Fault Diagnosis of Bearing Based on EEMD-MDE-Improved Binary Tree SVM Hybrid Algorithm

Author:

Yanyang Li1,Jindong Wang1,Haiyang Zhao1

Affiliation:

1. Northeast Petroleum University,College of Mechanical Science and Engineering,Daqing,China

Publisher

IEEE

Reference19 articles.

1. An approach to fault diagnosis of reciprocating compressor valves using Teager–Kaiser energy operator and deep belief networks

2. Intelligent Fault diagnosis method and research of mechanical equipment -- taking rotating machinery as an example[J];Liao;Value Engineering,2019

3. B-spline empirical mode decomposition endpoint effect suppression method based on neural network integration[J];Meng;Journal of Mechanical Engineering,2018

4. Dynamic modelling of spur gear pair and application of empirical mode decomposition-based statistical analysis for early detection of localized tooth defect

5. Amplitude and Fluctuation-Based Dispersion Entropy.[J];Mostafa;Entropy( Basel, Switzerland),2021

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