Rolling bearing fault diagnosis based on 1.5-dimensional spectrum

Signal de-noising and extraction of useful signal feature are significant problems in the work of scientific research. Higher-order cumulants (HOC) have a strong ability of noise reduction. However, the increase in the order number of HOC will lead to the increase in computation. This will bring great difficulties to practical application. This paper introduces the knowledge of 1.5-dimensional spectrum, which results from the HOC. 1.5-dimensional spectrum is actually a simplified calculation method of HOC. It also remains the HOC's excellent characteristic which can suppress the additive Gaussian noise. Consequently, 1.5-dimensional spectrum can be well applied in engineering practice. Meanwhile, the Hilbert transform is also introduced simply in this paper. The simulation signals and rolling failure data are processed with the 1.5-dimensional spectrum and Hilbert transform, respectively. The comparison results confirm the practical value of 1.5-dimensional spectrum.