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Wind Turbine Gearbox Condition Monitoring Vibration Analysis Benchmarking Datasets

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Wind turbine condition monitoring (CM) can potentially help the wind industry reduce turbine downtime and operation and maintenance (O&M) cost. NREL CM research has investigated various condition-monitoring techniques such as acoustic emission (AE specifically stress wave), vibration, electrical signature, lubricant and debris monitoring based on the Gearbox Reliability Collaborative dynamometer and field tests, and other test turbines and resources accessible by NREL. During the past several years, NREL CM research has shown that there are very few validation and verification efforts on commercial wind turbine CM systems. One of the reasons might be limited benchmarking datasets accessible by stakeholders. To fill this gap, NREL executed a data collection effort. The targeted users of these datasets include those investigating vibration-based wind turbine CM research, evaluating commercially available vibration-based CM systems, or testing prototyped vibration-based CM systems.

NREL collected data from a healthy and a damaged gearbox of the same design tested by the GRC. Vibration data were collected by accelerometers along with high-speed shaft RPM signals during the dynamometer testing. The healthy gearbox was only tested in the dynamometer. The damaged gearbox was first tested in the dynamometer and later sent to a wind farm close to NREL for field testing. In the field test, it experienced two loss-of-oil events that damaged its internal bearings and gear elements. The gearbox was brought back to NREL and it was retested in the dynamometer with CM systems deployed under controlled loading conditions that would not cause catastrophic failure of the gearbox.

The objective of releasing these datasets to the public along with information about the real damage that occurred to the damaged gearbox is to provide the wind industry with some benchmarking datasets. These datasets will benefit research, development, validation, verification, and advancement of vibration-based wind condition-monitoring techniques.

By accessing this data you acknowledge the terms outlined in the "License Information" document.

Please contract Shawn Sheng (NREL) if you have any questions on the data or would like to collaborate on publications based on the datasets.

Citation Formats

National Renewable Energy Laboratory. (2014). Wind Turbine Gearbox Condition Monitoring Vibration Analysis Benchmarking Datasets [data set]. Retrieved from https://dx.doi.org/10.25984/1844194.
Export Citation to RIS
Sheng, Shawn. Wind Turbine Gearbox Condition Monitoring Vibration Analysis Benchmarking Datasets. United States: N.p., 28 Mar, 2014. Web. doi: 10.25984/1844194.
Sheng, Shawn. Wind Turbine Gearbox Condition Monitoring Vibration Analysis Benchmarking Datasets. United States. https://dx.doi.org/10.25984/1844194
Sheng, Shawn. 2014. "Wind Turbine Gearbox Condition Monitoring Vibration Analysis Benchmarking Datasets". United States. https://dx.doi.org/10.25984/1844194. https://data.openei.org/submissions/738.
@div{oedi_738, title = {Wind Turbine Gearbox Condition Monitoring Vibration Analysis Benchmarking Datasets}, author = {Sheng, Shawn.}, abstractNote = {Wind turbine condition monitoring (CM) can potentially help the wind industry reduce turbine downtime and operation and maintenance (O&M) cost. NREL CM research has investigated various condition-monitoring techniques such as acoustic emission (AE specifically stress wave), vibration, electrical signature, lubricant and debris monitoring based on the Gearbox Reliability Collaborative dynamometer and field tests, and other test turbines and resources accessible by NREL. During the past several years, NREL CM research has shown that there are very few validation and verification efforts on commercial wind turbine CM systems. One of the reasons might be limited benchmarking datasets accessible by stakeholders. To fill this gap, NREL executed a data collection effort. The targeted users of these datasets include those investigating vibration-based wind turbine CM research, evaluating commercially available vibration-based CM systems, or testing prototyped vibration-based CM systems.

NREL collected data from a healthy and a damaged gearbox of the same design tested by the GRC. Vibration data were collected by accelerometers along with high-speed shaft RPM signals during the dynamometer testing. The healthy gearbox was only tested in the dynamometer. The damaged gearbox was first tested in the dynamometer and later sent to a wind farm close to NREL for field testing. In the field test, it experienced two loss-of-oil events that damaged its internal bearings and gear elements. The gearbox was brought back to NREL and it was retested in the dynamometer with CM systems deployed under controlled loading conditions that would not cause catastrophic failure of the gearbox.

The objective of releasing these datasets to the public along with information about the real damage that occurred to the damaged gearbox is to provide the wind industry with some benchmarking datasets. These datasets will benefit research, development, validation, verification, and advancement of vibration-based wind condition-monitoring techniques.

By accessing this data you acknowledge the terms outlined in the "License Information" document.

Please contract Shawn Sheng (NREL) if you have any questions on the data or would like to collaborate on publications based on the datasets.}, doi = {10.25984/1844194}, url = {https://data.openei.org/submissions/738}, journal = {}, number = , volume = , place = {United States}, year = {2014}, month = {03}}

Please contract Shawn Sheng (NREL) if you have any questions on the data or would like to collaborate on publications based on the datasets.}, doi = {10.25984/1844194}, url = {https://data.openei.org/submissions/738}, journal = {}, number = , volume = , place = {United States}, year = {2014}, month = {03}}" readonly />
https://dx.doi.org/10.25984/1844194

Details

Data from Mar 28, 2014

Last updated Jun 14, 2024

Submitted Jul 31, 2014

Organization

National Renewable Energy Laboratory

Contact

Shawn Sheng

Authors

Shawn Sheng

National Renewable Energy Laboratory

Research Areas

DOE Project Details

Project Name Wind Turbine Drivetrain Reliability

Project Number FY14 AOP 1.5.2.401

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