Open Access

The thermographic methods NDT division of BAM is aiming to develop a wind turbine blade (WTB) inspection tool using infrared thermographic scanning of operational wind turbines in the project EvalTherm.

A steady increase of wind energy infrastructure brings along a challenge of maintaining and operating wind turbines (WT) with its multiple components. Inspection of wind turbine rotor blades (WTB) is an important part of maintaining the overall health and safety of a WT. It involves visually or mechanically examining the blades for signs of damage or wear that could affect their performance and structural integrity of the entire WT. A WTB is a complex structure due to its ever-increasing scale (going beyond 100 m for a 16 MW WT) as well as multi-material construction. Passive infrared thermography offers an alternative to contact- or proximity-based inspection techniques currently in use such as visual inspection performed by technical personnel (using a lift or a drone) and involves looking for signs of damage on the surface of the blades, and ultrasonic testing to detect internal defects. In contrast to active thermography, passive thermography uses the sun as source of heat, instead of conventional heat lamps, flash, or laser. An inspection technique to (semi-autonomously) inspect the WTBs of an operating WT from the ground has been developed. Given the optimum thermal contrast (weather conditions for field measurements), external as well as internal features of the WTB can be visualised with appropriate post-processing. The work presented here is part of an ongoing multi-partner project titled “EvalTherm”: the evaluation of passive thermography as a non-destructive inspection tool of WTBs in operation. In this work, artificial defects representative of realistic defects in glass fibre reinforced plastic (GFRP) WTBs are introduced in out-of-service WTB pieces. These are scanned using X-ray computed tomography to obtain a three-dimensional reconstruction to be used as input for finite-element based thermal simulation using COMSOL Multiphysics. The simulation data is compared with infrared thermal inspection of the same WTB section, in order to compare the effect of thermal contrast caused in certain weather conditions. In addition, the influence of defect characteristics such as defect size, morphology, and location on detectability is investigated. Validated simulation models are used to predict thermal signatures of defects along with the optimal thermal contrast. Such simulation models in combination with weather forecast data can assist operators of wind turbine infrastructure to plan passive thermography inspection without the need of dangerous inspection procedures and associated shutdown of energy production.

With increasing wind energy capacity and installation of wind turbines, new inspection techniques are being explored to examine wind turbine rotor blades, especially during operation. A common result of surface damage phenomena (such as leading-edge erosion) is the premature transition of laminar to turbulent flow on the surface of rotor blades. In the KI-VISIR (Künstliche Intelligenz Visuell und Infrarot Thermografie – Artificial Intelligence-Visual and Infrared Thermography) project, infrared thermography is used as an inspection tool to capture so-called thermal turbulence patterns (TTP) that result from such surface contamination or damage. To compliment the thermographic inspections, high-resolution photography is performed to visualise, in detail, the sites where these turbulence patterns initiate. A convolutional neural network (CNN) was developed and used to detect and localise the turbulence patterns. A unique dataset combining the thermograms and visual images of operational wind turbine rotor blades has been provided, along with the simplified annotations for the turbulence patterns. Additional tools are available to allow users to use the data requiring only basic Python programming skills.

Welded steel structures used in the offshore wind industry are exposed to harsh marine environments, which can result in corrosion-induced fatigue damage. Of particular concern is the heat affected zone (HAZ) of welded joints, a region known for its altered microstructure and mechanical properties, which can significantly influence the initiation and propagation of fatigue cracks. This study investigates the short and long fatigue crack growth rates, and the effect of seawater exposure, for the HAZ in S355 steel weldments. Single-edge notch bend (SENB) specimens are used, with a shallow notch in the HAZ. A series of specimens is immersed in synthetic seawater that is continuously circulated at a controlled temperature to assess the synergistic effects of corrosion and fatigue. The experimental method integrates a novel application of front face strain compliance for monitoring short cracks, alongside an extended back-face strain compliance approach for monitoring long crack propagation. It is concluded that the short fatigue crack growth rate of the HAZ is 2.7 to 3.5 times higher in seawater as compared to air. As the crack propagates and enters into the long crack regime, the ratio decreases to 2.2 times at the transition point of the two-stage crack growth curve and further decreases to 1.5 times when the notch advances towards fracture. The findings indicate that the fatigue crack growth rates documented in standards tend to be on the conservative side. This study significantly enriches the fatigue crack growth data available in literature, which will contribute to a more accurate lifetime assessment offshore wind turbine structures.

The growing wind energy infrastructure presents a significant challenge in the maintenance and operation of wind turbines (WT) and their intricate components. An important aspect of WT maintenance is the inspection of wind turbine rotor blades (WTB) to ensure the overall health and safety of the turbine. This inspection process involves both visual and mechanical examinations of the blades to identify any indicators of damage or wear that could compromise their performance and, consequently, the structural integrity of the entire WT system. The complexity of WTBs is compounded by their ever-expanding dimensions, exceeding 100 meters in length for 16 MW WT systems, and their multi-material composition. Within this context, passive infrared thermography emerges as a potential alternative to conventional contact- or proximity-based inspection methods. Unlike active thermography, passive thermography uses solar radiation and ambient temperature variation for thermal contrast, eliminating the need for traditional heat lamps, flash, or laser-based techniques. A novel inspection method has been developed to semi-autonomously assess wind turbine blades (WTBs) while the wind turbine (WT) is operational, from ground level. This approach leverages optimal thermal contrast, which depends on prevailing weather conditions during field measurements, enabling the visualization of both external and internal features of the WTBs through post-processing techniques. In this study, thermal data obtained through passive thermography is compared with contemporaneous visual imagery to definitively classify observed features in thermal images as either surface or sub-surface features. This analysis, coupled with corresponding weather conditions, provides valuable insights into the capabilities and limitations of the inspection technique. Additionally, finite-element-based (FE) thermal simulations of a WTB section are employed to parametrically assess the influence of weather conditions, beyond those observed during field measurements, based on a validated model. In addition, the thermal images also consist of thermal signatures of leading-edge turbulence due to possible leading-edge erosion in WTBs. These are primarily vortices, and their shape and size depend on the morphology of the damage as well as the rotational speed of the WTBs. The inspections are accompanied by automatic data evaluation of the thermal signatures. To improve the precision of erosion damage identification, a fully convolutional network (FCN) is employed, trained, and tested using over 1000 annotated thermographic blade images. Additionally, the study introduces strategies for grouping smaller damage indications and simplification rules based on realistic thermal imaging resolutions. As leading-edge erosion could potentially lead to annual energy production (AEP) losses, this technique could prove to be a powerful tool in establishing the presence of damage and the resulting AEP loss.