An enhancement deep feature fusion method for rotating machinery fault diagnosis
作者：
Highlights：
• A new deep learning method is proposed to automatically learn the useful fault features from the raw vibration signals.
• A new deep auto-encoder model is constructed for the enhancement of feature learning ability.
• Locality preserving projection is adopted to fuse the deep features to extract the most representative information.
摘要
•A new deep learning method is proposed to automatically learn the useful fault features from the raw vibration signals.•A new deep auto-encoder model is constructed for the enhancement of feature learning ability.•Locality preserving projection is adopted to fuse the deep features to extract the most representative information.
论文关键词：Deep feature fusion,Feature enhancement,Fault diagnosis,Rotating machinery,Locality preserving projection
论文评审过程：Received 10 August 2016, Revised 9 December 2016, Accepted 11 December 2016, Available online 13 December 2016, Version of Record 25 January 2017.
论文官网地址：https://doi.org/10.1016/j.knosys.2016.12.012
