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基于深度学习的机械设备故障诊断方法研究
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
基于深度学习机械设备故障诊断模型
This repository is for the Few-shot Learning for the fault diagnosis of large industrial equipment.
This is the corresponding repository of paper Limited Data Rolling Bearing Fault Diagnosis with Few-shot Learning
Implementation of the mechanical fault diagnosis method using model agnostic meta-learning (MAML)
CNN for mechanical fault diagnosis
meta learning for fault diagnosis
The source codes of Meta-learning for few-shot cross-domain fault diagnosis.
Source codes for the paper "Few-shot bearing fault diagnosis based on meta-learning with discriminant space optimization" which published in MST
Open rotating mechanical fault datasets (开源旋转机械故障数据集整理)
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