Gearbox Fault Diagnosis Using Two-Dimensional Wavelet Transform
In this paper, a novel technique for denoising gearbox vibration has been proposed. We first convert the vibration signal into a two-dimensional matrix such that each row of the resulting matrix contains exactly one revolution of the gear. This matrix is subsequently denoised using two-dimensional wavelet thresholding method. We apply our proposed method to an experimental data set to investigate the improvement in denoising performance. The experimental data is generated using a test rig on which different damage levels are simulated. The experimental results show that the impulses in the vibration signal can be detected easily from the denoised signal even for slight localized tooth damage. The proposed method is compared to time synchronous averaging and the combination of the time synchronous averaging and the one-dimensional wavelet denoising. The kurtosis value of the denoised signal is used for comparing the denoising performance of these three methods. The comparison study shows that the proposed method outperforms both competing methods, especially in early stages of the fault.
- 1.McFadden PD, Smith JD (1985) A signal processing technique for detecting local defects in a gear from the signal average of the vibration. In: Proceedings of the institution of mechanical engineers, vol 199(C4). pp 287–292Google Scholar
- 2.Hochmann D, Sadok M (2004) Theory of synchronous averaging. In: Proceedings of IEEE aerospace conference; 6–13 March; Big Sky, MO. vol 6. pp 3636–3653Google Scholar
- 5.Tian X (2004) Dynamic simulation for system response of gearbox including localized gear faults. [MS Thesis]. University of Alberta, Edmonton, CanadaGoogle Scholar
- 7.Wang J, Huang HK (2009) Handbook of medical image processing and analysis: three-dimensional image compression with wavelet transforms, 2nd edn. Academic Press, New YorkGoogle Scholar
- 9.Yuan J, Pan H (2011) Gearbox vibration signal online de-noise method based on regularized particle filter. J Comput Inf Syst 7(3):786–793Google Scholar