A multi-demodulation band recognition strategy and its application in the multiple source fault diagnosis of wheelset-bearing system
Wenpeng Liu, Shaopu Yang, Yongqiang Liu, Rujiang Hao, Xiaohui Gu, Feiyue DengTo address the limitations of Kurtogram in handling high-amplitude impacts in wheel–rail noise and its inability to effectively identify composite faults in the wheelset-bearing system, this study introduces a novel Weight Kurtogram-based multi-demodulation band recognition strategy. This strategy firstly introduces a flexible frequency band division approach based on the fluctuation state of the Fourier spectrum. Additionally, a novel Weight Kurtosis indicator is designed to fully utilize the impulsiveness and periodicity of fault signatures, providing a great immunity to high-amplitude shocks. Furthermore, inspired by the observed multi-layer sub-band clustering in the Weight Kurtogram, a unique multi-resonant frequency band identification strategy is introduced to fully reveal all informative frequency bands. To validate the efficacy of this method, simulations and tests are conducted using real wheelset-bearing system vibration signals. The results indicate that the multi-band demodulation strategy is an effective method for detecting multiple source faults in the wheelset-bearing system.