Vibration analysis of rotating machinery using time–frequency analysis and wavelet techniques

Al-Badour, Fadi; Sunar, M.; Cheded, Lahouari

doi:10.1016/j.ymssp.2011.01.017

Cited by 262 publications

(122 citation statements)

References 14 publications

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“…Studies have also been carried out to examine the application of WPT to detect faults in rotating machinery using signals obtained experimentally from a custom-built rotor kit [59]. The experimental set-up simulated the main operating conditions of rotating machinery, at laboratory scale, which are used in a wide range of industrial applications involving several different pieces of equipment.…”

Section: Wavelet Packets Transformmentioning

confidence: 99%

“…In practice, this can be carried out by comparing the shape of the fault to be detected with the wavelet function to be used. Symmetric wavelets were found to be more effective in singularity analysis, for example, a very narrow pulse-like anti-symmetric wavelet, such as db10 or any higher-order of Daubechies family where it was also found to perform well [59]. Specifically, in crack detection, the maximum cross-correlation coefficients computed between the fault signal and the different wavelet functions from the library will give the optimal wavelet function, as shown in [68].…”

Section: Wavelet Transform Parameters Selectionmentioning

confidence: 99%

See 1 more Smart Citation

Review of Recent Advances in the Application of the Wavelet Transform to Diagnose Cracked Rotors

2016

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Wavelet transform (WT) has been used in the diagnosis of cracked rotors since the 1990s. At present, WT is one of the most commonly used tools to treat signals in several fields. Understandably, this has been an area of extensive scientific research, which is why this paper aims to summarize briefly the major advances in the field since 2008. The present review considers advances in the use and application of WT, the selection of the parameters used, and the key achievements in using WT for crack diagnosis.

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Section: Wavelet Packets Transformmentioning

confidence: 99%

Section: Wavelet Transform Parameters Selectionmentioning

confidence: 99%

Review of Recent Advances in the Application of the Wavelet Transform to Diagnose Cracked Rotors

2016

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“…There are more works that are dealing with damage detection in rotating machines, as for: rotors [2], ball bearings [3], electrical motor [4,5] or motor winding [6], driving tooth wheels [7] or mechanical transmission [8], rotating machinery [9], wind turbines [10].…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Damage detection in rotating machinery by means of entropy-based parameters

Tocarciuc¹,

Bereteu²,

Drăgănescu³

2014

AIP Conference Proceedings

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Abstract. The paper is proposing two new entropy-based parameters, namely Renyi Entropy Index (REI) and SharmaMittal Entropy Index (SMEI), for detecting the presence of failures (or damages) in rotating machinery, namely: belt structural damage, belt wheels misalignment, failure of the fixing bolt of the machine to its baseplate and eccentricities (i.e.: due to detaching a small piece of material or bad mounting of the rotating components of the machine). The algorithms to obtain the proposed entropy-based parameters are described and test data is used in order to assess their sensitivity. A vibration test bench is used for measuring the levels of vibration while artificially inducing damage. The deviation of the two entropy-based parameters is compared in two states of the vibration test bench: not damaged and damaged. At the end of the study, their sensitivity is compared to Shannon Entropic Index.

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“…Instead, wavelet transform and empirical mode decomposition (EMD) have shown their effectiveness in providing high resolution in both time and frequency domain, which have been successfully applied in the field of fault diagnosis of shafts, such as continuous wavelet transform coefficients were used in works [1]- [5]. Apart from that, wavelet packets Corresponding author: Lei Shu (email: lshu@lincoln.ac.uk) decomposition (WPD) benefits from effectively decomposing frequency bands into detail and approximate coefficients with multi-levels [6], which has been applied in [7], [8]. The advent of EMD, proposed by Huang and Wu, provides a powerful self-adaptive signal processing method for analyzing nonstationary and non-linear signals by decomposing the signals into a set of intrinsic mode functions (IMFs) [9]- [11], which are determined by the signal itself rather than the pre-defined kernels compared with wavelet analysis.…”

Section: Introductionmentioning

confidence: 99%

A comparative study of WPD and EMD for shaft fault diagnosis

Huo

Shu

2017

IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society

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Abstract-Fault diagnosis of incipient crack failure in rotating shafts allows the detection and identification of performance degradation as early as possible in industrial plants, such as downtime and potential injury to personnel. The present work studies the performance and effectiveness of crack fault detection by means of applying wavelet packet decomposition (WPD) and empirical mode decomposition (EMD) on fault diagnosis of rotating shafts using multiscale entropy (MSE). After WPD and EMD, the most sensitive reconstruction vectors and intrinsic mode functions (IMFs) are selected using Shannon entropy. Then, these feature vectors are fed into support vector machine (SVM) for fault classification, where the entropy features represent the complexity of vibration signals with different scales. Experimental results have demonstrated that WPD combined with MSE can achieve an accuracy of 97.3% for crack fault detection in rotating shafts, whilst EMD combined with MSE has shown a higher detection rate of 98.5%.

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Vibration analysis of rotating machinery using time–frequency analysis and wavelet techniques

Cited by 262 publications

References 14 publications

Review of Recent Advances in the Application of the Wavelet Transform to Diagnose Cracked Rotors

Review of Recent Advances in the Application of the Wavelet Transform to Diagnose Cracked Rotors

Damage detection in rotating machinery by means of entropy-based parameters

A comparative study of WPD and EMD for shaft fault diagnosis

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