Metric Learning-Guided Semi-Supervised Path-Interaction Fault Diagnosis Method for Extremely Limited Labeled Samples under Variable Working Conditions

The lack of labeled data and variable working conditions brings challenges to the application of intelligent fault diagnosis. Given this, extracting labeled information and learning distribution-invariant representation provides a feasible and promising way. Enlightened by metric learning and semi-s...

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Hlavní autoři:	Zheng Yang, Fei Chen, Binbin Xu, Boquan Ma, Zege Qu, Xin Zhou
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2023-08-01
Edice:	Sensors
Témata:	intelligent fault diagnosis semi-supervised metric learning limited labeled sample variable working condition
On-line přístup:	https://www.mdpi.com/1424-8220/23/15/6951
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