Single domain generalization method based on anti-causal learning for rotating machinery fault diagnosis

Guowei Zhang, Xianguang Kong, Qibin Wang, Jingli Du, Jinrui Wang and Hongbo Ma

Reliability Engineering and System Safety, 2024, vol. 250, issue C

Abstract: Single-domain generalization (SDG) fault diagnosis methods are promising approach because they can diagnose unknown domains by training only one domain. However, there have been fewer studies on fault diagnosis for SDG. Existing studies focus on extending the distribution of source domain, but fail to consider how to estimate domain shifts between domains. Therefore, we propose an SDG fault diagnosis learning paradigm, i.e., simulation-inference-adaptation, which first establishes a pseudo-domain as the target domain to simulate the domain shifts, then reasons the causes of the domain shifts, and finally performs the domain adaptation. In this paradigm, an anti-causal learning approach is proposed, whereby the cause of the domain shifts between the pseudo-domain and the source domain is inferred during training and the learned knowledge is used to analyze the cause of the domain shifts between the target domain and the source domain during testing. Specifically, data augmentation is utilized to perform combinatorial transformation of source data to generate pseudo-domains, perform anti-causal inference to learn to discover causal factors for domain shift between pseudo-domains and source domains, and impose the inferred causality into a weighted domain adaptation network. Finally, the experimental demonstration validated the proposed method's validity and its ability to inference causality.

Keywords: Rotating machinery; Single-domain generalization; Fault diagnosis; Anti-causal learning; Data augmentation (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832024003247
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:250:y:2024:i:c:s0951832024003247

DOI: 10.1016/j.ress.2024.110252

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().