A novel dual-stream self-attention neural network for remaining useful life estimation of mechanical systems

•A novel dual-stream data-driven framework is proposed for RUL estimation.•Multi-head self-attention mechanism is employed to enrich features with correlation information.•A data transformation algorithm is designed to obtain internal differences of data.•Experiments on the C-MAPSS datasets show the superiority of the proposed method.