Offshore wind turbines are an important cornerstone of the renewable energy sector, enabling a capacity utilization of up to four thousand full load hours. However, like any other structure, they require regular maintenance and inspections. These inspections are often expensive, time-consuming, and risky, as they are still partly carried out on-site by divers.
The use of remotely operated underwater vehicles (ROVs) has been increasing for years, but is mostly limited to RGB-based video techniques or the use of sonar. As a result, comprehensive quantification of damage is limited.
The new MISO-Inspector (Multi Input Single Output) sensor carrier is intended to improve this process. This multivariate inspection and analysis system, in addition to existing sensor technologies, will test and offer the use of new types of sensor technology for underwater applications. Mounted on an ROV, the MISO-Inspector is capable of performing inspection tasks both above and underwater.
The included sensors comprise, among others, a snapshot hyperspectral camera. This camera enables non-contact detection, differentiation, and analysis of materials. Since it is challenging for engineers to distinguish rust or other damage from marine growth, contamination, etc., with underwater RGB images alone, the hyperspectral camera offers completely new possibilities for damage identification.
Steel Tube Spectroscopy
Different materials (steel pipe without corrosion, steel pipe with corrosion, aluminum coating, and paint coating) were used as test objects, which are characteristic of offshore structures. For the measurements, the Hyperspectral VNIR Camera FireflEYE 185 was encased in a modified waterproof housing, allowing for depths of up to 60 meters. For underwater illumination, different light sources, such as LED and halogen lamps, were tested. The underwater investigations were carried out in a test basin at a depth of 1 meter.
In the initial measurements, the focus was on investigating the discriminability of relevant materials, the influence of different light sources, and the practicality of reflectance calibration in an underwater environment. The measurements were performed using both halogen and LED illumination.
To determine the reflectance values underwater, a white target was included with the sensor. Differentiation between the materials was possible with both LED and halogen light sources.
Pan image (true color) of the steel pipes with corresponding spectral signatures, as taken in Cubert Cuvis software. The white circle on the bottom left is the white target that was used for reflectance calibration. The uncorrected spectral signatures of the test objects (steel without corrosion, steel with corrosion, aluminum and paint coating) and the background are based on LED illumination.
The spectral signatures represent all averaged pixels inside the particular colored rectangles drawn in the image on the left. The error bars show the standard deviation for each wavelength. The spectrum beyond 780 nm is not included in the comparison since there is strong absorption in the infrared spectral range in water, and the LED illumination used does not cover this spectral range.
After successful testing in the test basin, the spectral camera was integrated into the MISO-Inspector, which in turn was integrated into an ROV. To withstand the harsher conditions in seawater and deeper water, the hyperspectral camera was equipped with SubConn underwater cables and connected to the MISO-Inspector system carrier. The next test took place in the port of Rostock, Northern Germany. This involved submerging a pipe node equipped with the test objects to be examined in the harbor basin.
Final Examination
The final examination of the MISO-Inspector was carried out under real conditions at an offshore structure. The pictures show the wind farm, the test facility, and the deployment of the ROV with the MISO-Inspector. The tests demonstrated how organization-intensive and weather-dependent the inspection process can be. Nevertheless, the measurements with the MISO-Inspector and the hyperspectral camera were successfully carried out, enabling the analysis of the measurements in the next step.
The underwater images show the offshore structure at a depth of 30 meters with different materials, such as paint coating, organic materials, and not clearly identifiable bright areas—either aluminum or of organic origin. Identifying these aluminum areas is crucial as they may indicate possible damage to the offshore structure, which cannot be determined using only RGB or black-and-white images. Hyperspectral imaging allows the identification of these materials. By analyzing the spectral information, the objects were confirmed to be aluminum. This evaluation, combined with further information about the offshore structure, enables an improved assessment of its current condition and provides a more reliable foundation for decisions on further action.
What’s Next?
Since the MISO-Inspector also passed the seawater testing successfully, the system is now undergoing further evaluation at its final destination, i.e., offshore wind parks in both the North Sea and the Baltic Sea. The project demonstrated how hyperspectral snapshot imaging can contribute to new applications, such as damage detection of metal structures underwater. We are excited to see more underwater applications in the future, as this is an exciting new frontier for spectral imaging!
Project Information
The project was funded by the BMWK (Federal Ministry for Economic Affairs and Climate Action) under FKZ: 03SX449A. The following partners joined the project:
About the Author
Dr. Viktoriya Tsyganskaya is the Head of Project Management at Cubert GmbH and has been leading research and customer projects since 2018. She earned her PhD in Remote Sensing from Ludwig Maximilian University of Munich, specializing in radar remote sensing and environmental monitoring. Viktoriya has extensive experience from her scientific work, including the project “Dikes under Pressure,” and expertise in sustainable environmental solutions. Her deep knowledge in remote sensing makes her a key contact for innovative hyperspectral technologies at Cubert.
