Intelligent Algorithm for Variable Scale Adaptive Feature Separation of Mechanical Composite Fault Signals
With the development of modern industry and scientific technology, production equipment plays an increasingly important role in military and industrial production, and the fault detection signal of gears and bearings state in transmission equipment becomes very important. Therefore, this paper propo...
Enregistré dans:
Auteurs principaux: | Shu Han, Xiaoming Liu, Yan Yang, Hailin Cao, Yuanhong Zhong, Chuanlian Luo |
---|---|
Format: | article |
Langue: | EN |
Publié: |
MDPI AG
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/efc0bb6fb0a44c0f8b3be222af63f6c3 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Intelligent Fault Diagnosis and Forecast of Time-Varying Bearing Based on Deep Learning VMD-DenseNet
par: Shih-Lin Lin
Publié: (2021) -
Intelligent Fault Diagnosis Method of Wind Turbines Planetary Gearboxes Based on a Multi-Scale Dense Fusion Network
par: Xinghua Huang, et autres
Publié: (2021) -
Statistical Feature Extraction Combined with Generalized Discriminant Component Analysis Driven SVM for Fault Diagnosis of HVDC GIS
par: Ruixu Zhou, et autres
Publié: (2021) -
A fault feature extraction algorithm based on CEEMD-TVD-MOMEDA
par: Jingzong Yang, et autres
Publié: (2021) -
Peak-Load-Regulation Nuclear Power Unit Fault Diagnosis Using Thermal Sensors Combined with Improved ICA-RF Algorithm
par: Yifan Wu, et autres
Publié: (2021)