Name
Title | ||
|---|---|---|
A method for using BP neural network to monitor running state of a steam turbine gearbox |
Abstract | ||
|---|---|---|
The relationship between the gearbox's running state and the characteristic parameters is complex and nonlinear. In this paper, a diagnostic method for BP neural network gear box's running state based on principal component analysis is proposed. The method is mainly extracted from 8 main characteristic parameters and 10 groups of training samples. On this basis, the BP neural network classifier is designed, and use the network to identify steam turbine gearbox's running state identify the operational status, so as to facilitate timely maintenance, reduce production costs and create some economic benefits. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/COGINF.2011.6016134 | IEEE ICCI*CC |
Keywords | Field | DocType |
bp neural network,gears,gearbox running state monitoring,running state,monitoring,computerised monitoring,backpropagation,diagnostic method,fault diagnosis,steam turbines,principal component analysis,mechanical engineering computing,steam turbine gearbox,neural nets,characteristic parameters,neural network | Transmission (mechanics),Nonlinear system,Neural network classifier,Computer science,Control engineering,Steam turbine,Backpropagation,Artificial neural network,Principal component analysis,Economic benefits | Conference |
Volume | Issue | ISBN |
null | null | 978-1-4577-1695-9 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xinghua Liu | 1 | 11 | 6.76 |
| Jike Ge | 2 | 52 | 6.46 |
| Yu Luo | 3 | 0 | 0.34 |
| Yang Cheng | 4 | 12 | 3.72 |