Resolving the effects of peak-splitting alike artefacts in FBG measurements for fatigue assessments of an offshore wind turbine foundation

Abstract

Abstract Fiber Bragg grating (FBG) based optical strain sensors have become more commonplace for fatigue monitoring applications of large structures. Despite many advantages above conventional strain gauges, in some cases FBG measurements can become corrupted by complicated failure modes, which might relate to fiber integrity or interpretation of optical signals. In this article, over one month of corrupted FBG strain data obtained from a monopile of an operational wind turbine will be assessed, with the objective to resolve the issues around the severe jump-like distortions which are present in the data. To this end, an initial working hypothesis is formulated which states that removing the jump-like distortions will improve the quality of the data and increase usability. Throughout the article this hypothesis will be tested and adjusted, as the amount of information used in the assessment will be step-wise increased. The results show that the initial goal of removing jump-like artefacts is achievable, resulting in a visually much-improved signal; however, the results obtained using the fatigue-related metrics show inconsistencies when compared with predicted fatigue quantities; these predictions are obtained using two virtual sensing methods, which extrapolate strain reference data, in terms of damage equivalent moments and time series, to the locations of the corrupted FBG sensors. Results indicate that the observed failure mode is more complex than initially expected. Finally the hypothesized failure mode is revisited, and recommendations about the usability of the data are discussed.