Generator Damage Recognition Based on Artificial Neural Network
This article simulates the wind generator set which has
two fault bearing collar rail destruction and the gear box oil leak fault.
The electric current signal which produced by the generator, We use
Empirical Mode Decomposition (EMD) as well as Fast Fourier
Transform (FFT) obtains the frequency range-s signal figure and
characteristic value. The last step is use a kind of Artificial Neural
Network (ANN) classifies which determination fault signal's type and
reason. The ANN purpose of the automatic identification wind
generator set fault..
[1] Satish Rajagopalan, Thomas G. Habetler, Ronald G. Harley, Tomy
Sebastian, and Bruno Lequesne, " Current/Voltage-Based Detection of
Faults in Gears Coupled to Electric Motors," IEEE Transactions on
industry applications, Vol. 42, No. 6, November/December 2006.
[2] Antonio Garcia Espinosa, Javier A. Rosero, Jordi Cusido, Luis Rormeral,
and Juan Antonio Ortega, "Fault Detection by Means of Hilbert-Huang
Transform of the Stator Current in a PMSM With Demagnetization,"
IEEE Transactions on energy conversion, Vol. 25, No. 2, June 2010.
[3] J. W. Cooley and J. W. Tukey, "An algorithm for the machine calculation
of complex Fourier series, "Math. Comput., vol. 19, pp. 297-301, April
1965.
[4] Y.C.Lee," Analysis and Diagnosis of Wind Power System Mechanical
Abnormality", February 2012
[5] L. Wei, H. Wang, and F. Li, "Fault diagnosis of turbine generator
vibration based on wavelet packet and data-driven," in Proceedings of the
ISECS International Colloquium on Computing, Communication,
Control, and Management, 2009, vol. 2, pp. 29-32.
[6] B. Liu, S. Riemenschneider, and Y. Xu, "Gearbox fault diagnosis using
empirical mode decomposition and Hilbert spectrum," Mechanical
System and Signal Processing, vol. 20, pp. 718-734, 2006.
[7] P. D. McFadden, "Low frequency vibration generated by gear tooth
impacts," NDT International Elsevier, vol. 18, no. 5, pp. 279-282, 1985.
[8] J. R. Cameron, W. T. Thomson, and S. Roach, "Vibration and current
monitoring for detecting airgap eccentricity in large induction motors," in
Proceedings of the IEE Electric Engineering Applications, vol. 133, no. 3,
pp. 155-163, May. 1986.
[1] Satish Rajagopalan, Thomas G. Habetler, Ronald G. Harley, Tomy
Sebastian, and Bruno Lequesne, " Current/Voltage-Based Detection of
Faults in Gears Coupled to Electric Motors," IEEE Transactions on
industry applications, Vol. 42, No. 6, November/December 2006.
[2] Antonio Garcia Espinosa, Javier A. Rosero, Jordi Cusido, Luis Rormeral,
and Juan Antonio Ortega, "Fault Detection by Means of Hilbert-Huang
Transform of the Stator Current in a PMSM With Demagnetization,"
IEEE Transactions on energy conversion, Vol. 25, No. 2, June 2010.
[3] J. W. Cooley and J. W. Tukey, "An algorithm for the machine calculation
of complex Fourier series, "Math. Comput., vol. 19, pp. 297-301, April
1965.
[4] Y.C.Lee," Analysis and Diagnosis of Wind Power System Mechanical
Abnormality", February 2012
[5] L. Wei, H. Wang, and F. Li, "Fault diagnosis of turbine generator
vibration based on wavelet packet and data-driven," in Proceedings of the
ISECS International Colloquium on Computing, Communication,
Control, and Management, 2009, vol. 2, pp. 29-32.
[6] B. Liu, S. Riemenschneider, and Y. Xu, "Gearbox fault diagnosis using
empirical mode decomposition and Hilbert spectrum," Mechanical
System and Signal Processing, vol. 20, pp. 718-734, 2006.
[7] P. D. McFadden, "Low frequency vibration generated by gear tooth
impacts," NDT International Elsevier, vol. 18, no. 5, pp. 279-282, 1985.
[8] J. R. Cameron, W. T. Thomson, and S. Roach, "Vibration and current
monitoring for detecting airgap eccentricity in large induction motors," in
Proceedings of the IEE Electric Engineering Applications, vol. 133, no. 3,
pp. 155-163, May. 1986.
@article{"International Journal of Electrical, Electronic and Communication Sciences:61780", author = "Chang-Hung Hsu and Chun-Yao Lee and Guan-Lin Liao and Yung-Tsan Jou and Jin-Maun Ho and Yu-Hua Hsieh and Yi-Xing Shen", title = "Generator Damage Recognition Based on Artificial Neural Network", abstract = "This article simulates the wind generator set which has
two fault bearing collar rail destruction and the gear box oil leak fault.
The electric current signal which produced by the generator, We use
Empirical Mode Decomposition (EMD) as well as Fast Fourier
Transform (FFT) obtains the frequency range-s signal figure and
characteristic value. The last step is use a kind of Artificial Neural
Network (ANN) classifies which determination fault signal's type and
reason. The ANN purpose of the automatic identification wind
generator set fault..", keywords = "Wind-driven generator, Fast Fourier Transform,
Neural network", volume = "6", number = "5", pages = "521-4", }