Role of image feature enhancement in intelligent fault diagnosis for mechanical equipment: A review

Y Sun, W Wang - Engineering Failure Analysis, 2024 - Elsevier
In the modern manufacturing industry, mechanical equipment plays a crucial role.
Equipment working in harsh environments for a long time is more likely to break down …

A graph-guided collaborative convolutional neural network for fault diagnosis of electromechanical systems

Y Xu, JC Ji, Q Ni, K Feng, M Beer, H Chen - Mechanical Systems and …, 2023 - Elsevier
Collaborative fault diagnosis has become a hot research topic in fault detection and
identification, greatly benefiting from emerging multisensory fusion techniques and newly …

Dconformer: A denoising convolutional transformer with joint learning strategy for intelligent diagnosis of bearing faults

S Li, JC Ji, Y Xu, K Feng, K Zhang, J Feng… - … Systems and Signal …, 2024 - Elsevier
Rolling bearings are the core components of rotating machinery, and their normal operation
is crucial to entire industrial applications. Most existing condition monitoring methods have …

[HTML][HTML] Spatio-temporal attention-based hidden physics-informed neural network for remaining useful life prediction

F Jiang, X Hou, M Xia - Advanced Engineering Informatics, 2025 - Elsevier
Abstract Predicting the Remaining Useful Life (RUL) is essential in Prognostic Health
Management (PHM) for industrial systems. Although deep learning approaches have …

A fault diagnosis method for analog circuits based on EEMD-PSO-SVM

S Zhao, X Liang, L Wang, H Zhang, G Li, J Chen - Heliyon, 2024 - cell.com
Analog circuit is an crucial component of electronic equipment, and the ability to diagnose its
fault state quickly and accurately is essential for ensuring the safety and reliability of these …

Generalized transfer extreme learning machine for unsupervised cross-domain fault diagnosis with small and imbalanced samples

A Qin, H Mao, J Zhong, Z Huang, X Li - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
In most engineering scenarios, the collected datasets typically have small and imbalanced
characteristics and usually possess different data distributions between variable working …

Robust optimized weights spectrum: Enhanced interpretable fault feature extraction method by solving frequency fluctuation problem

Y Wang, D Wang, B Hou, S Lu, Z Peng - Mechanical Systems and Signal …, 2025 - Elsevier
Abstract Machine condition monitoring (MCM) plays a pivotal role in ensuring the reliability,
safety, and efficiency of a production and operation system. Fault feature extraction (FFE), as …

A simulation-driven difference mode decomposition method for fault diagnosis in axial piston pumps

J Guo, Y Liu, R Yang, W Sun, J Xiang - Advanced Engineering Informatics, 2024 - Elsevier
The strong periodic shocks produced by axial piston pumps during normal operation greatly
weaken the performance of fault diagnosis methods. Extracting the fault resonance band …

Combined Weighted Envelope Spectrum: An enhanced demodulation framework for extracting characteristic frequency of rotating machinery

K Wu, W Tong, B Huang, D Wu - Mechanical Systems and Signal …, 2024 - Elsevier
Envelope spectrum plays a pivotal role in the surveillance and diagnostics of rotating
machinery. Two prevailing techniques for constructing this spectral quantity are narrowband …

Optimal Weighted Envelope Spectrum: An enhanced demodulation method for extracting specific characteristic frequency of rotating machinery

K Wu, W Tong, J Xie, F Wang, B Huang… - Mechanical Systems and …, 2024 - Elsevier
Envelope spectrum plays a crucial role in fault diagnosis of rotating machinery. Narrowband
demodulation and cyclostationary analysis are two mainstream methods to construct this …