Name
Abstract | ||
|---|---|---|
Considering the issues that the relationship between the fault of oil pump existent and fault information is a complicated and nonlinear system, and it is very difficult to found the process model to describe it. The fuzzy neural network has the advantages of both fuzzy theory and neural network. In this paper, a fault detection method of oil pump based on fuzzy neural network is presented, moreover, we construct the structure of fuzzy neural network that used for the fault detection of oil pump, and adopt the Levenberg- Marquart optimizing algorithm to train fuzzy neural network. With the ability of strong self-learning and function approach of fuzzy neural network, the detection method can truly diagnosticate the fault of oil pump by learning the fault information of oil pump. The real detection results show that this method is feasible and effective. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICNC.2007.375 | ICNC |
Keywords | Field | DocType |
marquart optimizing algorithm,detection method,neural network,fuzzy theory,fuzzy neural network,oil pump,fault detection,real detection result,fault detection method,fault information,process model,nonlinear system | Neuro-fuzzy,Nonlinear system,Computer science,Fault detection and isolation,Fuzzy logic,Fuzzy neural nets,Oil pump,Artificial intelligence,Adaptive neuro fuzzy inference system,Artificial neural network,Machine learning | Conference |
ISBN | Citations | PageRank |
0-7695-2875-9 | 0 | 0.34 |
References | Authors | |
3 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jingwen Tian | 1 | 36 | 13.10 |
| Meijuan Gao | 2 | 32 | 12.32 |
| Liting Cao | 3 | 0 | 1.69 |
| Kai Li | 4 | 3 | 3.30 |