Fault Diagnosis of Planetary Gearboxes Based on LSTM Improved via Feature Extraction Using VMD, Fusion Entropy, and Random Forest

Extracting effective fault features from the complex vibration signals of planetary gearboxes is the key to conducting efficient fault diagnosis, and it involves signal processing, feature extraction, and feature selection. In this paper, a novel feature extraction method is proposed using variation...

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Bibliographic Details

Published in:	Entropy
Main Authors:	Xin Xia, Haoyu Sun, Aiguo Wang
Format:	Article
Language:	English
Published:	MDPI AG 2025-09-01
Subjects:	fault diagnosis planetary gearbox fusion entropy random forest LSTM
Online Access:	https://www.mdpi.com/1099-4300/27/9/956