Analysis of Vibration Signal of DC Motor Based on Hilbert-Huang Transform
This paper presents a signal analysis process for
improving energy completeness based on the Hilbert-Huang
Transform (HHT). Firstly, the vibration signal of a DC Motor obtained
by employing an accelerometer is the model used to analyze the
signal. Secondly, the intrinsic mode functions (IMFs) and Hilbert
spectrum of the decomposed signal are obtained by applying HHT.
The results of the IMFs constituent and the original signal are
compared and the process of energy loss is discussed. Finally, the
differences between Wavelet Transform (WT) and HHT in analyzing
the signal are compared. The simulated results reveal the analysis
process based on HHT is advantageous for the enhancement of energy
completeness.
[1] G. S. Maruthi. and K. P. Vittal "Electrical fault detection in three phase
squirrel cage induction motor by vibration analysis using MEMS
accelerometer," in Proc. 2006 IEEE Power Electronics and Drives
Systems conf., pp. 838-843.
[2] H. Ocak, and K. A. Loparo "Estimation of the running speed and bearing
defect frequencies of an induction motor from vibration data," in Proc.
2004 Mechanical Systems and Signal, pp. 515-533.
[3] H. Zhang, K. Bradley, and P. Zanchetta "A None-intrusive Load and
Efficiency Evaluation Method for In-Service Motors Using Vibration
Tests with an Accelerometer," in Proc. 2008 IEEE Industry Applications
Society Annual Meeting conf., pp 1-6.
[4] M. Kawada, and K. Yamada "Visualization of Vibration Phenomena on
Model Turbine Rotor Using Cross-Correlation Method Based on In-Place
Fast Haar Wavelet Transform," in Proc. 2008 IEEE Power and Energy
Society General Meeting conf., pp 1-6.
[5] R. Yan, and R. X. Gao, Senior Member, " Hilbert-Huang
Transform-Based Vibration Signal Analysis for Machine Health
Monitoring," IEEE Trans. Instrumentation and measurement, vol. 55, pp.
2320-2329, Dec. 2006.
[6] A. Roy, C.-H. Wen, J. F. Doherty, and J. D. Mathews, " Signal Feature
Extraction From Microbarograph Observations Using the Hilbert-Huang
Transform," IEEE Trans. Geoscience and Remote Sensing, vol. 46, no. 5,
May 2008.
[7] N. E. Huang and S. R. Long, "The ages of large amplitude coastal
seicheson the Caribbean coast of Puerto Rico," Journal Phys. Ocean., vol.
30, pp.2001-2012, Aug. 2000.
[8] N. E. Huang, Z. Shen, and S. R. Long, "A new review of nonlinearwater
waves: The Hilbert spectrum," Annu. Rev. Fluid Mech., vol. 31, pp.
417-457, Jan. 1999.
[1] G. S. Maruthi. and K. P. Vittal "Electrical fault detection in three phase
squirrel cage induction motor by vibration analysis using MEMS
accelerometer," in Proc. 2006 IEEE Power Electronics and Drives
Systems conf., pp. 838-843.
[2] H. Ocak, and K. A. Loparo "Estimation of the running speed and bearing
defect frequencies of an induction motor from vibration data," in Proc.
2004 Mechanical Systems and Signal, pp. 515-533.
[3] H. Zhang, K. Bradley, and P. Zanchetta "A None-intrusive Load and
Efficiency Evaluation Method for In-Service Motors Using Vibration
Tests with an Accelerometer," in Proc. 2008 IEEE Industry Applications
Society Annual Meeting conf., pp 1-6.
[4] M. Kawada, and K. Yamada "Visualization of Vibration Phenomena on
Model Turbine Rotor Using Cross-Correlation Method Based on In-Place
Fast Haar Wavelet Transform," in Proc. 2008 IEEE Power and Energy
Society General Meeting conf., pp 1-6.
[5] R. Yan, and R. X. Gao, Senior Member, " Hilbert-Huang
Transform-Based Vibration Signal Analysis for Machine Health
Monitoring," IEEE Trans. Instrumentation and measurement, vol. 55, pp.
2320-2329, Dec. 2006.
[6] A. Roy, C.-H. Wen, J. F. Doherty, and J. D. Mathews, " Signal Feature
Extraction From Microbarograph Observations Using the Hilbert-Huang
Transform," IEEE Trans. Geoscience and Remote Sensing, vol. 46, no. 5,
May 2008.
[7] N. E. Huang and S. R. Long, "The ages of large amplitude coastal
seicheson the Caribbean coast of Puerto Rico," Journal Phys. Ocean., vol.
30, pp.2001-2012, Aug. 2000.
[8] N. E. Huang, Z. Shen, and S. R. Long, "A new review of nonlinearwater
waves: The Hilbert spectrum," Annu. Rev. Fluid Mech., vol. 31, pp.
417-457, Jan. 1999.
@article{"International Journal of Electrical, Electronic and Communication Sciences:55040", author = "Chun-Yao Lee and Hung-Chi Lin", title = "Analysis of Vibration Signal of DC Motor Based on Hilbert-Huang Transform", abstract = "This paper presents a signal analysis process for
improving energy completeness based on the Hilbert-Huang
Transform (HHT). Firstly, the vibration signal of a DC Motor obtained
by employing an accelerometer is the model used to analyze the
signal. Secondly, the intrinsic mode functions (IMFs) and Hilbert
spectrum of the decomposed signal are obtained by applying HHT.
The results of the IMFs constituent and the original signal are
compared and the process of energy loss is discussed. Finally, the
differences between Wavelet Transform (WT) and HHT in analyzing
the signal are compared. The simulated results reveal the analysis
process based on HHT is advantageous for the enhancement of energy
completeness.", keywords = "Hilbert-Huang transform, Hilbert spectrum, Wavelettransform, Wavelet spectrum, DC Motor.", volume = "4", number = "12", pages = "1759-3", }