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Operational model updating of low-order horizontal axis wind turbine models for structural health monitoring applications.

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Title: Operational model updating of low-order horizontal axis wind turbine models for structural health monitoring applications.
Authors: Velazquez, Antonio1, Swartz, R. Andrew1 raswartz@mtu.edu
Source: Journal of Intelligent Material Systems & Structures. Sep2015, Vol. 26 Issue 13, p1739-1752. 14p.
Subjects: Horizontal axis wind turbines, Structural health monitoring, Rotational motion, Nonlinear analysis, Computer-aided design, Mechanical loads, Aerodynamics
Abstract: Rotational machinery such as horizontal axis wind turbines exhibits complex and nonlinear dynamics (e.g. precession and Coriolis effects, torsional coupling) and is subjected to nonlinear constrained conditions (i.e. aeroelastic interaction). For those reasons, aeroelastic and computer-aided models reproduced under controlled conditions may fail to predict the correct non-stationary loading and resistance patterns of wind turbines in actual operation. Operational techniques for extracting modal properties under actual non-stationary loadings are needed in order to improve computer-aided elasto-aerodynamic models to better characterize the actual behavior of horizontal axis wind turbines in operational scenarios, monitor and diagnose the system for integrity and damage through time, and optimize control systems. For structural health monitoring applications, model updating of stochastic aerodynamic problems has gained interest over the past decades. A probability theory framework is employed in this study to update a horizontal axis wind turbine model using such a stochastic global optimization approach. Structural identification is addressed under regular wind turbine operation conditions for non-stationary, unmeasured, and uncontrolled excitations by means of stochastic subspace identification techniques. This numerical framework is then coupled with an adaptive simulated annealing numerical engine for solving the problem of model updating. Numerical results are presented for an experimental deployment of a small horizontal axis wind turbine structure. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Intelligent Material Systems & Structures is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 109030254
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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IllustrationInfo
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  Data: Operational model updating of low-order horizontal axis wind turbine models for structural health monitoring applications.
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  Data: <searchLink fieldCode="AR" term="%22Velazquez%2C+Antonio%22">Velazquez, Antonio</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Swartz%2C+R%2E+Andrew%22">Swartz, R. Andrew</searchLink><relatesTo>1</relatesTo><i> raswartz@mtu.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Intelligent+Material+Systems+%26+Structures%22">Journal of Intelligent Material Systems & Structures</searchLink>. Sep2015, Vol. 26 Issue 13, p1739-1752. 14p.
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  Data: <searchLink fieldCode="DE" term="%22Horizontal+axis+wind+turbines%22">Horizontal axis wind turbines</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+health+monitoring%22">Structural health monitoring</searchLink><br /><searchLink fieldCode="DE" term="%22Rotational+motion%22">Rotational motion</searchLink><br /><searchLink fieldCode="DE" term="%22Nonlinear+analysis%22">Nonlinear analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Computer-aided+design%22">Computer-aided design</searchLink><br /><searchLink fieldCode="DE" term="%22Mechanical+loads%22">Mechanical loads</searchLink><br /><searchLink fieldCode="DE" term="%22Aerodynamics%22">Aerodynamics</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Rotational machinery such as horizontal axis wind turbines exhibits complex and nonlinear dynamics (e.g. precession and Coriolis effects, torsional coupling) and is subjected to nonlinear constrained conditions (i.e. aeroelastic interaction). For those reasons, aeroelastic and computer-aided models reproduced under controlled conditions may fail to predict the correct non-stationary loading and resistance patterns of wind turbines in actual operation. Operational techniques for extracting modal properties under actual non-stationary loadings are needed in order to improve computer-aided elasto-aerodynamic models to better characterize the actual behavior of horizontal axis wind turbines in operational scenarios, monitor and diagnose the system for integrity and damage through time, and optimize control systems. For structural health monitoring applications, model updating of stochastic aerodynamic problems has gained interest over the past decades. A probability theory framework is employed in this study to update a horizontal axis wind turbine model using such a stochastic global optimization approach. Structural identification is addressed under regular wind turbine operation conditions for non-stationary, unmeasured, and uncontrolled excitations by means of stochastic subspace identification techniques. This numerical framework is then coupled with an adaptive simulated annealing numerical engine for solving the problem of model updating. Numerical results are presented for an experimental deployment of a small horizontal axis wind turbine structure. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Intelligent Material Systems & Structures is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1177/1045389X14563864
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 14
        StartPage: 1739
    Subjects:
      – SubjectFull: Horizontal axis wind turbines
        Type: general
      – SubjectFull: Structural health monitoring
        Type: general
      – SubjectFull: Rotational motion
        Type: general
      – SubjectFull: Nonlinear analysis
        Type: general
      – SubjectFull: Computer-aided design
        Type: general
      – SubjectFull: Mechanical loads
        Type: general
      – SubjectFull: Aerodynamics
        Type: general
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      – TitleFull: Operational model updating of low-order horizontal axis wind turbine models for structural health monitoring applications.
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            NameFull: Velazquez, Antonio
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            NameFull: Swartz, R. Andrew
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            – D: 01
              M: 09
              Text: Sep2015
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              Y: 2015
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