A novel order tracking method for wind turbine planetary gearbox vibration analysis based on discrete spectrum correction technique

He, Guolin; Ding, Kang; Li, Weihua; Jiao, Xintao

doi:10.1016/j.renene.2015.10.036

Cited by 82 publications

(42 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Qi et al [4] used the ensemble empirical mode decomposition algorithm to obtain the monocomponent intrinsic mode functions of the signal, which are subsequently used to obtain the phase information of the shaft of interest. He et al [17] proposed using the discrete spectrum correction technique to order track the vibration signal obtained from a wind turbine. Leclere et al [9] proposed a multi-order approach for instantaneous angular speed estimation.…”

Section: Introductionmentioning

confidence: 99%

A tacholess order tracking methodology based on a probabilistic approach to incorporate angular acceleration information into the maxima tracking process

Schmidt

Heyns

Villiers

2018

Mechanical Systems and Signal Processing

View full text Add to dashboard Cite

Rotational speed or phase measurements are important in the rotating machine condition monitoring field. Rotating machines often operate in the presence of fluctuating rotational speeds and its components generate signals which are periodical in the angle domain. Hence, it is essential to perform order tracking when condition monitoring is performed under varying speed conditions. Computed order tracking is performed with a measured tachometer signal and it requires additional hardware to be installed on the machine, which may not be feasible nor practical. This article presents a tacholess order tracking method which is capable of accurately estimating the phase of a shaft of interest in the presence of large angular accelerations and noise. An improved maxima tracking procedure is used with an angular-displacement Vold-Kalman filter and the Hilbert transform to estimate the instantaneous phase of the shaft under consideration. The estimated instantaneous phase is used to resample the vibration signal from the time to the angle domain. The proposed tacholess order tracking technique is critically investigated on three numerical and three experimental rotational speed profiles. The minimum and maximum phase error obtained for the experimental data was 0.037697 and 0.05022 radians respectively, which highlights the potential of the technique.

show abstract

Section: Introductionmentioning

confidence: 99%

A tacholess order tracking methodology based on a probabilistic approach to incorporate angular acceleration information into the maxima tracking process

Schmidt

Heyns

Villiers

2018

Mechanical Systems and Signal Processing

View full text Add to dashboard Cite

show abstract

“…Confronted with those challenges, the condition monitoring of machinery under VSC is gaining increasing attention in both industry and academia [5,6,7,8,9]. A number of research papers, technical reports, and conference proceedings have published on this topic in the last five years.…”

Section: Introductionmentioning

confidence: 99%

“…Consequently, the non-stationary phenomena caused by speed variation can be largely removed if the signal is represented in angular domain. Benefitting from that, the second group first utilizes order tracking technique to transform the raw signal from time domain to angular domain, and then treats it as a conventional constant speed problem [8,22]. However, it should be stressed that the signals measured under VSC is inherently more informative than these in constant speed.…”

Section: Introductionmentioning

confidence: 99%

Feature Mining and Health Assessment for Gearboxes Using Run-Up/Coast-Down Signals

Zhao

Lin

Miao

et al. 2016

Sensors

View full text Add to dashboard Cite

Vibration signals measured in the run-up/coast-down (R/C) processes usually carry rich information about the health status of machinery. However, a major challenge in R/C signals analysis lies in how to exploit more diagnostic information, and how this information could be properly integrated to achieve a more reliable maintenance decision. Aiming at this problem, a framework of R/C signals analysis is presented for the health assessment of gearbox. In the proposed methodology, we first investigate the data preprocessing and feature selection issues for R/C signals. Based on that, a sparsity-guided feature enhancement scheme is then proposed to extract the weak phase jitter associated with gear defect. In order for an effective feature mining and integration under R/C, a generalized phase demodulation technique is further established to reveal the evolution of modulation feature with operating speed and rotation angle. The experimental results indicate that the proposed methodology could not only detect the presence of gear damage, but also offer a novel insight into the dynamic behavior of gearbox.

show abstract

“…The Short Time Fourier Transform (STFT) [2][3][4], however, can overcome the aforementioned problem. However, the main problem with the method concerns about the constant resolution for all frequencies because it uses the same window for the analysis of the entire signal.…”

Section: Introductionmentioning

confidence: 99%

Bevel Gearbox Fault Diagnosis using Vibration Measurements

Hartono

Halim

Widodo

et al. 2016

MATEC Web of Conferences

View full text Add to dashboard Cite

Abstract.The use of vibration measurementanalysis has been proven to be effective for gearbox fault diagnosis. However, the complexity of vibration signals observed from a gearbox makes it difficult to accurately detectfaults in the gearbox. This work is based on a comparative studyof several time-frequency signal processing methods that can be used to extract information from transient vibration signals containing useful diagnostic information. Experiments were performed on a bevel gearbox test rig using vibration measurements obtained from accelerometers. Initially, thediscrete wavelet transform was implementedfor vibration signal analysis to extract the frequency content of signal from the relevant frequency region. Several time-frequency signal processing methods werethen incorporated to extract the fault features of vibration signals and their diagnostic performances were compared. It was shown thatthe Short Time Fourier Transform (STFT) could not offer a good time resolution to detect the periodicity of the faulty gear tooth due the difficulty in choosing an appropriate window length to capture the impulse signal. The Continuous Wavelet Transform (CWT), on the other hand, was suitable to detection of vibration transients generated by localized fault from a gearbox due to its multi-scale property. However, both methods still require a thorough visual inspection. In contrast, it was shown from the experiments that the diagnostic method using the Cepstrumanalysis could provide a direct indication of the faulty tooth without the need of a thorough visual inspection as required by CWT and STFT.

show abstract

A novel order tracking method for wind turbine planetary gearbox vibration analysis based on discrete spectrum correction technique

Cited by 82 publications

References 30 publications

A tacholess order tracking methodology based on a probabilistic approach to incorporate angular acceleration information into the maxima tracking process

A tacholess order tracking methodology based on a probabilistic approach to incorporate angular acceleration information into the maxima tracking process

Feature Mining and Health Assessment for Gearboxes Using Run-Up/Coast-Down Signals

Bevel Gearbox Fault Diagnosis using Vibration Measurements

Contact Info

Product

Resources

About