This article investigates the fault trend prediction problem of high-speed train suspension systems in the case of data missing *** the perspective of data distribution,Transformer architecture with improved temporal ...
详细信息
ISBN:
(数字)9789887581581
ISBN:
(纸本)9798350366907
This article investigates the fault trend prediction problem of high-speed train suspension systems in the case of data missing *** the perspective of data distribution,Transformer architecture with improved temporaldistributionmatching(TDM) algorithm is proposed in this paper to further explore the field of fault trend ***,calculating the sensitivity,degree and location of faults to missing ***,the reorganization of encoder layer in TDM algorithm is ***,experiments in SIMPACK-MATLAB/Simulink co-simulation environment is used to validate the effectiveness of the improved TDM algorithm in fault prediction,especially when missing data leads to significant differences in data distribution.
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