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Review
. 2022 Feb 18;22(4):1627.
doi: 10.3390/s22041627.

Non-Destructive Techniques for the Condition and Structural Health Monitoring of Wind Turbines: A Literature Review of the Last 20 Years

Affiliations
Review

Non-Destructive Techniques for the Condition and Structural Health Monitoring of Wind Turbines: A Literature Review of the Last 20 Years

Marco Civera et al. Sensors (Basel). .

Abstract

A complete surveillance strategy for wind turbines requires both the condition monitoring (CM) of their mechanical components and the structural health monitoring (SHM) of their load-bearing structural elements (foundations, tower, and blades). Therefore, it spans both the civil and mechanical engineering fields. Several traditional and advanced non-destructive techniques (NDTs) have been proposed for both areas of application throughout the last years. These include visual inspection (VI), acoustic emissions (AEs), ultrasonic testing (UT), infrared thermography (IRT), radiographic testing (RT), electromagnetic testing (ET), oil monitoring, and many other methods. These NDTs can be performed by human personnel, robots, or unmanned aerial vehicles (UAVs); they can also be applied both for isolated wind turbines or systematically for whole onshore or offshore wind farms. These non-destructive approaches have been extensively reviewed here; more than 300 scientific articles, technical reports, and other documents are included in this review, encompassing all the main aspects of these survey strategies. Particular attention was dedicated to the latest developments in the last two decades (2000-2021). Highly influential research works, which received major attention from the scientific community, are highlighted and commented upon. Furthermore, for each strategy, a selection of relevant applications is reported by way of example, including newer and less developed strategies as well.

Keywords: artificial intelligence; blade monitoring; condition monitoring; damage detection; fault diagnostics; non-destructive testing; structural health monitoring; wind farm; wind turbine.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 2
Figure 2
Bar chart of the estimated investment (left) and O&M (right) costs per MW of an onshore HAWT, according to the class of mean electric power produced. Based on data retrieved from Ref. [27].
Figure 3
Figure 3
Estimated costs of a HAWT, as a percentage of the total and excluding foundations. Based on data retrieved from Ref. [30].
Figure 1
Figure 1
Percentage of new WT installations in 2020 (both on- and offshore), in terms of produced MW capacity. Based on data retrieved from [14].
Figure 4
Figure 4
Structural components of a fixed offshore HAWT according to IEC 61400-3-1.
Figure 5
Figure 5
Key components of a typical wind turbine blade. The upper and lower surfaces are also known as the suction (or windward) and pressure (or lee) sides, respectively. The blade root bolt connection shown here is a classic T-bolt type.
Figure 6
Figure 6
Mechanical and electrical components inside the nacelle of a conventional HAWT.
Figure 7
Figure 7
Damage and failure statistics. (a) Percentage of unforeseen malfunctions as recorded in Germany for 1500 wind turbines. Based on data retrieved from Ref. [42], collected over 15 years (34,582 events). (b,c) percentage distribution of the total number of failures and downtime for WTs. Based on data retrieved from Ref. [43], collected from several sources in Sweden, totalling about 600 WTs from 2000 to 2004 (1202 events, 156,202 h). The nomenclature used in the original sources is reproduced for all charts.
Figure 8
Figure 8
Maintenance strategies according to EN 13306:2017.
Figure 9
Figure 9
The range of the electromagnetic spectrum that can be covered by common optical techniques (digital, multi/hyperspectral, and thermographic cameras), as well as Gamma-ray, X-ray, microwave, and terahertz testing technologies.
Figure 10
Figure 10
The main IRT techniques available as of 2021.
Figure 11
Figure 11
The basic concept of AE event detection.
Figure 12
Figure 12
The basic concept of UT. (a) conventional, i.e., through the thickness (reflection mode), (b) guided waves. (through transmission mode).
Figure 13
Figure 13
Qualitative distribution of costs and deployment levels of different NDTs. Based on data from Refs. [329,330,331].

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