With the development of complexity and integration of machines, the multiple components of
the system are prone to simultaneous failures and the multi-fault signals may be measured …

Nuclear norm maximization has shown the power to enhance the transferability of
unsupervised domain adaptation model (UDA) in an empirical scheme. In this paper, we …

Adversarial domain adaptation has made remarkable in promoting feature transferability,
while recent work reveals that there exists an unexpected degradation of feature …

Abstract Domain adaptation (DA) as a critical and valuable tool is devoted to minimizing the
distribution discrepancy across domains, which has been successfully utilized in intelligent …

For cross-domain fault diagnosis of rotating machinery, how to reduce the discrepancy
between the source and target data distributions is still a key problem. To this end, this study …

Nonintrusive load monitoring (NILM) is a technology that analyzes the load consumption
and usage of an appliance from the total load. NILM is becoming increasingly important …

A growing number of research areas such as location-based social networks, intelligent
transportation systems, and urban computing utilize large amounts of trajectory data for …

Domain adaptation (DA) has the promising potential to mitigate the distribution gap between
source and target data in fault diagnosis. However, many DA methods only attempt to align …

Unsupervised Domain Adaptation (UDA) methods have been successful in reducing label
dependency by minimizing the domain discrepancy between labeled source domains and …

Domain adaptation (DA) models for fault diagnosis typically assume a shared label space
between source and target domains. However, in real industrial applications, the target label …