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Parameter sharing adversarial domain adaptation networks for fault transfer diagnosis of planetary gearboxes

机译：Plantary Tearboxes故障诊断的参数共享对抗域适配网络

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摘要

The domain adaptation (DA) model, aiming to solve the task of unlabeled or less-labeled target domain fault classification through the training of labeled source domain fault data, is widely used in the transfer diagnosis task of mechanical faults by unsupervised learning. However, traditional transfer learning models such as deep domain confusion (DDC) and RevGrad still have the problems of high training cost and low classification accuracy. Therefore, this paper proposes a parameter sharing adversarial domain adaptation network (PSADAN). The proposed approach constructs a shared classifier to unify fault classifiers and domain classifiers to reduce the complexity of network structure (i.e. the number of hyperparameters), and adds the CORAL loss for adversarial training to enhance the domain confusion. Meanwhile, an unbalanced adversarial training strategy is proposed for improving the domain confusion ability of the feature extractor, so as to improve the accuracy of transfer diagnosis. The effectiveness and advantage of the proposed method is verified by the planetary gearbox fault transfer diagnosis experiments including several transfer tasks of load condition, speed condition, and measurement point.
机译：域适应（DA）模型，旨在通过培训标记的源域故障数据的训练来解决未标记或较少标记的目标域故障分类的任务，广泛应用于无监督学习的机械故障的转移诊断任务。然而，传统的转移学习模型如深域混淆（DDC）和Revgrad仍然具有高训练成本和低分类准确性的问题。因此，本文提出了参数共享对抗域适应网络（PSADAN）。该方法构造了共享分类器，以统一故障分类器和域分类器，以降低网络结构的复杂性（即，超公数的数量），并增加了对抗性训练的珊瑚损失，以增强域混淆。同时，提出了一种不平衡的对抗性培训策略来改善特征提取器的域混淆能力，从而提高转移诊断的准确性。所提出的方法的有效性和优点是通过行星齿轮箱故障转移诊断实验验证，包括负载条件，速度条件和测量点的几个转移任务。

著录项

  • 来源
    《Mechanical systems and signal processing》 |2021年第11期|107936.1-107936.13|共13页
  • 作者

    Yi Qin; Qunwang Yao; Yi Wang; Yongfang Mao;

  • 作者单位

    State Key Laboratory of Mechanical Transmission Chongqing University Chongqing 400044 China College of Mechanical and Vehicle Engineering Chongqing University Chongqing 400044 China School of Automation Chongqing University Chongqing 400044 China;

    State Key Laboratory of Mechanical Transmission Chongqing University Chongqing 400044 China College of Mechanical and Vehicle Engineering Chongqing University Chongqing 400044 China School of Automation Chongqing University Chongqing 400044 China;

    State Key Laboratory of Mechanical Transmission Chongqing University Chongqing 400044 China College of Mechanical and Vehicle Engineering Chongqing University Chongqing 400044 China School of Automation Chongqing University Chongqing 400044 China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Domain adaptation; Planetary gearbox; Fault diagnosis; Parameter sharing; Domain-adversarial training;

    机译：域适应;行星齿轮箱;故障诊断;参数共享;领域 - 对抗培训;

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