Name
Abstract | ||
|---|---|---|
It is important to identify loads on aircraft to facilitate the designing of aircraft and ground environmental experiments. A new approach of load identification in frequency domain based on least squares support vector machine (LSSVM) and particle swarm optimization (PSO) was proposed. The principle of load identification using LSSVM was derived and the corresponding model of relationship between loads and responses was constructed using LSSVM. To get better performance of identification, PSO was adopted to find optimal hyper-parameters of LSSVM with the best generalization ability of the identification model. The results of numerical simulation and random vibration experiments of simplified aircraft show that the proposed approach can identify not only singlesource load, but also multisource loads effectively with high precision, which demonstrate the proposed approach is greatly applicable to engineering project. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-05253-8_26 | AICI |
Keywords | Field | DocType |
frequency domain,corresponding model,identification model,aircraft show,load identification,engineering project,singlesource load,new approach,better performance,random vibration,inverse problem,least squares support vector machine,numerical simulation | Frequency domain,Particle swarm optimization,Least squares support vector machine,Computer simulation,Computer science,Artificial intelligence,Inverse problem,Machine learning,Random vibration | Conference |
Volume | ISSN | Citations |
5855 | 0302-9743 | 2 |
PageRank | References | Authors |
0.42 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dike Hu | 1 | 11 | 0.96 |
| Wentao Mao | 2 | 112 | 11.54 |
| Jinwei Zhao | 3 | 11 | 1.93 |
| Guirong Yan | 4 | 97 | 6.55 |