Distribution Network Fault Diagnosis with Noise-Assisted Multivariate Empirical Mode Decomposition and a Modified Multiple Branch Convolutional Neural Network

A novel method based on noise-assisted multivariate empirical mode decomposition (NA-MEMD) combined with a modified multiple branch convolutional neural network (MMBCNN) is designed to detect fault events in distribution networks and to classify various faults in a distribution system. Given the pre...

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Autori principali:	Fei Xiao, Xiaoya Shang, Qinxue Li, Yiyi Zhan, Rui Li, Qian Ai, Yi Zhang
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	MDPI AG 2026-04-01
Serie:	Energies
Soggetti:	noise-assisted multivariate empirical mode decomposition modified multiple branch convolutional neural network ring image Clarke transform modified pooling function
Accesso online:	https://www.mdpi.com/1996-1073/19/9/2187
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