With global warming and the depletion of fossil energy sources, renewable energy is
gradually replacing non-renewable energy as the main energy in the future. As one of the …

Blades are critical components in wind turbines (WTs) for power generation, and condition
monitoring (CM) of WT blades is a crucial and challenging issue under operating conditions …

Monitoring of modal frequencies under an unsupervised learning framework is a practical
strategy for damage assessment of civil structures, especially bridges. However, the key …

Cross-domain machinery fault diagnosis aims to transfer enriched diagnosis knowledge
from a labeled source domain to a new unlabeled target domain. Most existing methods …

Planetary gearbox fault detection is important in terms of life-threatening failure prevention
and maintenance optimization. This article focuses on the representation of the planetary …

To improve the efficiency and reliability of wind power generation, condition monitoring of
wind turbines has drawn extensive attention worldwide. However, blade health monitoring is …

The estimation of the posterior probability distribution of unknown parameters remains a
challenging issue for model updating with uncertainties. Most current studies are based on …

This study presents a novel artificial neural network (ANN) based methodology within a
vibration-based structural health monitoring framework for robust damage detection. The …

Offshore wind turbines are exposed during their serviceable lifetime to a wide range of loads
from aero-, hydro-and structural dynamics. This complex loading scenario will have an …

This paper proposes a Bayesian framework based on particle filters for online fatigue
damage diagnosis and prognosis for wind turbine blades (WTBs). The framework integrates …