Inge Coudron, Jia Wan and Agusmian Partogi Ompusunggu
Flanders Make, Corelab DecisionS, Gaston Geenslaan 8, B-3001, Leuven, Belgium
Corrosion is the main root cause for offshore wind turbine (WT) structures failure (Price & Figueira, 2017; Martinez-Luengo, et al., 2016), and it has the lowest probability of detection and the biggest severity in the event of failure. Improper corrosion protection follow-up and inadequate management can result in structural degradation, e.g., offshore wind turbine support structures. Cost of repairing the corrosion protection system can be much higher than the initial installation cost of the corrosion protection system by itself. Therefore, initial corrosion protection solutions are of crucial relevance for offshore renewable energy system components such as WT towers, WT transition piece, WT sub-structure (fixed or floating platforms). Although initial corrosion protection solutions would have been installed on all these parts, however, these solutions can still be harshly damaged by the corrosive environmental offshore conditions.
To avoid WT structures failure that leads to wind energy production downtime, a non-destructive corrosion monitoring system combined with diagnosis, prognosis and decision support tools is a necessity for aiding the operation and maintenance (O&M) of WT structures subject to corrosion degradation. The online corrosion monitoring data is processed by the diagnosis, prognosis or decision support tool to extract relevant information that interests the stakeholder, e.g. the WT operator, O&M manager, etc. Furthermore, this information can be visualized by overlaying it on the CAD model of each WT to create a Digital Twin (DT) of the WT. The DT concept for general structural health monitoring purposes has been proposed in (Grosse, July 2019) and in particular for corrosion monitoring of offshore structures (Adey, et al., 2020). In the era of Industrie 4.0, the DT concept has been introduced into many sectors and applications.
In this paper, we discuss the development of a 3D visualization tool that can facilitate in building a DT of an offshore WT. The tool is based on Pvbrowser which is an open-source SCADA application framework and has been used in real SCADA systems, e.g. in Romania spanning 10,000 square kilometres with 50 power switches (Engineering, Retrieved in March 2020). The proposed architecture and the developed human-machine interface (HMI) are shown in Figure 1. Note that the main rationale behind the selection of the open platform was its open-source codes philosophy and flexibility that will enable us to interface with measurement data stored in a given database and also to integrate with the corrosion diagnosis, prognosis and decision support tools that are currently under development.
Figure 1: (a) The proposed architecture of the 3D visualization tool (b) The human-machine interface (HMI) layout
An important feature that might distinguish the proposed 3D visualization software tool from the commercial solution (Adey, et al., 2020) is the ability to combine a CAD WT model with both corrosion measurement data, e.g. based on ultrasound (US) sensing principle, coming from fixed array US sensors and a mobile US sensor (e.g. embedded into a drone) or diagnostic and prognostic results. The corrosion state estimated by the diagnostic/prognostic tools will be visualized on top of the CAD WT model interactively. Furthermore, a 2D graph where various indicators, such as the absolute wall thickness, the wall thickness reduction or other corrosion indicators estimated at the locations of interest, can also be visualized over time.
This work was carried out in the framework of the WATEREYE project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 851207.
Adey, R., Peratta, C. & Baynham, J., 2020. Corrosion Data Management Using 3D Visualisation and a Digital Twin. NACE International.
Engineering, L. S., Retrieved in March 2020. The process visualization browser. https://pvbrowser.de/pvbrowser/index.php., s.l.: s.n.
Grosse, C. U., July 2019. Monitoring and Inspection Techniques Supporting a Digital Twin Concept in Civil Engineering. Kingston University, London, UK, Fifth International Conference on Sustainable Construction Materials and Technologies (SCMT5).
Martinez-Luengo, M., Kolios, A. & Wang, L., 2016. Structural health monitoring of offshore wind turbines: A review through the Statistical Pattern Recognition Paradigm. Renewable and Sustainable Energy Reviews, Volume 64, pp. 91 – 105.
Price, S. & Figueira, R., 2017. Corrosion Protection Systems and Fatigue Corrosion in OffshoreWind Structures: Current Status and Future Perspectives,. Coatings, 7(2).