TITLE:
Research on Feature Extraction Method for Low-Speed Reciprocating Bearings Based on Segmented Short Signal Modulation Signal Bispectrum Slicing
AUTHORS:
Hao Zhang
KEYWORDS:
Fault Diagnosis, The Modulation Signal Bispectrum, Short Signal, Low-Speed Reciprocating Bearings, Slewing Bearing
JOURNAL NAME:
Open Journal of Applied Sciences,
Vol.13 No.12,
December
18,
2023
ABSTRACT: Bearing condition
monitoring and fault diagnosis (CMFD) can investigate bearing faults in the
early stages, preventing the subsequent impacts of machine bearing failures
effectively. CMFD for low-speed, non-continuous operation bearings, such as yaw
bearings and pitch bearings in wind turbines, and rotating support bearings in
space launch towers, presents more challenges compared to continuous rolling
bearings. Firstly, these bearings have very slow speeds, resulting in weak
collected fault signals that are heavily masked by severe noise interference.
Secondly, their limited rotational angles during operation lead to a restricted
number of fault signals. Lastly, the interference from deceleration and
direction-changing impact signals significantly affects fault impact signals.
To address these challenges, this paper proposes a method for extracting fault
features in low-speed reciprocating bearings based on short signal segmentation
and modulation signal bispectrum (MSB) slicing. This method initially separates
short signals corresponding to individual cycles from the vibration signals
based on encoder signals. Subsequently, MSB analysis is performed on each short
signal to generate MSB carrier-slice spectra. The optimal carrier frequency and
its corresponding modulation signal slice spectrum are determined based on the
carrier-slice spectra. Finally, the MSB modulation signal slice spectra of the
short signal set are averaged to obtain the overall average feature of the
sliced spectra.