Monitoring vibrations in rotating machinery allows effective diagnostics, as abnormal
functioning states are related to specific patterns that can be extracted from vibration signals …

Wind turbines play an increasingly important role in renewable power generation. To ensure
the efficient production and financial viability of wind power, it is crucial to maintain wind …

Maintaining electrical machines in good working order and increasing their life expectancy
is one of the main challenges. Precocious and accurate detection of faults is crucial to this …

Investigation of deep transfer learning on machinery fault diagnosis is helpful to overcome
the limitations of a large volume of training data, and accelerate the practical applications of …

This paper presents a digital twin (DT) condition monitoring approach for drivetrains on
floating offshore wind turbines. Digital twin in this context consists of torsional dynamic …

Deep learning has gained a great achievement in the intelligent fault diagnosis of rotating
machineries. However, the labeled data is scarce in actual engineering and the marginal …

The fault characteristics of the rolling bearings of wind turbine gearboxes are unstable under
actual operating conditions. Problems such as inadequate fault sample data, imbalanced …

The recent advances in artificial intelligence have already begun to penetrate our daily lives.
Even though the development is still in its infancy, it has been shown that it can outperform …

In a wind turbine, the rolling bearing is the critical component. However, it has a high failure
rate. Therefore, the failure analysis and fault diagnosis of wind power rolling bearings are …

This work reviews the failure modes, mechanisms and causes of bearings in mechanical
equipment. Bearings are among the most important basic mechanical components. Their …