Name
Title | ||
|---|---|---|
A Deep Learning Network via Shunt-wound Restricted Boltzmann Machines Using Raw Data for Fault Detection |
Abstract | ||
|---|---|---|
Intelligent fault detection has been widely used for feature extraction and fault classification. However, various complex signal processing methods are adopted in many researches. This article presents a novel deep learning network via shunt-wound restricted Boltzmann machines (RBMs) with layerwise feature learning to learn the fault features from big raw vibration signals directly. The network c... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TIM.2019.2953436 | IEEE Transactions on Instrumentation and Measurement |
Keywords | DocType | Volume |
Feature extraction,Fault detection,Vibrations,Deep learning,Fault diagnosis,Training,Rolling bearings | Journal | 69 |
Issue | ISSN | Citations |
7 | 0018-9456 | 1 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tongyang Pan | 1 | 3 | 4.77 |
| Jinglong Chen | 2 | 3 | 3.08 |
| Jun Pan | 3 | 1 | 0.34 |
| Zitong Zhou | 4 | 18 | 5.08 |