机械制造与自动化Issue(5)：219-222,4.DOI:10.19344/j.cnki.issn1671-5276.2017.05.056
基于极限学习机的航空旋转整流器故障诊断技术研究
Fault Diagnosis Technology Research of Aircraft Generator Rotating Rectifier Based on Extreme Learning Machine
王潇雅 1崔江 1唐军祥 1叶纪青1
作者信息
- 1. 南京航空航天大学 自动化学院,江苏 南京211106
- 折叠
摘要
Abstract
Aircraft generator is the core component of aircraft electrical power system. Because the problems of slow fault diagnosis and difficultly selecting parameters exist in the fault diagnosis of aircraft generator rofafing rectifier by use of artificial intelligence algo-rithm, this paper introduces the exfreme learning machine into this fault diagnosis. It takes the three-stage generator for example, analyzes the failure mode of the rotating rectifier, and then, establishes the generator model and simulates the failur mode of the ro-tating rectifier in Matlab/simulink. The simulation results indicate that ELM has good fault diagnosis accuracy. Compared with conven-tional fault diagnosis method, it is of higher efficiency of the fault diagnosis.关键词
航空发电机/旋转整流器/极限学习机/故障诊断Key words
aircraft generator/rotating rectifier/extreme learning machine( ELM)/fault diagnosis分类
信息技术与安全科学引用本文复制引用
王潇雅,崔江,唐军祥,叶纪青..基于极限学习机的航空旋转整流器故障诊断技术研究[J].机械制造与自动化,2017,(5):219-222,4.
