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This paper presents a new multiscale deep attention reinforcement learning (MDARL) approach for imbalanced fault diagnosis of gearbox.
Dec 1, 2023 · A novel approach called multiscale deep attention Q network (MDAQN) is proposed for imbalanced gearbox fault diagnosis from a deep reinforcement learning (DRL) ...
Based on deep reinforcement learning, an intelligent fault diagnosis method of the planetary gearbox using the deep wide convolution Q network is proposed.
A deep feature enhanced reinforcement learning method is proposed for the fault diagnosis of rolling bearing.
Missing: Multiscale Gearboxes.
This paper develops a deep reinforcement learning-based diagnosis method that models fault diagnosis as a sequential decision-making process.
Multiscale Deep Attention Q Network: A New Deep Reinforcement Learning Method for Imbalanced Fault Diagnosis in Gearboxes · Engineering, Computer Science. IEEE ...
Based on deep reinforcement learning, an intelligent fault diagnosis method of the planetary gearbox using the deep wide convolution Q network is proposed.
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Jan 7, 2024 · This research proposes a gearbox fault diagnosis method integrated with lightweight channel attention mechanism, and further realizes the cross-component ...
Missing: Multiscale | Show results with:Multiscale
The results show that the proposed multi-scale path attention residual network can improve the feature learning ability of the multi-scale structure and achieve ...
Missing: Reinforcement | Show results with:Reinforcement
The proposed multi-scale recursive semi-supervised deep learning fault diagnosis method with attention gate (MRAE-AG) can efficiently improve the fault ...