Contrastive adversarial domain adaptation for machine remaining useful life prediction

• Main Authors: Mohamed Ragab, Chen, Zhenghua, Wu, Min, Foo, Chuan Sheng, Kwoh, Chee Keong, Yan, Ruqiang, Li, Xiaoli
• 其他作者: School of Computer Science and Engineering
• 格式: Article
• 語言: English
• 出版: 2022
• 主題: Engineering::Computer science and engineering; Domain Adaptation; Deep Learning
• 在線閱讀: https://hdl.handle.net/10356/157026

Enabling precise forecasting of the remaining useful life (RUL) for machines can reduce maintenance cost, increase availability, and prevent catastrophic consequences. Data-driven RUL prediction methods have already achieved acclaimed performance. However, they usually assume that the training and t...