2025 International Conference on Equipment Intelligent Operation and Maintenance (ICEIOM2025)

179 / 2025-06-12 13:46:55

A novel adaptive filtering method based on frequency slicing function

rolling bearing; fault diagnosis; frequency slice function; Gini index

Special Sessions > SSL 05 Condition monitoring, fault diagnosis and intelligent maintenance of mechanical equipment

Aiming at the difficulty of frequency domain filtering of vibration signals caused by rolling bearing faults in complex environments, a frequency domain adaptive filtering method based on frequency slicing function is proposed. This method first uses the cepstrum to quantify the characteristics of periodic components in the frequency domain to generate a trend spectrum, and then adaptively determines the filtering boundary based on the local minimum points in the trend spectrum. A filter bank is constructed based on the frequency slicing function to separate the signal components. Finally, a robust modulated Gini index is introduced to enhance the fault feature detection capability. Simulation verifies the ability of this method to effectively extract periodic impact pulses, and experiments confirm its practicality in the diagnosis of inner and outer race faults of rolling bearings.