed with a 100-year return period is 1.5% less than the 1994 design value, and that the bridge has been subjected to this design event once on November 7, 2001. The dynamic characteristics of the instrumented spans of the bridge including frequencies, mode shapes and damping are in good agreement with published values reported by others. The on-site monitoring data show bridge response to be that of turbulent buffeting which is consistent with the response predicted at the design stage.