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

Mechanical Systems and Signal Processing, Journal Year: 2024, Volume and Issue: 210, P. 111142 - 111142

Published: Jan. 23, 2024

Language: Английский

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Deep dynamic high-order graph convolutional network for wear fault diagnosis of hydrodynamic mechanical seal

Reliability Engineering & System Safety, Journal Year: 2024, Volume and Issue: 247, P. 110117 - 110117

Published: April 5, 2024

Language: Английский

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ReF-DDPM: A novel DDPM-based data augmentation method for imbalanced rolling bearing fault diagnosis

Reliability Engineering & System Safety, Journal Year: 2024, Volume and Issue: 251, P. 110343 - 110343

Published: July 9, 2024

Language: Английский

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Review of research on signal decomposition and fault diagnosis of rolling bearing based on vibration signal

Measurement Science and Technology, Journal Year: 2024, Volume and Issue: 35(9), P. 092001 - 092001

Published: May 22, 2024

Abstract Rolling bearings are critical components that prone to faults in the operation of rotating equipment. Therefore, it is utmost importance accurately diagnose state rolling bearings. This review comprehensively discusses classical algorithms for fault diagnosis based on vibration signal, focusing three key aspects: data preprocessing, feature extraction, and identification. The main principles, features, application difficulties, suitable occasions various thoroughly examined. Additionally, different methods reviewed compared using Case Western Reserve University bearing dataset. Based current research status diagnosis, future development directions also anticipated. It expected this will serve as a valuable reference researchers aiming enhance their understanding improve technology diagnosis.

Language: Английский

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MRCFN: A multi-sensor residual convolutional fusion network for intelligent fault diagnosis of bearings in noisy and small sample scenarios

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 259, P. 125214 - 125214

Published: Aug. 30, 2024

Language: Английский

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A performance-interpretable intelligent fusion of sound and vibration signals for bearing fault diagnosis via dynamic CAME

Nonlinear Dynamics, Journal Year: 2024, Volume and Issue: 112(23), P. 20903 - 20940

Published: Aug. 24, 2024

Language: Английский

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Digital twin-assisted interpretable transfer learning: A novel wavelet-based framework for intelligent fault diagnostics from simulated domain to real industrial domain

Advanced Engineering Informatics, Journal Year: 2024, Volume and Issue: 62, P. 102681 - 102681

Published: July 13, 2024

Language: Английский

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A novel lightweight DDPM-based data augmentation method for rotating machinery fault diagnosis with small sample

Mechanical Systems and Signal Processing, Journal Year: 2025, Volume and Issue: 232, P. 112741 - 112741

Published: April 16, 2025

Language: Английский

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Source-free domain adaptation framework for fault diagnosis of rotation machinery under data privacy

Reliability Engineering & System Safety, Journal Year: 2023, Volume and Issue: 238, P. 109468 - 109468

Published: June 23, 2023

Language: Английский

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LSTA-Net framework: Pioneering intelligent diagnostics for insulating bearings under real-world complex operational conditions and its interpretability

Mechanical Systems and Signal Processing, Journal Year: 2024, Volume and Issue: 222, P. 111779 - 111779

Published: July 27, 2024

Language: Английский

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