摘要
为了提高双离合器自动变速器(dual-clutch transmission,DCT)电控系统故障诊断精度,文章提出了一种基于神经网络和证据理论的DCT电控系统故障诊断方法。该方法首先分别用BP神经网络和RBF神经网络对DCT电控系统进行故障诊断,然后利用D-S证据理论将两者的诊断结果进行决策融合,得出最终的诊断结果。仿真结果表明,该方法能够有效提高DCT电控系统故障诊断的精度。
In order to improve the fault diagnosis accuracy of dual‐clutch transmission(DCT ) electronic control system ,a fault diagnosis scheme based on neural network and D‐S evidence theory is devel‐oped .Both the fault diagnosis based on BP neural network and based on RBF neural network of DCT electronic control system are studied .Then the D‐S evidence theory is applied to fusing the diagnosis results of BP neural network and RBF neural network .The simulation results are presented to demon‐strate the validity and effectiveness of the fault diagnosis scheme .
出处
《合肥工业大学学报(自然科学版)》
CAS
CSCD
北大核心
2015年第9期1193-1196,共4页
Journal of Hefei University of Technology:Natural Science
基金
中央高校基本科研业务费专项资金资助项目(2014HGCH0003)
关键词
故障诊断
DC
T电控系统
神经网络
D-S证据理论
fault diagnosis
dual-clutch transmission(DCT) electronic control system
neural network
Dempster-Shafer(D-S) evidence theory