随着大规模风电场的建设, 风电机组的状态监测和故障诊断成为一个重要的研究课题.
早期的风电机组状态监测和故障诊断依靠人工巡检, 而随着风电机组装机容量的不断增长 …

Accurate life and reliability prognosis are critical goals pursued by structural digital twin
modeling. However, prognosis of in-service structures subject to uncertainties from both …

The proposed work introduces a novel, lightweight feature fusion network model based on
the attention mechanism to address the issues of high time consumption and poor …

The development of AI has enabled the fault detection of industrial components to be
achieved through the combination with deep learning. A detection method combined with …

This work is dedicated to develop a novel discrete probabilistic entropy-based health
indicator (HI) and long short-term memory (LSTM)-based method to forecast bearing health …

Wind turbine blades are easily affected by the working environment and often show damage
features such as cracks and surface shedding. An improved convolution neural network, ED …

Fatigue damage has become one of the key issues affecting the service safety of steel
bridges with the continuous increase of vehicle load and traffic volume. In this paper, fatigue …

Digital twin (DT) technology provides unlimited possibilities for remote intelligent operation
and maintenance of wind turbine blade (WTB) in operation. However, the urgent demand for …

The monitoring of wind turbine (WT) systems allows operators to maximize their
performance, consequently minimizing untimely shutdowns and related hazard situations …

Structural health monitoring (SHM) and the operational condition assessment of blades are
greatly important for the operation of wind turbines that are at a high risk of disease in …