• Smart Structures and Systems
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• 제21권5호
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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.

• 한국태양에너지학회 논문집
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• 제29권6호
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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.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2009년도 춘계학술발표대회 논문집
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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.

• Smart Structures and Systems
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• 제12권2호
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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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• 제16권4호
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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.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2005년도 춘계학술대회
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• pp.64-67
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• 2005

A vibration monitoring system for a small size wind turbine (WIT) is established and operated. The monitoring system consists of monolithic integrated chip accelerometer for vibration monitoring, anemometers for wind data acquisition and auxiliary sensors for atmospheric data. Using the monitoring system, vibration response of a 6kW stand alone WIT generator is investigated. Acceleration data of the WIT tower under various operation condition is acquired in real time using LabVIEW and the data are remotely transferred from the test site to the laboratory in school by internet. Vibration response characteristics of the tower structure are diagnosed in the aspect of stability of W/T. Wind data and electrical power performance are also investigated with the stability problem.

• 한국태양에너지학회 논문집
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• 제30권3호
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• pp.25-32
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• 2010

A real-time monitoring system was developed for transfer, receive, backup and analysis of wind power data at three wind farm(Hang won, Hankyung and Sung san) in Jeju. For this monitoring system a communication system analysis, a collection of data and transmission module development, data base construction and data analysis and management module was developed, respectively. These modules deal with mechanical, electrical and environmental problem. Especially, time series graphic is supported by the data analysis and management module automatically. The time series graphic make easier to raw data analysis. Also, the real-time monitoring system is connected with wind power forecasting system through internet web for data transfer to wind power forecasting system's data base.

• 한국정밀공학회지
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• 제20권5호
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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.

• Smart Structures and Systems
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• 제21권5호
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• 산업기술연구
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• 제26권A호
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• pp.63-68
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• 2006

In this paper, remote monitoring system for wind turbine is developed. The developed system consists of data acquisition for wind sensor, and monitoring for site environment. In order to accomplish effective monitoring, the system uses Datasocket, SMB, FTP, Web Server, and G Web Server. Two computer system - one is data acquisition computer using Windows-XP and the other is monitoring computer using UNIX - constraint the distribute system with individual tasks. By using this system, one can perform various monitoring and control tasks in Wind-Turbine application, efficiently.