Compound fault diagnosis for a rolling bearing using adaptive DTCWPT with higher order spectra-Reference-Cited by-同舟云学术

Compound fault diagnosis for a rolling bearing using adaptive DTCWPT with higher order spectra

Published:2020-05-19 Issue:3 Volume:32 Page:342-353
ISSN:0898-2112
Container-title:Quality Engineering
language:en
Short-container-title:Quality Engineering

Author:

Shao Haidong¹,Lin Jing²^ORCID,Zhang Liangwei³,Wei Muheng⁴

Affiliation:

1. State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China;

2. Department of Civil, Environmental and Natural Resources Engineering, Luleå University of Technology, Luleå, Sweden;

3. Department of Industrial Engineering, Dongguan University of Technology, Dongguan, China;

4. ZhenDui Industry Artificial Intelligence Co., Ltd, Shenzhen, China

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Safety, Risk, Reliability and Quality

Link

https://www.tandfonline.com/doi/pdf/10.1080/08982112.2020.1749654

Reference41 articles.

1. Feature selection with SVD entropy: Some modification and extension

2. Compound faults detection of rotating machinery using improved adaptive redundant lifting multiwavelet

3. HIGHER-ORDER SPECTRA: THE BISPECTRUM AND TRISPECTRUM

4. Interharmonics based high impedance fault detection in distribution systems using maximum overlap wavelet packet transform and a modified empirical mode decomposition

5. The new chirp-Wigner higher order spectra for transient signals with any known nonlinear frequency variation

Cited by 17 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. Compound fault diagnosis of diesel engines by combining generative adversarial networks and transfer learning;Expert Systems with Applications;2024-10

2. Integrated decision-making with adaptive feature weighting adversarial network for multi-target domain compound fault diagnosis of machinery;Advanced Engineering Informatics;2024-10

3. Motor Current Time-Varying Quadratic Phase Coupling Analysis and Its Application in Traction Motor Fault Detection Under Varying-Speed Condition;IEEE Sensors Journal;2024-04-15

4. A Partial-Label U-Net Learning Method for Compound-Fault Diagnosis With Fault- Sample Class Imbalance;IEEE Transactions on Industrial Informatics;2024-02

5. Generalized Gini indices–enhanced sparsity decomposition for rotating machinery health assessment using a rotary encoder;Nondestructive Testing and Evaluation;2023-12-28