现代电子技术2015，Vol.38Issue(17)：107-109,3.
基于改进的LVQ神经网络的发动机故障诊断
Fault diagnosis for engines based on improved LVQ neural network
郭增波 1巴寅亮 2王书提 2谢鑫2
作者信息
- 1. 克拉玛依职业技术学院,新疆 克拉玛依 834000
- 2. 新疆农业大学 机械交通学院,新疆 乌鲁木齐 830052
- 折叠
摘要
Abstract
Since learning vector quantization (LVQ) neural network can classify input vector pattern accurately by super-vised learning,the fault diagnosis method for engines based on LVQ neural network is proposed. LVQ neural network and its im-proved learning method are introduced. Taking Great Wall Harvard GW2.8TC engine as the experimental subject,faults are set for the engine under idle speed condition. The data stream of the engine is collected by using Kinder KT600 computer fault diag-nosis tester. The diagnosis model was established by using the improved LVQ neural network. The diagnosis results show that the improved LVQ neural network can classify engine faults accurately,and the precision rate is relatively high.关键词
改进的LVQ神经网络/发动机/故障诊断/神经元Key words
improved LVQ neural network/engine/fault diagnosis/neurone分类
信息技术与安全科学引用本文复制引用
郭增波,巴寅亮,王书提,谢鑫..基于改进的LVQ神经网络的发动机故障诊断[J].现代电子技术,2015,38(17):107-109,3.
