Time–frequency manifold for nonlinear feature extraction in machinery fault diagnosis-Reference-Cited by-同舟云学术

Time–frequency manifold for nonlinear feature extraction in machinery fault diagnosis

Published:2013-02 Issue:1-2 Volume:35 Page:200-218
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

He Qingbo

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference31 articles.

1. The analysis of non-stationary signals using time–frequency methods;Hammond;J. Sound Vib.,1996

2. Time–frequency feature representation using energy concentration: an overview of recent advances;Sejdić;Digit. Signal Process.,2009

3. Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics;Qiu;J. Sound Vib.,2006

4. Recovery of vibration signal based on a super-exponential algorithm;Li;J. Sound Vib.,2008

5. Optimal filtering of gear signals for early damage detection based on the spectral kurtosis;Combet;Mech. Syst. Signal Process.,2009

Cited by 65 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Smart CEEMDAN, Bessel Transform and CNN-Based Scheme for Compound Gear-Bearing Fault Diagnosis;Journal of Vibration Engineering & Technologies;2024-05-15

2. Feature Fusion Based on Locally Linear Embedding in Fault Diagnosis of A Single-Phase PWM Rectifier;2023 7th International Conference on Smart Grid and Smart Cities (ICSGSC);2023-09-22

3. A Unified Approach for Compound Gear-Bearing Fault Diagnosis Using Bessel Transform, Artificial Bee Colony-Based Feature Selection and LSTM Networks;Journal of Vibration Engineering & Technologies;2023-05-30

4. Enhanced order spectrum analysis based on iterative adaptive crucial mode decomposition for planetary gearbox fault diagnosis under large speed variations;Mechanical Systems and Signal Processing;2023-02

5. An intelligent compound gear-bearing fault identification approach using Bessel kernel-based time-frequency distribution;Metrology and Measurement Systems;2022-12-29