Processing Method for End Effect of Local Mean Decomposition Based on Extreme Point and Distant


Article Preview

The end effect of the local Mean Decomposition (LMD) causes serious distortion of the LMD decomposition results. And the most important factor of influence end effect is the extreme point and its distance, so the paper extracted the several factors, and composed of different sequences, using support vector machine (SVM) method respectively on the sets of data to predict, makes the original data can be extended. The research on the simulation signal and vibration signal shows that the method can effectively restrain the end effect of the decomposition.



Edited by:

Prof. Jong Wan Hu




Q. C. Chi et al., "Processing Method for End Effect of Local Mean Decomposition Based on Extreme Point and Distant", Applied Mechanics and Materials, Vol. 851, pp. 574-581, 2016

Online since:

August 2016




[1] J. S. Smith, The local mean decomposition and its application to EEG perception data, J. Roy. Soc. Interf. 2(5) (2005) 443–454.

[2] K. Zhang, J. S. Cheng, Y. Yang, Processing method for end effect of LMD based on self-adaptive waveform matching extending, China Mech. Eng. 4 (2010) 457-462.

[3] Z. Meng, S. S. Li, Y. Ji, Restraining Method for end effect of LMD based on energy operator demodulation of symmetrical differencing, J. Mech. Eng. 50(13) (2014) 80-87.


[4] H. H. Shao, The theory and its application of SVM, Autom. Panorma, (S1) (2003) 94-99.

[5] B. L. Fan, C. H. Bai, J. P. Li, Forecasting model of coalface gas emission based on LMD-SVM method, J. Ming Safety Eng. 30(6) (2013) 946-952.

[6] B. J. Xu, J. M. Zhang, X. L. Xu, A study on the method of restraining the ending effect of empirical mode decomposition, Transacting BeiJing Inst. Technol. (3) (2006) 196-200.

[7] Q. Hao, Y. M. Liu, Application of EMD-SVM combined model in prediction of strip tension, Comput. Meas. Control, (4) (2014) 1279-1281.

[8] C. F. Cao, S. X. Yang, J. X. Yang, A new method for restraining the end effect of empirical mode decomposition and its application to signal feature extraction, J. Eibration Eng. (6) (2008) 588-593.

[9] C. H. Bai, X. C. Zhou, D. C. Lin, Z. Q. Wang, PSO-SVM method based on elimination of end effect in EMD, Syst. Eng. Theor. Prantice, (5) (2013) 1298-1306.

[10] X. K. Xie, A study on the method of restraining the ending effect of EMD, KunMing University of Science and Technology, (2010).

[11] D. Q. Ren, S. X. Yang, Z. T. Wu, G. B. Yan, Research on End Effcet of LMD Based Time-frequency Analysis in Rotating Machinery Fault Diagnosis, China Mech. Eng. 23(8) (2012).

[12] X. M. Wang, F. L. Huang, Practical Method to Restrain the End Effect of EMD, J. Vib. Meas. Diagnosis, 32(3) (2012) 493-497.

[13] C. F. Wang, G. An, K. Wang, Y. P. Hu, Improves Method for End Effect of EMD Based on Mirror Extension and Neural Network, J. Acad. Amored Force Eng. 24(2) (2010).

[14] J. S. Cheng, Z. K. Huang, Y. Yang, D. J. Yu, Comparison between the methods of local mean decomposition and empirical mode decomposition, J. Vib. Shock, 28(5) (2009) 13-16.

[15] D. Q. Ren, Z. T. Wu, G. B. Yan, Evaluation of the EMD end effort and its window based method, Manuf. Autom. 29(1) (2007) 21-24.

[16] Z. F. Xu, K. Liu, Method of Empirical Mode Decomposition End Effect Based on Anlysis of Extreme Valua Symbol Sequence, J. Vib. Meas. Diagnosis, 35(2) (2015) 309-315.