Modified multiscale weighted permutation entropy and optimized support vector machine method for rolling bearing fault diagnosis with complex signals

Z Wang, L Yao, G Chen, J Ding - ISA transactions, 2021 - Elsevier
The rolling bearing vibration signals are complex, non-linear, and non-stationary, it is difficult
to extract the sensitive features and diagnose faults by conventional signal processing …

Review of local mean decomposition and its application in fault diagnosis of rotating machinery

LI Yongbo, SI Shubin, LIU Zhiliang… - Journal of Systems …, 2019 - ieeexplore.ieee.org
Rotating machinery is widely used in the industry. They are vulnerable to many kinds of
damages especially for those working under tough and time-varying operation conditions …

Multiscale symbolic fuzzy entropy: An entropy denoising method for weak feature extraction of rotating machinery

Y Li, S Wang, Y Yang, Z Deng - Mechanical Systems and Signal …, 2022 - Elsevier
The entropy-based method has been demonstrated to be an effective approach to extract
the fault features by estimating the complexity of signals, but how to remove the strong …

Sound based fault diagnosis for RPMs based on multi-scale fractional permutation entropy and two-scale algorithm

Y Sun, Y Cao, G **
A Ismail, S Abdlerazek, IM El-Henawy - Sustainability, 2020 - mdpi.com
This paper presents an effective solution based on speech recognition to provide elderly
people, patients and disabled people with an easy control system. The goal is to build a low …