Work

A Survey on Wind Turbine Condition Monitoring and Fault Diagnosis—Part I: Components and Subsystems

Year: 2015

Type: article

Source: IEEE Transactions on Industrial Electronics

DOI: 10.1109/tie.2015.2422112

Authors: Wei Qiao, Dingguo Lu

Institution: University of Nebraska–Lincoln

Language: English

Topic: Machine Fault Diagnosis Techniques

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: closed

Funders: National Science Foundation, U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy

Awards: AN ONLINE INTELLIGENT PROGNOSTIC HEALTH MONITORING SYSTEM FOR WIND TURBINES, Cognitive Prediction-Enabled Online Intelligent Fault Diagnosis and Prognosis for Wind Energy Systems

OpenAlex ID: W1605077306

FWCI: 27.65

Cites: 74

Cited by: 552

Related to: 10