Deep multisource parallel bilinear-fusion network for remaining useful life prediction of machinery

•A feature encoding subnetwork is constructed to automatically learn spatio-temporal features.•The learning strategy of multiple parallel subnetworks is proposed.•Bilinear fusion module enables sufficient interaction between multisource features.•The approximate dimensionality reduction method is included to avoid high-dimensional problems during feature fusion.