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Lyapunov Exponent Employing Fractional Spline Wavelet for Fault Diagnosis of Rolling Bearing

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A novel Fractional Spline Wavelet Transform (FrSWT) method used as denoise is presented based on the different correlativity of different signals in fractional wavelet field, then the method combined with Lyapunov exponent is applied to fault diagnosis of rolling bearing. Compared with the traditional wavelet packet transform, firstly the excellent denoising performance of this proposed method is illustrated though simulated signals form bearing system, then the simulation results demonstrates that Lyapunov exponent employing fractional spline wavelet for fault diagnosis of rolling bearing is more accurate and effective to recognize the fault of rolling bearing than its counterpart.
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Keywords: FAULT DIAGNOSIS; FRACTIONAL SPLINE WAVELET; LYAPUNOV EXPONENT; ROLLING BEARING

Document Type: Research Article

Publication date: 2012-03-01

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  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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