The velocity synchronous discrete Fourier transform for order tracking in the field of rotating machinery

Borghesani, Pietro; Pennacchi, Paolo; Chatterton, Steven; Ricci, R.

doi:10.1016/j.ymssp.2013.03.026

Cited by 89 publications

(47 citation statements)

References 20 publications

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“…Metal bellow couplings (2) and (4) connect the shafts of motor, eddy current brake and gearbox. Using this setup the gearbox can be operated at input speeds up to 10 000 min −1 and output torques up to 40 N m. The gearbox mount is supported by two triaxial force sensors (6).…”

Section: Experimental Set-upmentioning

confidence: 99%

“…Thus, the index k uniquely identifies a spectral component. Now (3) is inserted into (2) and (1) is applied to the result.…”

Section: Modeling Gear Mesh Vibrationmentioning

confidence: 99%

“…Also it performs acceptably in the case of non-constant angular velocity. Here FFT based approaches need to re-sample the measured data as explained in [2].…”

Section: Modeling Gear Mesh Vibrationmentioning

confidence: 99%

“…It is mostly performed off-line using recorded vibration data. Borghesani et al [2] explain how this can be performed using state of the art methods. They categorize the known approaches into three classes: "the resampling methods, the Kalman filter based methods and the transform based methods".…”

Section: Introductionmentioning

confidence: 99%

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Real-Time Order Tracking of Gear Mesh Vibration in High Speed Planetary Gearboxes

2018

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Abstract. Possible approaches to real-time order tracking are discussed. Two methods for real-time order tracking are developed and validated experimentally for the entire audible spectrum. An adaptive heterodyne filter bank is compared to a direct integral transform. The performance of both methods is adequate for usage in an active vibration control (AVC) algorithm. Vold-Kalman filters are not suitable for AVC. The vibration data of three different planetary gearboxes is analyzed using order tracking. While some of the existing research could be reproduced, the data contradicts statements made by several authors. Lastly, the architecture of a novel AVC algorithm is sketched out.

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Section: Experimental Set-upmentioning

confidence: 99%

“…Thus, the index k uniquely identifies a spectral component. Now (3) is inserted into (2) and (1) is applied to the result.…”

Section: Modeling Gear Mesh Vibrationmentioning

confidence: 99%

“…Also it performs acceptably in the case of non-constant angular velocity. Here FFT based approaches need to re-sample the measured data as explained in [2].…”

Section: Modeling Gear Mesh Vibrationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Real-Time Order Tracking of Gear Mesh Vibration in High Speed Planetary Gearboxes

2018

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“…It has been for long an essential quantity in rotor dynamics and in NVH applications concerned with the testing of rotating machines in transient regimes such as runups and shutdowns. In this context, the IAS makes possible the synchronization of Fourier analysis on the shaft rotation -a practice known as order (spectral) analysis -or the tracking of the evolution of the Fourier coefficients as a function of speed -a practice known as order tracking [5][6][7]. Early successes of order tracking are exemplified by the Vold-Kalman filter [8][9][10][11][12][13][14], a model-based approach well suited to slow-speed variations and high SNRs.…”

Section: Introductionmentioning

confidence: 99%

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

Leclère

André²,

Antoni

2016

Mechanical Systems and Signal Processing

113

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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 ...). 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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Prediction of wind turbine generator failure using two‐stage cluster‐classification methodology

et al. 2019

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Reducing wind turbine downtime through innovations surrounding asset management has the potential to greatly influence the levelised cost of energy (LCoE) for large wind farm developments. Focusing on generator bearing failure and vibration data, this paper presents a two‐stage methodology to predict failure within 1 to 2 months of occurrence. Results are obtained by building up a database of failures and training machine learning algorithms to classify the bearing as healthy or unhealthy. This is achieved by first using clustering techniques to produce subpopulations of data based on operating conditions, which this paper demonstrates can greatly influence the ability to diagnose a fault. Secondly, this work classifies individual clusters as healthy or unhealthy from vibration‐based condition monitoring systems by applying order analysis techniques to extract features. Using the methodology explained in the report, an accuracy of up to 81.6% correct failure prediction was achieved.

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The velocity synchronous discrete Fourier transform for order tracking in the field of rotating machinery

Cited by 89 publications

References 20 publications

Real-Time Order Tracking of Gear Mesh Vibration in High Speed Planetary Gearboxes

Real-Time Order Tracking of Gear Mesh Vibration in High Speed Planetary Gearboxes

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

Prediction of wind turbine generator failure using two‐stage cluster‐classification methodology

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