A multi-order probabilistic approach for Instantaneous Angular Speed tracking debriefing of the CMMNO'14 diagnosis contest

A multi-order probabilistic approach for Instantaneous Angular Speed tracking debriefing of the CMMNO'14 diagnosis contest

The aim of this work is to propose a novel approach for the estimation of the Instantaneous Angular Speed (IAS) of rotating machines from vibration measurements. This work is originated from the organisation, by the authors of this paper, of a contest during the conference CMMNO 2014, that was held...

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Bibliographic Details
Published in:Mechanical systems and signal processing Vol. 81; pp. 375 - 386
Main Authors: Leclerea, Quentin, Andreb, Hugo, Antonia, Jerome
Format: Journal Article
Language:English
Published: Elsevier 15-12-2016
Subjects:
Acoustics
Angular speed
Diagnosis
Harmonics
Mechanical systems
Mechanics
Meshing
Physics
Spectra
Tracking
Wind turbines
demodulation
wind turbines
virtual tacho
order tracking
Instantaneous Angular Speed
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Summary:The aim of this work is to propose a novel approach for the estimation of the Instantaneous Angular Speed (IAS) of rotating machines from vibration measurements. This work is originated from the organisation, by the authors of this paper, of a contest during the conference CMMNO 2014, that was held in Lyon, December 2014. One purpose of the contest was to extract the IAS of a wind turbine from a gearbox accelerometer signal. The analysis of contestant contributions led to the observation that the main source of error in this exercise was the wrong association of one selected and tracked harmonic component with one mechanical periodic phenomenon, this association being assumed as an a priori hypothesis by all the methods used by the contestants. The approach proposed in this work does not need this kind of a priori assumption. A majority (but not necessarily all) periodical mechanical events are considered from a preliminary analysis of the kinematics of the machine (harmonics of shaft rotation speeds, meshing frequencies, etc.). The IAS is then determined from probability density functions that are constructed from instantaneous spectra of the signal. The efficiency and robustness of the proposed approach are illustrated in the frame of the CMMNO 2014 contest case.
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ISSN:0888-3270
1096-1216
DOI:10.1016/j.ymssp.2016.02.053