A trackable multi-domain collaborative generative adversarial network for rotating machinery fault diagnosis

Mechanical Systems and Signal Processing, Год журнала: 2024, Номер 224, С. 111950 - 111950

Опубликована: Сен. 25, 2024

Язык: Английский

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Multi-sensor data fusion-enabled lightweight convolutional double regularization contrast transformer for aerospace bearing small samples fault diagnosis

Advanced Engineering Informatics, Год журнала: 2024, Номер 62, С. 102573 - 102573

Опубликована: Май 2, 2024

Язык: Английский

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A lightweight progressive joint transfer ensemble network inspired by the Markov process for imbalanced mechanical fault diagnosis

Mechanical Systems and Signal Processing, Год журнала: 2024, Номер 224, С. 111994 - 111994

Опубликована: Окт. 1, 2024

Язык: Английский

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An interpretable multiscale lifting wavelet contrast network for planetary gearbox fault diagnosis with small samples

Reliability Engineering & System Safety, Год журнала: 2024, Номер 251, С. 110404 - 110404

Опубликована: Июль 28, 2024

Язык: Английский

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Dynamic weighted adversarial domain adaptation network with sparse representation denoising module for rotating machinery fault diagnosis

Engineering Applications of Artificial Intelligence, Год журнала: 2025, Номер 142, С. 109963 - 109963

Опубликована: Янв. 5, 2025

Язык: Английский

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A Novel Reinforcement Learning Agent for Rotating Machinery Fault Diagnosis with Data Augmentation

Reliability Engineering & System Safety, Год журнала: 2024, Номер 253, С. 110570 - 110570

Опубликована: Окт. 6, 2024

Язык: Английский

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Multi-source domain adaptation using diffusion denoising for bearing fault diagnosis under variable working conditions

Knowledge-Based Systems, Год журнала: 2024, Номер 302, С. 112396 - 112396

Опубликована: Авг. 24, 2024

Язык: Английский

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Multi-source domain self-supervised enhanced transfer fault diagnosis approach with source sample refinement strategy

Reliability Engineering & System Safety, Год журнала: 2024, Номер 251, С. 110380 - 110380

Опубликована: Июль 26, 2024

Язык: Английский

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A weighted frequency domain energy operator spectral method based on soft thresholding fast iterative filtering for rolling bearing incipient fault feature extraction

Structural Health Monitoring, Год журнала: 2025, Номер unknown

Опубликована: Янв. 10, 2025

The incipient features in the vibration signal are a typical signature of rolling bearing faults, and their extraction is vital for early-stage fault diagnosis, yet quite challenging given complexity noisy signal. Therefore, weighted frequency domain energy operator (FDEO) spectral method based on soft thresholding fast iterative filtering (FIF) proposed this work. Firstly, FIF technique to improve equivalent filter properties such as continuity transition band lengths. Secondly, an integrated sparsity measure named average Shannon kurtosis entropy that incorporates randomness impulse characteristics constructed estimate feature information Finally, FDEO spectrum designed complete identification, it suppresses chaotic component domain. framework evaluated by simulation experiment, its performance intense noise background verified through comparisons with other decomposition methods.

Язык: Английский

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融合注意力机制与GNN的可见光室内定位方法

Acta Optica Sinica, Год журнала: 2025, Номер 45(2), С. 0206003 - 0206003

Опубликована: Янв. 1, 2025

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