Gino Iannace1*, Giuseppe Ciaburro1, and Amelia Trematerra1

 

1Department of Architecutre and Industrial Design Università degli Studi della Campania Luigi Vanvitelli, Borgo San Lorenzo 81031 Aversa (Ce) Italy

Download Citation: |
Download PDF


ABSTRACT

The wind has been a source of energy for the human being since ancient times, mainly because it is widely available in different areas of the world. Several companies are investing huge capital to build wind farms with the aim of obtaining the maximum possible economic return. Therefore, a precise definition of the dynamics of operation of the turbines is necessary in order to appropriately define a system that takes full advantage of the wind energy. In this study, the measurements of the noise emitted by different wind turbines were used to obtain information on the dynamics of operation. A selected range of average spectral levels was extracted in a 1/3 octave band. A model based on the neural network for detection has been developed and applied to identify the operating conditions of wind turbines. The prediction and identification model have returned a high precision that suggests the adoption of this tool for several other applications.


Keywords: Artificial neural network; feature selection; low-frequency sound; random forest; wind turbine noise.


Share this article with your colleagues

 


REFERENCES

  1. [1] P. Gipe, "Wind energy comes of age," vol. 4, New York, John Wiley & Sons, 1995.

  2. [2] P. Jain, "Wind energy engineering," New York, McGraw-Hill, 2011.

  3. [3] J. F. Manwell, J. G. McGowan, and A. L. Rogers, "Wind energy explained: theory, design and application," John Wiley & Sons, 2010. https://doi.org/10.1002/9781119994367

  4. [4] G. M. Joselin Herbert, S. Iniyan, E. Sreevalsan, and S. Rajapandian, "A review of wind energy technologies," Renewable and Sustainable Energy Reviews, vol. 11, no. 6, pp. 1117-1145, 2007. https://doi.org/10.1016/j.rser.2005.08.004

  5. [5] G. Boyle, "Renewable energy/ edited by Godfrey Boyle," Oxford University Press, New York, 2004.

  6. [6] S. Mathew, "Wind energy: fundamentals, resource analysis and economics," vol. 1, Berlin, Springer, 2006. https://doi.org/10.1007/3-540-30906-3

  7. [7] A. L. Rogers, J. F. Manwell, and M. S. Wright, "Wind turbine acoustic noise," Renewable Energy Research Laboratory, University of Massachusetts at Amherst, 2006

  8. [8] International Electrotechnical Commission, International Standard IEC 61400-11, "Wind Turbine Generator Systems-Part 11: Acoustic Noise Measurement Techniques," Geneva Switzerland, 2012.

  9. [9] C. C. Wang, C. L. Chen, and H. T. Yau, "Bifurcation and chaotic analysis of aeroelastic systems," Journal of Computational and Nonlinear Dynamics, Apr., 2014. https://doi.org/10.1115/1.4025124

  10. [10] G. Iannace, G. Ciaburro, and A. Trematerra, "Heating, Ventilation, and Air Conditioning (HVAC) Noise Detection in Open-Plan Offices Using Recursive Partitioning," Buildings, vol. 8, no. 12, 2018. https://doi.org/10.3390/buildings8120169

  11. [11] C. T. Hsieh, H. T. Yau, C. C. Wang, and Y. S. Hsieh, "Particle swarm optimization used with proportional-derivative control to analyze nonlinear behavior in the atomic force microscope," Advances in Mechanical Engineering, vol. 8, no. 9, 2016. https://doi.org/10.1177/1687814016667271

  12. [12] G. Iannace, G. Ciaburro, and A. Trematerra, "Fault Diagnosis for UAV Blades Using Artificial Neural Network," Robotics, vol. 8, no. 3, 2019. https://doi.org/10.3390/robotics8030059

  13. [13] C. T. Hsieh, H. T. Yau, and C. C. Wang, "Control circuit design and chaos analysis in an ultrasonic machining system," Engineering Computations, vol 34, no. 7, pp. 2189-2211, 2017. https://doi.org/10.1108/EC-02-2017-0044

  14. [14] V. Puyana Romero, L. Maffei, G. Brambilla, and G. Ciaburro, "Acoustic, visual and spatial indicators for the description of the soundscape of waterfront areas with and without road traffic flow," International journal of environmental research and public health, vol. 13, no. 9, 2016. https://doi.org/10.3390/ijerph13090934

  15. [15] C. J. Lin, W. L. Chu, C. C. Wang, C. K. Chen, and I. T. Chen, "Diagnosis of ball-bearing faults using support vector machine based on the artificial fish-swarm algorithm," Journal of Low Frequency Noise, Vibration and Active Control, 2019. https://doi.org/10.1177/1461348419861822

  16. [16] L. Maffei, M. Masullo, G. Ciaburro, R. A. Toma, and H. B. Firat, "Awaking the awareness of the movida noise on residents: measurements, experiments and modelling." In proceeding of INTER-NOISE and NOISE-CON Congress and Conference Proceedings, Madrid Spain, June 16-19, 2019, pp. 935-944.

