SDE网络在高速列车转向架未知故障诊断中的应用

转向架作为高速列车车体与轨道的连接部位,承载着保证列车在轨道上安全运行的重任.然而,在列车长期服役过程中,轨道不平顺以及轮轨磨耗等原因会造成转向架部件故障,严重影响列车的安全运行.实际运行过程中故障的发生具有随机性,无法将转向架故障诊断简单归类于已知组别分类问题.针对深度学习无法辨别未知故障的缺陷,在卷积神经网络(CN...

Application of SDE-net in Out-of-distribution Fault Diagnosis of High-speed Train Bogie

As the connecting system of the high-speed train body and the track,the bogie plays an important part in ensuring the safe operation of the trains on the track.However,the track irregularity and wheel-rail wear will cause the bogie to malfunction during the long-term service of the trains,which will seriously affect the safe operation of the trains.The occurrence of faults during actual operation is random.Therefore,it is inappropriate to classify fault diagnosis of bogie into the problem of known category classification simply.Aiming at the defect that deep learning can not distinguish unknown faults,stochastic differential equation(SDE)is added into the convolutional neural network(CNN)to distinguish known and unknown bogie faults.Experiments show that the stochastic differential equation network(SDE-net)can not only distinguish known faults accurately,but also distinguish unknown faults effectively,and the accuracy rates are over 93%.At the same time,the superiority of the proposed method is demonstrated by comparison with the one-dimensional CNN network.