A De-Noising Method for Track State Detection Signal Based on EMD
- 1 College of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai, China
- 2 College of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai, China
- 3 College of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai, China
- 4 College of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai, China
Abstract
In the track irregularity detection, the acceleration signals of the inertial measurement unit (IMU) output which with low frequency components and noise, this paper studied a de-noising algorithm. Based on the criterion of consecutive mean square error, a de-noising method for IMU acceleration signals based on empirical mode decomposition (EMD) was proposed. This method can divide the intrinsic mode functions (IMFs) derived from EMD into signal dominant modes and noise dominant modes, then the modes reflecting the important structures of a signal were combined together to form partially reconstructed de-noised signal. Simulations were conducted for simulated signals and a real IMU acceleration signals using this method. Experimental results indicate that this method can efficiently and adaptively remove noise, and this method can better meet the precision requirement.
- Zheng, S.B., Lin, J.H. and Lin, G.B. (2007) Maglev Track Long-Wave Irregularity Detection Based on Inertia Method and Its Implementation. Journal of Electronic Measurement and Instrument, 21, 61-65.
- Zheng, S.B., Lin, J.H. and Lin, G.B. (2007) High-Speed Maglev Track Long-Wave Irregularity Detection System Design. Chinese Journal of Scientific Instrument, 28, 1781-1786.
- Du, H.T. (2000) Long Wavelength Track Irregularity Detection Method of Digital Filter. China Railway Science, 4, 58-64.
- Zhu, H.T., Cai, J. and Wang, Z.Y. (2007) Based on the Orbit of Fiber Optic Gyroscope Direction Irregularity Detection System. Microcomputer Information, 23, 268-269.
- Boudraa, A.O. and Cexus, E.-C. (2007) EMD-Based Signal Filtering. IEEE Transactions on Instrumentation and Measurement, 56, 2196-2202. http://dx.doi.org/10.1109/TIM.2007.907967
- Tan, S.W., Qin, S.R. and Tang, B.P. (2004) The Hilbert-Huang Transform Filtering Properties and Application. Journal of Chongqing University, 27, 9-14.
- Zhao, W.W. and Zeng, X.W. (2008) A New Method of EMD De-Noising. Electronic Science and Technology, 5, 30- 32, 36.
- Zhu, W.F., Chai, X.D. and Zheng, S.B. (2012) Based on the Integration Filter Displacement Information Acquisition. Instrument Technique and Sensor, 11, 87-90.
- Ren, C.H., Xiong, L.X. and Zhao, X.J. (2010) Wavelet Threshold Filtering in Signal Processing, the Application of Fiber Optic Gyroscope. Piezoelectrics & Acoustooptics, 32, 957-959.
- Wang, T. (2010) The EMD Algorithm and Its Application in Signal Denoising. Haerbin Engineering University, Haerbin.
- Liu, L.J., Shen, Y. and Wang, Y. (2012) Radar Signal Filter Design Base on HHT Method. Control Conference (CCC), 3611-3616.
- Antonino-Daviu, J., Roger-Folch, J., Pons-Llinares, J., Pineda-Sanchez, M., Perez, R.B. and Charlton-Perez, C. (2011) Application of the Empirical Mode Decomposition to Condition Monitoring of Damper Bars in Synchronous Motors. Industrial Electronics (ISIE), Gdansk, 27-30 June 2011, 2118-2123.
- Yang, G.L., Zhu, Y.Q. and Yu, H.Y. (2010) The Automatic Seismic Signal Denoising Algorithm Based on HHT. Journal of Geodesy and Geodynamics, 3, 39-42.
- Zhu, L.P., Liu, A.J. and Wang, H.X. (2011) Based on the Radar Clutter Suppression of HHT. Modern Defense Technology, 6, 185-190.