  17. [17] H. T. Yau, C. C. Wang, J. Y. Chang, and X. Y. Su, "A study on the application of synchronized chaotic systems of different fractional orders for cutting tool wear diagnosis and identification," IEEE Access, vol. 7, pp. 15903-15911, 2019. https://doi.org/10.1109/ACCESS.2019.2894815

  18. [18] B. L. Jian, C. C. Wang, J. Y. Chang, X. Y. Su, and H. T. Yau, "Machine Tool Chatter Identification Based on Dynamic Errors of Different Self-Synchronized Chaotic Systems of Various Fractional Orders," IEEE Access, vol. 7, pp. 67278-67286, 2019. https://doi.org/10.1109/ACCESS.2019.2917094

  19. [19] B. L. Jian, C. C. Wang, C. T. Hsieh, Y. P. Kuo, M. C. Houng, and H. T. Yau, "Predicting spindle displacement caused by heat using the general regression neural network," The International Journal of Advanced Manufacturing Technology, vol. 104, pp. 4665-4674, 2019. https://doi.org/10.1007/s00170-019-04261-5

  20. [20] M. Sessarego, J. Feng, N. Ramos-García, and S. G. Horcas, "Design optimization of a curved wind turbine blade using neural networks and an aero-elastic vortex method under turbulent inflow," Renewable Energy, vol. 146, pp. 1524-1535, 2020. https://doi.org/10.1016/j.renene.2019.07.046

  21. [21] G. Ciulla, A. D'Amico, V. Di Dio, and V. L. Brano, "Modelling and analysis of real-world wind turbine power curves: Assessing deviations from nominal curve by neural networks," Renewable energy, vol. 140, pp. 477-492, 2019. https://doi.org/10.1016/j.renene.2019.03.075

  22. [22] B. Manobel, F. Sehnke, J. A. Lazzús, I. Salfate, M. Felder, and S. Montecinos, "Wind turbine power curve modeling based on Gaussian Processes and Artificial Neural Networks," Renewable Energy, vol. 125, pp. 1015-1020, 2018. https://doi.org/10.1016/j.renene.2018.02.081

  23. [23] A. P. Marugán, F. P. G. Márquez, J. M. P. Perez, and D. Ruiz-Hernández, "A survey of artificial neural network in wind energy systems," Applied energy, vol. 228, pp. 1822-1836, 2018. https://doi.org/10.1016/j.apenergy.2018.07.084

  24. [24] M. B. Kursa and W. R. Rudnicki, "Feature selection with the Boruta package," Journal of Statistical Software, vol. 36, no. 11, pp.1-13, 2010. https://doi.org/10.18637/jss.v036.i11

  25. [25] A. Liaw and M. Wiener, "Classification and regression by randomForest," R news, vol. 2/3, pp.18-22, 2002.

  26. [26] S. Fritsch, F. Guenther, and M. F. Guenther, "Package 'neuralnet'," The Comprehensive R Archive Network, 2016.

  27. [27] F. Günther and S. Fritsch, "Neuralnet: Training of neural networks," The R journal, vol. 2:1, pp. 30-38, 2010. https://doi.org/10.32614/RJ-2010-006

  28. [28] R. J. May, H. R. Maier, and G. C. Dandy, "Data splitting for artificial neural networks using SOM-based stratified sampling," Neural Networks, vol. 23, no. 2, pp. 283-294, 2010. https://doi.org/10.1016/j.neunet.2009.11.009

  29. [29] M. Kuhn, "Classification and regression training (CARET). R programming language package," Journal of Statistical Software, vol. 28, no. 5, 2015. https://doi.org/10.18637/jss.v028.i05


ARTICLE INFORMATION

Received: 2019-11-02

Accepted: 2019-11-02
Available Online: 2020-06-01


Cite this article:

Iannace, G., Ciaburro. G. and Trematerra. A. (2020) Neural Networks Model to Detect Wind Turbine Dynamics. Int. j. autom. smart technol. https://doi.org/10.5875/ausmt.v10i1.2225

  Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Other people also read...