Application of Mathematical Morphological Filter in Vibration Signal Processing

Abstract:

The morphological filter as a nonlinear filtering method has been widely used for image (or signal) processing. Unlike the traditional digital filters, mathematical morphological operations are shape-based computing. Feature extraction of signals is entirely in the time domain without the transforming of the signal from the time domain to frequency domain. The vibration signal contaminated with noise is processed using morphological filter and Butterworth filter respectively. To compare the outputs of the two filters, we find that morphological filter shows better performance. It is effective in suppressing noise while maintaining the original signal both in the time and frequency domain. In addition, an outstanding advantage of morphological filter is its ability to keep the phase of the original signal. Its computing speed is faster. In the end, its low-pass characteristic is verified by processing vibration signal.

• Periodical: Applied Mechanics and Materials (Volumes 71-78)
• Pages: 4564-4567
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.71-78.4564
• Online since: July 2011
• Authors: Ai Jun Hu, Jing Jing Sun, Wan Li Ma
• Keywords: Filter, IIR, Mathematical Morphology, Phase, Vibration

References

[1] Maragos P，Schafer R W, Morphological fi1ters -Part I: Their set theoretic analysis and relation to linear shift invariant filters, IEEE Trans on ASSP. Vol. 35(1987), pp.1153-1169.

DOI: 10.1109/tassp.1987.1165259

[2] Maragos P，Schafer R W, Morphological fi1ters—Part II: Their relation to median, order-statistic, and stack filters, IEEE Trans on ASSP. Vol. 35(1987), pp.1170-1184.

DOI: 10.1109/tassp.1987.1165254

[3] Peters, Richard Alan II, New algorithm for image noise reduction using mathematical morphology, IEEE Transactions on Image Processing. Vol. 4(1995), pp.554-568.

DOI: 10.1109/83.382491

[4] NIKOLAOU N G, ANTONIADIS I A. Application of morphological operators as envelope extractors for impulsive-type periodic signals, Mechanical System and Signal Processing, Vol. l7(2003), p.1147-l 162.

DOI: 10.1006/mssp.2002.1576

[5] LUO Zhong-hui, XUE Xiao-ning, WANG Xiao-zhen. Study on the method of incipient motor bearing fault diagnosis based on wavelet transform and EMD, Chinese Journal of Proceedings of the Csee, Vol. 14(2005), pp.125-129.

[6] ZHANG Lijun, YANG Debin, XV Jinwu and CHEN Zhixin. Approach to extracting gear fault feature based on mathematical morphological filtering, Chinese Journal of Mechanical Engineering, Vol. 43(2007), p.71～75.

DOI: 10.3901/jme.2007.02.071