1. Date of download: 10/5/2017
Copyright © ASME. All rights reserved.
From: Fault Monitoring of Wind Turbine Generator Brushes: A Data-Mining Approach
J. Sol. Energy Eng. 2012;134(2): doi: /
Figure Legend:
Cause and effect diagram of the “generator brush worn” fault

2. Date of download: 10/5/2017
Copyright © ASME. All rights reserved.
From: Fault Monitoring of Wind Turbine Generator Brushes: A Data-Mining Approach
J. Sol. Energy Eng. 2012;134(2): doi: /
Figure Legend:
Samples of worn out carbon brushes

3. Date of download: 10/5/2017
Copyright © ASME. All rights reserved.
From: Fault Monitoring of Wind Turbine Generator Brushes: A Data-Mining Approach
J. Sol. Energy Eng. 2012;134(2): doi: /
Figure Legend:
Distribution of generator brush worn out faults across 27 wind turbines

4. Date of download: 10/5/2017
Copyright © ASME. All rights reserved.
From: Fault Monitoring of Wind Turbine Generator Brushes: A Data-Mining Approach
J. Sol. Energy Eng. 2012;134(2): doi: /
Figure Legend:
Identifying Tomek links

5. Date of download: 10/5/2017
Copyright © ASME. All rights reserved.
From: Fault Monitoring of Wind Turbine Generator Brushes: A Data-Mining Approach
J. Sol. Energy Eng. 2012;134(2): doi: /
Figure Legend:
Iterative sampling of dataset t + 21 using Tomek links

6. Date of download: 10/5/2017
Copyright © ASME. All rights reserved.
From: Fault Monitoring of Wind Turbine Generator Brushes: A Data-Mining Approach
J. Sol. Energy Eng. 2012;134(2): doi: /
Figure Legend:
Process flow for random forest based data sampling approach

7. Date of download: 10/5/2017
Copyright © ASME. All rights reserved.
From: Fault Monitoring of Wind Turbine Generator Brushes: A Data-Mining Approach
J. Sol. Energy Eng. 2012;134(2): doi: /
Figure Legend:
Boosted tree plot of prediction error function for dataset t + 21

8. Date of download: 10/5/2017
Copyright © ASME. All rights reserved.
From: Fault Monitoring of Wind Turbine Generator Brushes: A Data-Mining Approach
J. Sol. Energy Eng. 2012;134(2): doi: /
Figure Legend:
The relative contribution of f_measure corresponding to different data sampling techniques