Learning representations with local and global geometries preserved for machine fault diagnosis

• Main Authors: Li, Yue, Lekamalage, Chamara Kasun Liyanaarachchi, Liu, Tianchi, Chen, Pin-An, Huang, Guang-Bin
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Electrical and electronic engineering; Autoencoder; Machine Fault Diagnosis
• Online Access: https://hdl.handle.net/10356/155210
• Institution: Nanyang Technological University

Recently, deep learning-based representation learning methods have attracted increasing attention in machine fault diagnosis. However, few existing methods consider the geometry of data samples. In this paper, we propose a novel method to obtain representations that preserve the geometry of input da...