Name
Title | ||
|---|---|---|
A Deep Coupled Network for Health State Assessment of Cutting Tools Based on Fusion of Multisensory Signals. |
Abstract | ||
|---|---|---|
The cutting tool is a key part of a machine system, which plays an important role in modern manufacturing systems. To avoid an unexpected tool failure, it is necessary to carry out health condition assessment of cutting tools. In this paper, a deep coupled restricted Boltzmann machine (DCRBM) is proposed for health state assessment of cutting tools based on fusion of vibration signals and acoustic... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TII.2019.2912428 | IEEE Transactions on Industrial Informatics |
Keywords | Field | DocType |
Cutting tools,Tools,Sensors,Feature extraction,Vibrations,Data models,Monitoring | Restricted Boltzmann machine,Boltzmann machine,Feature vector,Computer science,Fusion,Control engineering,Vibration,Acoustic emission,Condition assessment,Cutting tool | Journal |
Volume | Issue | ISSN |
15 | 12 | 1551-3203 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Meng Ma | 1 | 82 | 12.29 |
| Chuang Sun | 2 | 70 | 8.35 |
| XueFeng Chen | 3 | 441 | 55.44 |
| Xingwu Zhang | 4 | 16 | 3.51 |
| Ruqiang Yan | 5 | 532 | 55.59 |