A review on the role of tunable Q-factor wavelet transform in fault diagnosis of rolling element bearings
A Anwarsha, T Narendiranath Babu - Journal of Vibration Engineering & …, 2022 - Springer
Background Tunable Q-factor wavelet transform (TQWT) is a newly developed, updated
version of the wavelet transform that can break down any vibration signal into low Q-factor …
version of the wavelet transform that can break down any vibration signal into low Q-factor …
Fault detection and quantitative assessment of wheel diameter difference based on ensemble adaptive tunable Q-factor wavelet transform and mixed kernel principal …
S Sui, K Wang, S Chen - Measurement Science and Technology, 2023 - iopscience.iop.org
Tread wear is inevitable for railway vehicles. Because of the complicated railway condition,
the wear rates of the two wheels of a wheelset are usually unequal, which leads to the wheel …
the wear rates of the two wheels of a wheelset are usually unequal, which leads to the wheel …
Weighted IMF-based denoising and multi-scale kurtosis weighted K singular value decomposition dictionary learning model for bearing fault diagnosis
A Wang, T Gou, W Cui, R **ao, X Wan… - Journal of Vibration …, 2024 - journals.sagepub.com
Generally, bearing early failure-induced impulses is weak and easily submerged by strong
background noise. How to extract weak impulses is a big challenge. In this paper, based on …
background noise. How to extract weak impulses is a big challenge. In this paper, based on …
Harmonic Source Identification in Microgrid using TQWT and SVM Classifier
The detection and characterization of harmonic sources within Microgrid is an essential
responsibility of power engineers, given its direct impact on the system's stability and …
responsibility of power engineers, given its direct impact on the system's stability and …
Signal adaptive Q factor selection for resonance based signal separation using tunable-Q wavelet transform
N Ozkurt - 2018 41st International Conference on …, 2018 - ieeexplore.ieee.org
Tunable Q wavelet transform (TQWT) was recently proposed as an efficient wavelet
decomposition method which can match to the oscillatory behaviour of the signal. The …
decomposition method which can match to the oscillatory behaviour of the signal. The …
Fault Diagnosis of Rolling Bearing Based on Tunable Q-Factor Wavelet Transform and Convolutional Neural Network.
L Hou, Z Li - International Journal of Online & Biomedical …, 2020 - search.ebscohost.com
The rolling bearing plays is used extensively in rotary machines and industrial processes.
Effective fault diagnosis technology for a rolling bearing directly affects the life and operator …
Effective fault diagnosis technology for a rolling bearing directly affects the life and operator …
Bearing fault diagnosis using hyper-laplacian priors and non-convex optimization
Bearing fault diagnosis is one of the most important topics in the condition-based
maintenance and is also a challenging problem because of the heavy noise interference …
maintenance and is also a challenging problem because of the heavy noise interference …