scholarly journals Fault Prognostics for the Predictive Maintenance of Wind Turbines: State of the Art

2019 ◽  
pp. 113-125
Author(s):  
Koceila Abid ◽  
Moamar Sayed Mouchaweh ◽  
Laurence Cornez
Keyword(s):  
Wind Turbines ◽  
State Of The Art ◽  
Predictive Maintenance ◽  
Fault Prognostics

Failure Monitoring and Predictive Maintenance of Hydraulic Cylinder - State-of-the-Art Review

2021 ◽  
pp. 1-1 ◽  
Author(s):  
Vignesh Vishnudas Shanbhag ◽  
Thomas J. J. Meyer ◽  
Leo W. Caspers ◽  
Rune Schlanbusch
Keyword(s):  
State Of The Art ◽  
Hydraulic Cylinder ◽  
Predictive Maintenance ◽  
Failure Monitoring

The State of the Art of Hidden Markov Models for Predictive Maintenance of Diesel Engines

2017 ◽  
Vol 33 (8) ◽  
pp. 2765-2779 ◽  
Author(s):  
António Simões ◽  
José Manuel Viegas ◽  
José Torres Farinha ◽  
Inácio Fonseca
Keyword(s):  
Hidden Markov Models ◽  
Diesel Engines ◽  
Markov Models ◽  
State Of The Art ◽  
Hidden Markov ◽  
The State ◽  
Predictive Maintenance

Comparison of Wind Turbine Performance Prediction and Measurement

1982 ◽  
Vol 104 (2) ◽  
pp. 84-88 ◽  
Author(s):  
J. L. Tangler
Keyword(s):  
Test Data ◽  
Wind Turbines ◽  
Performance Prediction ◽  
State Of The Art ◽  
Correlation Study ◽  
Performance Models ◽  
Rocky Flats ◽  
Turbine Performance ◽  
Horizontal Axis Wind Turbines ◽  
Development Center

The purpose of this work was to evaluate the state-of-the-art of performance prediction for small horizontal-axis wind turbines. This effort was undertaken since few of the existing performance methods used to predict rotor power output have been validated with reliable test data. The program involved evaluating several existing performance models from four contractors by comparing their predictions for two wind turbines with actual test data. Test data were acquired by Rocky Flats Test and Development Center and furnished to the contractors after submission of their prediction reports. The results of the correlation study will help identify areas in which existing rotor performance models are inadequate and, where possible, the reasons for the models shortcomings. In addition, several problems associated with obtaining accurate test data will be discussed.

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