Possibilities of faults detection of rolling bearings using energetic descriptors of vibrations signals

The need for fast and reliable evaluation of technical state of rotating machines forces constant development and research for condition monitoring techniques. The paper presents energetic characteristics of vibration signals as a promising new approach in condition monitoring of rolling bearings . The presented approach is based on application of the differential Teager-Kaiser energy operator . The operator makes possible to the detection of short-time disturbances in the signal which are caused by developing faults. Authors assumed that the energetic characteristics and measures would be good tool for detection of faults and defects in rolling bearings , especially when vibration signals are non-stationary in the amplitude and/or the frequency sense. The paper presents the energetic characteristics of the bearing vibration signal in the form of the time history , the energetic trajectories and measures parameterizing them. The obtained results give ability to determine the basic features of characteristics and measures,. The presentation of qualitative changes in the form of characteristics caused by different kinds of faults of rolling bearings was one of the main aims of the research. From practical point of view the assessment of the sensitivity of the above-mentioned energetic measures on changes in technical condition of bearings was also crucial. The presented results have been obtained by testing the set of tapered roller bearings of the same type and size. New bearings, defective ones and bearings with artificially introduced faults were tested.

[1]  Brian Griffiths,et al.  Condition Monitoring and Diagnostic Engineering Management , 1990 .

[2]  R. G. Harker,et al.  Rolling Element Bearing Monitoring Using High Gain Eddy Current Transducers , 1985 .

[3]  D. E. Butler,et al.  The Shock-pulse method for the detection of damaged rolling bearings , 1973 .

[4]  Chun Hua Zhao,et al.  Fault Diagnosis for Wind Turbine Gearboxes Based on EMD and the Energy Operator , 2013 .

[5]  J. F. Kaiser,et al.  On a simple algorithm to calculate the 'energy' of a signal , 1990, International Conference on Acoustics, Speech, and Signal Processing.

[6]  Petros Maragos,et al.  On amplitude and frequency demodulation using energy operators , 1993, IEEE Trans. Signal Process..

[7]  I. Soltani Bozchalooi,et al.  An energy operator approach to joint application of amplitude and frequency-demodulations for bearing fault detection ☆ , 2010 .

[8]  Czesław Cempel,et al.  Inżynieria diagnostyki maszyn , 2004 .

[9]  Balbir S. Dhillon,et al.  Early fault diagnosis of rotating machinery based on wavelet packets—Empirical mode decomposition feature extraction and neural network , 2012 .

[10]  A. Gałęzia Averaged signal measures of TKEO energy waveform in detection of tooth break in gearbox , 2014 .

[11]  Keith Worden,et al.  Envelope Analysis Using the Teager-Kaiser Energy Operator for Condition Monitoring of a Wind Turbine Bearing , 2014 .

[12]  Radoslaw Zimroz,et al.  Rolling bearing diagnosing method based on Empirical Mode Decomposition of machine vibration signal , 2014 .

[13]  Petros Maragos,et al.  Higher order differential energy operators , 1995, IEEE Signal Processing Letters.

[14]  Govindappa Krishnappa,et al.  Bearing Diagnostics Based on Pattern Recognition of Statistical Parameters , 2000 .

[15]  Robert B. Randall,et al.  Vibration-based Condition Monitoring: Industrial, Aerospace and Automotive Applications , 2011 .

[16]  Shaoze Yan,et al.  Teager Energy Spectrum for Fault Diagnosis of Rolling Element Bearings , 2011 .

[17]  Thomas R. Kurfess,et al.  Rolling element bearing diagnostics in run-to-failure lifetime testing , 2001 .

[18]  Robert B. Randall,et al.  Rolling element bearing diagnostics—A tutorial , 2011 .

[19]  L. Tang,et al.  Gear Fault Detection Based on Teager-Huang Transform , 2010 .

[20]  N. Tandon,et al.  A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings , 1999 .

[21]  Eivind Kvedalen Signal processing using the Teager Energy Operator and other nonlinear operators , 2003 .

[22]  Hui Li,et al.  Bearing fault detection and diagnosis based on order tracking and Teager-Huang transform , 2010 .

[23]  Hui Li Bi-spectrum analysis based bearing fault diagnosis , 2010, 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery.

[24]  Miguel A. Ferrer,et al.  Application of the Teager-Kaiser energy operator in bearing fault diagnosis. , 2013, ISA transactions.

[25]  A. Gałęzia,et al.  Signals representation on energetic plane based on Teager-Kaiser energy operator , 2014 .