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...
Saved in:
Main Authors: | Shu Han, Xiaoming Liu, Yan Yang, Hailin Cao, Yuanhong Zhong, Chuanlian Luo |
---|---|
Format: | article |
Language: | EN |
Published: |
MDPI AG
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/efc0bb6fb0a44c0f8b3be222af63f6c3 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Intelligent Fault Diagnosis and Forecast of Time-Varying Bearing Based on Deep Learning VMD-DenseNet
by: Shih-Lin Lin
Published: (2021) -
Intelligent Fault Diagnosis Method of Wind Turbines Planetary Gearboxes Based on a Multi-Scale Dense Fusion Network
by: Xinghua Huang, et al.
Published: (2021) -
Statistical Feature Extraction Combined with Generalized Discriminant Component Analysis Driven SVM for Fault Diagnosis of HVDC GIS
by: Ruixu Zhou, et al.
Published: (2021) -
A fault feature extraction algorithm based on CEEMD-TVD-MOMEDA
by: Jingzong Yang, et al.
Published: (2021) -
Peak-Load-Regulation Nuclear Power Unit Fault Diagnosis Using Thermal Sensors Combined with Improved ICA-RF Algorithm
by: Yifan Wu, et al.
Published: (2021)