Split-Point and Attribute-Reduced Classifier Approach for Fault Diagnosis of Wind Turbine Blade through Vibration Signals

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/923/1/012009 ◽

2020 ◽

Vol 923 ◽

pp. 012009

Author(s):

A Joshuva ◽

M Arjun ◽

B Sujith Adhithya ◽

B Akash ◽

S Abdul Wahaab

Keyword(s):

Fault Diagnosis ◽

Wind Turbine ◽

Turbine Blade ◽

Wind Turbine Blade ◽

Vibration Signals ◽

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Wind Turbine Blade Fault Diagnosis Using Vibration Signals through Decision Tree Algorithm

Indian Journal of Science and Technology ◽

10.17485/ijst/2016/v9i48/107936 ◽

2016 ◽

Vol 9 (48) ◽

Author(s):

A. Joshuva ◽

V. Sugumaran

Keyword(s):

Fault Diagnosis ◽

Decision Tree ◽

Wind Turbine ◽

Turbine Blade ◽

Wind Turbine Blade ◽

Decision Tree Algorithm ◽

Vibration Signals ◽

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Wind Turbine Blade Bearing Fault Diagnosis Under Fluctuating Speed Operations via Bayesian Augmented Lagrangian Analysis

IEEE Transactions on Industrial Informatics ◽

10.1109/tii.2020.3012408 ◽

2020 ◽

pp. 1-1

Author(s):

Zepeng Liu ◽

Xiaoquan Tang ◽

Xuefei Wang ◽

Jose Errea Mugica ◽

Long Zhang

Keyword(s):

Fault Diagnosis ◽

Wind Turbine ◽

Turbine Blade ◽

Augmented Lagrangian ◽

Wind Turbine Blade ◽

Lagrangian Analysis ◽

Bearing Fault ◽

Bearing Fault Diagnosis

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Noise study for wind turbine blade vibration signals based on fast ICA algorithm

2015 8th International Congress on Image and Signal Processing (CISP) ◽

10.1109/cisp.2015.7408113 ◽

2015 ◽

Author(s):

Qian Zhao ◽

Wei Li ◽

Yichuan Shao ◽

Xingjia Yao ◽

Haonan Tian ◽

...

Keyword(s):

Wind Turbine ◽

Turbine Blade ◽

Wind Turbine Blade ◽

Blade Vibration ◽

Vibration Signals ◽

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Selection of a meta classifier-data model for classifying wind turbine blade fault conditions using histogram features and vibration signals: a data-mining study

Progress in Industrial Ecology An International Journal ◽

10.1504/pie.2019.10022055 ◽

2019 ◽

Vol 13 (3) ◽

pp. 232 ◽

Author(s):

A. Joshuva ◽

V. Sugumaran

Keyword(s):

Data Mining ◽

Wind Turbine ◽

Turbine Blade ◽

Wind Turbine Blade ◽

Vibration Signals ◽

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Comparative Study on Tree Classifiers for Application to Condition Monitoring of Wind Turbine Blade through Histogram Features Using Vibration Signals: A Data-Mining Approach

Structural Durability & Health Monitoring ◽

10.32604/sdhm.2019.03014 ◽

2019 ◽

Vol 13 (4) ◽

pp. 399-416 ◽

Author(s):

A. Joshuva ◽

V. Sugumaran

Keyword(s):

Data Mining ◽

Comparative Study ◽

Wind Turbine ◽

Turbine Blade ◽

Condition Monitoring ◽

Wind Turbine Blade ◽

Vibration Signals ◽

Data Mining Approach

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A lazy learning approach for condition monitoring of wind turbine blade using vibration signals and histogram features

Measurement ◽

10.1016/j.measurement.2019.107295 ◽

2020 ◽

Vol 152 ◽

pp. 107295

Author(s):

A. Joshuva ◽

V. Sugumaran

Keyword(s):

Wind Turbine ◽

Turbine Blade ◽

Condition Monitoring ◽

Wind Turbine Blade ◽

Learning Approach ◽

Lazy Learning ◽

Vibration Signals

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A data driven approach for condition monitoring of wind turbine blade using vibration signals through best-first tree algorithm and functional trees algorithm: A comparative study

ISA Transactions ◽

10.1016/j.isatra.2017.02.002 ◽

2017 ◽

Vol 67 ◽

pp. 160-172 ◽

Author(s):

A Joshuva. ◽

V Sugumaran.

Keyword(s):

Comparative Study ◽

Wind Turbine ◽

Turbine Blade ◽

Condition Monitoring ◽

Wind Turbine Blade ◽

Data Driven ◽

Vibration Signals ◽

Tree Algorithm ◽

Data Driven Approach

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Fault diagnosis of wind turbine blade based on robust residual error design

2016 Chinese Control and Decision Conference (CCDC) ◽

10.1109/ccdc.2016.7531051 ◽

2016 ◽

Author(s):

Lei Wang ◽

Chuanbo Wen

Keyword(s):

Fault Diagnosis ◽

Wind Turbine ◽

Turbine Blade ◽

Wind Turbine Blade ◽

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ICOPE-15-C026 Research of Wind Turbine Blade Surface Fault Diagnosis Based on Computer Vision Method

The Proceedings of the International Conference on Power Engineering (ICOPE) ◽

10.1299/jsmeicope.2015.12._icope-15-_126 ◽

2015 ◽

Vol 2015.12 (0) ◽

pp. _ICOPE-15--_ICOPE-15-

Author(s):

Zhang Lei ◽

Yang Tao ◽

Shuhong Huang

Keyword(s):

Computer Vision ◽

Fault Diagnosis ◽

Wind Turbine ◽

Turbine Blade ◽

Wind Turbine Blade ◽

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Fault Diagnosis of Industrial Wind Turbine Blade Bearing Using Acoustic Emission Analysis

IEEE Transactions on Instrumentation and Measurement ◽

10.1109/tim.2020.2969062 ◽

2020 ◽

Vol 69 (9) ◽

pp. 6630-6639 ◽

Author(s):

Zepeng Liu ◽

Xuefei Wang ◽

Long Zhang

Keyword(s):

Acoustic Emission ◽

Fault Diagnosis ◽

Wind Turbine ◽

Turbine Blade ◽

Wind Turbine Blade ◽

Emission Analysis ◽

Acoustic Emission Analysis

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