Wind Turbine Gearbox Failure Identification With Deep Neural Networks

By Long Wang, Zijun Zhang, Huan Long, Jia Xu, Ruihua Liu. IEEE Transactions on Industrial Informatics, 2017

295 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/655315372c163f2343c228b901b396faa677b3f1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. David Flynn
2. Dong Yang
3. Weiting Zhang
4. Valentin Robu
5. Hongchao Wang

In Mechanical Engineering

1. David Flynn
2. Dong Yang
3. Weiting Zhang
4. Valentin Robu
5. Hongchao Wang

Citations in the corpus

• Data-Driven Methods for Predictive Maintenance of Industrial Equipment: A Survey (2019, methodology): “According to [99], a DNN was employed to develop the prediction model for monitoring the wind turbine gearbox health”
• Machine learning methods for wind turbine condition monitoring: A review (2019, methodology): “[112] 2017 SCADA Lubricant pressure monitoring Regression/Normal”