1 | INTRODUCTION
The global wind energy production has been growing steadily for years as
demand for clean renewable energy increase to meet global climate goals.
Every year, tens of thousands of turbines are installed world-wide,
which makes reliability and low-maintenance operation critical for the
scalability and economic viability of wind energy production. One of the
most maintenance-heavy parts are the turbine blades. In particular, the
leading edge of the blade, which cuts through the air at speeds of
around 300 km/h and therefore experiences the strongest forces and
harshest conditions of the entire structure. Over time, collisions with
rain droplets and other particles may lead to erosion, degrading the
aerodynamic efficiency and thereby reducing the efficiency of the
turbine. As the length and tip-speed of turbine blades have increased
over the years to improve energy capacity per turbine, the challenge of
controlling leading edge erosion has become increasingly difficult. One
of the frontiers in this endeavor is in designing and testing durable
protective coatings that can absorb and dissipate the kinetic energy
from these impacts. The current industry standard for testing leading
edge protection and for estimation of the coating lifetime is a liquid
impingement test known as the whirling arm rain erosion test (RET)
[1]. In the whirling arm test, the erosion process is simulated by
spinning a blade sample inside an artificial rain field resulting in
repeated droplet impacts on the leading edge. The test uses high
rotational speed to accelerate the process, causing high stress loading,
initiation and propagation of cracks, and eventually complete erosion of
the coating. Previous studies have shown that the presence of subsurface
defects reduces the mechanical performance of the coating, leading to
crack formation and erosion [2,3]. Therefore, it is important to
understand the correlation between manufacturing defects and the
degradation of the coating performance. For characterization of RET
specimens and for quality control in manufacturing of blades, a fast,
non-destructive, portable, and cost-efficient scanning technology for
coatings is important.
Current methods for subsurface coating inspection include high-frequency
ultrasound (HFUS), THz imaging, thermographic imaging, and X-ray
computed tomography (XCT). HFUS and THz has the advantage that they can
penetrate all the way through the coating and into the underlying filler
and composite layers. However, due to their operation wavelength the
overall spatial resolution is typically limited to the order of hundred
or few hundreds microns [4,5]. In addition, HFUS requires physical
contact and a coupling medium, such as ultrasonic gel, which is
impractical when scanning curved surfaces. Thermographic methods infer
the presence of subsurface defects from the surface thermal radiation,
and as such, it is difficult to detect small or vertically stacked
defects, and the results are highly dependent on the thermal properties
of the sample [6,7]. XCT on the other hand can offer sub-micron
imaging resolution and in principle unlimited penetration. However, the
technology is limited by long processing time and the need for a
rotating system to perform 3D scanning [8–10]. As such, the
technique is mostly used as a laboratory technique on small cut-out
samples. Furthermore, the use of ionizing radiation not only poses a
risk to human health, but also a risk of damaging the sample by breaking
chemical bonds and thus creating artificial defects. Another promising
technology for non-destructive coating inspection is optical coherence
tomography (OCT).
OCT is an interferometric imaging technique based on backscattered laser
light from internal microstructures and material interfaces. It was
developed in 1991 for biomedical imaging and is widely used today as a
diagnostic tool within ophthalmology and dermatology [11–13]. In
recent years, the technology has also found applications within
non-destructive testing (NDT) due to the possibility of high resolution,
non-contact 3D imaging. However, the penetration depth in many materials
are severely limited by absorption and scattering, which depend on the
type of material and the wavelength of the laser. Consequently, there
are only a few examples in the literature where OCT has been applied for
the inspection of coatings, primarily for art and cultural heritage
preservation, as well as automotive and pharmaceutical coatings. Within
automotive coatings, OCT systems operating around the 0.83 to 0.93 µm
central wavelength range has been used to map the thickness of
individual coating layers with an axial (depth) resolution of 4–6 µm.
However, due to the short center wavelength only the top clear coat
layer was transparent, limiting the maximum penetration depth to about
100 µm [14–17]. Zhang et al. (2016) characterized automotive paints
with metal flakes using OCT at 0.832 µm and were in some cases able to
distinguish the clear coat, base coat, and primer layers, each around
20–60 µm in thickness with a depth resolution of 5 µm. In their system,
a 2 × 2 mm scan of 1536 × 600 × 2048 pixels was acquired in
~45 s and took ~60 s to process
[16]. Moving towards longer wavelengths in the mid-infrared, Cheung
et al. (2015) used a broadband supercontinuum (SC) laser to compare OCT
at 0.93 and 1.96 µm central wavelength for inspection of artistic oil
paintings. They found that despite the lower axial resolution of 13 µm,
the longer wavelength was able to penetrate the ~340 µm
layer of yellow ochre pigmented paint and provide more structural
information about the chalk base layer below [18]. SC lasers in
particular has had a major contribution to the development of OCT, since
they can provide a high spectral brightness over a broad bandwidth from
ultraviolet to mid-infrared, even exceeding that of synchrotron
radiation sources [19]. Using a SC laser, Zorin et al. presented
improved penetration in oil paints using 4 µm central wavelength,
although with a poor axial resolution of 50 µm and a slow line rate of
2.5 Hz [20]. Fast scanning and high-resolution in the mid-infrared
was first demonstrated by Israelsen et al., most recently achieving a 3
kHz line rate and 5.8 μm axial resolution at 4.1 µm central wavelength
[21,22]. The first study to investigate industrial coatings in the
mid-infrared was by Petersen et al. that demonstrated subsurface imaging
in marine coatings, including monitoring of wet film thickness during
curing of a 210 μm thickness blue-pigmented anti-fouling coating based
on cuprous oxide particles, and detection of substrate corrosion through
369 μm thickness white-pigmented high-gloss alkyd enamel [23]. In
those marine coatings, the surface roughness and large functional
particles presented the main limitations in terms of penetration depth.
So far, there has been no work published with OCT in relation to wind
turbine and leading edge coatings. Liu et al. used OCT with a central
wavelength of 1.55 μm to monitor delamination growth in an uncoated
fiber-glass epoxy composite used for the spar webs in wind turbine
blades [24]. They were able to image the delamination through 2 mm
of the composite material with an axial resolution of 17 μm and a scan
speed of 4 mm/s. In this work, OCT is used to non-destructively inspect
coated glass-fiber composite samples to investigate the penetration
depth and identify subsurface coating defects. The technique is compared
with traditional XCT and optical microscopy to quantify the imaging
depth and illustrate the difference in image contrast.
2 | MATERIALS AND METHODS
2.1 | Coated samples
Four coated glass-fiber composite samples were considered for testing.
Three of the samples (A, B, C) were rectangular with the dimensions of
40mm x 15mm and varying thickness from 4-11 mm. The fourth sample (D)
was curved, as it was cut from a model blade used for RET. The coatings
on all samples were made from polyurethane (PU) and applied in varying
thickness. For samples A and B, the PU coating was poured onto a
horizontal composite panel to obtain a thick layer, while for C and D
the coating was applied by airbrush to obtain a smooth and thin layer.
Images of the samples are shown in Figure 1, and the sample
characteristics are summarized in Table 1.