Lyapunov Exponent Employing Fractional Spline Wavelet for Fault Diagnosis of Rolling Bearing
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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Document Type: Research Article
Publication date: March 1, 2012
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