Envelope Spectrum L-Kurtosis and Its Application for Fault Detection of Rolling Element Bearings

Abstract

As one of the most important and essential elements of machines, rolling element bearings always fail due to the severe operating environment. Bearing failures usually result in the periodic impulses, which are the most crucial feature for the bearing diagnosis. These impulses may be overwhelmed by the background noises or other unrelated components. Many traditional features in the time domain such as kurtosis and root mean square (rms) are invalid in some cases. They are ineffective in detecting periodic impulses. This paper proposed a novel frequency-domain index, named envelope spectrum (ES) L-kurtosis (ESLK), to detect the periodicity of impulses. In this paper, simulations and bearing degradation data are utilized to clarify the properties of ESLK. In addition, this paper also proposed an ESLK-based method to locate the frequency range of periodic impulses. This method is verified by simulations and an experiment. The results illustrate that the proposed method performs better than the traditional kurtosis-based method.