TY - JOUR

T1 - A data-based model for condition monitoring and maintenance planning for protective coating systems for wind tower structures

AU - Momber, Andreas W.

AU - Nattkemper, Tim W.

AU - Langenkämper, Daniel

AU - Möller, Torben

AU - Brün, Daniel

AU - Schaumann, Peter

AU - Shojai, Mohammad Sulaiman

N1 - Funding Information: The project ISyMOO is funded by the Federal Ministry of Economic Affairs and Energy (BMWi) through the 6th National Energy Research Program under the funding number 0324254A . The authors are thankful to Mr. Martin Schubert, Omexom Renewable Energies Offshore GmbH, Oldenburg, Germany, for his support during the wind park site assessments.

PY - 2022/3

Y1 - 2022/3

N2 - 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.

AB - 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.

KW - Coatings

KW - Computer vision

KW - Corrosion

KW - Image processing

KW - Maintenance optimization

KW - Virtual twin

KW - Wind turbines

UR - http://www.scopus.com/inward/record.url?scp=85123685408&partnerID=8YFLogxK

U2 - 10.1016/j.renene.2022.01.022

DO - 10.1016/j.renene.2022.01.022

M3 - Article

AN - SCOPUS:85123685408

VL - 186

SP - 957

EP - 973

JO - Renewable energy

JF - Renewable energy

SN - 0960-1481

ER -