Demonstrates a diagnostic system that improves fault detection in offshore wind turbine gearboxes, highlighting its practical implications.
The rapid expansion of offshore wind energy underscores the critical need for reliable gearbox monitoring, especially for failure-prone planetary gearboxes in harsh marine environments. To address this, we propose two novel, physics-informed diagnostic parameters: the Filtered Root Mean Square (FRMS) and the Normalized Summation of the positive amplitudes of the Difference Spectrum (NSDS). These parameters enhance fault detection by isolating fault-related vibrations from healthy gearbox modulation. Furthermore, an integrated, real-time diagnosis system implementing these parameters is developed using LabVIEW. Experimental validation on a dedicated test bench demonstrates the system's effectiveness, achieving a diagnostic accuracy of 95.4 % and outperforming traditional methods. This work provides a practical and efficient solution for condition monitoring of offshore wind turbine gearboxes.
No takes yet. Share an insight, caveat, or question.
Shaohua et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: