Controlled generation of unseen faults for Partial and Open-Partial domain adaptation


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Date

2023-02

Publication Type

Journal Article

ETH Bibliography

yes

Citations

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Data

Abstract

New operating conditions can result in a significant performance drop of fault diagnostics models due to the domain shift between the training and the testing data distributions. While several domain adaptation approaches have been proposed to overcome such domain shifts, their application is limited if the fault classes represented in the two domains are not the same. To enable a better transferability between two different domains, particularly in setups where only the healthy data class is shared between the two domains, we propose a new framework for Partial and Open-Partial domain adaptation based on generating distinct fault signatures with a Wasserstein GAN. The main contribution of the proposed framework is the controlled data generation with two characteristics. Firstly, previously unobserved target faults can be generated by having only access to healthy target and faulty source samples. Secondly, distinct fault types and severity levels can be generated precisely. The proposed method is especially suited for extreme domain adaption settings that are particularly relevant in the context of complex and safety-critical systems, where only one class is shared between the two domains. We evaluate the proposed framework on Partial as well as Open-Partial domain adaptation tasks on two bearing fault diagnostics case studies. In the evaluated case studies the proposed methodology demonstrated superior results compared to other methods, particularly in the presence of large domain gaps. The experiments conducted in different label space settings (Partial and Open-Partial) showcase the versatility of the proposed framework.

Publication status

published

Editor

Book title

Volume

230

Pages / Article No.

108857

Publisher

Elsevier

Event

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Unseen fault generation; Controlled generation; Partial domain adaptation; Open-Partial domain adaptation

Organisational unit

09642 - Fink, Olga (ehemalig) / Fink, Olga (former) check_circle
02261 - Center for Sustainable Future Mobility / Center for Sustainable Future Mobility

Notes

INTERACT MI-Project

Funding

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