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Field measurement study reveals distinct height-dependent kinematic energy partitioning in a floating offshore wind turbine, highlighting stable baselines for structural health monitoring.
Floating offshore wind turbines (FOWTs) experience coupled aero–hydro–servo-elastic excitations that produce structurally distinct kinematic responses at different measurement heights. While field monitoring campaigns increasingly deploy multi-level inertial sensors, the quantitative spectral partitioning of response energy across measurement levels and its relationship to operational and environmental conditions remain poorly characterised for operational FOWTs. This study presents a systematic multi-level spectral decomposition of operational FOWT structural response using synchronised tower-base and nacelle strapdown inertial measurements acquired at 8 Hz over a six-day campaign (18–23 April 2023) at a semi-submersible FOWT in Chinese coastal waters. Six kinematic channels—three translational acceleration components and three translational velocity components—from each sensor are decomposed into four physically defined frequency bands: drift (0.005–0.05 Hz), wave (0.05–0.30 Hz), structural (0.30–0.50 Hz), and rotor (0.50–0.80 Hz). Three derived scalar metrics—band energy ratio (BER), Wave-to-Structural Dominance Ratio (WSDR), and Structural Amplification Factor (SAF)—are defined, with their complete computation specifications and parameter sensitivity analysis provided to ensure reproducibility. Across 36 ten-minute windows spanning diverse conditions (mean wind 4.2–12.1 m/s, Hs 0.8–3.1 m), results reveal a pronounced and consistent spectral separation: the tower base is strongly wave-dominated (BERwave = 75.9%, coefficient of variation CV = 15.0% across days), whereas the nacelle exhibits substantially elevated structural-band energy (BERstruct = 10.3%, 4.72-fold amplification relative to tower base, 95% CI [3.63, 5.81]) and rotor-band energy (11.8%, 3.77-fold amplification). The WSDR at the tower base (mean 200.9, 95% CI [101.4, 300.4]) exceeds that at the nacelle (mean 48.4, 95% CI [13.1, 83.7]) by a factor of 4.1×. One-way analysis of variance (ANOVA) reveals that nacelle structural-band BER is significantly modulated by SCADA operational regime (F=5.20, p=0.024, η2=0.16) and by significant wave height (p=0.031), while tower-base wave-band BER is primarily driven by Hs (p=0.018). Comparison with baseline features—root-mean-square acceleration, spectral peak frequency, and traditional broad-band energy ratio—demonstrates that the band-resolved BER provides finer discrimination between excitation mechanisms than aggregate metrics. Importantly, no structural damage events occurred during the monitoring period; therefore, the reported stability of these features is interpreted as a baseline characterisation under normal operational conditions, which could support future anomaly detection efforts but does not constitute validation of damage detection capability. A comprehensive limitations assessment is provided, covering single-turbine validation, frequency-band sensitivity, regime sample imbalance, and generalisability constraints.
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Ji et al. (2026) studied this question.
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