Comparison of envelope demodulation methods in the analysis of rolling bearing damage

In rotating machinery, especially in rolling bearing diagnostics, early and effective fault diagnosis is essential to ensure the reliability of rolling bearings. The commonly used vibration analysis gathers large amounts of information about the dynamics and the general condition of the bearings by recording vibrations generated by a rolling bearing. Within the vibration analysis, the location of the damage can be determined by using envelope demodulation. This is done by identifying the damage frequency within a damaged bearing. Peak-, Root-Mean-Square (RMS)-, and Hilbert-envelopes are the conventional demodulation methods in this field, but each of these methods is different and thus more or less suitable for particular applications. This paper presents a comparative study of these three methods. The selected envelopes are compared and evaluated through experiments, the evaluation of measurement data and the establishment of quality characteristics regarding efficiency and quality. In the process, a decision tool is created to help in the selection of a suitable envelope demodulation technique. A formula for calculating an optimal window size of the Peak-envelope is established, as well as a recommendation for selecting a window size of the RMS-envelope.

[1]  M. Bauer,et al.  Optimierung der Sensorpositionierung bei schwingungsbasierter Wälzlagerzustandsüberwachung unter Einbezug von Systemeigenmoden , 2021, tm - Technisches Messen.

[2]  Chen Huan,et al.  Research on envelope demodulation of reducer shock signals based on peak retention and down-sampling method , 2019, 2019 14th IEEE International Conference on Electronic Measurement & Instruments (ICEMI).

[3]  Yaguo Lei,et al.  Envelope harmonic-to-noise ratio for periodic impulses detection and its application to bearing diagnosis , 2016 .

[4]  Naseel Ibnu Azeez,et al.  Detection of rolling element bearing defects by vibration signature analysis: A review , 2014, 2014 Annual International Conference on Emerging Research Areas: Magnetics, Machines and Drives (AICERA/iCMMD).

[5]  Vasile Horga,et al.  Vibration Analysis Methods in Bearing Damage Detection , 2013 .

[6]  Eric Bechhoefer,et al.  Bearing envelope analysis window selection Using spectral kurtosis techniques , 2011, 2011 IEEE Conference on Prognostics and Health Management.

[7]  M. Feldman.  Hilbert transform in vibration analysis , 2011 .

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

[9]  I. Jaksch,et al.  Demodulation methods for exact induction motor rotor fault diagnostic , 2005, 2005 5th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives.

[10]  Carl de Boor,et al.  Convergence of Cubic Spline Interpolation with the Not-A-Knot Condition. , 1985 .

[11]  Robert H. Badgley,et al.  Application of High-Frequency Resonance Techniques for Bearing Diagnostics in Helicopter Gearboxes , 1974 .

[12]  R. Turley.  Cubic Interpolation with Irregularly-Spaced Points in Julia 1.4 , 2018 .

[13]  Cesare Alippi,et al.  Fault Diagnosis Systems , 2014 .

[14]  Petru Dobra,et al.  Comparison between envelope detection methods for bearing defects diagnose , 2013 .

[15]  Andreas Seeliger,et al.  Schwingungsdiagnose an Wälzlagern mit Hilfe der Hüllkurvenanalyse , 1995 .