A novel method for the optimal band selection for vibration signal demodulation and comparison with the Kurtogram

被引:534
作者
Barszcz, Tomasz [1 ]
Jablonski, Adam [1 ]
机构
[1] AGH Univ Sci & Technol, Dept Mech Engn & Robot, PL-30059 Krakow, Poland
关键词
Rolling bearing diagnostics; Spectral kurtosis; Narrowband amplitude demodulation; BEARING FAULT SIGNALS; SPECTRAL KURTOSIS; GEAR; NOISE;
D O I
10.1016/j.ymssp.2010.05.018
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The narrowband amplitude demodulation of a vibration signal enables the extraction of components carrying information about rotating machine faults. However, the quality of the demodulated signal depends on the frequency band selected for the demodulation. The spectral kurtosis (SK) was proved to be a very efficient method for detection of such faults, including defective rolling element bearings and gears Ill. Although there are conditions, under which SK yields valid results, there are also cases, when it fails, e.g. in the presence of a relatively strong, non-Gaussian noise containing high peaks or for a relatively high repetition rate of fault impulses. In this paper, a novel method for selection of the optimal frequency band, which attempts to overcome the aforementioned drawbacks, is presented. Subsequently, a new tool for presentation of results of the method, called the Protrugram, is proposed. The method is based on the kurtosis of the envelope spectrum amplitudes of the demodulated signal, rather than on the kurtosis of the filtered time signal. The advantage of the method is the ability to detect transients with smaller signal-to-noise ratio comparing to the SK-based Fast Kurtogram. The application of the proposed method is validated on simulated and real data, including a test rig, a simulated signal, and a jet engine vibration signal. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:431 / 451
页数:21
相关论文
共 17 条
[1]   The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines [J].
Antoni, J ;
Randall, RB .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2006, 20 (02) :308-331
[2]   The spectral kurtosis: a useful tool for characterising non-stationary signals [J].
Antoni, J .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2006, 20 (02) :282-307
[3]   Fast computation of the kurtogram for the detection of transient faults [J].
Antoni, Jerome .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2007, 21 (01) :108-124
[4]  
Barszcz T., 2009, P 16 INT C SOUND VIB
[5]   Application of spectral kurtosis for detection of a tooth crack in the planetary gear of a wind turbine [J].
Barszcz, Tomasz ;
Randall, Robert B. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2009, 23 (04) :1352-1365
[6]   A joint resonance frequency estimation and in-band noise reduction method for enhancing the detectability of bearing fault signals [J].
Bozchalooi, I. Soltani ;
Liang, Ming .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2008, 22 (04) :915-933
[7]  
Braun S., 1986, MECH SIGNATURE ANAL
[8]   Optimal filtering of gear signals for early damage detection based on the spectral kurtosis [J].
Combet, F. ;
Gelman, L. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2009, 23 (03) :652-668
[9]  
Courrech J., 1998, ENVELOPE ANAL KEY RO
[10]  
Dwyer R. F., 1983, Proceedings of ICASSP 83. IEEE International Conference on Acoustics, Speech and Signal Processing, P607