A Novel Method for Identifying Resonance Frequency Band in Weak Bearing Fault Diagnosis of Electric Driving System

Because of the uncertainty of the structure and environment of the electric driving system (EDS), the fault signature of the rotating mechanism is complicated. A novel method based on Hilbert transform with modified fast kurtogram (HTMFK), which is used for identifying the bearing faults in the EDS,...

Full description

Saved in:
Bibliographic Details
Published inShock and vibration Vol. 2024; pp. 1 - 20
Main Authors Yue, Cong, Zhu, Yu, Cheng, Ping, Wang, Bei, Wang, Kai
Format Journal Article
LanguageEnglish
Published Cairo Hindawi 2024
Hindawi Limited
Wiley
Subjects
Algorithms
Bearings
Electric vehicles
Fault detection
Fault diagnosis
Frequencies
High pass filters
Hilbert transformation
Kurtosis
Optimization
Resonance
Signal processing
Online AccessGet full text

Cover

More Information
Summary:Because of the uncertainty of the structure and environment of the electric driving system (EDS), the fault signature of the rotating mechanism is complicated. A novel method based on Hilbert transform with modified fast kurtogram (HTMFK), which is used for identifying the bearing faults in the EDS, is proposed. The modified principle and algorithm flow of the proposed method are derived. A high pass filter based on the frequency band identified by HTMFK is constructed and applied to fault diagnosis. Simulation signals demonstrate the ability of demodulating signals and identifying the fault resonance band. The bearing fault bench experiment of EDS is carried out in a semianechoic chamber. The corresponding fault tests are conducted according to different operating conditions. The applicability of HTMFK is verified by comparing the square envelope spectrums. Compared with other methods, the proposed method identifies the fault resonance frequency band more effectively and expands the application range of bearing fault diagnosis in EDS.
ISSN:1070-9622
1875-9203
DOI:10.1155/2024/2804173