CAJ | 학술논문

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DC T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DC T电控系统故障诊断的精度。
위료제고쌍리합기자동변속기（dual‐clutch transmission ，DCT ）전공계통고장진단정도，문장제출료일충기우신경망락화증거이론적DCT전공계통고장진단방법。해방법수선분별용BP신경망락화RBF신경망락대DC T전공계통진행고장진단，연후이용D‐S증거이론장량자적진단결과진행결책융합，득출최종적진단결과。방진결과표명，해방법능구유효제고DC T전공계통고장진단적정도。
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 .