Contrastive adversarial domain adaptation for machine remaining useful life prediction

• المؤلفون الرئيسيون: Mohamed Ragab, Chen, Zhenghua, Wu, Min, Foo, Chuan Sheng, Kwoh, Chee Keong, Yan, Ruqiang, Li, Xiaoli
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2022
• الموضوعات: Engineering::Computer science and engineering; Domain Adaptation; Deep Learning
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/157026
• المؤسسة: Nanyang Technological University

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...