ARL-Wavelet-BPF optimization using PSO algorithm for bearing fault diagnosis
Rotating element bearings are the backbone of every rotating machine. Vibration signals measured from these bearings are used to diagnose the health of the machine, but when the signal-to-noise ratio is low, it is challenging to diagnose the fault frequency. In this paper, a new method is proposed t...
Main Authors: | Muhammad Ahsan, Dariusz Bismor, Muhammad Arslan Manzoor |
---|---|
Format: | Article |
Language: | English |
Published: |
Polish Academy of Sciences
2023-09-01
|
Series: | Archives of Control Sciences |
Subjects: | |
Online Access: | https://journals.pan.pl/Content/128385/PDF/art06_int.pdf |
Similar Items
-
Novel technology based on the spectral kurtosis and wavelet transform for rolling bearing diagnosis
by: Gabrijel Persin, et al.
Published: (2013-01-01) -
Incipient Gear Fault Detection Using Adaptive Impulsive Wavelet Filter Based on Spectral Negentropy
by: Mang Gao, et al.
Published: (2022-02-01) -
The Detection of Motor Bearing Fault with Maximal Overlap Discrete Wavelet Packet Transform and Teager Energy Adaptive Spectral Kurtosis
by: D.-M. Yang
Published: (2021-10-01) -
Adaptive Reinforced Empirical Morlet Wavelet Transform and Its Application in Fault Diagnosis of Rotating Machinery
by: Yu Xin, et al.
Published: (2019-01-01) -
Novel Fault Diagnosis of Bearings and Gearboxes Based on Simultaneous Processing of Spectral Kurtoses
by: Len Gelman, et al.
Published: (2022-10-01)