Condition monitoring of rotating machinery under varying operating conditions based on Cyclo-Non-Stationary Indicators and a multi-order probabilistic approach for Instantaneous Angular Speed tracking. Issue 1 (July 2017)

• Record Type: Journal Article
• Authors: Gryllias, K.; Andre, H.; Leclere, Q.; Antoni, J.
• Is Part Of: IFAC-PapersOnLine. Volume 50:Issue 1(2017)
• Page Start: 4708
• Page End: 4713
• Publication Date: 2017-07
• Subjects: Condition monitoring -- Fault detection -- Instantaneous Angular Speed estimation -- Cyclo-Non-Stationary Indicators -- Rotating machinery -- Varying operating conditions; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2017.08.857
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: During the last decades, an emerging interest has been reported on modelling rotating machinery signals as cyclostationary. Several tools, such as the Spectral Correlation Density (SCD) and the Cyclic Modulation Spectrum (CMS) have been proposed, assuming constant or almost constant rotating speed. To overcome this limitation, generalizations of SCD and CMS have been proposed that display cyclic Order versus Frequency. On the other hand the estimation of the instantaneous angular speed of the rotating machine is a crucial issue that has to be tackled before any analysis or diagnosis of the machine operating under non-stationary conditions. This operation is generally carried out thanks to a tachometer, or an angle encoder, but in some cases this information can be missing for different reasons. The goal of this paper is to combine a novel approach for the analysis of cyclo-non-stationary signals based on the generalization of the indicators of cyclostationarity in order to cover the speed varying conditions, introducing a new speed-dependent angle averaging operator, with a new speed estimation method, that extracts from a vibration signal the most probable instantaneous rotation frequency without focusing on one specific order based on the a priori knowledge of the kinematics of the machine. The effectiveness of the ensemble method is evaluated on an acceleration signal captured at the wind turbine gearbox operating under speed varying conditions.