IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v186y2022icp957-973.html
   My bibliography  Save this article

A data-based model for condition monitoring and maintenance planning for protective coating systems for wind tower structures

Author

Listed:
  • Momber, Andreas W.
  • Nattkemper, Tim W.
  • Langenkämper, Daniel
  • Möller, Torben
  • Brün, Daniel
  • Schaumann, Peter
  • Shojai, Sulaiman

Abstract

The application of protective coating systems is the major measure against the corrosion of steel structures for onshore wind turbines. The organic coatings are, however, susceptible to atmospheric exposure and tend to deteriorate during the operation. At the same time, onshore turbines become more powerful and require taller and more resistant tower structures. The inspection and condition monitoring of protective coating systems on large onshore turbines (in excess of 120 m height) is a demanding and time-consuming procedure and requires high human effort. The rapid developments in digitization and data analysis offer opportunities to notably increase the efficiency of monitoring processes and to develop (semi-)automated standardized procedures. The paper describes a data-oriented approach to utilize digital data for the monitoring and maintenance planning of surface protection systems of large onshore wind turbines. The proposed approach includes the following steps: the segmentation of an existing wind power structure into a number of reference areas based on an In-situ Virtual Twin; the definition of a local deterioration degree for each individual reference area; the annotation of image data; the use of heterogenous multi-modal data (image data, geodetical data, meteorological data, profile scanning data) as the sources for condition assessment and monitoring. An example procedure is exercised for a tower structure of an onshore wind power turbine in order to illustrate the practical relevance of the approach.

Suggested Citation

  • Momber, Andreas W. & Nattkemper, Tim W. & Langenkämper, Daniel & Möller, Torben & Brün, Daniel & Schaumann, Peter & Shojai, Sulaiman, 2022. "A data-based model for condition monitoring and maintenance planning for protective coating systems for wind tower structures," Renewable Energy, Elsevier, vol. 186(C), pages 957-973.
    • Handle: RePEc:eee:renene:v:186:y:2022:i:c:p:957-973
    DOI: 10.1016/j.renene.2022.01.022
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148122000222
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2022.01.022?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Momber, A.W., 2016. "Quantitative performance assessment of corrosion protection systems for offshore wind power transmission platforms," Renewable Energy, Elsevier, vol. 94(C), pages 314-327.
    2. Nicolai, Robin P. & Dekker, Rommert & van Noortwijk, Jan M., 2007. "A comparison of models for measurable deterioration: An application to coatings on steel structures," Reliability Engineering and System Safety, Elsevier, vol. 92(12), pages 1635-1650.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nicolai, R.P. & Frenk, J.B.G. & Dekker, R., 2007. "Modelling and Optimizing Imperfect Maintenance of Coatings on Steel Structures," ERIM Report Series Research in Management ERS-2007-043-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. M D Pandey & T Cheng & J A M van der Weide, 2011. "Finite-time maintenance cost analysis of engineering systems affected by stochastic degradation," Journal of Risk and Reliability, , vol. 225(2), pages 241-250, June.
    3. de Jonge, Bram & Teunter, Ruud & Tinga, Tiedo, 2017. "The influence of practical factors on the benefits of condition-based maintenance over time-based maintenance," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 21-30.
    4. C Meier-Hirmer & G Riboulet & F Sourget & M Roussignol, 2009. "Maintenance optimization for a system with a gamma deterioration process and intervention delay: Application to track maintenance," Journal of Risk and Reliability, , vol. 223(3), pages 189-198, September.
    5. Cárdenas-Gallo, Iván & Sarmiento, Carlos A. & Morales, Gilberto A. & Bolivar, Manuel A. & Akhavan-Tabatabaei, Raha, 2017. "An ensemble classifier to predict track geometry degradation," Reliability Engineering and System Safety, Elsevier, vol. 161(C), pages 53-60.
    6. Zhang, Zhengxin & Si, Xiaosheng & Hu, Changhua & Lei, Yaguo, 2018. "Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods," European Journal of Operational Research, Elsevier, vol. 271(3), pages 775-796.
    7. Alaa H. Elwany & Nagi Z. Gebraeel & Lisa M. Maillart, 2011. "Structured Replacement Policies for Components with Complex Degradation Processes and Dedicated Sensors," Operations Research, INFORMS, vol. 59(3), pages 684-695, June.
    8. Boutros El Hajj & Bruno Castanier & Franck Schoefs & Thomas Yeung, 2016. "A risk-oriented degradation model for maintenance of reinforced concrete structure subjected to cracking," Journal of Risk and Reliability, , vol. 230(5), pages 521-530, October.
    9. Gulfam, Raza & Zhang, Peng, 2019. "Power generation and longevity improvement of renewable energy systems via slippery surfaces – A review," Renewable Energy, Elsevier, vol. 143(C), pages 922-938.
    10. Thomas Michael Welte & Iver Bakken Sperstad & Espen Høegh Sørum & Magne Lorentzen Kolstad, 2017. "Integration of Degradation Processes in a Strategic Offshore Wind Farm O&M Simulation Model," Energies, MDPI, vol. 10(7), pages 1-18, July.
    11. Guida, M. & Postiglione, F. & Pulcini, G., 2012. "A time-discrete extended gamma process for time-dependent degradation phenomena," Reliability Engineering and System Safety, Elsevier, vol. 105(C), pages 73-79.
    12. Baussaron, Julien & Mihaela, Barreau & Léo, Gerville-Réache & Fabrice, Guérin & Paul, Schimmerling, 2014. "Reliability assessment based on degradation measurements: How to compare some models?," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 236-241.
    13. Kuniewski, Sebastian P. & van der Weide, Johannes A.M. & van Noortwijk, Jan M., 2009. "Sampling inspection for the evaluation of time-dependent reliability of deteriorating systems under imperfect defect detection," Reliability Engineering and System Safety, Elsevier, vol. 94(9), pages 1480-1490.
    14. Zheng, Rui & Chen, Bingkun & Gu, Liudong, 2020. "Condition-based maintenance with dynamic thresholds for a system using the proportional hazards model," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    15. Cheng, Tianjin & Pandey, Mahesh D. & van der Weide, J.A.M., 2012. "The probability distribution of maintenance cost of a system affected by the gamma process of degradation: Finite time solution," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 65-76.
    16. van Noortwijk, J.M. & van der Weide, J.A.M., 2008. "Applications to continuous-time processes of computational techniques for discrete-time renewal processes," Reliability Engineering and System Safety, Elsevier, vol. 93(12), pages 1853-1860.
    17. Nicolai, R.P. & Koning, A.J., 2006. "A general framework for statistical inference on discrete event systems," Econometric Institute Research Papers EI 2006-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    18. Savage, Gordon J. & Kap Son, Young, 2011. "The set-theory method for systems reliability of structures with degrading components," Reliability Engineering and System Safety, Elsevier, vol. 96(1), pages 108-116.
    19. Calvert, Gareth & Neves, Luis & Andrews, John & Hamer, Matthew, 2020. "Multi-defect modelling of bridge deterioration using truncated inspection records," Reliability Engineering and System Safety, Elsevier, vol. 200(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:186:y:2022:i:c:p:957-973. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.