Small data challenges for intelligent prognostics and health management: a review
Guizhou University · Flanders Make (Belgium) · +4 more institutions
Abstract
Abstract Prognostics and health management (PHM) is critical for enhancing equipment reliability and reducing maintenance costs, and research on intelligent PHM has made significant progress driven by big data and deep learning techniques in recent years. However, complex working conditions and high-cost data collection inherent in real-world scenarios pose small-data challenges for the application of these methods. Given the urgent need for data-efficient PHM techniques in academia and industry, this paper aims to explore the fundamental concepts, ongoing research, and future trajectories of small data challenges in the PHM domain. This survey first elucidates the definition, causes, and impacts of small data…
Citation impact
- FWCI
- 71.68
- Percentile
- 100%
- References
- 214
Authors
6Topics & keywords
- Prognostics
- Computer science
- Data science
- Risk analysis (engineering)
- Data mining
- Medicine
- Industry, innovation and infrastructure