TDMSAE: A transferable decoupling multi-scale autoencoder for mechanical fault diagnosis-Reference-Cited by-同舟云学术

TDMSAE: A transferable decoupling multi-scale autoencoder for mechanical fault diagnosis

Published:2023-02 Issue: Volume:185 Page:109789
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Yu Shihang^ORCID,Wang Min^ORCID,Pang Shanchen^ORCID,Song Limei,Zhai Xue^ORCID,Zhao Yawu^ORCID

Publisher

Elsevier BV

Subject

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

Reference38 articles.

1. A novel strategy for signal denoising using reweighted SVD and its applications to weak fault feature enhancement of rotating machinery;Zhao;Mech. Syst. Signal Process.,2017

2. Wavelet transform based on inner product in fault diagnosis of rotating machinery: A review;Chen;Mech. Syst. Signal Process.,2016

3. Applications of machine learning to machine fault diagnosis: A review and roadmap;Lei;Mech. Syst. Signal Process.,2020

4. Noise subtraction and marginal enhanced square envelope spectrum (MESES) for the identification of bearing defects in centrifugal and axial pump;Kumar;Mech. Syst. Signal Process.,2022

5. A novel incipient fault diagnosis method for analog circuits based on GMKL-SVM and wavelet fusion features;Gao;IEEE Trans. Instrum. Meas.,2021

Cited by 26 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. IoT-Based Adaptive Multiplication-Convolution Sparse Denoising for Equipment Edge Condition Evaluation;IEEE Internet of Things Journal;2024-09-15

2. MOSGAT: Uniting Specificity-Aware GATs and Cross Modal-Attention to Integrate Multi-Omics Data for Disease Diagnosis;IEEE Journal of Biomedical and Health Informatics;2024-09

3. Hierarchical Knowledge Guided Fault Intensity Diagnosis of Complex Industrial Systems;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

4. ORgram: semi-supervised learning framework for inline bearing diagnosis in varying speed;The International Journal of Advanced Manufacturing Technology;2024-08-16

5. TSoft-Net: A novel transfer soft thresholding network based on self-attention for intelligent fault diagnosis of rotating machinery;Measurement;2024-03