Compound feature selection and parameter optimization of ELM for fault diagnosis of rolling element bearings

Author:

Luo Meng,Li Chaoshun,Zhang Xiaoyuan,Li Ruhai,An Xueli

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Applied Mathematics,Control and Systems Engineering,Electrical and Electronic Engineering,Computer Science Applications,Instrumentation

Reference40 articles.

1. Multi-fault diagnosis for rolling element bearings based on ensemble empirical mode decomposition and optimized support vector machines;Zhang;Mech Syst Signal Process,2013

2. Bearing fault diagnosis under unknown variable speed via gear noise cancellation and rotational order sideband identification;Wang;Mech Syst Signal Process,2015

3. A novel method for fault diagnosis of hydro generator based on NOFRFs;Xia;Int J Electr Power,2015

4. A time–frequency analysis approach for condition monitoring of a wind turbine gearbox under varying load conditions;Antoniadou;Mech Syst Signal Process,2015

5. Application of the envelope and wavelet transform analyses for the diagnosis of incipient faults in ball bearings;Rubini;Mech Syst signal Process,2001

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