Abstract
This chapter describes a successful application of spline-based wavelet packet transforms (WPTs) described in Chap. 4 to a complicated problem of detection of incipient defects in rolling element bearings by the analysis of recorded vibration signals. The methodology presented in this chapter is applied to the analysis of vibration data recorded from large bearings working in real unfavorable operation conditions in presence of strong noise and vibrations from multiple internal and external sources. It relies on properties of discrete spline-based wavelet packets such as orthogonality, near-rectangular spectra, transient oscillating shapes of testing waveforms and fast implementation of transforms. The methodology succeeded in detection of even small defects that commercial vibration monitoring systems failed to detect. This chapter is written in cooperation with Kari Saarinen (Ph. D, ABB AB Corporate Research and Department of Mathematical Information Technology, University of Jyväskylä, Finland).
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Averbuch, A.Z., Neittaanmäki, P., Zheludev, V.A. (2019). Detection of Incipient Bearing Fault in a Slowly Rotating Machine Using Spline Wavelet Packets. In: Spline and Spline Wavelet Methods with Applications to Signal and Image Processing. Springer, Cham. https://doi.org/10.1007/978-3-319-92123-5_13
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DOI: https://doi.org/10.1007/978-3-319-92123-5_13
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